Pharmaceutical care-based interventions in type 2 diabetes mellitus : a systematic review and meta-analysis of randomized clinical trials

Marcel Nogueira; Leonardo Jun Otuyama; Priscilla Alves Rocha; Vanusa Barbosa Pinto

doi:10.31744/einstein_journal/2020RW4686

. 2020 Jan 27;18:eRW4686. doi: 10.31744/einstein_journal/2020RW4686

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Pharmaceutical care-based interventions in type 2 diabetes mellitus : a systematic review and meta-analysis of randomized clinical trials

Marcel Nogueira ¹, Leonardo Jun Otuyama ¹, Priscilla Alves Rocha ¹, Vanusa Barbosa Pinto ¹

PMCID: PMC6986882 PMID: 32022107

ABSTRACT

Objective

To investigate the impact of pharmaceutical care-based interventions on type 2 diabetes mellitus .

Methods

PubMed^®, Cochrane and Web of Science data bases were searched for randomized controlled clinical trials. Studies evaluating pharmaceutical care-based interventions in type 2 diabetes mellitus published between 2012 and 2017 were included. Glycated hemoglobin was defined as the primary endpoint; blood pressure, triglycerides and cholesterol as secondary endpoints. The random effects model was used in meta-analysis.

Results

Fifteen trials involving 2,325 participants were included. Meta-analysis revealed considerable heterogeneity (I²>97%; p<0.001), reduction in glycated hemoglobin (-1.07%; 95%CI: -1.32; -0.83; p<0.001), glucose (-29.91mg/dL; 95%CI: -43.2; -16.6; p<0.001), triglyceride (19.8mg/dL; 95%CI: -36.6; -3.04; p=0.021), systolic blood pressure (-4.65mmHg; 95%CI: -8.9; -0.4; p=0.032) levels, and increased HDL levels (4.43mg/dL; 95%CI: 0.16; 8.70; p=0.042).

Conclusion

Pharmaceutical care-based clincal and education interventions have significant impact on type 2 diabetes mellitus . The tools Summary of Diabetes Self-Care Activities and the Morisky Medication Adherence Scale may be useful to monitor patients.

Keywords: Diabetes mellitus, type 2; Pharmaceutical services; Pharmacy service, hospital; Pharmacists

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is characterized by pre- and postprandial hyperglycemia, combined with relative insulin insufficiency resulting from inadequate insulin secretion and low insulin sensitivity.¹ Type 2 DM is a chronic disease with alarming growth rates in several countries, and is expected to become a serious health concern over the next decades.^{2 , 3} Type 2 is the most common form of diabetes and has been on the rise alongside cultural and social changes. Diabetes currently affects approximately 415 million people worldwide, with a global prevalence of 8.3% among adults; this number is expected to rise to 592 million, in 2035. Type 2 DM is thought to affect 14.3 million adult individuals in Brazil. Aside from individual costs associated with medical treatment of diabetes, the disease places a major economic burden on countries and respective health systems due to diabetes-related complications.⁴

Ongoing education is useful for patients,¹ since diabetes management is complex and involves glucose monitoring, adherence to treatment, physical activity and dietary changes.⁵ Glycated hemoglobin (HbA1c) reflects blood glucose levels over the last 120 days and is the gold standard biomarker for diabetes control assessment and prediction of severe complications.⁶ According to current guidelines, blood glucose levels should be close to normal in order to prevent or delay complications.¹ However, lack of adherence to treatment is common and may impact glycemic control, with increased mortality rates.⁷ Inadequate glycemic control is associated with increased risk of cardiovascular disease, neuropathy, retinopathy, nephropathy and hospitalization.^{6 , 8} Adherence to treatment is vital to fully benefit from therapeutic regimens. Approximately 20% to 50% of patients with chronic diseases report less than optimal adherence to drug therapy, which hinders effectiveness of treatment.^{9 , 10} Also, high glycemic indices have been reported in patients with poor adherence to treatment.^{11 , 12}

Several factors have been associated with non-adherence to treatment, including social and economic aspects, pharmacotherapy complexity and patients’ beliefs regarding drugs.¹³ As pharmacotherapy specialists, clinical pharmacists contribute to patient care by providing individual guidance (alone or with other health professionals), assisting in planning and monitoring of therapeutic strategies aimed to improve the pathological conditions, treatment and adherence by a process entitled “pharmaceutical care”.^{14 , 15} This may be defined as “responsible provision of pharmacotherapy to achieve outcomes associated with improved quality of life for patients.”¹⁶

Identification of drug-related problems is another a vital aspect of pharmaceutical care aimed to prevent events that may impact on treatment outcomes, such as pharmacotherapy effectiveness, adverse reactions and polypharmacy, which are common among diabetic patients.^{17 - 21} Pharmaceutical care also provides drug-related information to help patients understand pharmacotherapy risks and benefits, so as to improve adherence to treatment and clinical outcomes.¹³

However, decision making in diabetic patient care has not yet been fully understood.²² There is a need to determine which pharmacist interventions are currently applicable in clinical practice. Also, only one meta-analysis of studies investigating pharmaceutical care in T2DM has been published to date.²³ This study examined the hypothesis that pharmaceutical care would make significant contributions to T2DM control, particularly regarding HbA1c reduction in affected patients.

OBJECTIVE

To investigate the impact of pharmacist interventions on glycemic control in type 2 diabetes mellitus patients and other endpoints, such as blood pressure, triglycerides and cholesterol levels.

METHODS

Search strategy

A systematic review of randomized controlled clinical trials investigating the impact of pharmacist interventions in T2DM management was used as a reference for study selection and identification of new studies.²⁴ The following databases were searched: PubMed^®, Cochrane Central Register of Controlled Trials and Web of Science. Search strategies are detailed in appendix A.

Date of publication

Studies published between January 2012 and December 2014 were selected. Results of new searches were limited to articles published between January 2015 and October 2017.

Study selection

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations were used for systematic review and meta-analysis.²⁵ Studies with the following characteristics were selected: population comprising participants aged 18 years or older, with a diagnosis of T2DM; health team comprising one pharmacist capable of providing pharmaceutical care via clinical and/or educational interventions for management of participants with T2DM; comparing standard medical, nursing, and community pharmacy care, and defining HbA1c as the primary endpoint, and systolic (SBP) and diastolic blood pressure (DBP), triglycerides (TG) and cholesterol (low – LDL- and high density – HDL - lipoprotein) levels and adherence to treatment as secondary endpoints; conducted in outpatient clinics, hospitals and community pharmacies; prospective randomized controlled clinical trial design; published in English.

Studies conducted exclusively with participants suffering from type 1 diabetes mellitus , diabetes insipidus or gestational diabetes, involving interventions based exclusively on educational programs or leaflets, defining fasting blood glucose levels as primary endpoint, retrospective studies and non-randomized controlled clinical trials were excluded.

Risk of bias assessment

The Cochrane collaboration tool was used to assess selection, performance, detection, attrition, reporting and other biases. Selected studies were classified as having low, high or unclear risk of bias.

Data extraction

Selected studies were individually evaluated by a single author. Data were extracted in standard format using Microsoft Excel, and consisted of study characteristics, participant characteristics, pharmacist interventions carried out and outcome measures.

Statistical analysis

Statistical analyses were conducted using software (STATA 13; Statacorp, Texas, USA). The random effects model was selected to account for heterogeneity of studies included in the meta-analysis; I² was calculated to assess the magnitude of heterogeneity between studies (I² >50% and I² >75% indicate substantial and considerable heterogeneity, respectively). The χ² test was used to assess significance of heterogeneity (p<0.10).

Outcome measures

Outcome measures were defined as changes between the Intervention and the Control Group. Primary (HbA1c) and secondary (SBP, DBP, fasting glucose, TG, LDL and HDL cholesterol levels) endpoint measures were expressed as mean differences and 95% confidence intervals (95%CI). The findings were expressed using conventional measures: percentage for HbA1c; mmHg for SBP and DBP; and mg/dL for TG, LDL and HDL. The level of significance was set at 5%. Whenever results extracted from selected studies were expressed as mmol/L, these were converted to mg/dL.

RESULTS

Study selection

The systematic used as reference for this study yielded 36 clinical trials.²⁴ Of these, 25 were excluded due to non-conformity with selected time, and 11 were rated eligible. Four out of 11 eligible studies failed to define HbA1c as the primary endpoint. The final sample comprised seven studies.^{21 , 26 - 31}

The database search strategy adopted yielded 185 results. Seven duplicates were eliminated in the screening process. Following analysis of title and abstract of 161 articles, 17 were selected. Of these, five were excluded since they were not available in full text; two for not defining HbA1c as the primary endpoint and two for not being specific for T2DM. The remaining eight articles were included in the analysis. Overall, 15 articles were included in the systematic review and 10 in the meta-analysis ( Figure 1 ).

Study characteristics

Studies included in the systematic review were conducted in outpatient clinics and community pharmacies of different countries, as follows: three in Brazil, three in China, one in Malaysia, one in the United Kingdom, one in Singapore, one in Taiwan, one in Iran, one in Iraq, two in Jordan, and one in the Turkish Republic of Northern Cyprus. Experimental design was randomized controlled in all cases and one study was multicenter. Follow-up ranged from 3 to 12 months (mean 7.9 months). Clinical trials included participants with HbA1c ranging from 6.5% to 9%. Detailed description of studies included is given in table 1 .

Table 1. Characteristics of studies included.

