Infectious diseases, comorbidities and outcomes in hospitalized people who inject drugs (PWID)

Jacqueline Lim; Sureka Pavalagantharajah; Chris P Verschoor; Eric Lentz; Mark Loeb; Mitchell Levine; Marek Smieja; Lawrence Mbuagbaw; Dale Kalina; Jean-Eric Tarride; Tim O’Shea; Anna Cvetkovic; Sarah van Gaalen; Aidan Reid Findlater; Robin Lennox; Carol Bassim; Cynthia Lokker; Elizabeth Alvarez

doi:10.1371/journal.pone.0266663

. 2022 Apr 20;17(4):e0266663. doi: 10.1371/journal.pone.0266663

Infectious diseases, comorbidities and outcomes in hospitalized people who inject drugs (PWID)

Jacqueline Lim ^1,^¤,^#, Sureka Pavalagantharajah ^2,^#, Chris P Verschoor ^3,^#, Eric Lentz ^2,^#, Mark Loeb ^4,^#, Mitchell Levine ^5,^#, Marek Smieja ^4,^#, Lawrence Mbuagbaw ^5,^#, Dale Kalina ^2,^#, Jean-Eric Tarride ^5,^6,^#, Tim O’Shea ^2,^7,^#, Anna Cvetkovic ^2,^#, Sarah van Gaalen ^8,^#, Aidan Reid Findlater ^2,^#, Robin Lennox ^9,^#, Carol Bassim ^2,^#, Cynthia Lokker ^5,^#, Elizabeth Alvarez ^5,^6,^*

Editor: Yu Mon Saw¹⁰

¹Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada

²Department of Medicine, McMaster University, Hamilton, Ontario, Canada

³Health Sciences North Research Institute, Sudbury, Ontario, Canada

⁴Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada

⁵Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada

⁶Centre for Health Economics and Policy Analysis (CHEPA), McMaster University, Hamilton, Ontario, Canada

⁷Population Health Research Institute, Hamilton, Ontario, Canada

⁸Department of Family Medicine, Queen’s University, Kingston, Ontario, Canada

⁹Department of Family Medicine, McMaster University, Hamilton, Ontario, Canada

¹⁰Nagoya University Asian Satellite Campuses Institute, Nagoya University Graduate School of Medicine, JAPAN

Competing Interests: The authors have declared that no competing interests exist.

^¤

Current address: Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada

^✉

* E-mail: alvare@mcmaster.ca

Contributed equally.

Roles

Jacqueline Lim: Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

Sureka Pavalagantharajah: Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – review & editing

Chris P Verschoor: Formal analysis, Methodology, Software, Writing – original draft, Writing – review & editing

Eric Lentz: Data curation, Methodology, Writing – review & editing

Mark Loeb: Conceptualization, Writing – review & editing

Mitchell Levine: Conceptualization, Writing – review & editing

Marek Smieja: Conceptualization, Writing – review & editing

Lawrence Mbuagbaw: Conceptualization, Writing – review & editing

Dale Kalina: Conceptualization, Writing – review & editing

Jean-Eric Tarride: Conceptualization, Writing – review & editing

Tim O’Shea: Conceptualization, Methodology, Project administration, Software, Writing – review & editing

Anna Cvetkovic: Conceptualization, Methodology, Software, Writing – review & editing

Sarah van Gaalen: Conceptualization, Writing – review & editing

Aidan Reid Findlater: Conceptualization, Writing – review & editing

Robin Lennox: Conceptualization, Writing – review & editing

Carol Bassim: Conceptualization, Writing – review & editing

Cynthia Lokker: Conceptualization, Writing – review & editing

Elizabeth Alvarez: Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

Yu Mon Saw: Editor

PMCID: PMC9020696 PMID: 35443003

Abstract

Injection drug use poses a public health challenge. Clinical experience indicates that people who inject drugs (PWID) are hospitalized frequently for infectious diseases, but little is known about outcomes when admitted. Charts were identified from local hospitals between 2013–2018 using consultation lists and hospital record searches. Included individuals injected drugs in the past six months and presented with infection. Charts were accessed using the hospital information system, undergoing primary and secondary reviews using Research Electronic Data Capture (REDCap). The Wilcoxon rank-sum test was used for comparisons between outcome categories. Categorical data were summarized as count and frequency, and compared using Fisher’s exact test. Of 240 individuals, 33% were admitted to the intensive care unit, 36% underwent surgery, 12% left against medical advice (AMA), and 9% died. Infectious diagnoses included bacteremia (31%), abscess (29%), endocarditis (29%), cellulitis (20%), sepsis (10%), osteomyelitis (9%), septic arthritis (8%), pneumonia (7%), discitis (2%), meningitis/encephalitis (2%), or other (7%). Sixty-six percent had stable housing and 60% had a family physician. Fifty-four percent of patient-initiated discharges were seen in the emergency department within 30 days and 29% were readmitted. PWID are at risk for infections. Understanding their healthcare trajectory is essential to improve their care.

Introduction

Injection drug use is a major public health concern in Canada [1]. In 2016, there were an estimated 171,900 people who inject drugs (PWID) in Canada, representing 0.7% of the population [2]. PWID are at high risk for infectious complications of drug use, including blood-borne viral (e.g. Human immunodeficiency virus (HIV), hepatitis B and C) and bacterial infections (e.g. staphylococci that cause acute complications such as bacteremia with sepsis and endocarditis) [3,4].

