Structured abstract
Background
This study aimed to examine the prevalence of inappropriate tight glycemic control in older adults with type 2 diabetes and other chronic conditions in New York City, and to identify factors associated with this practice.
Methods
We conducted a retrospective cohort study using the INSIGHT Clinical Research Network. The study population included 11,728 and 15,196 older adults in New York City (age ≥ 75 years) with a diagnosis of type 2 diabetes, and at least one other chronic medical condition, in 2017 and 2022 respectively. The main outcome of interest was inappropriate tight glycemic control, defined as HbA1c <7.0% (<53 mmol/mol) with prescription of at least one high-risk agent (insulin or insulin secretagogue).
Results
The proportion of older adults with inappropriate tight glycemic control decreased by nearly 19% over a five-year period (19.4% in 2017 to 15.8% in 2022). There was a significant decrease in insulin (27.8% in 2017; 24.3% in 2022) and sulfonylurea (29.4% in 2017; 21.7% in 2022) medication prescription, and increase in use of GLP-1 agonists (1.8% in 2017; 11.4% in 2022) and SGLT-2 inhibitors (5.8% in 2017; 25.1% in 2022), amongst the total population. Factors associated with inappropriate tight glycemic control in 2022 included history of heart failure (adjusted odds ratio [aOR] 1.38), chronic kidney disease ([aOR] 1.93), colorectal cancer ([aOR] 1.38), acute myocardial infarction ([aOR] 1.28), “other” ([aOR] 0.72) or “unknown” ([aOR] 0.72) race, and a point increase in BMI ([aOR] 0.98).
Conclusions
We found an encouraging trend towards less use of high-risk medication strategies for older adults with type 2 diabetes and multiple chronic conditions. However, one in six patients in 2022 still had inappropriate tight glycemic control, indicating a need for continued efforts to optimize diabetes management in this population.
Keywords: Diabetes Mellitus, Glycemic control, Insulin
Introduction
The prevalence of type 2 diabetes increases with age.1 While many medications effectively treat type 2 diabetes, management in older patients can be challenging due to an increased risk of medication-related hypoglycemia from tight glucose control.1–3 Aside from direct consequences (e.g. hospitalization for severe hypoglycemic events), hypoglycemia has been associated with an increased risk of incident cardiovascular disease and dementia.1,4–8 In context of these potential harms, recent guidelines discourage tight glycemic control with medications (generally defined as hemoglobin a1c [HbA1c] <7.0% (<53 mmol/mol)) in patients aged ≥75 years with multiple chronic conditions, particularly with high-risk agents (insulin or insulin secretagogues) that increase the risk of hypoglycemia.9,10 In 2003, the American Diabetes Association first put forth the recommendation for less stringent treatment goals in older adults and individuals with comorbid conditions, in particular to minimize hypoglycemia.11
Despite these recommendations, research has consistently shown that a substantial proportion of older adults are overtreated, with more than half of the people over age ≥65 years within the NHANES dataset from 2001 through 2010 having tight glycemic control coupled with high-risk medication prescription.12 More recent research in 2018 and 2021 has found that tight glycemic control among older adults, including with high-risk agents, was still common.2,3 For example, a large registry study in 2018 found that over a quarter of older adults on medical therapy for type 2 diabetes had tight glycemic control and were prescribed high-risk agents.2 However, over the course of the past decade, options for type 2 diabetes have expanded with the approval of newer agents such as GLP-1 agonists and SGLT-2 inhibitors, that have a lower risk of hypoglycemia as well as beneficial off-target effects (e.g. lower mortality among patients with heart failure).13,14
In this context, we designed a real world observational study with three aims: first, to describe the prevalence of inappropriate tight glycemic control (defined as HbA1c <7.0% (<53 mmol/mol) and use of insulin or insulin secretagogues) in a large sample of older adults with type 2 diabetes and at least one other chronic medical condition in New York City (NYC); second, to determine the extent to which older adults with multiple chronic conditions receiving inappropriate tight glycemic control has changed over time in the context of newer type 2 diabetes agents being approved; and third, to determine factors associated with continued inappropriate tight glycemic control at the end of our observation period.