Reference	Settings	Population	Characterization of the sample	Follow-up	Interval of intervention	Pharmacist interventions	Control	Clinical endpoint measures
Mahwi et al.⁽²¹⁾	Diabetes center in Iraq	Type 2 diabetics aged 30 to 80 years	n=65/65* Lost to follow-up: 3/4* Age: 52.0±7, 86/53.4±10.81^† Sex: 71.0%/67.2% female	3 months	Monthly	Adherence, drug-related problems	Standard care by medical team	HbA1c, fasting glucose and drug-related problems, adherence
Jarab et al.⁽²⁶⁾	Diabetes outpatient service of a teaching hospital in Jordan	Type 2 diabetics aged ≥18 years, HbA1c ≥7.5%	n=85/86* Lost to follow-up: 8/7* Age: 63.4±10.1/65.3±9.2^† Sex: 42.4%/44.2% female	6 months	8 weeks (follow-up telephone calls)	Patient education, drug-related problems, follow-up telephone calls, self-care	Standard care by medical and nursing teams	HbA1c, adherence, blood pressure, TC, HDL, LDL, TG, BMI, self-care (SDSCA)
Wishah et al.⁽²⁷⁾	Diabetes outpatient service of a teaching hospital in Jordan	Type 2 diabetics aged ≥18 years, HbA1c ≥6.5%, use of oral hypoglycemic agent	n=52/54* Lost to follow-up: 2/3* Age: 52.9±9.6/53.2±11.2^† Sex: 61.5%/51.9% female	6 months	Not informed	Patient education, drug- related problems, self-care	Standard care by medical and nursing teams	HbA1c, blood pressure, TC, HDL, LDL, TG, BMI, fasting glucose, self-care (SDSCA)
Chung et al.⁽²⁸⁾	Teaching hospital in Malaysia	Type 2 diabetics aged ≥21 and <75 years, HbA1c ≥8%, use of oral hypoglycemic agent	n=120/121* Lost to follow-up: NR Age: 59.7±9.5/58.5±8.3^† Sex: 58.3%/53.7% female	12 months	3 to 4 months with monthly follow-up telephone calls	Medication review, diabetes education	Usual pharmacy services	HbA1c, fasting glucose, adherence
Ali et al.⁽²⁹⁾	Community pharmacies in the United Kingdom	Type 2 diabetics aged ≥18 years, HbA1c ≥7%, use of oral hypoglycemic agent	n=25/23* Lost to follow-up: 2/0* Age: 66.4±12.7/66.8±10.2^† Sex: 43.5%/56.5% male	12 months	Monthly in the first 2 months, then every 3 months	Medication review, patient education, referral to other healthcare professionals	Standard care by medical and nursing teams and community pharmacies	HbA1c, fasting glucose, blood pressure, LDL, HDL, TG, BMI, DQoL, HRQoL, adherence, diabetes knowledge test (DKT), SIMS
Mourão et al.⁽³⁰⁾	Primary Care Units in Brazil	Type 2 diabetics aged ≥18 years, HbA1c ≥7%, post-prandial glucose ≥180mg/dL, use of oral hypoglycemic agent	n=65/64* Lost to follow-up: 12/9* Age: 60.0±10.2/61.3±9.9^† Sex: 68.0%/66.0% female	12 months	Monthly	Drug-related problems, diabetes education	Standard care	HbA1c, blood pressure, LDL, HDL, TG, BMI, drug-related problems
Chan et al.⁽³¹⁾	Diabetes clinic of a public hospital in Hong Kong	Type 2 diabetics aged ≥18 years, HbA1c ≥8%, polypharmacy, use of oral hypoglycemic agent	n=51/54* Lost to follow-up: 0/0* Age: 63.2±9,5/61.74±11.2^† Gender: 58.8%/51.9% male	9 months	Not reported	Patient education, drug related problems	Standard care by medical team	HbA1c, blood pressure, LDL, HDL, TG, BMI, adherence, cardiovascular risk, cost-effectiveness
Korcegez et al.⁽³²⁾	Diabetes outpatient service in a public hospital in Turkish Republic of Northern Cyprus	Type 2 diabetics diagnosed at least 6 months prior to the study, HbA1c >7% and use of oral hypoglycemic agent	n=75/77* Lost to follow-up: 4/3* Age: 61.80±10.38/62.22±9.54^† Sex: 77.3%/74.0% female	12 months	2 months	Patient education, drug-related problems, self-care	Standard care by medical and nursing teams	HbA1c, blood pressure, TC, HDL, LDL, TG, BMI, fasting glucose, abdominal circumference, self-care (SDSCA)
Siaw et al.⁽³³⁾	Four outpatient services in Singapore	Type 2 diabetics aged ≥21 years, HbA1c ≥7%, polypharmacy and multiple comorbidities	n=214/197* Lost to follow-up: 3/1* Age: 59.2±8.2/60.1±8.1^† Sex: 52.3%/60.9% male	6 months	4 to 6 weeks	Patient education, drug-related problems, insulin dose adjustment based on symptoms (SIGN algorithm), follow-up telephone calls	Standard care by medical team	HbA1c, systolic blood pressure, LDL, TG, quality of life (PAID), satisfaction with treatment (DTSQ), use of health services, economic analysis
Cani et al.⁽³⁴⁾	Diabetes outpatient service at a teaching hospital in São Paulo	Type 2 diabetics aged ≥45 years, HbA1c ≥ 8.0%, use of insulin	n=37/41* Lost to follow-up: 3/5* Age: 61.91±9.58/61.58±8.14^† Sex: 34.0%/36% male	6 months	Not informed	Patient education, drug-related problems, insulin administration technique	Standard care	HbA1c, knowledge about diabetes, knowledge about drugs, adherence, insulin administration technique, glucose monitoring, quality of life (QoL)
Aguiar et al.⁽³⁵⁾	University secondary care hospital in São Paulo	Type 2 diabetics diagnosed at least 6 months prior to the study, HbA1c ≥7%, aged between 40 and 79 years, use of oral antidiabetic agent	n=36/37* Lost to follow-up: 0/0* Age: 61.1.6±7.9/62.4±8.2^† Sex: 69.4%/64,9% female	12 months	2 to 6 months (depending on glucose levels) and follow-up telephone calls between visits	Patient education, drug- related problems, insulin administration technique, follow-up telephone calls	Standard care by medical and nursing teams	HbA1c, blood pressure, LDL, adherence
Chen et al.⁽³⁶⁾	Nantou Hospital, in Taiwan	Type 2 diabetics aged ≥65 years, with HbA1c ≥9%	n=50/50* Lost to follow-up: NR Age: 72.16±6.6/72.76±5.9^† Sex: 50%/50% male and female	6 months	Monthly follow-up telephone calls	Patient education, drug-related problems, insulin administration technique, referral to other professionals, follow-up telephone calls	Standard care	HbA1c, fasting glucose, percentage of hospitalizations, economic analysis
Jahangard-Rafsanjani et al.⁽³⁷⁾	Community pharmacy in Teheran, Iran	Type 2 diabetics with HbA1c >7% and use of oral hypoglycemic agent	n=51/50* Lost to follow-up: 6/10* Age: 57.6±8.3/55.9±8.7*^† Sex: 25%/26% female	5 months	Monthly	Patient education, drug- related problems, follow-up telephone calls, self-care	Standard care by medical team	HbA1c, BMI, blood pressure, adherence, self-care (SDSCA)
Xin et al.⁽³⁸⁾	Tongde Hospital, Hangzhou province, China	Type 2 diabetics aged ≥18 years, no use of insulin over the last 18 months	n=120/120* Lost to follow-up: 6/7* Age: 58.8±14.4/59.2±14.2^† Sex: 51.8%/50.4% male	12 months	Not informed	Patient education, insulin administration technique, follow-up telephone calls	Standard care by medical team	HbA1c, adherence
Shao et al.⁽³⁹⁾	University hospital in Nanjing province, China	Type 2 diabetics aged ≥18 years, HbA1c ≥7%, diagnosed 3 months before or earlier, and use of oral hypoglycemic agent	n=20/120* Lost to follow-up: 20/21* Age: 58.86±10.59/59.20±10.34^† Sex: 51%/475% male	6 months	2 months (in-person) and monthly follow-up telephone calls	Patient education, follow-up telephone calls	Standard care by medical team	HbA1c, adherence, blood pressure, TC, HDL, LDL, TG, BMI, fasting glucose

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* relation between intervention and Control Group; ^† age in years (mean±standard deviation).

HbA1c: glycated hemoglobin; TC: total cholesterol; HDL: high density lipoprotein; LDL: low density lipoprotein; TG: triglycerides; BMI: body mass index; SDSCA: Summary of Diabetes Self-Care Activities Questionnaire; NR: not reported; DQoL: Diabetes Quality of Life Brief Clinical Inventory; HRQoL: Health-Related Quality of Life; DKT: Diabetes Knowledge Test; SIMS: Satisfaction with Information Received About Medicines; PAID: Problem Areas in Diabetes Questionnaire; DTSQ: Diabetes Treatment Satisfaction Questionnaire; QoL: Quality of Life.

Risk of bias

As regards selection bias, random sequence generation was thought to be adequate in most studies (10/15; 66.7%). Randomization strategy was not reported in four studies (4/15; 26.7%). High risk of bias was observed in one study (1/15; 6.7%) in which participants were randomized according to medical record number.³² Fourteen studies (14/15; 93.4%) failed to describe methods used to conceal random allocation sequences, and only one study reported auditing to ensure allocation concealment (multicenter study).³³

As regards performance bias, no studies reported blinding to pharmacist’s activities, and exchange of information between participants may have occurred in 14 studies conducted in a single setting, except the multicenter study by Siaw et al . ³³ That trial was thought to involve high risk of bias regarding blinding of participants and professionals, since participants in the Control Group were able to consult pharmacists, if required.³⁴

As regards detection bias, only one study reported blinding of raters, who were therefore unaware of groups being evaluated.³⁵ The remaining studies were thought to have unclear risk of bias, given measures employed to assess clinical outcomes were not described.

Attrition and reporting biases were limited to one study that retained high risk of bias due to lack of description of one of the secondary endpoints.²⁷

As for other biases, only two studies were thought to be free from other sources of bias (2/15; 13.4%). Thirteen studies included in this systematic review and meta-analysis (13/15; 86.7%) were thought to have unclear risk of bias, given limitations presented by authors were deemed insufficient to estimate whether significant risk of bias might impact participant outcomes ( Figure 2 and Appendix B).

Population characteristics

Studies included in this systematic review involved 2,325 participants, with samples ranging from 36 to 214 participants. The proportion of male participants ranged from 22% to 75%. Mean age ranged from 52 to 72 years. Mean baseline HbA1c levels corresponded to 9.06% and 8,79% in the Intervention and Control Group, respectively. Aside from T2DM, most studies included emphasized multiple comorbidities related to secondary clinical endpoints, such as dyslipidemia, hypertension and obesity ( Table 1 ).

Pharmacist interventions

Interventions were conducted during in-person pharmaceutical visits or via follow-up telephone calls (7/15; 46.7%). However, details of interventions conducted via follow-up telephone calls were not provided in all studies. All clinical trials emphasized patient education activities (15/15; 100%) and collaboration with medical teams (14/15; 93.4%). However, when search terms “drug-related problems” (12/15; 80.0%) or “medication review” (2/15; 26.7%) were used, instruments applied failed to be described. Two studies^{21 , 31} defined frequency of drug-related problems as a clinical outcome of participants, and only two^{30 , 35} described the use of Pharmacotherapy WorkUp⁴⁰ for the same purpose.

“Drug related problems” and “medication review ” tools were used to identify and solve drug-related problems during patient follow-up. These tools comprise key components of pharmacist interventions, such as: Feedback – recommendations regarding pharmacological treatment forwarded to medical teams in order to solve problems identified and optimize pharmacotherapy (adding, replacing or discontinuing medications, as well as dose adjustments). Follow-up telephone calls – pharmaceutical advice provided over the phone and assessment of adverse events. Patient education – educational interventions related to diabetes and its treatment for improved patient adherence, such as providing information about medications, adverse reactions, administration route and storage (particularly insulin), training aimed at recognition and correction of hypoglycemia, lifestyle changes (smoking cessation, alcoholism, proper diet and foot inspection), self-care promotion (glucose monitoring). All patients received verbal instructions; educational materials, such as leaflets, were also provided in some cases.

In one study, the clinical pharmacist was allowed to adjust insulin doses in naïve patients based on hypoglycemia signs/symptoms. An algorithm was validated for that purpose.³³

In two studies^{29 , 36} (2/15, 26.7%) participants were referred to other professionals, such as dieticians and nurses.

The Control Group consisted of standard care provided in outpatient settings and community pharmacies, excluding interventions provided by clinical pharmacists, or diabetes education provided by other healthcare professionals, such as physicians and nurses ( Table 1 ).

Adherence

Adherence to treatment was a clinical endpoint in ten studies. The Morisky Medication Adherence Scale (MMAS-8 and MMAS-4) was used to assess participant adherence at baseline and at the end of the follow-up period. Significant improvement in adherence in the Intervention Group as compared to the Control Group was reported in all studies (p<0.05).

Meta-analysis

Heterogeneity analysis

Ten studies were included in the meta-analysis,^{21 , 27 - 29 , 32 , 34 , 36 - 39} all of them with high heterogeneity for all endpoints (I² 97% to 99%; p<0.001). The efficacy of pharmaceutical care to promote reduction of SBP, HbA1c, fasting glucose and TG levels and increase of HDL levels was demonstrated in all studies, in spite of significant heterogeneity. However, the outcomes LDL levels and DBP had no statistically significant differences.