Clinical experience indicates that PWID are hospitalized and re-hospitalized frequently [5]. However, relatively little is known about the health trajectory of this population in that there are sparse data about how frequently PWID present to acute care and their longitudinal outcomes over time. The nature of their admissions is unclear when admitted to hospital for infectious complications of injection drug use. Risk for complications once PWID are hospitalized, such as death or admission to critical care, are ill-defined. Special concerns exist around PWID with infections and patient-initiated discharges, generally referred to as discharge against medical advice (AMA), and among those who leave with a peripherally inserted central catheter (PICC) line in place for the administration of long-term antibiotics or other therapies [6,7]. Patient-initiated discharges have been associated with increased readmission, morbidity and mortality, and healthcare costs in PWID [5]. Previous cohort studies have aimed to understand the relationship between specific infectious diseases (e.g., HIV, hepatitis C) and intravenous drug use, but these studies have not looked at all drug-related infections, of which may be more urgent and life-threatening than chronic diagnoses. Prior studies have not considered patients’ healthcare trajectories after hospitalization for infection, nor their effects on the health system [8–10]. Treatments of infections related to injection drug use, such as HIV and hepatitis C and their complications, have also shifted from acute care to community-based care as better treatments for these have been developed, so there has been a shift in infectious diseases treated in hospitals [11]. Understanding the types of infectious diseases managed in acute care and outcomes of PWID represents the first step in addressing these concerns. Achieving such an understanding could lead to focused interventions to enhance continuity of care in this population.

One objective of the current investigation was to review hospital admissions of PWID with infections who access hospitals in Hamilton, Ontario, Canada to understand the types of infections, comorbidities, hospital service use and outcomes, including patient-initiated discharge and death, among this population. This project will serve as a first, foundational step to understand PWID by establishing the feasibility of cohort studies among this group, and subsequently allow the analysis of their longitudinal healthcare trajectories needed to improve their overall care.

Methods

Study design

A retrospective chart review was conducted to study PWID admitted to hospitals in Hamilton, Ontario between 2013 and 2018 and who were treated for infection. The study protocol was approved by the Hamilton integrated Research Ethics Board (HiREB #5556). Due to the nature of the retrospective review, the requirement for obtaining informed consent from participants was waived by the ethics board.

Sample size, setting, and inclusion

Based on clinical experience and current literature, the expected proportion of patient-initiated discharge in this population is 25–30% [7]. A sample size of 246 participants was required to allow for identifying between 30 and 50 events, with a 95% confidence interval and a 5% margin of error [12]. This number would allow to test for differences in moderately prevalent factors between patient-initiated and planned discharges. Deaths during hospital admission were also used as an outcome measure but were not used for sample size determination. Since identification of PWID with infection can be challenging to conduct using discharge diagnoses, participants were identified using the following methods:

The Infectious Diseases consult services in Hamilton maintain a daily patient list from two local hospitals, Juravinski Hospital and Hamilton General Hospital, and have been doing so since 2013. Both participating hospitals are tertiary centres located in the downtown area of Hamilton. Juravinski Hospital is a full-service general hospital with 228 beds and Hamilton General Hospital is a teaching hospital with 607 beds. This list was reviewed to identify PWID by either identifying self-reporting PWID who were admitted for drug related infections (e.g. cellulitis), or by identifying those who fit other criteria leading to the possibility that they might use injection drugs (e.g., endocarditis).
Participants were also identified by searching hospital records for relevant International Statistical Classification of Diseases and Related Health Problems (ICD) Codes using the following terms: drug use, substance use, substance use disorder, drug abuse, drug addiction, injection drug use, opioid dependence AND cellulitis, bacteremia, endocarditis, HIV, hepatitis B, hepatitis C and osteomyelitis.

For each individual patient, data were extracted for their first identified hospital admission. If there were multiple admissions, the earliest admission was included. Participants were included in the study if they were identified to have injected drugs within the 6 months leading up to their index hospital admission. Use of injection drugs in the 6 months prior to admission was chosen, as this time period allows for balancing of self-reported drug use (i.e., individuals may be more open to disclosing past use than current use) with the relationship between drug use and infections (i.e., the infection is more likely to be related to drug use if the events are closer in time) [1]. Participants were excluded if they had not injected drugs within the past 6 months, had only a remote history of injection drug use, were unidentifiable using the hospital information system (Meditech), or were not treated for any infection.

Data collection, management, and storage

Patient files were accessed securely using Meditech. Data extractors inputted patient information into Research Electronic Data Capture (REDCap), a secure, web-based software platform [13]. Patient information was collected using two forms on REDCap. Primary reviewers extracted data and entered information into a study key, which included identifying information, such as the participant’s name, provincial health insurance number, and full date of birth. The second form was used to record details of the index hospital admission. Following primary extraction, secondary reviews were conducted by an independent reviewer who re-assessed details to ensure accuracy and consistency. For discrepancies between primary and secondary reviews, the inconsistency was logged, and a third reviewer was consulted. To respect the confidentiality and anonymity of patients, there were no paper records kept of the data at any point during this study. Only data extractors had access to REDCap, and all activities were logged through REDCap.

Data collected for every unique participant included demographic information (name, health insurance number, gender, date of birth, housing status, primary care physician) and information on the index admission: admitting diagnosis, diagnosis for which infectious disease service was consulted, comorbidities, HIV status, hepatitis B and C status, length of stay, events during the hospital stay (social work consult, ICU admission, surgery), discharge disposition (patient-initiated discharge, discharged home or to long-term care facility, death), and emergency room visit or readmission to hospital within 30 days after discharge. Consult notes, operative reports (if applicable), notes from social workers, discharge summaries, laboratory reports, and diagnostic codes for the index admission were used to abstract patient data for these queries. Comorbidities included those identified previously, as listed in the electronic record system, and those identified during the index hospitalization. Information about current substance use was also collected, if known; this information was extracted from consult notes or notes from the social workers, in which patients openly disclosed the substances being used leading up to the index admission. Results of urine toxicology tests were also referenced to obtain data on substances used, if available. Prescribed substances were not included for this query. While all substances can be prescribed medications, in this paper the use of these substances was collected in the context of IVDU and the formulation for use was not extracted as data. Information pertaining to whether or not a patient was receiving opioid agonist therapy was collected based on consult notes as well. Names and insurance numbers were collected to ensure these were unique individuals, but were anonymized prior to statistical analysis to protect confidentiality and reduce the risk of identifying participants.