Methods
Data source
We conducted a retrospective cohort study using data from the INSIGHT Clinical Research Network between 2017 and 2022. INSIGHT is a consortium of seven academic healthcare systems (Albert Einstein School of Medicine/Montefiore Medical Center, Columbia University, Weill Cornell Medicine, New York-Presbyterian Hospital, Icahn School of Medicine/Mount Sinai Health System, New York University School of Medicine/Langone Medical Center, and Houston Methodist)15,16 in New York City (NYC), NY and Houston, TX and contains a data repository with electronic health record data for 12 million patients that adheres to the PCORNET common data model.15 Houston Methodist data was not included in this analysis as our interest was in outcomes amongst NYC residents.
Patient Population
We restricted our study population to NYC resident patients with at least one outpatient visit at New York INSIGHT member institutions during either 2017 or 2022. Patients were included in the sample if they met the following criteria: (1) age 75 years or older; (2) diagnosis of type 2 diabetes via ICD-10 coding; (3) at least one HbA1c measurement; and (4) one or more other chronic medical conditions (i.e. history of stroke, heart failure, hypertension, chronic kidney disease, colorectal cancer, lung cancer, breast cancer, prostate cancer, hyperlipidemia, depression, ischemic heart disease, acute myocardial infarction, atrial fibrillation, COPD, asthma, arthritis [osteoarthritis or rheumatoid arthritis], osteoporosis). Chronic medical conditions were chosen based on a framework previously published by Lochner and Cox17 and based on the Department of Health and Human Services (HHS) Initiative on multiple chronic conditions.17 All diagnoses were determined through ICD-10 codes from all visits in the INSIGHT data repository. We excluded patients with diagnoses of metastatic cancer or dementia/Alzheimer’s disease given that type 2 diabetes in these patients is typically managed very differently from other ambulatory patients.
We selected 2017 and 2022 as comparison years to allow sufficient time for increased adoption of newer type 2 diabetes agents (GLP-1 agonists and SGLT-2 inhibitors) as well as to exclude the initial wave of COVID-19-related ambulatory care disruption. For patients with multiple readings (e.g., HbA1c, blood pressure, body mass index) within a single year, we retained the most recent reading for every patient.
Medications
The following diabetes medications were included in our analysis: insulin (any type), sulfonylureas, meglitinides, metformin, thiazolidinedione, dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide-1 receptor (GLP-1) agonists, sodium-glucose co-transporter 2 (SGLT-2) inhibitors. High-risk agents were defined as either insulin or insulin secretagogues (sulfonylureas, meglitinides) based on a prior taxonomy.2 Medications prescribed during an inpatient visit were excluded. Medication classes were defined using RxNorm codes.18
Prescription of a class of diabetes medication during the year of interest was defined as having at least one outpatient prescription during the year or having an outpatient prescription for the agent during the preceding year for a period that extended to the year in question.
Statistical Analysis
We first summarized overall characteristics of patients (e.g., age, BMI, chronic conditions, medications prescribed) seen in 2017 and 2022. We then identified the proportion of patients prescribed medications classified as high-risk agents in 2017 and 2022.
Our outcome of interest was inappropriate tight glycemic control, defined as HbA1c <7.0% (<53 mmol/mol) with a prescription of at least one high-risk diabetes agent, consistent with prior definitions.2,3,12 We assessed prescription rates of insulin, sulfonylureas, meglitinides, GLP-1 agonists, and SGLT-2 inhibitors in both tightly controlled and overall population for both study years. We reported changes in rates between 2017 and 2022 and associated p-values, and we interpreted p < 0.001 to be a statistically significant change. Inappropriate tight glycemic control was defined as use of any insulin, sulfonylurea, or meglitinide within the cohort classified as having tight glycemic control. We evaluated the change in prescription for each medication between the two years using a Generalized Estimating Equation (GEE), testing the null hypothesis that there was no change in rates between the years.