Glycated hemoglobin levels

With respect to HbA1c, ten studies^{21 , 27 - 29 , 32 , 34 , 36 - 39} including 715 participants with mean baseline levels of 9.0% were selected. Meta-analysis revealed a mean difference of – 1.07% (95%CI: -1.32; -0.83; p<0.001). The impact of pharmacist interventions on HbA1c reduction in the Control Group is shown in the forest plot ( Figure 3 ).

Fasting blood glucose levels

Six studies^{21 , 27 - 29 , 32 , 39} involving 457 participants revealed mean fasting blood glucose level reduction of – 29.91mg/dL (95%CI: -43.2; -16.6; p<0.001).

Triglycerides

Four studies^{27 , 29 , 32 , 39} involving 272 participants were included, with mean TG level reduction of – 19.8mg/dL (95%CI: -36.6; -3.04; p=0.021).

LDL and HDL

Variations in LDL and HDL levels were non-significant, with mean HDL level increase of 4.43mg/dL (95%CI: 0.16; 8.70; p=0.042), and mean LDL level reduction of – 5.263mg/dL (95%CI: -10.7; 0.18; p=0.058).^{27 , 29 , 32 , 39}

Systolic and diastolic blood pressure

Only SBP differed significantly (mean reduction, - 4.65mmHg; 95%CI: -8.9; -0.4; p=0.032) across all four studies included. Mean reduction in DBP (–1.81mmHg; 95%CI: -3.7; 0.1; p=0.065) was non-significant.^{29 , 32 , 37 , 39}

Frequency of interventions

Six studies involving frequent interventions (monthly or every two months) were included, with mean baseline HbA1c of 8.9%.^{21 , 29 , 32 , 36 , 37 , 39} Mean reduction of – 1.01% (p<0.001) was observed (95%CI: -1.2; -0.7). Mean reduction of – 1.17% (p<0.001; 95%CI: - 1.4; -0.8) was also observed in four studies that failed to report intervals between interventions or reporting intervention interval of three months.^{27 , 28 , 34 , 38} However, mean baseline HbA1c in this group was 9.48%.

DISCUSSION

According to meta-analysis results, all pharmacist interventions promoted significant reduction of SBP and HbA1c, fasting blood glucose, TG and HDL levels, with no impact on LDL levels or DBP. Santschi et al ., ⁴¹ conducted a meta-analysis of 39 randomized clinical trials with 14,224 participants with high cardiovascular risk (hypertension, dyslipidemia, diabetes, smoking and obesity) and observed SBP (− 7.6mmHg; 95%CI: -9.0; -6.3; I² = 67%) and DBP (− 3.9mmHg; 95%CI: -5.1; 2.8; I² = 83%) reduction in response to pharmacist interventions, such as patient education, feedback to medical teams, and identification of drug-related problems. Nonetheless, subgroup analysis to investigate differences between diabetic and non-diabetic participants in that study Santschi et al.,⁴¹ failed to reveal significant differences in SBP (– 6.4mmHg; 95%CI: -7.8; -5.1; p=0.37) and DBP (– 4.5mmHg; 95%CI: -6.3; -2.8; p=0.51). Results of this meta-analysis are in keeping with findings reported by Santschi et al.,⁴¹ with significant SBP reduction and no impact on DBP.

Deters et al.,⁴² included six studies in a meta-analysis of 640 participants in randomized clinical trials investigating the impact of pharmaceutical care on type 1 and type 2 diabetes. Mean HbA1c difference of – 0.66% (95%CI: - 0.86; -0.45) and non-significant heterogeneity (I² =7.9%; p=0.3659) were reported. Deters et al.,⁴² also considered the meta-analytic effect of pharmacist interventions and evaluated mean HbA1c differences associated with drug-related problems/medication review (-0.79%) and feedback to medical team (-0.81%), and determined the impact of each intervention on the educational component: diabetes-related complications (-0.60%); knowledge about medications (-0.74%); diet, physical exercise and smoking cessation (-0.66%); self-monitoring of blood glucose analysis (-0.74%); definition of individual targets (-0.81%); adherence (-0.60%) and knowledge about diabetes (-0.54%). This study did not include meta-analysis per intervention, since not all clinical trials selected provided detailed description of components, such as number of patients submitted to a given intervention (educational interventions in particular). Only three of the studies included^{27 , 32 , 37} used the Summary of Diabetes Self-Care Activities (SDSCA) to measure the impact of pharmaceutical care in patient self-care components, such as diet, physical exercise practice, self-monitoring of blood glucose, foot care and smoking cessation.

A meta-analysis of 22 randomized clinical trials involving 1,382 participants with T2DM conducted by Aguiar et al ., ²³ revealed a mean HbA1c reduction of – 0.85% (95%CI: -1.06; -0.65; p<0.0001) and significant (p<0.0001) and substantial (I² =67.3%) heterogeneity. Subgroup analyses were conducted to investigate potential causes of heterogeneity, as follows: country where the study was conducted, type of contact with patients, studies using medication review and frequency of interventions, among others. Low (0% to 40%), non-significant (p>0.10) heterogeneity was observed in studies with the following characteristics: clinical trials conducted in the United States; participants with baseline HbA1c levels ≤9%; community pharmacy settings; lack of educational material provision by pharmacists; pharmacist authorized to alter drug prescriptions; more than one intervention per month and proper randomization. Aguiar et al ., ²³ also observed higher mean HbA1c differences in patients with elevated baseline HbA1c levels. Findings of this study revealed greater HbA1c level reduction in trials with longer intervals between pharmacist interventions. However, those studies reported mean baseline HbA1c levels of 9.48%. Therefore, it can be argued that longer intervals between interventions are not associated with increased reduction of HbA1c levels. Likewise Aguiar et al ., ²³ this study showed that patients with elevated baseline HbA1c levels may benefit more from pharmaceutical care, given the mean baseline HbA1c level of participants included in this meta-analysis was 9.0%.

This study reproduced the analysis conducted by Aguiar et al, . ²³ to investigate potential causes of high heterogeneity between studies. Given the small number of studies (less than ten), meta-regression was not performed; rather, subgroup analysis was repeated using the random effect model according to trial characteristics (participants with baseline HbA1c levels <9%;^{27 , 32 , 34 , 36 , 37} interventions such as drug-related problems^{27 , 32 , 34 , 37 , 40} and medication review ; ^{28 , 29} frequent interventions -monthly or every 2 months;^{21 , 26 , 29 , 30 , 32 , 35 , 40 , 42} outpatient settings^{21 , 26 , 27 , 30 - 35} and community pharmacy;^{29 , 37} ) per sex ( i.e ., studies with larger proportion of males^{29 , 34 , 41 , 42} versus studies with larger proportion of females).^{21 , 27 , 28 , 32 , 37 , 39} All analyses revealed high and significant heterogeneity (I² >98%; p<0.001). Analysis with study exclusion was also conducted. One trial included only elderly patients (≥65 years).³⁸ This was thought to be potentially related to the high, significant heterogeneity observed; hence, sensitivity analysis excluding the aforementioned study was conducted, with similar results: I² = 99.2% (p<0.001). Results were also similar following exclusion of studies with short follow-up^{21 , 37} and inadequate randomization.³² It was not possible to determine whether lack of specific tools such as Pharmacotherapy WorkUp for drug-related problems might have contributed to heterogeneity, because only two studies reported the use of this tool for that specific purpose.^{30 , 35} Even if all 15 studies selected for systematic review had been included in this meta-analysis, results would still probably be similar. Significant heterogeneity may have reflected differences in inclusion criteria between trials. HbA1c levels for inclusion of studies in this meta-analysis ranged from 6.5% to 9%, with mean variations in baseline HbA1c levels of 9.0% and 8.7%, in the Intervention and Control Groups, respectively. Insulin use^{34 , 36 , 38} is yet another potential cause of heterogeneity, as well as age and sex proportions, short follow-up^{21 , 37} and small number of participants.^{29 , 34}

Given the multiculturalism of studies included in this systematic review and meta-analysis, cultural and ethnic differences may also have impacted on clinical outcomes, as may differences between health systems and educational and socioeconomic characteristics of participants. This analysis included studies conducted in different countries and regions around the world (South America, Europe, Eastern Mediterranean, Middle East and Asia), such as those of Chung et al ., ²⁸ and Siaw et al . ,³³ conducted in Malaysia and Singapore, respectively, enrolling participants of three different ethnic groups (Chinese, Malayans and Indians). Also worthy of notice are potential hurdles regarding intervention acceptance, which may vary in countries where pharmaceutical care is not well accepted. Aguiar et al ., ³⁵ were the only authors to describe frequency of interventions and acceptance rates (96.9%) by medical teams.

Methodological limitations of studies included in this meta-analysis must also be accounted for. The significance of pharmaceutical care in multiprofessional settings must be emphasized; however, several studies referred in this analysis described Control Group interventions as “standard care”, with no further specifications. The risk of bias in studies selected for this systematic review and meta-analysis was rated “unclear” regarding almost all aspects considered, as few authors reported allocation concealment methods and blinding of outcome raters. Settings where studies were conducted may have impacted results in some cases. Given the small size of the country in which one of the studies was conducted (Turkish Republic of Northern Cyprus), cross contamination between groups may have occurred.³² Therefore, the Control Group may have obtained data from the Intervention Group, even in studies conducted in a single outpatient setting (Hawthorne experience). In one of the studies, participants in the Control Group had access to baseline laboratory tests and may have mitigated the effects of pharmacist interventions by seeking greater medical attention.³⁰ Also, selected studies did not involve blinding of clinical pharmacists’ activities, with potential increase in care provided by other healthcare professionals in the Control Group. For example, in one trial the clinical pharmacist was allowed to counsel patients in the Control Group, if required.³⁴ Clear description of pharmaceutical care provided to participants in the Intervention Group was seldom given and few studies included SDSCA in the educational key component. Hence, statistical analysis per specific key component could not be performed, supporting results reported by Deters et al.,⁴² Overall, studies included in this meta-analysis reported that pharmacists involved in clinical trials were pharmacotherapy specialists and had been trained in diabetes education. However, data regarding training duration (hours) and healthcare professionals in charge were not always provided. Meta-analysis investigating participant adherence could not be conducted due to the wide variability of methods used to measure outcomes and the lack of standardized measures between studies. Standardization of instruments aimed to assess adherence and enable comparisons of findings across studies is therefore required. Frequency of intervention was not always clearly reported in studies in this analysis; conclusions regarding the ideal frequency of intervention could therefore not be drawn. Studies based on interventions performed every three months (or failing to report intervention intervals) reported greater reduction in HbA1c levels. However, mean baseline levels in this group of studies was greater than 9%, in contrast with less than 9% in studies involving monthly interventions. Hence, greater reduction in HbA1c levels may not be directly related to longer interval between interventions. As suggested by Aguiar et al . ,²³ this analysis supports the hypothesis that patients with higher baseline HbA1c levels in may benefit more from pharmaceutical care.

