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The author has conducted research on women re‐entering Cuyamaca Community College in California and compared traditional and non‐traditional women in regard to background characteristics, educational characteristics, attitudes toward women, work, family, and personality. The author lists eight recommendations which colleges might consider in attracting women back to higher education and introducing them to a wider range of course options.

Abstract Background Setting priorities for the funding of new anti-cancer agents is becoming increasingly complex. The funding of adjuvant trastuzumab for breast cancer has brought this dilemma to the fore. In this paper we review external factors that may influence decision-making bodies and present a case study of media response in Ontario, Canada to adjuvant trastuzumab for breast cancer. Methods A comprehensive search of the databases of Canadian national and local newspapers and television was performed. Articles pertaining to trastuzumab in adjuvant breast cancer as well as 17 other anti-cancer drugs and indications were retrieved. The search period was from the date when individual trial results were announced to the date funding was made available in Ontario. Results During the 2.6 months between the release of the trastuzumab results to funding approval in Ontario, we identified 51 episodes of media coverage. For the 17 other drugs/indications (7 breast and 10 non-breast), the median time to funding approval was 31 months (range 14–46). Other recent major advances in oncology such as adjuvant vinorelbine/cisplatin for resected NSCLC and docetaxel for advanced prostate cancer received considerably less media attention (17 media reports for each) than trastuzumab. The median number of media reports for breast cancer drugs was 4.5 compared to 2.5 for non-breast cancer drugs (p = 0.56). Conclusion Priority-setting for novel anti-cancer agents is a complex process that tries to ensure fair use of constrained resources to fund therapies with the best evidence of clinical benefit. However, this process is subject to external factors including the influence of media, patient advocates, politicians, and industry. The data in this case study serve to illustrate the significant involvement one (or all) of these external factors may play in the debate over priority-setting.

Introduction: Glucagon-like peptide 1 receptor agonists (GLP-1RA) are effective medications for type 2 diabetes mellitus (T2DM) and obesity, yet their uptake among patients most likely to benefit has been slow., Methods: We conducted a cross-sectional analysis of medication exposure in adults hospitalized at 16 hospitals in Ontario, Canada between 2015 and 2022. We estimated the proportion with T2DM, obesity, and cardiovascular disease. We identified the frequency of GLP-1RA use, and conducted multivariable logistic regression to identify factors associated with their use., Results: Across 1,278,863 hospitalizations, 396,084 (31%) had T2DM and approximately 327,844 (26%) had obesity. GLP-1RA use (n=1,274) was low among those with a diagnosis of T2DM (0.3%) or obesity (0.7%), despite high prevalence of cardiovascular disease (36%). In contrast, use of diabetes medications lacking cardiovascular benefits was high during inpatient hospitalizations related to diabetes: 60% (n=236,612) received insulin and 14% (n=54,885) received a sulfonylurea. Apart from T2DM (OR=29.6, 95% CI 23.5, 37.2), characteristics associated with greater odds of receiving GLP-1RA were age 50-70 years (OR=1.71, 95% CI 1.38, 2.11) compared to age < 50 years, hemoglobin A1C > 9% (OR=1.83, 95% CI 1.36, 2.47) compared to < 6.5%, and highest income quintile (OR=1.73, 95% CI 1.45, 2.07) compared to lowest income quintile., Conclusion: Knowledge translation interventions are needed to address the low adoption of GLP-1RA among hospitalized patients with T2DM and obesity, who are the most likely to benefit., (Copyright © 2024. Published by Elsevier Inc.)

Introduction: Continuous subcutaneous insulin infusion (CSII) in type 1 diabetes has been regarded as a major diabetic ketoacidosis (DKA) risk factor. We aimed to determine secular trends in risk since CSII implementation in the 1980s. Research Design and Methods: We assessed the relationship between time-varying CSII use and DKA events from 1983 to 2017 and by each decade in the 1441 Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study participants using crude and adjusted Cox proportional hazards models. Results: Time-varying CSII exposure was associated with significantly higher DKA risk in the 1980s (adjusted hazard ratio [HR] 5.81; 95% confidence interval [CI] 3.28-10.29; P < 0.001), but in the 2010s, this risk was not significantly elevated (adjusted HR 1.24; 95% CI 0.73-2.12; P = 0.43). Conclusions: DKA risk associated with CSII in type 1 diabetes has declined substantially since the 1980s such that the remaining risk in the past decade appears to be of low magnitude.