We then used a multivariable logistic regression to determine characteristics associated with inappropriate tight glycemic control in 2022, as repeated measures from patients seen in both study years had little effect on regression outcomes. Covariates were determined based on prior literature and clinical judgment. This included age, BMI, race, ethnicity, neighborhood poverty level, stroke, heart failure, hypertension, chronic kidney disease, lung cancer, breast cancer, prostate cancer, hyperlipidemia, depression, ischemic heart disease, myocardial infarction, atrial fibrillation, chronic obstructive pulmonary disease (COPD), asthma, arthritis, and osteoporosis. Neighborhood poverty level was determined as the percentage of residents in a neighborhood, identified by a patient’s 5-digit ZIP code, that lived below the federal poverty level (low: <10%; medium: 10% to <20%; high: 20% to <30%; very high: ≥30%), consistent with a prior methodology.19
Ethics and Dissemination
The study was approved by the NYU Grossman School of Medicine Institutional Review Board through a single IRB mechanism, with a waiver of informed consent given the retrospective and observational nature of the study. For the purposes of this study, limited datasets were provided at the patient level.
Results
Patient Population
The INSIGHT database contained 11,728 patients in 2017 and 15,196 in 2022 who met our initial study entry criteria. The 2017 cohort was of similar age to the 2022 cohort (80.6 vs. 80.5 years) with a similar percentage female (60.9% vs. 60.2%) (Table 1). The mean number of chronic conditions (other than diabetes) was higher in 2022 (5.3 vs. 4.0), and the 2017 cohort was slightly more obese (2017: 41.1%; 2022: 37.8%) (Table 1).
Table 1.
Study sample characteristics, 2017 and 2022
| 2017 (N = 11,728) | 2022 (N = 15,196) | |
|---|---|---|
| Age [years], mean ± SD | 80.6 ± 4.8 | 80.5 ± 4.7 |
| Female Sex (%) | 7,139 (60.9%) | 9,150 (60.2%) |
| Race | ||
| Asian (%) | 377 (3.2%) | 504 (3.3%) |
| Black (%) | 2,015 (17.2%) | 2,462 (16.2%) |
| White (%) | 3,510 (29.9%) | 4,724 (31.1%) |
| Other (%) | 3,785 (32.3%) | 4,685 (30.8%) |
| Unknown (%) | 2,041 (17.4%) | 2,821 (18.6%) |
| Ethnic group | ||
| Hispanic (%) | 3,288 (28.0%) | 4,041 (26.6%) |
| Non-Hispanic (%) | 6,399 (54.6%) | 8,334 (54.8%) |
| Unknown (%) | 2,041 (17.4%) | 2,821 (18.6%) |
| BMI [kg/m2], mean ± SD | 29.1 ± 5.6 | 28.6 ± 5.6 |
| Obese [>30 kg/m2], (%) | 4,817 (41.1%) | 5,741 (37.8%) |
| Neighbourhood poverty level | ||
| Low, (%) | 2,049 (17.5%) | 2,985 (19.6%) |
| Medium, (%) | 5,082 (43.3%) | 6,598 (43.4%) |
| High, (%) | 2,473 (21.1%) | 3,256 (21.4%) |
| Very High, (%) | 1,985 (16.9%) | 2,274 (15.0%) |
| Number of other Chronic conditions*, mean ± SD | 4.0 ± 1.9 | 5.3 ± 2.1 |
| Selected other chronic conditions (detail) | ||
| Heart failure, (%) | 2,122 (18.1%) | 3,921 (25.8%) |
| Hypertension, (%) | 10,802 (92.1%) | 14,768 (97.2%) |
| Chronic kidney disease**, (%) | 4,897 (41.8%) | 8,194 (53.9%) |
| Ischemic heart disease, (%) | 4,304 (36.7%) | 7,507 (49.4%) |
| COPD, (%) | 1,683 (14.4%) | 3,229 (21.2%) |
| Number of glucose-lowering medications, mean ± SD | 1.6 ± 0.8 | 1.8 ± 1.0 |
| Glycosylated Haemoglobin [HbA1c %], mean ± SD | 7.3 ± 1.4 | 7.2 ± 1.4 |
| Systolic blood Pressure [mmHg], mean ± SD | 134.7 ± 19.9 | 134.1 ± 19.0 |
| Diastolic blood pressure [mmHg], mean ± SD | 71.3 ± 9.8 | 71.6 ± 9.9 |
Consists of the following conditions: stroke, heart failure, hypertension, chronic kidney disease, colorectal cancer, lung cancer, breast cancer, prostate cancer, hyperlipidemia, depression, ischemic heart disease, acute myocardial infarction, atrial fibrillation, COPD, asthma, arthritis, osteoporosis