According to the American Diabetes Association (ADA) and Sociedade Brasileira de Diabetes (SBD), treatment of diabetes mellitus must be determined by an active multiprofessional team, capable of providing continuing education and good quality of care.^{1 , 43} As regards the pharmaceutical profession, SBD refers the Collegiate Resolution (RDC 44/2009) of the National Health Surveillance Agency (ANVISA - Agência Nacional de Vigilância Sanitária ) for delivery of pharmaceutical services – including pharmaceutical care and capillary glucose test,⁴³ while the ADA guidelines recommend assurance of rational use of insulin, and careful dosing supervision by pharmacists.¹ Nevertheless, these guidelines fail to describe other components required for multiprofessional patient care.^{1 , 44} Results of this meta-analysis suggest key components such as drug-related problems/medication review (including feedback to medical teams) , patient education and follow-up telephone calls are associated with satisfactory clinical outcomes regarding reduction of HbA1c levels. Tools aimed to assess self-care ( e.g . SDSCA)⁴⁵ and adherence ( e.g . MMAS-8),⁴⁶ or to identify drug-related problems may be useful in patient follow-up.

This study has some limitations. Not all clinical trials selected for systematic review were included in the meta-analysis due to differences in outcome measure reporting (mean, standard deviation, median, IQR and 95%CI). Only studies expressing measures as mean and standard deviation were included. Also, the objective of this study was to identify recent evidence of pharmacist interventions in T2DM and evaluate related impacts. Studies published between 2012 and 2017 were therefore selected. Extension of this time frame would have allowed the inclusion of a greater number of randomized clinical trials. However, studies published before 2012 would likely not reflect current pharmaceutical practices. Data extraction, review and analysis in this study were performed by a single researcher. Still integrity of data presented in this systematic review with meta-analysis can be guaranteed.

CONCLUSION

This meta-analysis revealed high, significant heterogeneity between studies. Still, the findings suggest pharmaceutical care-related interventions have significant impacts on reduction of systolic blood pressure, glycated hemoglobin, fasting glucose and triglyceride levels, and on increase of HDL levels. The findings also suggest such interventions do not impact on diastolic blood pressure or LDL levels, and that patients with elevated baseline glycated hemoglobin levels may benefit more from pharmaceutical care. However, more randomized clinical trials with better methodological design are warranted for clearer reporting of pharmaceutical intervention outcomes.

Appendix.

Appendix A. . Search strategy.

PubMed^®
1. Diabetes mellitus , type 2 [mh] (107.405)
2. Type 2 diabetes (144.283)
3. T2DM (13.054)
4. Non insulin dependent diabetes mellitus (130.159)
5. NIDDM (120.203)
6. 1 OR 2 OR 3 OR 4 OR 5 (156.111)
7. Pharmaceutical services [mh] (60.102)
8. Pharmaceutical care (86.683)
9. Clinical Pharmacy (71859)
10. Community pharmacy (22.968)
11. Pharmacist* (30.355)
12. 7 OR 8 OR 9 OR 10 OR 11 (170.150)
13. Randomized controlled trial [pt] (441.905)
14. Random* AND Control* (797.089)
15. 13 OR 14 (797.180)
16. 6 AND 12 AND 15 (479)
17. Cochrane Central Register of Controlled Trials filter according to date of publication (57)
Web of Science
1. ts= Type 2 diabetes (153.853)
2. ts = T2DM (13.045)
3. ts = Non insulin dependent diabetes mellitus (10.421)
4. ts = NIDDM (12.313)
5. 1 OR 2 OR 3 OR 4 (168.261)
6. ts = Pharmaceutical services (4.887)
7. ts = Pharmaceutical care (13.954)
8. ts = Clinical pharmacy (8.159)
9. ts = Community pharmacy (6.730)
10.ts = Pharmacist* (26.322)
11.6 OR 7 OR 8 OR 9 OR 10 (47.569)
12.ts = (Random* AND Control*) (586.584)
13. 5 AND 11 AND 12 (211)
14. Filter according to date of publication (59)
Cochrane Central Register of Controlled Trials
1. [mh Diabetes mellitus , type 2] (11.714)
2. Type 2 Diabetes (28.274)
3. T2DM (2.910)
4. Non insulin dependent diabetes mellitus (11.653)
5. NIDDM (1.115)
6. 1 OR 2 OR 3 OR 4 OR 5 (29.876)
7. [mh “Pharmaceutical services”] (1.698)
8. Pharmaceutical care (4.673)
9. Clinical pharmacy (10.716)
10. Community pharmacy (1.874)
11. Pharmacist* (4.188)
12. 7 OR 8 OR 9 OR 10 OR 11 (16.839)
13. 6 AND 12 (1.941)
14. Trials filtered according to date of publication (69)

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Appendix B. . Risk of bias.

	Selection bias		Performance bias	Detection bias	Attrition bias	Reporting bias	Other biases

Reference	Random sequence generation	Allocation concealment	Blinding of participants and professionals	Blinding of outcome raters	Incomplete outcomes	Selective outcome reporting	Other sources of bias
Mahwi et al.⁽²¹⁾	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Unclear risk of bias
Jarab et al.⁽²⁶⁾	Low risk	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Unclear risk of bias
Wishah et al. ⁽²⁷⁾	Low risk	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	High risk	High risk	Unclear risk of bias
Chung et al.⁽²⁸⁾	Unclear risk of bias	Potential risk of bias	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Unclear risk of bias
Ali et al.⁽²⁹⁾	Low risk	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Unclear risk of bias
Mourão et al.⁽³⁰⁾	Low risk	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Unclear risk of bias
Chan et al.⁽³¹⁾	Low risk	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Unclear risk of bias
Korcegez et al.⁽³²⁾	High risk	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Unclear risk of bias
Siaw et al.⁽³³⁾	Low risk	Low risk	Low risk	Unclear risk of bias	Low risk	Low risk	Low risk
Cani et al.⁽³⁴⁾	Low risk	Unclear risk of bias	High risk	Unclear risk of bias	Low risk	Low risk	Unclear risk of bias
Aguiar et al.⁽³⁵⁾	Low risk	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Low risk	Low risk
Chen et al.⁽³⁶⁾	Low risk	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Unclear risk of bias
Jahangard-Rafsanjani et al.⁽³⁷⁾	Low risk	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Unclear risk of bias
Xin et al.⁽³⁸⁾	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Risco de viés incerto
Shao et al.⁽³⁹⁾	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Unclear risk of bias	Low risk	Low risk	Unclear risk of bias

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Einstein (Sao Paulo). 2020 Jan 27;18:eRW4686. [Article in Portuguese]

Intervenções farmacêuticas no diabetes mellitus tipo 2: uma revisão sistemática e metanálise de ensaios clínicos randomizados

Marcel Nogueira ¹, Leonardo Jun Otuyama ¹, Priscilla Alves Rocha ¹, Vanusa Barbosa Pinto ¹

RESUMO

Objetivo

Identificar o impacto das intervenções providenciadas pelo cuidado farmacêutico no diabetes mellitus tipo 2.

Métodos

Buscas por ensaios clínicos randomizados controlados foram realizadas nas bases PubMed^®, Cochrane e Web of Science . Foram incluídos estudos publicados entre 2012 e 2017, que avaliaram o impacto do cuidado farmacêutico no diabetes mellitus tipo 2. A hemoglobina glicada foi o desfecho primário, e os secundários foram pressão arterial, triglicérides e colesterol. O modelo de efeitos aleatórios foi utilizado na metanálise.

Resultados

Foram incluídos 15 estudos envolvendo 2.325 participantes. A metanálise demonstrou heterogeneidade elevada (I²>97%; p<0,001), redução nos níveis de hemoglobina glicada (-1,07%; IC95%: -1,32; -0,83; p<0,001), glicose (-29,91mg/dL; IC95%: -43,2; -16,6; p<0,001), triglicérides (19,8mg/dL; IC95%: -36,6; -3,04; p=0,021), pressão arterial sistólica (-4,65mmHg; IC95%: -8,9; -0,4; p=0,032) e aumento do colesterol HDL (4,43mg/dL; IC95%: 0,16; 8,70; p=0,042).

Conclusão

As intervenções clínicas e educacionais providenciadas pelo cuidado farmacêutico têm impacto significativo no diabetes mellitus tipo 2. Ferramentas como o Summary of Diabetes Self-Care Activities e a Morisky Medication Adherence Scale podem ser úteis no acompanhamento dos pacientes.

Keywords: Diabetes mellitus tipo 2, Assistência farmacêutica, Serviço de farmácia hospitalar, Farmacêuticos

INTRODUÇÃO

O diabetes mellitus tipo 2 (DMT2) é caracterizado por hiperglicemia pré e pós-prandial, com insuficiência insulínica relativa, tendo origem na secreção inadequada de insulina com sensibilidade reduzida.¹ É uma doença crônica, que cresce de forma alarmante em diversos países, e deve ser considerado um grave problema de saúde nas próximas décadas.^{2 , 3} O tipo 2 é a forma mais comum do diabetes e tem aumentado em paralelo às mudanças culturais e sociais. Mundialmente estima-se que 415 milhões de pessoas tenham diabetes, com prevalência de 8,3% entre adultos, e estima-se que este número alcance 592 milhões em 2035. No Brasil, existem 14,3 milhões de adultos com diabetes. Além dos gastos do indivíduo com diabetes, devido ao custo da terapia medicamentosa, a doença também gera impacto econômico aos países e a seus respectivos sistemas de saúde, devido às complicações causadas pela doença.⁴

A educação contínua é útil aos pacientes,¹ já que o manejo do diabetes é complexo e requer esforços que envolvem o monitoramento glicêmico, a adesão ao tratamento, atividade física e mudanças na dieta.⁵ Para avaliar a efetividade do tratamento, a hemoglobina glicada (HbA1c) é um biomarcador utilizado como padrão-ouro para o controle do diabetes, pois reflete os níveis de glicose dos últimos 120 dias, sendo preditor de complicações crônicas severas.⁶ As diretrizes recomendam que os níveis glicêmicos estejam próximos dos níveis normais, para prevenir ou retardar complicações.¹ Contudo, a não adesão ao tratamento é comum, pode impactar no controle glicêmico e aumentar a mortalidade.⁷ Um controle glicêmico inadequado aumenta o risco de doenças cardiovasculares, neuropatia, retinopatia, nefropatia e hospitalizações.^{6 , 8} A adesão ao tratamento é um passo crucial para o benefício completo do regime terapêutico. Sabe-se que aproximadamente 20% a 50% dos pacientes com doenças crônicas relatam não ter adesão adequada aos medicamentos, o que compromete a efetividade do tratamento.^{9 , 10} Além disso, aqueles que não demonstram adesão apresentam níveis glicêmicos elevados.^{11 , 12}

Existem muitos fatores envolvidos na não adesão ao tratamento, incluindo aspectos sociais e econômicos, a complexidade da farmacoterapia e problemas relacionados às crenças do paciente sobre os medicamentos.¹³ Como especialista em farmacoterapia, o farmacêutico clínico contribui para o cuidado ao paciente, auxiliando-o individualmente ou com outros profissionais de saúde, na projeção e no monitoramento de planos terapêuticos, para melhorar o estado patológico, o tratamento e a adesão, por meio de um processo chamado “cuidado farmacêutico”.^{14 , 15} O cuidado farmacêutico pode ser definido como “a provisão responsável da farmacoterapia a fim de alcançar resultados que melhorem a qualidade de vida dos pacientes”.¹⁶

Também como parte do cuidado farmacêutico, a identificação de problemas relacionados aos medicamentos ( drug-related problems ) é essencial para evitar eventos que podem afetar o resultado do tratamento, por exemplo, a efetividade da farmacoterapia, as reações adversas e a polifarmácia, que frequentemente são comuns em pacientes com diabetes.^{17 - 21} O cuidado farmacêutico também providencia informações sobre os medicamentos, fazendo com que o paciente entenda os riscos e os benefícios da farmacoterapia, melhorando a adesão e o desfecho clínico do tratamento.¹³

Entretanto, ainda é necessário compreender as tomadas de decisões no cuidado dos pacientes com diabetes.²² Existe a necessidade de identificar quais intervenções farmacêuticas são aplicáveis à prática clínica atualmente. Além disso, há somente uma metanálise sobre o cuidado farmacêutico no DMT2.²³ A hipótese do nosso estudo é que o cuidado farmacêutico contribui significativamente para o controle do DMT2, reduzindo principalmente a HbA1c dos pacientes.