Background: Recent work demonstrated that detection of SARS-CoV-2 on the floor of long-term care facilities is associated with impending COVID-19 outbreaks. It is unknown if similar results will be observed in hospitals., Methods: Floor swabs were prospectively collected weekly from healthcare worker-only areas (eg, staff locker rooms) at two hospitals in Ontario, Canada for 39 weeks. Floor swabs were processed for SARS-CoV-2 using quantitative reverse-transcriptase polymerase chain reaction. Results were reported as percentage of positive floor swabs and viral copy number. Grouped fivefold cross-validation was used to evaluate model outbreak discrimination., Results: SARS-CoV-2 RNA was detected on 537 of 760 floor swabs (71%). At Hospital A, overall positivity was 90% (95% CI: 85%-93%; N = 280); at Hospital B, overall positivity was 60% (95% CI: 55%-64%; N = 480). There were four COVID-19 outbreaks at Hospital A and seven at Hospital B during the study period. The outbreaks consisted of primarily patient cases (ie, 140 patient cases and 4 staff cases). For every 10-fold increase in viral copies, there was a 22-fold higher odds of a COVID-19 outbreak (OR = 22.0, 95% CI 7.3, 91.8). The cross-validated area under the receiver operating curve for SARS-CoV-2 viral copies for predicting a contemporaneous outbreak was 0.86 (95% CI 0.82-0.90)., Conclusion: Viral burden of SARS-CoV-2 on floors, even in healthcare worker-only areas, was strongly associated with COVID-19 outbreaks in those hospital wards. Built environment sampling may support hospital COVID-19 outbreak identification, fill gaps in traditional surveillance, and guide infection prevention and control measures.

Introduction: Sodium glucose co-transporter-2 inhibitors (SGLT-2i) are increasingly being used among hospitalized patients. Our objective was to assess the risk of diabetic ketoacidosis (DKA) among hospitalized patients receiving an SGLT-2i., Research Design and Methods: We conducted a multicentre cohort study of patients hospitalized at 19 hospitals. We included patients over 18 years of age who received an SGLT-2i or a dipeptidyl peptidase-4 inhibitor (DPP-4i) in hospital. The primary outcome was the risk of DKA during their hospitalization., Results: 61,517 patients received a DPP-4i and 11,061 received an SGLT-2i. The risk of inpatient DKA was 0.07 % (N = 41 events) among adults who received a DPP-4i and 0.18 % (N = 20 events) among adults who received an SGLT-2i; adjusted odds ratio of 3.30 (95 % CI: 1.85-5.72)., Conclusions: In hospitalized patients, the absolute risk of DKA was 0.2 %, which corresponded to a three-fold higher relative risk., Competing Interests: Declaration of competing interest MF was a consultant for ProofDx, a start-up company creating point of care diagnostic tests for COVID-19 using CRISPR. MF is an advisor for SIGNAL1, a start-up company deploying machine learned models to improve inpatient care. MF has been paid for medicolegal cases unrelated to the content of this study. FR is a provincial clinical lead for quality improvement at Ontario Health (as a part-time salaried employee). This research was undertaken, in part, with funding from the Canada Research Chairs Program. AV is a part-time employee of Ontario Health and is supported by the Temerty Professorship of AI Research and Education in Medicine at the University of Toronto., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The Clinical Classification Software Refined (CCSR) is a tool that groups many thousands of International Classification of Diseases 10th Revision (ICD-10) diagnosis codes into approximately 500 clinically meaningful categories, simplifying analyses. However, CCSR was developed for use in the United States and may not work well with other country-specific ICD-10 coding systems., Method: We developed an algorithm for semi-automated matching of Canadian ICD-10 codes (ICD-10-CA) to CCSR categories using discharge diagnoses from adult admissions at 7 hospitals between Apr 1, 2010 and Dec 31, 2020, and manually validated the results. We then externally validated our approach using inpatient hospital encounters in Denmark from 2017 to 2018., Key Results: There were 383,972 Canadian hospital admissions with 5,186 distinct ICD-10-CA diagnosis codes and 1,855,837 Danish encounters with 4,612 ICD-10 diagnosis codes. Only 46.6% of Canadian codes and 49.4% of Danish codes could be directly categorized using the official CCSR tool. Our algorithm facilitated the mapping of 98.5% of all Canadian codes and 97.7% of Danish codes. Validation of our algorithm by clinicians demonstrated excellent accuracy (97.1% and 97.0% in Canadian and Danish data, respectively). Without our algorithm, many common conditions did not match directly to a