Chronic Kidney Disease is defined as GFR <60 mL/min/1.73m2
Tight Glycemic Control
In the 2017 sample, 5,768 older patients (49.2%) had tight glycemic control. This increased to 7,818 (51.4%) in 2022 (Figure 1). The proportion of older adults on one or more high-risk diabetes agents (indicating inappropriate tight glycemic control) decreased from 19.4% (2,280) in 2017 to 15.8% (2,398) in 2022, representing an 18.6% relative reduction (Figure 1). This represents 39.5% and 30.7% of adults within the overall tight control population, respectively (Supplementary Table 1, 2, 3).
Figure 1.
Prevalence of tight glycemic control and inappropriate tight glycemic control, 2017 and 2022
Blue circles and line = tight glycemic control group (P-value <0.001)
Orange circles and line = inappropriate tight glycemic control group (P-value <0.001)
Medication Prescription
Between 2017 and 2022, there was a significant increase in the prescription of GLP-1 agonists and SGLT-2 inhibitors among the overall patient population (GLP-1 agonist: 1.8% to 11.4%; SGLT-2 inhibitors: 5.8% to 25.1%) (Figure 4). A similar change in prescription was noted among the subset with tight glycemic control (GLP-1 agonist: 1.1% to 9.2%; SGLT-2 inhibitors: 4.2% to 18.8%) (Figure 2).
Figure 4.
Prevalence of diabetes medication by drug class in overall study sample, 2017 and 2022
Blue circles and lines = Insulin prescription group (P-value <0.001)
Orange circles and lines = Sulfonylurea prescription group (P-value <0.001)
Red circles and lines = Meglitinides prescription group (P-value = 0.146)
Purple circles and lines = GLP-1 agonist prescription group (P-value <0.001)
Green circles and lines = SGLT-2 inhibitor prescription group (P-value <0.001)
Figure 2.
Prevalence of diabetes medication prescription by drug class in study samples with tight glycemic control, 2017 and 2022
Blue circles and lines = Insulin prescription group (P-value = 0.024)
Orange circles and lines = Sulfonylurea prescription group (P-value <0.001)
Red circles and lines = Meglitinides prescription group (P-value = 0.599)
Purple circles and lines = GLP-1 agonist prescription group (P-value <0.001)
Green circles and lines = SGLT-2 inhibitor prescription group (P-value <0.001)
During the same period, there was a significant decrease in use of insulin (27.8% to 24.3%) as well as sulfonylurea medications (29.4% to 21.7%) (Figure 4) in the overall patient population. In patients with tight glycemic control, the decrease was larger for sulfonylureas (24.7% to 16.1%) than for insulin prescription among the subset (15.3% to 13.9%) (Figure 2).
Multivariable modeling
We performed multivariable logistic regression modeling to determine factors associated with inappropriate tight glycemic control in 2022. We found that patients with a history of heart failure (adjusted odds ratio [aOR] 1.38, 95% confidence interval [CI] 1.15 – 1.66), chronic kidney disease (aOR 1.93, CI 1.64 – 2.27), colorectal cancer (aOR 1.38, CI 1.01 – 1.88), and acute myocardial infarction (aOR 1.28, CI 1.04 – 1.57) had a greater odds of inappropriate tight glycemic control, while self-identification of race as “other” (aOR 0.72, CI 0.54 – 0.94) or “unknown” (aOR 0.72, CI 0.53 – 0.98) and a point increase in BMI value (aOR 0.98, CI 0.97 – 0.99) were associated with lower odds (Figure 3). There was no association between age, sex, or neighborhood poverty level and inappropriate tight glycemic control.