OBJETIVO

Avaliar o impacto das intervenções farmacêuticas no controle glicêmico de pacientes com diabetes mellitus tipo 2 e outros desfechos, como pressão arterial, triglicérides e colesterol.

MÉTODOS

Estratégia de busca

Inicialmente, uma revisão sistemática de ensaios clínicos randomizados controlados sobre o impacto das intervenções farmacêuticas no manejo do DMT2 foi utilizada como referência para inclusão de alguns estudos e, para encontrar novos estudos, também foi adotada a mesma estratégia de busca utilizada pela referida revisão sistemática.²⁴ Foram realizadas buscas nas bases de dados PubMed^®, Cochrane Central Register of Controlled Trials e Web of Science . A estratégia de busca encontra-se disponível no apêndice A.

Data de publicação

Foram selecionados estudos publicados entre janeiro de 2012 e dezembro de 2014. Os resultados das novas buscas foram limitados a publicações de janeiro de 2015 a outubro de 2017.

Seleção dos estudos

A recomendação Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) foi utilizada para conduzir a revisão sistemática e metanálise.²⁵ Foram selecionados estudos com as seguintes características: com população correspondente a participantes com idade maior ou igual a 18 anos, diagnosticados com DMT2; em que o farmacêutico estivesse inserido na equipe de saúde e apto a realizar o cuidado farmacêutico com intervenções clínicas e/ou educacionais no manejo de participantes com DMT2; que comparassem cuidados usuais da equipe médica, da enfermagem e de farmácias comunitárias; cujo desfecho primário tivesse sido a HbA1c e os secundários pressão arterial sistólica (PAS) e diastólica (PAD), triglicérides (TG), colesterol (lipoproteína de baixa – LDL − e alta – HDL − densidade) e adesão ao tratamento; realizados em clínicas ambulatoriais, hospitais e farmácias comunitárias; e cujo desenho fosse o de ensaios clínicos randomizados controlados prospectivos, publicados em inglês.

Foram excluídos estudos que envolveram exclusivamente participantes com diabetes mellitus tipo 1, diabetes insipidus e diabetes gestacional; tiveram intervenções baseadas apenas em programas educacionais ou no uso de folhetos; cujo desfecho primário foi a glicose (glicemia de jejum); e estudos retrospectivos e ensaios clínicos não randomizados controlados.

Avaliação do risco de viés

Foi utilizada a ferramenta de colaboração Cochrane, para avaliar o risco de viés de seleção, performance, detecção, atrito, relato e outros vieses. Os estudos selecionados foram classificados como com baixo risco de viés, alto risco de viés e risco de viés incerto.

Extração dos dados

Os estudos incluídos foram avaliados individualmente por um único autor. Os dados foram extraídos em formato padrão no Microsoft Excel e consistem em características dos estudos, características dos participantes, intervenções farmacêuticas realizadas e as medidas de desfecho.

Análise estatística

Todas as análises estatísticas foram realizadas usando o software STATA 13 (Statacorp, Texas, EUA). Devido à heterogeneidade dos estudos incluídos na metanálise, o modelo de efeitos aleatórios ( random-effects model ) foi selecionado. O I² foi calculado para avaliar a magnitude entre os estudos, sendo que I² >50% indica heterogeneidade substancial e >75%, heterogeneidade considerável. O teste χ² foi utilizado para avaliar a significância da heterogeneidade (p<0,10).

Medidas de desfecho

Os resultados das medidas de desfecho foram as alterações entre o grupo intervenção e o controle. A diferença média e o intervalo de confiança de 95% (IC95%) foram utilizados para o desfecho primário (HbA1c) e secundários – glicose (glicemia de jejum), PAS, PAD, TG, colesterol (LDL e HDL). Os resultados foram apresentados com as medidas tradicionais: percentagem para HbA1c; mmHg para PAS e PAD; e mg/dL para TG, LDL e HDL. O nível de significância estatística foi considerado como 5%. Resultados extraídos dos estudos selecionados expressos em mmol/L foram convertidos para mg/dL.

RESULTADOS

Seleção dos estudos

Foram extraídos da revisão sistemática utilizada como referência para este estudo 36 ensaios clínicos.²⁴ A partir dessa revisão sistemática, 25 ensaios foram excluídos, pois estavam fora do período referido de publicação, sendo 11 elegíveis. Dos estudos elegíveis, quatro não apresentaram HbA1c como desfecho primário. Ao final, sete estudos foram incluídos.^{21 , 26 - 31}

A estratégia de busca utilizada nas bases de dados resultou em 185 resultados. Na triagem, sete duplicadas foram removidas. Após a análise dos títulos e dos resumos de 161 artigos, 17 foram selecionados. Destes estudos, cinco foram excluídos, pois os artigos não estavam disponíveis na íntegra; dois não apresentaram a HbA1c como desfecho primário; e dois não foram específicos para DMT2. As buscas nas bases de dados resultaram em oito artigos incluídos. No total, 15 artigos foram incluídos na revisão sistemática e 10 na metanálise ( Figura 1 ).

Características dos estudos

Os estudos incluídos na revisão sistemática foram conduzidos em clínicas ambulatoriais e farmácias comunitárias de diferentes países, sendo três realizados no Brasil, três na China, um na Malásia, um no Reino Unido, um em Singapura, um em Taiwan, um no Irã, um no Iraque, dois na Jordânia e um na República Turca de Chipre do Norte. O desenho dos estudos incluídos foi randomizado controlado e um multicêntrico. A duração do acompanhamento variou entre 3 a 12 meses, com média de 7,9 meses. Os ensaios clínicos incluíram participantes com HbA1c entre 6,5% a 9%. A descrição detalhada dos estudos incluídos está representada na tabela 1 .

Tabela 1. Características dos estudos incluídos.

Referência	Cenário	População	Caracterização da amostra	Tempo de acompanhamento	Intervalo de intervenção	Intervenções farmacêuticas	Controle	Medidas de desfecho clínico
Mahwi et al.⁽²¹⁾	Centro de diabetes no Iraque	Diabéticos tipo 2, com idade entre 30 e 80 anos	n=65/65* Perdidos no acompanhamento: 3/4* Idade: 52,0±7,86/53,4±10,81^†Sexo: 71,0%/ 67,2% feminino	3 meses	Mensal	Adesão, drug-related problems	Cuidados usuais da equipe médica	HbA1c, glicemia de jejum e drug-related problems, adesão
Jarab et al.⁽²⁶⁾	Ambulatório de diabetes de um hospital escola na Jordânia	Diabéticos tipo 2 com idade ≥18 anos, HbA1c ≥7,5%	n=85/86* Perdidos no acompanhamento: 8/7* Idade: 63,4±10,1/65,3±9,2^†Sexo: 42,4%/44,2% feminino	6 meses	8 semanas (acompanhamento telefônico)	Educação do paciente, drug-related problems , acompanhamento telefônico, autocuidado	Cuidados usuais da equipe médica/enfermagem	HbA1c, adesão, pressão arterial, CT, HDL, LDL, TG, IMC, autocuidado (SDSCA)
Wishah et al.⁽²⁷⁾	Ambulatório de diabetes de um hospital escola na Jordânia	Diabéticos tipo 2 com idade ≥18 anos, HbA1c ≥6,5%, em uso de hipoglicemiante oral	n=52/54* Perdidos no acompanhamento: 2/3* Idade: 52,9±9,6/53,2±11,2^†Sexo: 61,5%/51,9% feminino	6 meses	Não informado	Educação do paciente, drug- related problems , autocuidado	Cuidados usuais da equipe médica/enfermagem	HbA1c, pressão arterial, CT, HDL, LDL, TG, IMC, glicemia de jejum, autocuidado (SDSCA)
Chung et al.⁽²⁸⁾	Hospital escola na Malásia	Diabéticos tipo 2 com idade ≥21 anos e <75 anos, HbA1c ≥8%, em uso de hipoglicemiante oral	n=120/121* Perdidos no acompanhamento: NR Idade: 59,7±9,5/58,5±8,3^†Sexo: 58,3%/53,7% feminino	12 meses	3 a 4 meses com acompanhamento telefônico mensal	Revisão da medicação, educação em diabetes	Serviços usuais de farmácias	HbA1c, glicemia de jejum, adesão
Ali et al.⁽²⁹⁾	Farmácias comunitárias do Reino Unido	Diabéticos tipo 2 com idade ≥18 anos, HbA1c ≥7%, em uso de hipoglicemiante oral	n=25/23* Perdidos no acompanhamento: 2/0* Idade: 66,4±12,7/66,8±10,2^†Sexo: 43,5%/56,5% masculino	12 meses	Mensal pelos 2 primeiros meses e, após, a cada 3 meses	Revisão da medicação, educação do paciente, encaminhamento para outros profissionais de saúde	Cuidados usuais da equipe médica/enfermagem e farmácias comunitárias	HbA1c, glicemia de jejum, pressão arterial, LDL, HDL, TG, IMC, DQoL, HRQoL, adesão, conhecimentos em diabetes (DKT), SIMS
Mourão et al.⁽³⁰⁾	Unidades Básicas de Saúde no Brasil	Diabéticos tipo 2 com idade ≥18 anos, HbA1c ≥7%, glicemia pós-prandial ≥180mg/dL, em uso de hipoglicemiante oral	n=65/64* Perdidos no acompanhamento: 12/9* Idade: 60,0±10,2/61,3±9,9^†Sexo: 68,0%/66,0% feminino	12 meses	Mensal	Drug-related problems , educação em diabetes	Cuidados usuais	HbA1c, pressão arterial, LDL, HDL, TG, IMC, drug-related problems
Chan et al.⁽³¹⁾	Clínica de diabetes de um hospital público de Hong Kong	Diabéticos tipo 2 com idade ≥18 anos, HbA1c ≥8%, polifármacia, em uso de hipoglicemiante oral	n=51/54* Perdidos no acompanhamento: 0/0* Idade: 63,2±9,5/61,74±11,2^†Gênero: 58,8%/51,9% masculino	9 meses	Não reportado	Educação do paciente, drug related problems	Cuidados usuais da equipe médica	HbA1c, pressão arterial, LDL, HDL, TG, IMC, adesão, risco cardiovascular, custo-efetividasde
Korcegez et al.⁽³²⁾	Ambulatório de diabetes de um hospital público da República Turca de Chipre do Norte	Diabéticos tipo 2 com diagnóstico há pelo 6 meses, HbA1c >7% e uso de hipoglicemiante oral	n= 75/77* Perdidos no acompanhamento: 4/3* Idade: 61,80±10,38/62,22±9,54^†Sexo: 77,3%/74,0% feminino	12 meses	2 meses	Educação do paciente, drug-related problems, autocuidado	Cuidados usuais da equipe médica/enfermagem	HbA1c, pressão arterial, CT, HDL, LDL, TG, IMC, glicemia de jejum, circunferência abdominal, autocuidado (SDSCA)
Siaw et al.⁽³³⁾	Quatro ambulatórios médicos em Cingapura	Diabéticos tipo 2 com idade ≥21 anos, HbA1c ≥7%, polifarmácia e múltiplas comorbidades	n= 214/197* Perdidos no acompanhamento: 3/1* Idade: 59,2±8,2/60,1±8,1^†Sexo: 52,3%/60,9% masculino	6 meses	4 a 6 semanas	Educação do paciente, drug-related problems , ajuste de dose de insulina baseado em sintomas (SIGN algorithm ), acompanhamento telefônico	Cuidados usuais da equipe médica	HbA1c, pressão arterial sistólica, LDL, TG, qualidade de vida (PAID), satisfação com o tratamento (DTSQ), uso de serviços de saúde, análise econômica
Cani et al.⁽³⁴⁾	Ambulatório de diabetes de um hospital-escola em São Paulo	Diabéticos tipo 2 com idade ≥45 anos, HbA1c ≥8,0%, em uso de insulina	n=37/41* Perdidos no acompanhamento: 3/5* Idade: 61,91±9,58/61,58±8,14^†Sexo: 34,0%/36% masculino	6 meses	Não informado	Educação do paciente, drug-related problems , técnica de aplicação de insulina	Cuidados usuais	HbA1c, conhecimento em diabetes, conhecimento sobre medicamentos, adesão, técnica de aplicação de insulina, monitoramento glicêmico, qualidade de vida (QoL).
Aguiar et al.⁽³⁵⁾	Hospital universitário secundário em São Paulo	Diabéticos tipo 2 com diagnóstico há pelo menos 6 meses, HbA1c ≥7%, idade entre 40 e 79 anos, em uso de antidiabético oral	n=36/37* Perdidos no acompanhamento: 0/0* Idade: 61,1,6±7,9/62,4±8,2^†Sexo: 69,4%/64,9% feminino	12 meses	2 a 6 meses (dependendo dos níveis glicêmicos) e acompanhamento telefônico no intervalo das consultas	Educação do paciente, drug- related problems , técnica de aplicação de insulina, acompanhamento telefônico	Cuidados usuais da equipe médica/enfermagem	HbA1c, pressão arterial, LDL, adesão
Chen et al.⁽³⁶⁾	Nantou Hospital, em Taiwan	Diabéticos tipo 2 com idade ≥65 anos, com HbA1c ≥9%	n=50/50* Perdidos no acompanhamento: NR Idade: 72,16±6,6/72,76 ±5,9^†Sexo: 50%/50% masculino e feminino	6 meses	Acompanhamento telefônico mensal	Educação do paciente, drug-related problems , técnica de aplicação de insulina, encaminhamento para outros profissionais, acompanhamento telefônico	Cuidados usuais	HbA1c, glicemia de jejum, percentagem de hospitalizações, análise econômica
Jahangard-Rafsanjani et al.⁽³⁷⁾	Farmácia comunitária no Teerã, Irã	Diabéticos tipo 2 com HbA1c >7% e uso de hipoglicemiante oral	n=51/50* Perdidos no acompanhamento: 6/10* Idade: 57,6±8,3/55,9±8,7*^†Sexo: 25%/26% feminino	5 meses	Mensal	Educação do paciente, drug- related problems , acompanhamento telefônico, autocuidado	Cuidados usuais da equipe médica.	HbA1c, IMC, pressão arterial, adesão, autocuidado (SDSCA)
Xin et al.⁽³⁸⁾	Tongde Hospital, na província de Hangzhou, China	Diabéticos tipo 2 com idade ≥18 anos, sem uso de insulina nos últimos 18 meses	n=120/120* Perdidos no acompanhamento: 6/7* Idade: 58,8±14,4/59,2±14,2^†Sexo: 51,8%/50,4% masculino	12 meses	Não informado	Educação do paciente, técnica de aplicação de insulina, acompanhamento telefônico	Cuidados usuais da equipe médica	HbA1c, adesão
Shao et al.⁽³⁹⁾	Hospital universitário na província de Nanjing, China	Diabéticos tipo 2 com idade ≥18 anos, HbA1c ≥7%, diagnóstico de diabetes há pelo menos 3 meses ou mais com uso de hipoglicemiante oral	n=120/120* Perdidos no acompanhamento: 20/21* Idade: 58,86±10,59/59,20±10,34^†Sexo: 51%/475% masculino	6 meses	2 meses (presencial) e acompanhamento telefônico mensal	Educação do paciente, acompanhamento telefônico	Cuidados usuais da equipe médica	HbA1c, adesão, pressão arterial, CT, HDL, LDL, TG, IMC, glicemia de jejum