Statistical analysis

For data pertaining to demographics, infectious disease diagnoses, and events during hospital stay, continuous variables were summarized as the median and range, and categorical variables as the count and frequency. To evaluate potential risk factors of our primary outcomes, patient-initiated discharge and death, patients were stratified by either outcome and the distribution of the aforementioned variable compared by either Wilcoxon rank-sum test or Fisher’s exact test; missing data was removed prior to these analyses, and p<0.05 was considered statistically significant. All analyses were performed in the R environment (v3.6) [14].

Data audit

An audit was conducted for a subset of 10 charts to ensure that patient information was captured accurately. This subset of charts was randomly selected. Survey responses for these charts on REDCap were compared against the patient charts on Meditech. The audit was conducted by three of the authors, who independently ensured the survey responses reflected the original dictations. Discrepancies subject to interpretation were noted and brought forth to the other auditors. Changes to survey responses were only made following discussion and approval from the three authors conducting the audit.

Data sharing and availability

There are legal restrictions to sharing the de-identified data set. The original data is held by the respective hospitals, and data sharing agreements with the involved institutions that contributed data prohibit the authors from making the dataset publicly available. The full dataset creation plan is available from the authors upon request. For requests for de-identified and specified data access, contact the faculty in charge of the dataset at alvare@mcmaster.ca, or for hospital data requests, please contact the Hamilton Health Sciences Decision Support Team at DecisionSupport@hhsc.ca.

Results

From the 280 unique charts initially retrieved, our final eligible sample consisted of 240 patients. Following the application of the above criteria, 27 individuals were excluded from 211 identified through the first search method (infectious diseases inpatient lists), and 13 individuals were excluded from the 69 identified through the second search method (using ICD codes) from 964 charts found through the searches. Individuals were excluded on the basis of their drug use as well as their admitting diagnosis upon inspection of their charts on the Meditech system. If there was evidence in the consult notes to suggest that a patient had not injected drugs in the 6 months prior to their index admission, or the list of admitting diagnoses did not include an infectious disease, individuals were considered ineligible to be included in our study.

Demographic data are summarized in Table 1. At the time of admission, the average age of the sample was 38 years and 55% were male. One hundred fifty-eight (66%) of the sample were stably housed and 143 (60%) had a primary care physician at the time of their hospitalization. During the index hospital admission, 161 (68%) individuals had hepatitis C, 10 (4%) had HIV, and 4 (2%) had hepatitis B. Primary infectious disease diagnoses included bacteremia (31%), abscess (29%), endocarditis (29%), cellulitis (20%), sepsis (10%), osteomyelitis (9%), septic arthritis (8%), pneumonia (7%), discitis (5%), meningitis/encephalitis (2%), and other (7%). Overall, the median length of stay was 11 days, during which 129 (54%) received a consultation from social work, 79 (33%) were admitted to the ICU, and 87 (36%) underwent surgery. Twenty-one (9%) of the sample died during hospitalization and 28 (12%) discharges were self-initiated during the index admission. Within 30 days following discharge, 70 (29%) were seen in the ER again and 32 (13%) were readmitted to the hospital. For patient-initiated discharges, 15 (54%) were seen in the ER and eight (29%) were readmitted within 30 days of leaving the hospital. One hundred forty-four (60%) individuals had a PICC line placed during the index hospital admission, and five (2.1%) patients self-initiated their discharge with a PICC line in place (data not shown). Significant differences were identified among patient-initiated discharges in regard to housing status, primary care physician status, comorbid HIV, readmissions within 30 days, and ER visits within 30 days.

Table 1. Demographics, infectious disease diagnoses and outcomes.

Demographics and comorbid infectious disease diagnoses ^§	Total	Patient-initiated discharge (Missing N = 9)		Died (Missing N = 1)
Demographics and comorbid infectious disease diagnoses ^§	(N = 240)	Yes (N = 28)	No (N = 203)	Yes (N = 21)	No (N = 218)
Age (years), median (range)	38 (18–68)	35 (25–50)	38 (18–68)^*	42 (21–63)	37 (18–68)
Sex [Female], n (%)	109 (45%)	14 (50%)	89 (44%)	8 (38%)	101 (46%)
Housing status [Stable], n (%)	158 (66%)^β	12 (43%) ^β	140 (69%) ^*^β	14 (67%)^β	143 (65%)^β
Primary care physician [Yes], n (%)	143 (60%)^Փ	10 (36%) ^β	130 (64%)^*^Փ	11 (52%)^Փ	131 (60%)^Փ
HIV, n (%)	10 (4%)	4 (14%)	6 (3%) ^*	1 (5%)	9 (4%)
Hepatitis B, n (%)	4 (2%)	1 (4%)	3 (1%)	0 (0%)	4 (2%)
Hepatitis C, n (%)	161 (68%)	19 (68%)	136 (67%)	12 (57%)	149 (68%)
Infectious disease diagnoses, n (%) ^§
Bacteremia	75 (31%)	6 (21%)	67 (33%)	8 (38%)	67 (31%)
Abscess	70 (29%)	6 (21%)	64 (32%)	2 (10%)	68 (31%) ^*
Endocarditis	70 (29%)	8 (29%)	55 (27%)	9 (43%)	60 (28%)
Cellulitis	49 (20%)	7 (25%)	41 (20%)	1 (5%)	48 (22%)
Sepsis	24 (10%)	0 (0%)	23 (11%)	9 (43%)	15 (7%) ^***
Osteomyelitis	21 (9%)	3 (11%)	17 (8%)	0 (0%)	21 (10%)
Septic arthritis	18 (8%)	1 (4%)	17 (8%)	0 (0%)	18 (8%)
Pneumonia	17(7%)	1 (4%)	16 (8%)	1 (5%)	16 (7%)
Discitis	11 (5%)	1 (4%)	10 (5%)	0 (0%)	11 (5%)
Meningitis/encephalitis	5 (2%)	1 (4%)	4 (2%)	1 (5%)	4 (2%)
Other infectious disease diagnosis	17 (7%)	3 (11%)	13 (6%)	0 (0%)	17 (8%)
Diagnosis count/patient, median (range)	1 (1–5)	1 (1–4)	1 (1–5)	1 (1–3)	1 (1–5)
Events and outcomes ^§
Length of stay (days), median (range)	11 (0–229)^Փ	8 (0–70)	11 (0–229)^Փ	8 (1–27)^Փ	11 (0–229)^Փ
Social work consult, n (%)	129 (54%)	18 (64%)	107 (53%)	12 (57%)	116 (53%)
ICU admission, n (%)	79 (33%)^Փ	6 (21%)	68 (33%)	20(95%)	58 (27%)^***^Փ
Surgery, n (%)	87 (36%)^Փ	9 (32%)	72 (35%)	7 (33%)	79 (36%)^Փ
Readmission (30 days), n (%)	32 (13%)^Փ	8 (29%)	23 (11%) ^*^Փ	N/A	32 (15%)^Փ
ER Visit (30 days), n (%)	70 (29%)^Փ	15 (54%) ^Փ	53 (26%) ^** ^Փ	N/A	70 (32%)^Փ