Figure 3.
Adjusted odds ratio of clinical features for high-risk diabetic agent* prescription in patients with tight glycemic control in 2022
* = Insulin or Insulin-secreting analogues
Discussion
Our analysis had several key findings. First, the proportion of older adults with inappropriate tight glycemic control (defined as HbA1c <7.0% (<53 mmol/mol) and on a high-risk agent) decreased by nearly 19% over a five-year period, from 19.4% in 2017 to 15.8% in 2022. Second, and relatedly, we observed a marked decline in the use of insulin and sulfonylurea medications with a concomitant increase of GLP-1 agonists and SGLT-2 inhibitors over the same time period in our total population. Third, predictors for inappropriate tight glycemic control in 2022 included medical comorbidities (history of heart failure, history of chronic kidney disease, history of colorectal cancer, history of acute myocardial infarction) but not other factors (e.g. neighborhood poverty) that may intuitively seem more connected with an inability to obtain newer and safer medications.
Our findings are derived from a large, diverse sample of patients in NYC. While we acknowledge that regional variation may exist, our data suggest a promising trend: an overall reduction in a high-risk management strategy for older adults (tight glycemic control with high-risk agents) that has been associated with a range of adverse outcomes such as hospitalization and mortality.20,21 Prior to the beginning of our observation period (2017), where we observed a 19.4% rate of inappropriate tight glycemic control, rates were even higher: for example, Arnold et al. estimated that 26% of older patients with type 2 diabetes met criteria for this measure, using data from the Diabetes Collaborative registry between 2014 and 2016.2 An analysis of the global DISCOVER study, which included 15,992 patients across 38 countries from 2014 to 2016, demonstrated a similarly high rate.3
While this trend of increase in the use of SGLT-2 inhibitors and GLP-1 agonists is encouraging and clinical trials have demonstrated their general safety and efficacy, none of these trials were restricted solely to an older population. Thus, long term effects of these medications on older adults remains understudied. Beyond clinical efficacy, the cost burden of prescribing these medications may also be high for older adults with limited financial means. Over the same observation period, DPP-4 inhibitor use declined (from 30.0% in 2017 to 25.2% in 2022). These medications are generally safe in older patients, but they were likely replaced by injectable GLP-1 agonists given the stronger effect of GLP-1 agonists on A1c lowering, as well as their growing evidence base for cardiovascular risk reduction. As this is an observational study, this remains speculative.
Due to the retrospective nature of our study, we did not directly measure factors accountable for our observed trend, but we postulate several reasons: First, the U.S. FDA approved two new diabetes medications over the past decade (SGLT-2 inhibitors in 2014 and GLP-1 agonists in 2017) with several subsequent landmark clinical trials demonstrating efficacy of these agents in improving a wide range of clinical outcomes among patients with diabetes.22,23 Second, and in parallel, professional society advocacy has raised awareness among clinicians about the risks of aggressively using insulin or insulin secretagogues in older adults with diabetes. The American Geriatrics Society’s (AGS) Beers List, which is updated regularly, represents one such effort; sulfonylureas are currently listed with a recommendation of “avoid” with cited risks of hypoglycemia and cardiovascular events.24 In addition, both AGS9 and the American Diabetes Association10 have endorsed guidelines for less stringent control of glucose (e.g. HbA1c 7.0%–8.0% (53 mmol/mol-64 mmol/mol) is acceptable) in older adults with multiple comorbidities where the harms of aggressive control outweighs the potential benefits, especially in the setting of limited life expectancy.