CCSR category, such as 96.6% of hospital admissions for heart failure., Conclusion: The GEMINI CCSR matching algorithm (available as an open-source package at https://github.com/GEMINI-Medicine/gemini-ccsr) improves the categorization of Canadian and Danish ICD-10 codes into clinically coherent categories compared to the original CCSR tool. We expect this approach to generalize well to other countries and enable a wide range of research and quality measurement applications., Competing Interests: Declaration of competing interest Mike Fralick was a consultant for ProofDx, a start-up company creating a point of care diagnostic test for COVID-19. Mike Fralick is an advisor for SIGNAL1, a start-up company deploying machine learned models to improve inpatient care. The remaining authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: In Canada, one in seven adults has diabetes (i.e., 2.3 million) and the lifetime risk of developing diabetes is approximately 30% by age 65. Although 30% of patients admitted to the hospital have diabetes, data from inpatient hospitalizations for patients with diabetes are lacking, both in Canada and globally., Objective: To validate International Classification of Diseases 10th edition Canadian version (ICD-10-CA) codes for the identification of patients with diabetes, to create a multicenter database of patients with diabetes hospitalized under internal medicine in Ontario, and to determine their baseline characteristics, medication use, and admission characteristics., Study Design: We created a database of people who had diabetes and were hospitalized between 2010 and 2020 at 8 hospitals in Ontario that were part of the General Medicine Inpatient Initiative (GEMINI) hospital data-sharing network. Patients who had diabetes were identified using chart review, based upon either (i) a previous physician diagnosis of diabetes, (ii) a recorded hemoglobin A1c ≥ 6.5% or (iii) outpatient prescription of a diabetes medication preceding the hospitalization. The test characteristics of ICD-10-CA codes for diabetes were evaluated. We compared baseline demographics, medication use and hospitalization details among patients with and without diabetes. For hospitalization details, we collected information on the admission diagnosis, comorbidity index, length of stay, receipt of ICU-level care, and inpatient mortality., Results: There were 384,588 admissions within the total study cohort, of which 118,987 (30.9%) had an ICD-10-CA diagnosis code of diabetes (E10.x, E11.x, E13.x, E14.x). The sensitivity and specificity of ICD-10-CA diagnostic codes was 95.9% and 98.8%, respectively. Most patients with an ICD-10-CA code for diabetes had a code for type 2 diabetes (93.9%) and a code for type 1 diabetes was rare (6.1%). The mean age was 66.4 years for patients without diabetes and 71.3 years for those with an ICD-10-CA diagnosis code for diabetes. Patients with diabetes had a higher prevalence of hypertension (64% vs. 37.9%), coronary artery disease (28.7% vs. 15.3%), heart failure (24.5% vs. 12.1%) and renal failure (33.8% vs. 17.3%) in comparison to those without diabetes. The most prevalent diabetes medications received in hospital were metformin (43%), DPP4 inhibitors (22.7%) and sulfonylureas (18.8%). The most common reason for admission among patients with diabetes was heart failure (9.0%), and among patients without diabetes was pneumonia (7.8%). Median length of stay was longer for patients with diabetes (5.5 vs. 4.5 days) and in-hospital mortality was similar between groups (6.8% with diabetes vs. 6.5% without diabetes)., Importance: Diabetes is one of the most prevalent chronic medical conditions, affecting roughly one third of all patients hospitalized on an internal medicine ward and is associated with other comorbidities and longer hospital stays. ICD-10-CA codes were highly accurate in identifying patients with diabetes. The development of an inpatient cohort will allow for further study of in-hospital practices and outcomes among patients with diabetes., Competing Interests: MF was a consultant for ProofDx, a start-up company creating a point of care diagnostic test for COVID-19. MF is an advisor for Signal1, a start-up company deploying machine learned models to improve inpatient care. TBS was a steering committee member of the Amgen-financed GALACTIC-HF trial, of the Boehringer Ingelheim financed SHARP3 trial, of “LUX-Dx TRENDS Evaluates Diagnostics Sensors in Heart Failure Patients Receiving Boston Scientific's Investigational ICM System” trial; advisory board: Amgen, CSL Seqirus and GSK; chief investigator of the Sanofi Pasteur financed “NUDGE-FLU”, “DANFLU-1”, and “DANFLU-2” trials; speaker honorarium: Bayer, Novartis, Sanofi Pasteur, GE healthcare and GSK; consultant