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§Statistics are for the dichotomous category in square brackets or the "yes" category if not explicitly stated.

Statistically significant differences between outcome strata are denoted by asterisks

*** p<0.001

** p<0.01

*p<0.05.

Փ Missing <5%; β Missing <10%.

N/A—not applicable.

A variety of comorbid conditions were noted during hospitalization, the most common being chronic pain (20%), depression (18%), anxiety/panic disorder (12%), and asthma (12%). The median number of comorbidities was one and ranged from zero to nine. For the full list of comorbidities, see Table 2. For those with abscesses (N = 70), the majority were located on the upper extremities (26%), spine (23%), or hip/pelvis (14%); the full range of sites are summarized in Table 3.

Table 2. Comorbidities.

Comorbidities^*		Total (N = 240) n (%)
Mental health	Depression	42 (18%)
	Anxiety / panic disorder	28 (12%)
	Bipolar disorder	16 (7%)
	Attention-deficit/hyperactivity disorder (ADHD)	12 (5%)
	Schizophrenia / psychosis / hallucinations	10 (4%)
	Post-traumatic stress disorder (PTSD)	9 (4%)
	Other mental health conditions	13 (5%)
Chronic pain	Chronic pain	48 (20%)
Neurologic	Seizure disorder	7 (3%)
	Brain injury	6 (2%)
	Stroke	5 (2%)
	Other neurologic conditions	9 (4%)
Pulmonary / respiratory	Asthma	29 (12%)
	Chronic obstructive pulmonary disease (COPD)	13 (5%)
	Other pulmonary respiratory conditions	4 (2%)
Cardiovascular	Hypertension	22 (9%)
	Thrombosis (e.g., deep vein thrombosis, pulmonary embolism)	13 (5%)
	Congestive heart failure	9 (4%)
	Valvular conditions	7 (3%)
	Arrhythmias	6 (2%)
	Dyslipidemia	5 (2%)
	Other cardiovascular conditions	14 (6%)
Gastrointestinal	Gastroesophageal reflux disease (GERD)	12 (5%)
	Ulcer	8 (3%)
	Other gastrointestinal conditions	16 (7%)
Metabolic / endocrine	Diabetes (type 1, type 2 or unspecified)	11 (5%)
	Other metabolic / endocrine conditions	9 (4%)
Renal	Renal failure or dysfunction	5 (2%)
	Other renal conditions	5 (2%)
Musculoskeletal / rheumatologic	Arthritis	12 (5%)
	Systemic inflammatory conditions	5 (2%)
	Other musculoskeletal / rheumatologic	15 (6%)
Hematologic / oncologic	Anemia	12 (5%)
	Other hematological or oncological conditions	7 (3%)
Comorbidity count/patient, median (range)		1 (0–11)

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*Could have more than one comorbidity.

Table 3. Site of abscesses.

Site of Abscess^*	Total (N = 70) n (%)
Upper extremity	18 (26%)
Spine	16 (23%)
Hip / pelvis	10 (14%)
Lower extremity	8 (11%)
Chest	8 (11%)
Abdominal	6 (9%)
Head/neck	5 (7%)
Brain	4 (6%)
Not specified	3 (4%)

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*Could have more than one site.

The most commonly used opioids among the sample were hydromorphone (35%), unspecified opioids (20%) and heroin (19%). Common non-opioid substances used by the sample included cocaine (40%), methamphetamines (21%), and alcohol (18%) (see Table 4 for full list of substances used). The median number of substances used was two. Eighty-one (34%) of individuals were on opioid agonist therapy prior to and at the time of hospitalization, of which, 68 (28%) were receiving methadone and 13 (5.4%) were receiving buprenorphine/naloxone.

Table 4. Substances used and OAT (Opioid agonist therapy).

Substances^*	Total (N = 240) n (%)
Opioid
Hydromorphone	83 (35%)
Unspecified opioid	49 (20%)
Heroin	46 (19%)
Fentanyl	16 (7%)
Oxycodone	15 (6%)
Morphine	13 (5%)
Codeine	3 (1%)
Hydrocodone	1 (0%)
Non-Opioid Substances
Cocaine	96 (40%)
Methamphetamines	51 (21%)
Alcohol	43 (18%)
Cannabis	31 (13%)
Benzodiazepines	9 (4%)
Other	39 (16%)
Unknown	46 (19%)
Substance count/participant, median (range)	2 (1–8)
Opioid agonist therapy (OAT)
On OAT	81 (34%)^Փ
Type of OAT
Methadone	68 (28%)
Buprenorphine / Naloxone	13 (5.4%)

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*Could use more than one substance.

Փ Missing <5%.

Discussion

Main findings

Between 2013–2018, 240 individual PWID were admitted with infections at two academic hospitals in Hamilton, Ontario. Other hospitals in the area were not included in this study, as our target sample size was achieved through applying our search to the two included hospitals. It is expected that more unique PWID are admitted to all Hamilton hospitals for infections. Within our sample, 21 patients (9%) died. Sepsis and ICU admission were associated with higher rates of death. During the index hospital admission, 79 (33%) individuals were admitted to the ICU, and 87 (36%) underwent surgery.