Notably, in 2022, there were still 1 in 6 patients in our sample with inappropriate tight glycemic control. We found that patients with chronic kidney disease were 1.9 times more likely to have inappropriate tight glycemic control in 2022. This may reflect clinicians’ more limited options in using other classes of medications in this population (e.g. due to contraindications to SGLT-2 inhibitor use in the setting of advanced renal impairment). However, as we did not have more detailed information on renal function (stage of CKD) or reasons for prescriber decision-making, this remains speculative. It also may be that these comorbidities led prescribers to be more aggressive about lowering HbA1c in the belief that this would improve outcomes. Further, while we hypothesized that neighborhood poverty may predict inappropriate tight glycemic control (due to the prohibitive cost of newer and safer medications), we found no such association. However, neighborhood poverty may be a poor proxy of individual poverty, and we acknowledge that other social determinants of health, such as education and income, were not available in the current dataset and therefore could not be tested.
There are several other limitations that warrant consideration. First, while we analyzed data on medication prescription, we did not have information on medication adherence (which can be challenging to obtain in large administrative datasets). Second, we did not analyze outcomes (e.g. hospitalization rate) among patients with inappropriate tight glycemic control, although extensive prior literature2,20,21 has demonstrated that this treatment strategy is associated with adverse outcomes. While this is beyond the scope of our current dataset, replicating prior findings in the INSIGHT registry is a worthy avenue for future research. Given our use of administrative datasets, there is also the potential for misclassification (e.g. of patients with Type 1 diabetes being classified as having type 2 diabetes), which would result in an overestimate of the proportion of older adults with inappropriate tight glycemic control. However, given that the percentage of patients with the subtype of type 1 diabetes decreases with advancing age, based on population-representatve studies (4.6% among adults aged 45–64 and 3.3% among adults aged ≥65),25 we expect that a small number of misclassified patients are unlikely to affect our overall findings. Furthermore, this study is limited in that our measure of overtreatment did not take into account professional recommendations for different sub-populations of older adults. Given the administrative nature of our dataset, we were unable to include this level of specificity (e.g. higher A1c targets for patients with cognitive impairment or functional dependence) as we lacked adequate data to effectively differentiate between these different populations. We also did not have other measures of glycemic control (e.g. fructosamine or other glycated end products) in our dataset, which may be relevant for certain patients with clinically significant anemias that could affect HbA1c values. Finally, the generalizability of our findings may be limited, as we restricted analyses to NYC residents who were seen within large academic health systems. Nonetheless, the diversity of our sample (60% women, with broad distribution of race and neighborhood poverty) enhances the external validity of our findings.
In summary, among patients ≥75 years of age with diabetes and other comorbidities in NYC, there was a decline in the rate of inappropriate tight glycemic control from 2017–2022, with a concomitant increase in the use of safer agents. Factors associated with continued inappropriate tight glycemic control remain incompletely understood.
Supplementary Material
Supplementary Material Descriptive title
Supplementary Table 1. Extended Characteristics of patient population aged 75 years and above with diabetes and other chronic medical conditions
Supplementary Table 2. Extended Characteristics of patient population aged 75 years and above with diabetes and other chronic medical conditions
Supplementary Table 3. Extended Characteristics of patient population aged 75 years and above with diabetes and other chronic medical conditions
Key points.
For older adults with diabetes in New York City, the rate of inappropriate tight glycemic control (defined as HbA1c <7.0% with use of insulin or insulin secretagogues) declined by nearly 19% between 2017 and 2022.
There was a concomitant increase in use of Glucagon-like peptide 1 agonists and Sodium-glucose cotransporter 2 inhibitor prescriptions over the same period.
Despite this trend, several comorbidities (heart failure, chronic kidney disease, colorectal cancer, and acute myocardial infarction) were associated with residual inappropriate tight glycemic control in 2022.
Why does this paper matter?
Management of type 2 diabetes mellitus in older adults is challenging due to negative effects from tight glycemic control (defined as HbA1c <7.0%), particularly with insulin or insulin-secretagogues. Using a large, diverse electronic health-based research network, we found that inappropriate tight glycemic control declined over time, implying safer management for older adults by using alternative medications.