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* relação entre grupo intervenção e grupo controle;^†idade em anos (média±desvio padrão).

HbA1c: hemoglobina glicada; CT: colesterol total; HDL: lipoproteína de alta densidade; LDL: lipoproteína de baixa densidade; TG: triglicérides; IMC: índice de massa corporal; SDSCA: Summary of Diabetes Self-Care Activities Questionnaire ; NR: não reportado; DQoL: Diabetes Quality of Life Brief Clinical Inventory ; HRQoL: Health-Related Quality of Life; DKT: Diabetes Knowledge Test ; SIMS: Satisfaction with Information Received About Medicines ; PAID: Problem Areas in Diabetes Questionnaire ; DTSQ: Diabetes Treatment Satisfaction Questionnaire ; QoL: Quality of Life .

Risco de viés

Sobre o viés de seleção, a geração de sequência aleatória foi considerada adequada na maioria dos estudos (10/15; 66,7%). Quatro (4/15; 26,7%) não reportaram como os participantes foram randomizados. Houve alto risco de viés em um estudo (1/15; 6,7%), no qual os participantes foram randomizados usando o número de registro do prontuário.³² O método utilizado para ocultar a sequência aleatória de randomização não foi descrito em 14 estudos (14/15; 93,4%) e apenas um relatou que auditorias foram realizadas para garantir a ocultação de alocação, pois tratava-se de estudo multicêntrico.³³

Já com relação ao viés de performance, em nenhum estudo houve cegamento das atividades do farmacêutico. Além disso, em 14 estudos, existiu a possibilidade de troca de informações entre os participantes, porque os ensaios foram conduzidos em um único cenário, exceto o estudo multicêntrico de Siaw et al.³³ Trata-se de um ensaio foi considerado com alto risco de viés de cegamento de participantes e profissionais, pois os participantes do Grupo Controle puderam solicitar informações ao farmacêutico, quando necessário.³⁴

Sobre o viés de detecção, apenas um estudo relatou que os avaliadores foram cegados e, dessa forma, não tiveram conhecimento de qual grupo avaliou os desfechos.³⁵ Os demais estudos permaneceram com risco de viés incerto, por não descreverem as medidas utilizadas para avaliação dos desfechos clínicos.

Viés de atrito e viés de relato foram encontrados em apenas um estudo, que permaneceu com alto risco de viés, pois um dos desfechos secundários não foi reportado.²⁷

Sobre outros vieses, consideramos apenas dois estudos livres de outras fontes de viés (2/15; 13,4%). Treze estudos incluídos nessa revisão sistemática e metanálise (13/15; 86,7%) foram classificados como risco de viés incerto, pois as limitações apresentadas pelos autores foram insuficientes para julgar se um importante risco de viés poderia impactar nos desfechos dos participantes ( Figura 2 e Apêndice B).

Características da população

Foram envolvidos nos estudos incluídos nessa revisão sistemática 2.325 participantes. A amostra variou de 36 a 214 participantes. A proporção de participantes do sexo masculino variou de 22% a 75%. A média da idade variou de 52 a 72 anos. A média basal de HbA1c foi de 9,06% no Grupo Intervenção e 8,79% no Grupo Controle. Além do DMT2, a maior parte dos estudos incluídos enfatizou múltiplas comorbidades no desfecho clínico secundário, como dislipidemia, hipertensão e obesidade ( Tabela 1 ).

Intervenções farmacêuticas

As intervenções foram conduzidas em consultas farmacêuticas presenciais e em alguns estudos, também por acompanhamento telefônico (7/15; 46,7%). Entretanto, nem todos os estudos esclareceram as intervenções realizadas no acompanhamento telefônico. Todos os ensaios incluídos tiveram foco em ações educacionais com o paciente (15/15; 100%), além de ações colaborativas com a equipe médica (14/15; 93,4%). Porém, quando os termos “ drug-related problems ” (12/15; 80,0%) ou “ medication review ” (2/15; 26,7%) foram utilizados, não houve explicações claras de quais instrumentos foram aplicados. Dois estudos^{21 , 31} consideraram a frequência de drug-related problems como desfecho clínico dos participantes, e apenas dois^{30 , 35} descreveram que o Pharmacotherapy WorkUp ⁴⁰ foi utilizado como ferramenta para tal finalidade.

No acompanhamento dos participantes, as ferramentas “ drug related problems ” e “medication review” foram utilizadas para identificar e solucionar problemas relacionados aos medicamentos. Tais ferramentas incluem componentes-chave de intervenções farmacêuticas como: Feedback – recomendações sobre o tratamento farmacológico foram direcionadas à equipe médica com o objetivo de solucionar os problemas identificados e otimizar a farmacoterapia (adicionar, substituir ou suspender medicamentos, além de ajustar doses). Acompanhamento telefônico – orientação farmacêutica por telefone e avaliação de eventos adversos. Educação do paciente – intervenções educacionais sobre o diabetes e o tratamento também foram realizadas para melhorar a adesão dos participantes, como o fornecimento de informações sobre os medicamentos, reações adversas, forma de administração e armazenamento (especialmente de insulina), treinamento no reconhecimento e na correção de hipoglicemia, alterações no estilo de vida (cessação do tabagismo, etilismo, dieta adequada e inspeção dos pés), promoção ao autocuidado (monitoramento glicêmico). Todos os pacientes receberam instruções verbais e, em alguns casos, também foram utilizados materiais educativos, como folhetos.

Em um estudo, o farmacêutico clínico teve autoridade para realizar ajustes nas doses de insulina em pacientes virgens de tratamento, baseando-se em sinais/sintomas de hipoglicemia. Para isso, um algoritmo foi validado.³³

Em dois estudos^{29 , 36} (2/15, 26,7%), os participantes foram encaminhados a outros profissionais de saúde como nutricionistas e enfermeiros.

O Grupo Controle consistiu nos cuidados usuais realizados apenas pelas unidades ambulatoriais e farmácias comunitárias, sem as intervenções do farmacêutico clínico ou educação em diabetes providenciada por outros profissionais de saúde, como médicos e enfermeiros ( Tabela 1 ).

Adesão

A adesão ao tratamento foi considerada um desfecho clínico em dez estudos. Para avaliar a adesão dos participantes, foi utilizada a Morisky Medication Adherence Scale (MMAS-8 e MMAS-4) na linha de base do início do estudo e no final do acompanhamento. Em todos os estudos, foram reportadas melhoras significativas da adesão no Grupo Intervenção versus Grupo Controle (p<0,05).

Metanálise

Análise da heterogeneidade

Dez estudos foram incluídos na metanálise.^{21 , 27 - 29 , 32 , 34 , 36 - 39} Todos apresentaram heterogeneidade elevada, com o I² entre 97% e 99% (p<0,001) para todos os desfechos. Mesmo com a considerável heterogeneidade, os resultados demonstraram que o cuidado farmacêutico é eficaz em reduzir os níveis de HbA1c, glicose (glicemia de jejum), TG e PAS, e, também, de elevar o HDL. Entretanto, não houve diferenças estatisticamente significativas nos desfechos de LDL e PAD.