Twelve percent (28 individuals) had a patient-initiated discharge; which was associated with increased rates of hospital readmission and ER visits within 30 days of discharge. The proportion of patient-initiated discharges in our study is low compared to previous findings that report up to 25–30% of patient-initiated discharges among PWID [5]. We also found that PWID who had a self-initiated discharge were more likely to have unstable housing, lack a primary care physician, and be living with HIV. The relationship between homelessness, decreased antiretroviral use, increased active drug use and types of drugs used, specifically shorter-acting drugs such as cocaine, have been described [15–17]. The frequency of social work consults were not found to be significantly different for those with patient-initiated discharge. There is a need for further exploration on how to best support PWID, and in particular, individuals experiencing homelessness while in the hospital [6,18]. Thirty-four percent of the sample were using OAT at the time of admission, which is relatively low compared to the 55–66% reported nationally [19].

Fit within the literature

Our findings are concordant with Canadian national statistics and other studies. National surveillance initiatives report that 66–68% of PWID have evidence of chronic or past hepatitis C infection [3,20]. The proportion of our sample with hepatitis C was 68%. Similar reports estimate that HIV prevalence among PWID has been increasing in Canada. In 1997, the prevalence of HIV among PWID was 4.7%, but more recent reports indicate this to be closer to 10% [3,20,21]. In our sample from 2013–2018, 4% of individuals were HIV positive. However, as a cross-sectional study, increases in incidence during this time were not ascertained. Similarly, our findings surrounding substances used is comparable to the statistics reported in a needs assessment and feasibility study done for the Hamilton supervised injection site. Survey responses in this report indicated that the top five most commonly injected drugs among respondents included crystal meth, hydromorphone, cocaine, heroin, and morphine [1]. The most commonly injected opioids in our study were hydromorphone and heroin, and of non-opioid substances, cocaine and methamphetamines were most common. The alignment with national health reports and current survey statistics ensures credibility and indicates our sample is similar to Canadian PWID at large.

However, our investigation is unique in its aim and depth through collecting data on relevant factors and health outcomes of PWID. A related study by this group is looking at features of health programs and services in Canada for the prevention and management of infections in PWID, the findings of which reveal a gap in the literature; there are very few studies focusing on hospitalization among PWID [22]. This investigation thus offers detailed insight on a variety of indicators that are not typically explored in current research, such as infectious diseases and outcomes linked to acute care for PWID.

Strengths and limitations

Our study used individual-level data. Using these records ensures accurate reflection of recent approaches to care of PWID in local hospitals. Additionally, data were extracted in duplicate to minimize errors. Any discrepancies between primary and secondary reviews were adjudicated by a third independent reviewer. As a final step, an audit of the data was conducted to ensure the data correctly reflected patient records. Implementing such thorough protocols help ensure the consistency and accuracy of data collection.

However, electronic medical record systems are not perfect. Although hospital records are typically detailed and coherent, some patients were missing initial consult and/or discharge reports and details regarding their index admission were thus recorded as “unknown” or “missing” responses during data collection. Another limitation is the method of identifying eligible participants. As the majority of study participants were selected by referencing ID consult lists, our sample consists of patients with more severe presentations. Thus, the generalizability and applicability of our findings may be limited to more severe cases among the PWID population and in non-urban centres. It is also important to note that cross-sectional investigations, such as the present study, are incomplete in their ability to capture an individual’s changing health status and their recurring interactions with the healthcare system. For instance, diagnoses of HIV and hepatitis could be overlooked if patients were not tested for these viral infections during the index admission. Patients may self-initiate their discharge during subsequent admissions, implicating their outcomes and risk of re-hospitalization in a manner that was not captured initially. This limitation highlights the importance of future studies dedicated to longitudinal analyses of the outcomes and trajectories of PWID. Lastly, it is important to recognize the limitations with our methods of statistical analysis. With bivariate analyses, our investigation is limited in the number of covariates that can be included.

Implications for policy and practice

Given the high rates of ICU admissions, deaths, patient-initiated discharges and other indicators, there is a need for hospital-level interventions to address the needs of PWID with infectious complications of drug use. Knowledge of the types of infections and comorbidities that PWID commonly present with may inform planning at the hospital level for health services and resource allocation. Additionally, understanding the characteristics of patient-initiated discharge among PWID allows for the development of targeted approaches to prevent said outcome.

Social determinants of health and continuity of care are evidently important factors in the health of PWID. Rates of unstable housing and access to primary care were low in our study population, and both were associated with higher rates of patient-directed discharge. As such, initiatives to enhance primary care attachment and address housing insecurity for PWID after hospitalization should be explored. Access to low-barrier HIV services and treatment, as well as pre-exposure prophylaxis in the prevention of HIV, are important considerations for this subgroup of PWID [23,24].

Implications for future research

This study demonstrated that there are sufficient numbers of PWID who experience infectious complications of drug use to develop a prospective cohort to further elucidate the healthcare trajectories and health services utilization of PWID. Given the limitations of a cross-sectional study design, longer term and preferably prospective analyses of hospital admissions and health care utilization among PWID are warranted to understand the healthcare trajectories of this population. Approaching future research with a wider scope may lead to a more comprehensive understanding of healthcare trajectories, such as social service use and health outcomes, and can inform practice with more acuity.

Another avenue for investigation entails the linking of the current data with administrative information to understand the outcomes and risk factors applicable to PWID, such as re-hospitalization, death, resource utilization, and the associated economic costs. Having a validated search string to identify PWID with infections from administrative databases would be helpful to identify a larger sample to further explore risk factors identified in this and previous studies.

Conclusion

Injection drug use poses a significant public health challenge, as PWID are at high risk of serious infectious complications of drug use that require admission to hospital. Furthermore, we found that PWID patients frequently self-initiate their discharge from the hospital, which was associated with hospital readmission and ER visits. Social factors such as housing status and access to primary care were also related to patient-initiated discharge, and may thus implicate the healthcare trajectories of PWID. Ergo, it is important to focus on the types of infections PWID experience, their comorbidities, as well as health care service use and outcomes. This may help in the planning of hospital and integrated health and social services for this high-risk population.