Acknowledgments
Funding disclosure
This work was supported by a grant from the NIH/NIA (R01AG073321). Dr. Dodson is further supported by a mid-career mentoring award (K24AG080025) from the NIH/NIA.
Footnotes
Conflicts of Interest
The authors report no conflicts of interest.
Financial Disclosures
No authors report financial disclosures relevant to the current work.
Prior Presentation disclosure
Preliminary results were presented in the form of a poster board at the America College of Cardiology Scientific Sessions 2024 in Atlanta from 6 to 8 April 2024.
Data Availability
The data that support the findings of this study are available from INSIGHT Clinical Research Network but restrictions apply to the availability of these data, which were used under license for the current study and therefore are not publicly available. Data is however available from the authors upon reasonable request and with permission of INSIGHT Clinical Research Network. Datasets used were provided at a limited patient level.
References
- 1.Sircar M, Bhatia A, Munshi M. Review of Hypoglycemia in the Older Adult: Clinical Implications and Management. Can J Diabetes. 2016;40(1):66–72. doi: 10.1016/j.jcjd.2015.10.004 [DOI] [PubMed] [Google Scholar]
- 2.Arnold SV, Lipska KJ, Wang J, Seman L, Mehta SN, Kosiborod M. Use of Intensive Glycemic Management in Older Adults with Diabetes Mellitus. Journal of the American Geriatrics Society. 2018;66(6):1190–1194. doi: 10.1111/jgs.15335 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Bongaerts B, Arnold SV, Charbonnel BH, et al. Inappropriate intensification of glucose-lowering treatment in older patients with type 2 diabetes: the global DISCOVER study. BMJ Open Diabetes Res Care. 2021;9(1):e001585. doi: 10.1136/bmjdrc-2020-001585 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Snell-Bergeon JK, Wadwa RP. Hypoglycemia, Diabetes, and Cardiovascular Disease. Diabetes Technol Ther. 2012;14(Suppl 1):S-51–S-58. doi: 10.1089/dia.2012.0031 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Malabu U, Vangaveti V, Kennedy R. Disease burden evaluation of fall-related events in the elderly due to hypoglycemia and other diabetic complications: A clinical review. Clinical epidemiology. 2014;6:287–294. doi: 10.2147/CLEP.S66821 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Zoungas S, Patel A, Chalmers J, et al. Severe hypoglycemia and risks of vascular events and death. N Engl J Med. 2010;363(15):1410–1418. doi: 10.1056/NEJMoa1003795 [DOI] [PubMed] [Google Scholar]
- 7.Goto A, Arah OA, Goto M, Terauchi Y, Noda M. Severe hypoglycaemia and cardiovascular disease: systematic review and meta-analysis with bias analysis. BMJ. 2013;347:f4533. doi: 10.1136/bmj.f4533 [DOI] [PubMed] [Google Scholar]
- 8.Yaffe K, Falvey CM, Hamilton N, et al. Association Between Hypoglycemia and Dementia in a Biracial Cohort of Older Adults With Diabetes Mellitus. JAMA Intern Med. 2013;173(14):1300–1306. doi: 10.1001/jamainternmed.2013.6176 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Guidelines Abstracted from the American Geriatrics Society Guidelines for Improving the Care of Older Adults with Diabetes Mellitus: 2013 Update. J Am Geriatr Soc. 2013;61(11):2020–2026. doi: 10.1111/jgs.12514 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.ElSayed NA, Aleppo G, Aroda VR, et al. 13. Older Adults: Standards of Care in Diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S216–S229. doi: 10.2337/dc23-S013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.American Diabetes Association. Standards of medical care for patients with diabetes mellitus. Diabetes Care. 2003;26 Suppl 1:S33–50. doi: 10.2337/diacare.26.2007.s33 [DOI] [PubMed] [Google Scholar]
- 12.Lipska KJ, Ross JS, Miao Y, Shah ND, Lee SJ, Steinman MA. Potential overtreatment of diabetes mellitus in older adults with tight glycemic control. JAMA Intern Med. 2015;175(3):356–362. doi: 10.1001/jamainternmed.2014.7345 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Solomon SD, McMurray JJV, Claggett B, et al. Dapagliflozin in Heart Failure with Mildly Reduced or Preserved Ejection Fraction. N Engl J Med. 2022;387(12):1089–1098. doi: 10.1056/NEJMoa2206286 [DOI] [PubMed] [Google Scholar]