Níveis de hemoglobina glicada

Para o desfecho de HbA1c, foram selecionados dez estudos^{21 , 27 - 29 , 32 , 34 , 36 - 39} que incluíram 715 participantes com média basal de 9,0%, e a metanálise resultou em diferença média de -1,07% (IC95%: -1,32; -0,83; p<0,001). O impacto das intervenções farmacêuticas comparado ao Grupo Controle na redução de HbA1c é demonstrado no gráfico de floresta da figura 3 .

Glicose (glicemia de jejum)

Seis estudos^{21 , 27 - 29 , 32 , 39} realizados em um total de 457 participantes demonstraram redução média de -29,91mg/dL (IC95%: -43,2; -16,6; p<0,001).

Triglicérides

Foram incluídos quatro estudos^{27 , 29 , 32 , 39} conduzidos em 272 participantes, e houve redução média de -19,8mg/dL (IC95%: -36,6; -3,04; p=0,021).

LDL e HDL

Houve aumento médio de 4,43mg/dL (IC95%: 0,16; 8,70; p=0,042) para o HDL, e, para o desfecho de LDL, observou-se redução média de -5,263mg/dL (IC95%: -10,7; 0,18; p=0,058), não sendo estatisticamente significativo.^{27 , 29 , 32 , 39}

Pressão arterial sistólica e pressão arterial diastólica

Em quatro estudos incluídos, houve diferença estatisticamente significativa apenas para o desfecho de PAS, com redução média de -4,65mmHg (IC95%: -8,9; -0,4; p =0,032). Para o desfecho de PAD, foi observada redução de -1,81mmHg (IC95%: -3,7; 0,1; p=0,065), não sendo estatisticamente significativa.^{29 , 32 , 37 , 39}

Frequência de intervenções

Foram analisados seis estudos que fizeram intervenções frequentes (mensais ou a cada dois meses), com média de HbA1c basal de 8,9%.^{21 , 29 , 32 , 36 , 37 , 39} Houve uma redução média de -1,01% (p<0,001) IC95% (-1.2; -0,7). Também observamos uma redução média de -1,17% (p<0,001) IC95% (-1,4; -0,8) para quatro estudos que não especificaram o intervalo de intervenções ou que foram realizadas a cada três meses.^{27 , 28 , 34 , 38} Porém, a média de HbA1c basal neste grupo foi de 9,48%.

DISCUSSÃO

Os resultados da metanálise demonstraram que todas as intervenções farmacêuticas reduziram de forma significativa os níveis de HbA1c, glicemia de jejum, TG, PAS e HDL, não tendo impacto na LDL e nem na PAD. Santschi et al.,⁴¹ realizaram metanálise de 39 ensaios clínicos randomizados com 14.224 participantes com risco cardiovascular elevado (hipertensão, dislipidemia, diabetes, tabagismo e obesidade) e observou-se que as intervenções farmacêuticas, como educação do paciente, feedback à equipe médica e identificação de problemas relacionados aos medicamentos reduziram a PAS (−7,6mmHg; IC95%: -9,0; -6,3; I² = 67%) e PAD (−3,9mmHg; IC95%: -5,1; -2,8; I² = 83%). Porém Santschi et al.,⁴¹ também realizaram análise de subgrupo que verificou se houve diferença estatisticamente significativa entre grupos de estudos de participantes com diabetes versus estudos com participantes sem diabetes. O resultado não revelou diferença estatisticamente significativa entre os dois grupos de estudos: PAS -6,4mmHg (IC95%: -7,8; -5,1; p=0,37) e PAD -4,5mmHg (IC95%: -6,3; -2,8; p=0,51). Corroboramos o que foi apresentado por Santschi et al.,⁴¹ pois também observamos redução estatisticamente significativa na PAS, mesmo sem impacto na redução da PAD em nossa metanálise.

Deters et al.,⁴² incluíram seis estudos em metanálise de 640 participantes de ensaios clínicos randomizados em diabetes tipos 1 e 2, que avaliou o impacto do cuidado farmacêutico. Houve diferença média de HbA1c de - 0,66% (IC95%: -0,86; -0,45) com heterogeneidade insignificante (I² =7,9%; p=0,3659). Uma análise do efeito metanalítico das intervenções farmacêuticas também foi executada por Deters et al.,⁴² que, além de avaliarem a diferença média de HbA1c relacionada ao drug-related problems/medication review (-0,79%) e ao feedback à equipe médica (-0,81%), especificaram o impacto de cada intervenção realizada no componente educacional: complicações relacionadas ao diabetes (-0,60%); conhecimentos sobre os medicamentos (-0,74%); dieta, exercícios físicos e cessação do tabagismo (-0,66%); análise do automonitoramento glicêmico (-0,74%); definição de metas individuais (-0,81%); adesão (-0,60%); e conhecimentos em diabetes (-0,54%). Não realizamos metanálise por intervenções farmacêuticas, pois nem todos os ensaios clínicos incluídos em nosso estudo especificaram os componentes detalhadamente, como o número de pacientes submetidos a tipos de intervenções, especialmente as educacionais. Apenas três estudos incluídos^{27 , 32 , 37} utilizaram o Summary of Diabetes Self-Care Activities (SDSCA) para mensurar o impacto do cuidado farmacêutico no autocuidado dos participantes em componentes como dieta, prática de exercícios físicos, automonitoramento glicêmico, cuidados com os pés e cessação do tabagismo.

Aguiar et al.,²³ conduziram metanálise de 22 ensaios clínicos randomizados em 1.382 participantes com DMT2, que revelou redução média para HbA1c de -0,85% (IC95%: -1,06; -0,65; p<0,0001) e heterogeneidade significativa (p<0,0001) e substancial (I² =67,3%). Para explorar as causas de heterogeneidade, análises de subgrupos foram executadas da seguinte forma: país em que o estudo foi conduzido; forma de contato com o paciente; estudos que utilizaram o medication review; frequência de intervenções, entre outras. Foi observado que não houve heterogeneidade elevada (0% a 40%) e não significativa (p>0,10) nos estudos com as seguintes características: ensaios clínicos conduzidos nos Estados Unidos; participantes com HbA1c basal ≤9%; farmácias comunitárias como cenário ; sem uso de materiais de suporte educacional fornecidos pelo farmacêutico; farmacêutico com autonomia para alterar a prescrição de medicamentos; frequência de intervenções mais de uma vez ao mês e processo de randomização adequado. Aguiar et al.,²³ também observaram que as diferenças médias nos níveis de HbA1c aumentam com HbA1c basal elevada. Nossos resultados demonstraram também maior redução de HbA1c em estudos que tiveram intervalo de tempo mais longo nas intervenções farmacêuticas. Entretanto, esses estudos apresentaram média basal de HbA1c de 9,48%, e, por esse motivo, podemos supor que um maior intervalo de intervenções não está associado com maior redução de HbA1c. Com isso, assim como Aguiar et al.,²³ afirmamos que pacientes com níveis basais elevados de HbA1c podem ter melhores benefícios do cuidado farmacêutico, já que a média basal de HbA1c dos participantes incluídos em nossa metanálise foi de 9,0%.

Para explorar as possíveis causas da heterogeneidade elevada entre os estudos, reproduzimos análise semelhante à realizada por Aguiar et al.²³ Não realizamos metarregressão por conta do número pequeno de estudos (menos que dez) e, dessa forma, conduzimos novamente a análise de subgrupos usando o modelo de efeitos aleatórios, de acordo com as características de cada ensaio: participantes com valores basais de HbA1c <9%;^{27 , 32 , 34 , 36 , 37} intervenções como drug-related problems ^{27 , 32 , 34 , 37 , 40} e medication review; ^{28 , 29} intervenções frequentes (mensais ou a cada 2 meses);^{21 , 26 , 29 , 30 , 32 , 35 , 40 , 42} por cenários ambulatorial^{21 , 26 , 27 , 30 - 35} e da farmácia comunitária;^{29 , 37} por sexo, ou seja, estudos com maior proporção de homens^{29 , 34 , 41 , 42} contra estudos com maior proporção de mulheres.^{21 , 27 , 28 , 32 , 37 , 39} Todas as análises demonstraram heterogeneidade elevada e significativa (I² >98%; p<0,001). Realizamos também análises por exclusão de estudos. Um dos ensaios incluiu apenas idosos (≥65 anos)³⁸ e levantando a hipótese de que isso poderia ter relação com a heterogeneidade elevada e significativa, a análise de sensibilidade também foi executada sem a inclusão desse estudo e não mostrou resultado diferente: I² = 99,2% (p<0,001). Também não encontramos resultados diferentes ao excluir estudos que tiveram curto período de acompanhamento^{21 , 37} e processo de randomização inadequado.³² Não foi possível identificar se a ausência de uma ferramenta específica, como o Pharmacotherapy WorkUp , utilizada para drug-related problems, poderia contribuir para a heterogeneidade, pois somente dois ensaios clínicos declararam utilizá-la para essa finalidade.^{30 , 35} Mesmo se os 15 estudos selecionados para revisão sistemática fossem incluídos em nossa metanálise, provavelmente, não encontraríamos resultado diferente. Entre as prováveis causas da heterogeneidade significativa, estão os diferentes critérios de inclusão dos ensaios conduzidos. Os níveis de HbA1c exigidos para inclusão dos participantes nos estudos incluídos foi de 6,5% a 9%. Isso resultou em variação média de HbA1c basal de 9,0% no Grupo Intervenção e 8,7% no Grupo Controle. O uso de insulina^{34 , 36 , 38} também pode ser considerado provável causa, assim como a proporção de idade e sexo, o período curto de acompanhamento^{21 , 37} e o número pequeno de participantes.^{29 , 34}

Devido ao multiculturalismo dos estudos incluídos em nossa revisão sistemática com metanálise, é possível que as diferenças culturais e étnicas também tenham influenciado no desfecho clínico, além das diferenças entre os sistemas de saúde, nível educacional e socioeconômico dos participantes. Incluímos estudos de diferentes países e regiões do mundo (América do Sul, Europa, Mediterrâneo Oriental, Oriente Médio e Ásia), como, por exemplo, os estudos de Chung et al.,²⁸ e Siaw et al.,³³ realizados na Malásia e Cingapura, respectivamente. Esses ensaios envolveram participantes de três grupos étnicos diferentes (chineses, malaios e indianos). Também é necessário considerar possíveis obstáculos sob a aceitação das intervenções, que podem variar em países onde o cuidado farmacêutico não é bem aceito. Somente Aguiar et al.,³⁵ descreveram a frequência das intervenções realizadas e a taxa de aceitação (96,9%) pela equipe médica.