Acknowledgments

We wish to thank all the data extractors who helped review charts: Alice Lu, Jessica Jung, Edward Koo, Ravinder Sandhu, Michael Collins, E. Dimitra Bednar, Mylini Saposan, Quinten K. Clarke, David Beisel, and Eden Shaul.

Data Availability

There are legal restrictions to sharing a de-identified data set. The reasons are outlined here: The original data is held by the respective hospitals, and data sharing agreements with the involved institutions that contributed data prohibit the authors from making the dataset publicly available. The full dataset creation plan is available from the authors upon request. For requests for de-identified and specified data access, contact the faculty in charge of the dataset at alvare@mcmaster.ca or dcampbel@stjosham.on.ca, or if you are interested in requesting hospital data, please contact the Hamilton Health Sciences Decision Support Team at DecisionSupport@hhsc.ca.

Funding Statement

The author(s) received no specific funding for this work.

References

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PLoS One. doi: 10.1371/journal.pone.0266663.r001

Decision Letter 0

Judith I Tsui

9 Jul 2021

PONE-D-21-11155

Infectious diseases, comorbidities and outcomes in hospitalized people who inject drugs (PWID)

PLOS ONE

Dear Dr. Alvarez,

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Reviewer #2: Partly

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Reviewer #1: Yes

Reviewer #2: No

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Reviewer #1: No

Reviewer #2: No

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Summary: This manuscript used hospital charts/records to abstract data from people who inject drugs and hospital diagnoses and outcomes. 240 individuals were included in the analysis from two hospitals in Hamilton, Ontario. One third were admitted to the ICU, 36% had surgery, 9% died and 12% left AMA. Bacteremia was the most common diagnosis. Many of those who left AMA were seen in the ER or re-admitted within 30 days. In general, the topic of health outcomes in PWID is important to try and improve hospital care. However, the paper lacks details in some areas to help conceptualize the findings.

Major comments:

1. A better understanding of the hospitals included in this manuscript would be helpful—all hospitals in Hamilton? What kind of hospitals, etc. it sounds like these are urban? Those who aren’t familiar with Hamilton and/or Ontaria would benefit from a better understanding of this.

2. Could you please describe the data audit in more detail? What happened if discrepancies were found? Who conducted the audit?

3. In general, there are many areas that I would recommend adding more detail either in the body of the text or in a supplement. What criteria were used to abstract patient data including: HIV status (based on labs, meds, diagnosis codes’]?); Hep C status (labs? Treated/untreated?); comorbid conditions? Were these included if documented in a note or need ICD9/10? A line in the discussion describes missing HIV or Hep C diagnoses if they were tested during the index admission—so was this the only way these diagnoses were captured? The index admission was used but where chart records examined prior to index admission?

4. The use of two reviewers, a third as a tie-breaker, and an audit adds rigor to the study.

Minor comments:

1. Could you clarify that those charts who were excluded in paragraph 1 of the results were because they didn’t mean eligibility criteria upon further inspection?

2. Substances used: is this inpatient? Or prior to admission? Hydromorphone is a prescription drug but is it being misused/abused/bought in these settings?

Reviewer #2: This manuscript is a descriptive, retrospective chart review study of PWID admitted to two hospitals with infections in a Hamilton, Ontario between 2013 and 2018. The authors report demographics, diagnoses, as well as healthcare utilization for this cohort and provide stratified results by patient-initiated and death-status. While the study nicely describes PWID/ID hospital care utilization, the manuscript lacks focus and the principal conclusions that patient directed discharges and readmissions are common have been demonstrated previously in national datasets. I think the introduction and discussion could better frame the primary hypotheses and contextualize the limited analyses performed. Additionally, the authors frame the manuscript as an initial baseline study to address longer term trajectories and improve care for PWID but do not describe any addiction interventions or withdrawal management approaches in the hospital which is essential and could be one of the strengths of retrospective chart review study like this (similar studies using publicly available databases lack detailed inpatient medication administration records or other interventions). Overall, the authors have done considerable work to gather this data yet lacks key information and requires additional focus. Below are several additional suggestions to strengthen the manuscript.

Major comments:

1. Abstract: “little is known about outcomes” – The manuscript would be better framed with more specific identification of the gap and the goals. Which outcomes? There’s a fairly robust literature on outcomes related to specific infectious diseases (HIV, HCV, endocarditis) though less about this larger collection of diagnoses.

2. Intro: Little is known about “health trajectory of this population.” I would define this term as it is important theoretically to the framing (over what time period, what outcomes).

3. Intro: P 4, line 85: The authors argue that by including all infections among PWID together this manuscript fills a gap in the literature. Each of these infections has distinct presentations and clinical courses, I think the manuscript would be stronger with a theoretical argument about why it is crucial to group these infections together.

4. P5 line 98: “This project will set the stage to further study healthcare trajectories of PWID with infections.” I’m not clear where this is going or what this means. I would suggest using this space in the manuscript instead to set up the analyses you are doing in this paper.

5. P5 Line 99: “The overall aim…” – I would delete or make this sentence much more focused. Based on the analyses later in the manuscript, it seems the goal of this manuscript is to understand characteristics of people who do and do not have patient initiated discharges but the introduction doesn’t really set this up.

6. P5, Line 107 --- This is pretty well documented in the literature in addition to clinical experience.

7. Methods: I would encourage the authors to describe a bit more about how injection drug use in the last 6 months determined/verified.

8. If patient-initiated discharges are indeed the focus of this paper, it would be valuable to report on medication for opioid use disorder provision in the hospital and/or withdrawal management strategy which has been shown to be linked with discharge. The authors report on medication for opioid use disorder provision prior to the hospitalization but not how the hospital approaches addiction treatment.