- 14.McMurray JJV, Solomon SD, Inzucchi SE, et al. Dapagliflozin in Patients with Heart Failure and Reduced Ejection Fraction. N Engl J Med. 2019;381(21):1995–2008. doi: 10.1056/NEJMoa1911303 [DOI] [PubMed] [Google Scholar]
- 15.Data Our. Published June 28, 2019. Accessed August 21, 2023. https://insightcrn.org/our-data/
- 16.Kaushal R, Hripcsak G, Ascheim DD, et al. Changing the research landscape: the New York City Clinical Data Research Network. J Am Med Inform Assoc. 2014;21(4):587–590. doi: 10.1136/amiajnl-2014-002764 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Lochner KA, Cox CS. Prevalence of multiple chronic conditions among Medicare beneficiaries, United States, 2010. Prev Chronic Dis. 2013;10:E61. doi: 10.5888/pcd10.120137 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Nelson SJ, Zeng K, Kilbourne J, Powell T, Moore R. Normalized names for clinical drugs: RxNorm at 6 years. J Am Med Inform Assoc. 2011;18(4):441–448. doi: 10.1136/amiajnl-2011-000116 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.New York City Department of Health and Mental Hygiene. Neighborhood Poverty and Infectious Diseases: Health Disparities in New York City. Published online March 2016:9. [Google Scholar]
- 20.Huang ES, Laiteerapong N, Liu JY, John PM, Moffet HH, Karter AJ. Rates of Complications and Mortality in Older Diabetes Patients: The Diabetes and Aging Study. JAMA Intern Med. 2014;174(2):251–258. doi: 10.1001/jamainternmed.2013.12956 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Geller AI, Shehab N, Lovegrove MC, et al. National estimates of insulin-related hypoglycemia and errors leading to emergency department visits and hospitalizations. JAMA Intern Med. 2014;174(5):678–686. doi: 10.1001/jamainternmed.2014.136 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Baigent C, Emberson J, Haynes R, et al. Impact of diabetes on the effects of sodium glucose co-transporter-2 inhibitors on kidney outcomes: collaborative meta-analysis of large placebo-controlled trials. The Lancet. 2022;400(10365):1788–1801. doi: 10.1016/S0140-6736(22)02074-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Marso SP, Daniels GH, Brown-Frandsen K, et al. Liraglutide and Cardiovascular Outcomes in Type 2 Diabetes. N Engl J Med. 2016;375(4):311–322. doi: 10.1056/NEJMoa1603827 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.By the 2023 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2023 updated AGS Beers Criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2023;71(7):2052–2081. doi: 10.1111/jgs.18372 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Xu G, Liu B, Sun Y, et al. Prevalence of diagnosed type 1 and type 2 diabetes among US adults in 2016 and 2017: population based study. BMJ. 2018;362:k1497. doi: 10.1136/bmj.k1497 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Material Descriptive title
Supplementary Table 1. Extended Characteristics of patient population aged 75 years and above with diabetes and other chronic medical conditions
Supplementary Table 2. Extended Characteristics of patient population aged 75 years and above with diabetes and other chronic medical conditions
Supplementary Table 3. Extended Characteristics of patient population aged 75 years and above with diabetes and other chronic medical conditions
Data Availability Statement
The data that support the findings of this study are available from INSIGHT Clinical Research Network but restrictions apply to the availability of these data, which were used under license for the current study and therefore are not publicly available. Data is however available from the authors upon reasonable request and with permission of INSIGHT Clinical Research Network. Datasets used were provided at a limited patient level.