Além disso, temos que considerar todas as limitações metodológicas dos estudos incluídos em nossa metanálise. Ressaltamos que o cuidado farmacêutico é importante dentro de um contexto multiprofissional, embora diversos estudos aqui citados relataram as intervenções do Grupo Controle como “cuidados usuais”, sem maiores especificações. O risco de viés dos estudos selecionados para essa revisão sistemática com metanálise prevaleceu como incerto em quase todos os aspectos avaliados, já que poucos autores reportaram os métodos de ocultação de alocação e de cegamento dos avaliadores de desfecho. Alguns cenários utilizados para a condução dos estudos podem ter influenciado nos resultados. Devido ao pequeno país em que um dos estudos foi realizado (República Turca de Chipre do Norte), houve o risco de contaminação cruzada entre os grupos.³² Dessa forma, é possível que o Grupo Controle tenha obtido informações com o Grupo Intervenção, até mesmo em estudos conduzidos em um único cenário ambulatorial (experiência de Hawthorne ). Em um dos estudos, os participantes do Grupo Controle tiveram acesso aos exames laboratoriais na linha de base e, dessa forma, ao solicitar maior atenção médica, poderiam minimizar os efeitos da intervenção farmacêutica.³⁰ Também não houve cegamento das atividades do farmacêutico clínico nos estudos selecionados e, com isso, possivelmente houve aumento no cuidado de outros profissionais de saúde no Grupo Controle. Por exemplo, em um ensaio, o farmacêutico clínico estava disponível para orientar pacientes do grupo controle, se necessário.³⁴ Poucos autores descreveram claramente o cuidado farmacêutico recebido pelos participantes do Grupo Intervenção. Também, poucos ensaios utilizaram o SDSCA no componente-chave educacional. Por isso, não foi possível executar análise estatística específica por componente-chave, contribuindo com os resultados apresentados por Deters et al.⁴² No geral, todos os estudos incluídos na metanálise declararam que os farmacêuticos envolvidos nos ensaios clínicos eram especialistas em farmacoterapia e receberam treinamento para serem educadores em diabetes. Porém, nem todos especificaram a duração do treinamento (em horas) e qual profissional de saúde foi providenciado para treinar os farmacêuticos. Também não realizamos metanálise de adesão dos participantes, pois a ampla variabilidade de métodos utilizados para mensurar os resultados e a falta de medidas padronizadas entre os estudos não permitiram avaliação. Isso demonstra que é necessário padronizar os instrumentos utilizados para avaliar a adesão e, dessa forma, possibilitar a comparação dos resultados de diferentes estudos. Nosso resultado também não permitiu concluir com qual frequência as intervenções farmacêuticas devem ser realizadas, pois nem todos os autores reportaram com clareza essas informações. Foi observado que o grupo de estudos que realizou intervenções a cada 3 meses (ou que não relatou o intervalo de intervenções) apresentou maior redução nos níveis de HbA1c. Porém, a média basal nesse grupo foi maior que 9% e a do grupo de estudos que realizou intervenções mensais, menor que 9%. Portanto, é provável que um maior efeito na redução de HbA1c não tenha relação direta com intervalo maior de intervenções, pois, assim como Aguiar et al.,²³ corroboramos que os pacientes com maiores níveis basais de HbA1c terão melhor benefício do cuidado farmacêutico.

As diretrizes da American Diabetes Association (ADA) e da Sociedade Brasileira de Diabetes (SBD) afirmam que o processo terapêutico no diabetes mellitus deve ser estabelecido por equipe multiprofissional ativa, capacitada para providenciar educação contínua, além de assistência de qualidade.^{1 , 43} No âmbito farmacêutico, a SBD cita a Resolução da Diretoria Colegiada (RDC) 44/2009 da Agência Nacional de Vigilância Sanitária (Anvisa), que normatizou a prestação de serviços farmacêuticos – entre eles, o cuidado farmacêutico e a glicemia capilar.⁴³ Por outro lado, as diretrizes da ADA recomendam a garantia do uso racional de insulina e da supervisão meticulosa do farmacêutico sobre a dose administrada.¹ Entretanto, essas diretrizes não especificam outros componentes necessários para prestar o cuidado ao paciente no âmbito multiprofissional.^{1 , 44} Os resultados da nossa metanálise sugerem que componentes-chave, como drug-related problems/medication review (incluindo o feedback à equipe médica) , educação do paciente e acompanhamento telefônico são intervenções que demonstraram desfecho clínico satisfatório na redução de HbA1c dos participantes. O uso de ferramentas que avaliam o autocuidado, como o SDSCA,⁴⁵ a adesão, como o MMAS-8,⁴⁶ e que ajudam a identificar problemas relacionados aos medicamentos ( drug-related problems ) podem ser úteis no acompanhamento dos pacientes.

Nosso estudo também apresenta algumas limitações. Nem todos os ensaios clínicos selecionados para a revisão sistemática foram incluídos na metanálise, por apresentarem diferentes medidas nos relatos de desfecho clínico (média, desvio padrão, mediana, IQR e IC95%). Por esse motivo, incluímos apenas estudos cujas medidas foram descritas como média e desvio padrão. Além disso, nosso objetivo foi identificar evidências mais recentes das intervenções farmacêuticas no DMT2 e avaliar seu impacto. Por isso, selecionamos estudos publicados nos entre 2012 e 2017. Um período de referência maior permitiria incluir mais ensaios clínicos randomizados. Porém, provavelmente, a inclusão de estudos anteriores ao ano de 2012 não refletiria a prática farmacêutica atual. Ainda que apenas um único autor tenha extraído, revisado e analisado todos os dados, garantimos a integridade dos dados apresentados nessa revisão sistemática com metanálise.

CONCLUSÃO

Embora nossa metanálise tenha demonstrado heterogeneidade elevada e significativa, nossos resultados sugerem que as intervenções providenciadas pelo cuidado farmacêutico têm impacto significativo na redução de hemoglobina glicada, glicemia de jejum, triglicérides, pressão arterial sistólica e no aumento dos níveis do HDL. Nossos resultados também sugerem que essas intervenções não geram impacto na pressão arterial diastólica e na LDL. Além disso, pacientes com níveis basais elevados de hemoglobina glicada devem ter maiores benefícios do cuidado farmacêutico. No entanto, mais ensaios clínicos randomizados devem ser realizados, com melhor delineamento metodológico, para que seja possível reportar com maior clareza as intervenções farmacêuticas.

Apêndice.

Apêndice A. . Estratégia de busca.

PubMed®
1. Diabetes mellitus , type 2 [mh] (107.405)
2. Type 2 diabetes (144.283)
3. T2DM (13.054)
4. Non insulin dependent diabetes mellitus (130.159)
5. NIDDM (120.203)
6. 1 OR 2 OR 3 OR 4 OR 5 (156.111)
7. Pharmaceutical services [mh] (60.102)
8. Pharmaceutical care (86.683)
9. Clinical Pharmacy (71859)
10. Community pharmacy (22.968)
11. Pharmacist* (30.355)
12. 7 OR 8 OR 9 OR 10 OR 11 (170.150)
13. Randomized controlled trial [pt] (441.905)
14. Random* AND Control* (797.089)
15. 13 OR 14 (797.180)
16. 6 AND 12 AND 15 (479)
17. Filtro da Cochrane Central Register of Controlled Trials por data de publicação (57)
*Web of Science*
1. ts= Type 2 diabetes (153.853)
2. ts = T2DM (13.045)
3. ts = Non insulin dependent diabetes mellitus (10.421)
4. ts = NIDDM (12.313)
5. 1 OR 2 OR 3 OR 4 (168.261)
6. ts = Pharmaceutical services (4.887)
7. ts = Pharmaceutical care (13.954)
8. ts = Clinical pharmacy (8.159)
9. ts = Community pharmacy (6.730)
10.ts = Pharmacist* (26.322)
11.6 OR 7 OR 8 OR 9 OR 10 (47.569)
12.ts = (Random* AND Control*) (586.584)
13. 5 AND 11 AND 12 (211)
14. Com filtro por data de publicação (59)
*Cochrane Central Register of Controlled Trials*
1. [mh Diabetes mellitus , type 2] (11.714)
2. Type 2 Diabetes (28.274)
3. T2DM (2.910)
4. Non insulin dependent diabetes mellitus (11.653)
5. NIDDM (1.115)
6. 1 OR 2 OR 3 OR 4 OR 5 (29.876)
7. [mh “Pharmaceutical services”] (1.698)
8. Pharmaceutical care (4.673)
9. Clinical pharmacy (10.716)
10. Community pharmacy (1.874)
11. Pharmacist* (4.188)
12. 7 OR 8 OR 9 OR 10 OR 11 (16.839)
13. 6 AND 12 (1.941)
14. Trials com filtro por data de publicação (69)

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Apêndice B. . Risco de viés.

	Viés de seleção		Viés de performance	Viés de detecção	Viés de atrito	Viés de relato	Outros vieses

Referência	Geração de sequência aleatória	Ocultação de alocação	Cegamento de participantes e profissionais	Cegamento de avaliadores de desfecho	Desfechos incompletos	Relato de desfecho seletivo	Outras fontes de viés
Mahwi et al.⁽²¹⁾	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto
Jarab et al.⁽²⁶⁾	Baixo risco	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto
Wishah et al.⁽²⁷⁾	Baixo risco	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Alto risco	Alto risco	Risco de viés incerto
Chung et al.⁽²⁸⁾	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto
Ali et al.⁽²⁹⁾	Baixo risco	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto
Mourão et al.⁽³⁰⁾	Baixo risco	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto
Chan et al.⁽³¹⁾	Baixo risco	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto
Korcegez et al.⁽³²⁾	Alto risco	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto
Siaw et al.⁽³³⁾	Baixo risco	Baixo risco	Baixo risco	Risco de viés incerto	Baixo risco	Baixo risco	Baixo risco
Cani et al.⁽³⁴⁾	Baixo risco	Risco de viés incerto	Alto risco	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto
Aguiar et al.⁽³⁵⁾	Baixo risco	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Baixo risco	Baixo risco
Chen et al.⁽³⁶⁾	Baixo risco	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto
Jahangard-Rafsanjani et al.⁽³⁷⁾	Baixo risco	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto
Xin et al.⁽³⁸⁾	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto
Shao et al.⁽³⁹⁾	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Risco de viés incerto	Baixo risco	Baixo risco	Risco de viés incerto

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PERMALINK

Pharmaceutical care-based interventions in type 2 diabetes mellitus : a systematic review and meta-analysis of randomized clinical trials

Marcel Nogueira

Leonardo Jun Otuyama

Priscilla Alves Rocha

Vanusa Barbosa Pinto

ABSTRACT

Objective

Methods

Results

Conclusion

INTRODUCTION

OBJECTIVE

METHODS

Search strategy

Date of publication

Study selection

Risk of bias assessment

Data extraction

Statistical analysis

Outcome measures

RESULTS

Study selection

Figure 1. Study selection flowchart.

Study characteristics

Table 1. Characteristics of studies included.

Risk of bias

Figure 2. Risk of bias.

Population characteristics

Pharmacist interventions

Adherence

Meta-analysis

Heterogeneity analysis

Glycated hemoglobin levels

Figure 3. Forest plot.

Fasting blood glucose levels

Triglycerides

LDL and HDL

Systolic and diastolic blood pressure

Frequency of interventions

DISCUSSION

CONCLUSION

Appendix.

Appendix A. . Search strategy.

Appendix B. . Risk of bias.

REFERENCES

Intervenções farmacêuticas no diabetes mellitus tipo 2: uma revisão sistemática e metanálise de ensaios clínicos randomizados

Marcel Nogueira

Leonardo Jun Otuyama

Priscilla Alves Rocha

Vanusa Barbosa Pinto

RESUMO

Objetivo

Métodos

Resultados

Conclusão

INTRODUÇÃO

OBJETIVO

MÉTODOS

Estratégia de busca

Data de publicação

Seleção dos estudos

Avaliação do risco de viés

Extração dos dados

Análise estatística

Medidas de desfecho

RESULTADOS

Seleção dos estudos

Figura 1. Fluxograma de seleção dos estudos.

Características dos estudos

Tabela 1. Características dos estudos incluídos.

Risco de viés

Figura 2. Risco de viés.

Características da população

Intervenções farmacêuticas

Adesão

Metanálise

Análise da heterogeneidade

Níveis de hemoglobina glicada

Figura 3. Forest plot.