9. Additional analyses to consider: do people with serious deeper infections leave later in the hospitalization than people with less serious infections (cellulitis, abscesses vs endocarditis, bacteremia, etc).

10. Are the comorbidities baseline or identified during the hospitalization?

11. Page 17 Line 293-94 – would move sentence about HIV/HCV diagnosis to the limitations section.

12. It is interesting that 55% of the population was injected unspecified opioids or hydromorphone. Can the authors provide additional information about the local context?

13. Limitations: This is descriptive data with bivariate analyses and does not adjust for co-variates. The authors could consider a basic, simple logistic regression model looking at factors associated with patient initiated discharge or mortality, but will be limited in the number of covariates that can be included. Regardless, the limitations section should acknowledge the limitations of this kind of analysis.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2022 Apr 20;17(4):e0266663. doi: 10.1371/journal.pone.0266663.r002

Author response to Decision Letter 0

7 Oct 2021

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response: Thank you for outlining formatting requirements. We have reviewed the samples provided. Our title page and main manuscript have been revised to ensure compliance with formatting requirements as noted in the templates provided above.

2. Please include in your Methods section (or in Supplementary Information files) the participating hospitals/institutions.

Response: Thank you. As Reviewer #1 indicated the same suggestion, our methods section has been expanded to include a brief description of the two participating hospitals.

Response: Thank you for outlining these instructions. We have elaborated on the patient records used under our Methods section in our manuscript. We also specified that we used patient names and insurance numbers to prevent duplicate data entries. We anonymized the data set prior to statistical analyses.

In your revised cover letter, please address the following prompts:

We will update your Data Availability statement on your behalf to reflect the information you provide.

Response: Thank you for outlining these instructions. The team has agreed that we wish to preserve patient privacy where possible, as our data contains potentially identifying information (such as hospital sites and diagnoses) and considering the sensitivity and stigma surrounding injection drug use. Our protocol was approved by the Hamilton integrated Research Ethics Board. We have briefly summarized these sentiments and included contact information for the ethics board in our cover letter.

Comments to the Author

Response: Thank you for taking the time to review our manuscript, we appreciate your consideration and thoughtful feedback. We have addressed each comment to ensure our paper includes the details as suggested.

Major comments:

Response: Thank you for this suggestion, we agree that further detail on the participating hospitals would benefit readers outside of Ontario. We have therefore listed the participating hospitals and included a brief description of them in our methods section.

2. Could you please describe the data audit in more detail? What happened if discrepancies were found? Who conducted the audit?

Response: Thank you for your comment, we see that more explanation of the audit process is warranted to fully capture our team’s commitment to accuracy in data collection. A more thorough explanation of the data audit has been added to the methods section accordingly.

Response: Thank you for your suggestion, we agree that the additional detail to our data extraction and collection process is needed, as the criteria for abstraction was not clear. We have elaborated upon this step in our methods section to indicate how and where data was extracted from in Meditech.

4. The use of two reviewers, a third as a tie-breaker, and an audit adds rigor to the study.

Response: Thank you, we appreciate this feedback. We have further expanded on our data audit process to ensure this rigor.

Minor comments:

1. Could you clarify that those charts who were excluded in paragraph 1 of the results were because they didn’t mean eligibility criteria upon further inspection?

Response: Thank you for suggesting this clarification, we agree this suggestion will improve the cohesiveness of our paper. We have thus restated our exclusion criteria in the first paragraph of the results section.

2. Substances used: is this inpatient? Or prior to admission? Hydromorphone is a prescription drug but is it being misused/abused/bought in these settings?

Response: Thank you for your comment, we agree this was unclear in our original submission. We have included a more detailed explanation of how information regarding used substances was obtained from the charts.

Response: Thank you for taking the time to review our manuscript. We greatly appreciate your insightful feedback for our paper. We would like to clarify that our goal with this chart review was the establish the feasibility of studying injection drug use in Hamilton. Studies in the past have described general statistics of people who inject drugs, but have not yet considered the nature of hospital admissions for this group. This investigation is a first step to develop a better understanding this population for future studies to be conducted surrounding trajectories and interventions.

Major comments:

Response: Thank you for your comment, we have clarified this point in our abstract.

2. Intro: Little is known about “health trajectory of this population.” I would define this term as it is important theoretically to the framing (over what time period, what outcomes).

Response: Thank you for your comment, we have clarified this point in our introduction. We agree that the term “health trajectories” may not be intuitive and warrants clarification.

Response: Thank you for this consideration to help strengthen our paper. We have clarified the importance of considering all drug-related infections for this population accordingly.

Response: Thank you for your comment, we understand our original wording may not have been clear. We have clarified our aims for our study and ensured it flows with our analysis.

Response: Thank you for your suggestion, we acknowledge that this sentence is rather broad. We have modified the sentence for more specificity and incorporated the suggestion from the last comment to ensure our aims are clearer and more reflective of our work.

6. P5, Line 107 --- This is pretty well documented in the literature in addition to clinical experience.

Response: Thank you for your comment. We have changed this sentence to reflect this.

7. Methods: I would encourage the authors to describe a bit more about how injection drug use in the last 6 months determined/verified.

Response: Thank you for this excellent suggestion. Reviewer #1 expressed a similar sentiment above. As such, we have added more detail to explain our data extraction process by including how each survey query was answered and which parts of the patient chart were referenced for each query.

Response: Thank you for your comments. We would like to clarify that patient-initiated discharges represent one of the multiple outcomes we focused on in our investigation. Unfortunately, there is little available on how the participating hospitals respond to and address addictions treatment, aside from what was found in consult notes surrounding opioid substitution therapy. We agree that linking substitution or withdrawal management with discharge data would be an excellent addition. We hope that our study, as a first step into investigating outcomes of PWID, will be conducive to such analysis in the near future.

Response: Thank you for these excellent suggestions. We agree that such analyses would yield important and insightful considerations in developing strategies to better care for this population. As mentioned above, we hope our study will allow further analyses to be carried out among this population to better understand the impact of infections of varying severities.

10. Are the comorbidities baseline or identified during the hospitalization?

Response: Thank you for this question. We have clarified that information on comorbidities included those at baseline (made available in the electronic records system) as well as those identified during the hospitalization.

11. Page 17 Line 293-94 – would move sentence about HIV/HCV diagnosis to the limitations section.

Response: Thank you for this suggestion, we agree that this makes more sense in structuring our paper. This portion originally in the fit within literature subsection has been moved above to the limitations subsection as suggested.

12. It is interesting that 55% of the population was injected unspecified opioids or hydromorphone. Can the authors provide additional information about the local context?

Response: Thank you for suggesting this addition. We agree that providing additional information with local data would fortify the clinical picture. We have included local data from a needs assessment and feasibility study for the Hamilton supervised injection site to help contextualize our findings. This addition was written into our discussion section, under the fit within literature subsection.

Response: Thank you for your comment. We agree that limitations in our statistical analyses should be recognized. We have addressed this issue in our limitations subsection.

Attachment

Submitted filename: Response to Reviewers.docx

pone.0266663.s001.docx^{(51.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0266663.r003

Decision Letter 1

Jianhong Zhou

6 Dec 2021

PONE-D-21-11155R1Infectious diseases, comorbidities and outcomes in hospitalized people who inject drugs (PWID)PLOS ONE

Dear Dr. Alvarez,

Specifically, please address reviewers' remaining concerns, and particularly specify if data underlying the findings is fully available.

Please submit your revised manuscript by Jan 17 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Jianhong Zhou

Associate Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

Reviewer #2: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: Thank you for responding to the reviewer comments. I think this has strengthened the manuscript. This manuscript contributes to the literature of PWID and hospitalizations, patient-initiated discharges, and deaths.

One minor comment--hydromorphone was the most commonly injected substance, though it is also a prescription pain medication. perhaps the first time that hydromorphone is introduced in the paper that it can be described as mis-used/illicit hydromorphone? I suspect that this is hydromorphone pills that are crushed and injected as opposed to the IV hydromorphone formulation but perhaps authors can comment on this? I think there may be differences in infection risk between these two formulations...

Reviewer #2: The authors have largely addressed my comments but I think the methods section still feels a bit disjointed and does not set up the specific analyses performed. Perhaps the authors could move their discussion of sample size as it related to number of events to the statistical analysis section. The authors report detailed data collection strategy but could lay out more clearly which outcomes they will examine. The statistical analysis section can then more clearly state which comparison will be performed, etc.

**********

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Reviewer #1: No

Reviewer #2: No

PLoS One. 2022 Apr 20;17(4):e0266663. doi: 10.1371/journal.pone.0266663.r004

Author response to Decision Letter 1

20 Dec 2021

Please see below responses to reviewers’ comments:

Specifically, please address reviewers' remaining concerns, and particularly specify if data underlying the findings is fully available.

RESPONSE: A data sharing and availability section was added under methods

Journal Requirements:

RESPONSE: A review of referenced articles has been completed. No articles were found to have been retracted. A couple of links have been updated.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

RESPONSE: Thank you

________________________________________

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

Reviewer #2: No

RESPONSE: A data sharing and availability section was added under methods

________________________________________

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

6. Review Comments to the Author

RESPONSE: Thank you!

RESPONSE: Thank you, this was clarified in the methods section under data collection.

RESPONSE: Clarifications were added throughout the methods section to address these points.

________________________________________

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #1: No

Reviewer #2: No

Thank you again for your reviews.

Attachment

Submitted filename: Response to reviewers_2021Dec.docx

pone.0266663.s002.docx^{(17.9KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0266663.r005

Decision Letter 2

Yu Mon Saw

25 Mar 2022

Infectious diseases, comorbidities and outcomes in hospitalized people who inject drugs (PWID)

PONE-D-21-11155R2

Dear Dr. Alvarez,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Yu Mon Saw

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

**********

6. Review Comments to the Author

Reviewer #1: Thank you for addressing my comment re: formulations of medications. This helps to clarify that substances can be regularly prescribed but in this case were used illicitly and injected in this way.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

PLoS One. doi: 10.1371/journal.pone.0266663.r006

Acceptance letter

Yu Mon Saw

8 Apr 2022

PONE-D-21-11155R2

Infectious diseases, comorbidities and outcomes in hospitalized people who inject drugs (PWID)

Dear Dr. Alvarez:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Yu Mon Saw

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Attachment

Submitted filename: Response to Reviewers.docx

pone.0266663.s001.docx^{(51.8KB, docx)}

Attachment

Submitted filename: Response to reviewers_2021Dec.docx

pone.0266663.s002.docx^{(17.9KB, docx)}

Data Availability Statement

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PERMALINK

Infectious diseases, comorbidities and outcomes in hospitalized people who inject drugs (PWID)

Jacqueline Lim

Sureka Pavalagantharajah

Chris P Verschoor

Eric Lentz

Mark Loeb

Mitchell Levine

Marek Smieja

Lawrence Mbuagbaw

Dale Kalina

Jean-Eric Tarride

Tim O’Shea

Anna Cvetkovic

Sarah van Gaalen

Aidan Reid Findlater

Robin Lennox

Carol Bassim

Cynthia Lokker

Elizabeth Alvarez

Roles

Abstract

Introduction

Methods

Study design

Sample size, setting, and inclusion

Data collection, management, and storage

Statistical analysis

Data audit

Data sharing and availability

Results

Table 1. Demographics, infectious disease diagnoses and outcomes.

Table 2. Comorbidities.

Table 3. Site of abscesses.

Table 4. Substances used and OAT (Opioid agonist therapy).

Discussion

Main findings

Fit within the literature

Strengths and limitations

Implications for policy and practice

Implications for future research

Conclusion

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Judith I Tsui

Roles

Author response to Decision Letter 0

Decision Letter 1

Jianhong Zhou

Roles

Author response to Decision Letter 1

Decision Letter 2

Yu Mon Saw

Roles

Acceptance letter

Yu Mon Saw

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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