appointments: Novo Nordisk, IQVIA and Parexel; and research grants: GE Healthcare, AstraZeneca, Novo Nordisk and Sanofi Pasteur. Outside of the submitted work, AV is a part-time employee of Ontario Health and a co-inventor of an AI-based early warning system for patient deterioration that was acquired by the start-up company Signal1. FR is a part-time employee of Ontario Health. The development of the GEMINI data platform has been supported with funding from sources such as the Canadian Cancer Society, the Canadian Frailty Network, the Canadian Institutes of Health Research, the Canadian Medical Protective Agency, Green Shield Canada Foundation, the Natural Sciences and Engineering Research Council of Canada, Ontario Health, the St. Michael’s Hospital Association Innovation Fund, the University of Toronto Department of Medicine, and in-kind support from partner hospitals and the Vector Institute. FR holds a salary award from Canada Research Chairs Program, University of Toronto and the PSI Graham Farquharson Knowledge Translation Fellowship. No funding sources from FR influenced the writing of this manuscript. There are no patents, products in development or marketed products to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials. All other authors have no reported conflicts of interest., (Copyright: © 2024 Colacci et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objectives: Whether vaginal estradiol use is associated with an increased risk of recurrent venous thromboembolism (VTE) in women with prior VTE is unknown. We sought to evaluate the association between vaginal estradiol use and recurrent VTE in women with prior VTE., Methods: We performed a nationwide nested case-control study among 44 024 women aged ≥45 years who developed a first VTE without a history of vaginal estrogen use prior to VTE diagnosis. Cases with recurrent VTE were matched 1:2 on birth year with controls using incidence density sampling. Exposure to vaginal estradiol tablets was categorized into current use (0-2 months before index), prior use (2-24 months before index) and past use (more than 24 months prior to index)., Results: We identified 5066 cases and 10 127 age-matched controls. In fully adjusted analysis vaginal estrogen was not associated with recurrent VTE with a hazard ratio of 0.75, p = .07 for current use, 0.83, p = .13 for prior use, and 1.24, p = .06 for past use., Conclusion: Use of vaginal estradiol tablets in women with prior VTE was not associated with an increased rate of recurrent VTE. Our study indicates that vaginal estradiol therapy is unlikely to increase risk of recurrent VTE in women with prior VTE., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Background: It is unclear whether antibiotics impact delirium outcomes in older adults with pyuria or bacteriuria in the absence of systemic signs of infection or genitourinary symptoms., Methods: We registered our systematic review protocol with PROSPERO (CRD42023418091). We searched the Medline and Embase databases from inception until April 2023 for studies investigating the impact of antimicrobial treatment on the duration and severity of delirium in older adults (≥60 years) with pyuria (white blood cells detected on urinalysis or dipstick) or bacteriuria (bacteria growing on urine culture) and without systemic signs of infection (temperature > 37.9C [>100.2F] or 1.5C [2.4F] increase above baseline temperature, and/or hemodynamic instability) or genitourinary symptoms (acute dysuria or new/worsening urinary symptoms). Two reviewers independently screened search results, abstracted data, and appraised the risk of bias. Full-text randomized controlled trials (RCTs) and observational study designs were included without restriction on study language, duration, or year of publication., Results: We screened 984 citations and included 4 studies comprising 652 older adults (mean age was 84.6 years and 63.5% were women). The four studies were published between 1996 and 2022, and included one RCT, two prospective observational cohort studies, and one retrospective chart review. None of the four studies demonstrated a significant effect of antibiotics on delirium outcomes, with two studies reported a worsening of outcomes among adults who received antibiotics. The three observational studies included had a moderate or serious overall risk of bias, while the one RCT had a high overall risk of bias., Conclusions: Our systematic review found no evidence that treatment with antibiotics is associated with improved delirium outcomes in older adults with pyuria or bacteriuria and without systemic signs of infection or genitourinary symptoms. Overall, the evidence was limited, largely observational, and had substantial risk of bias., (© 2024 The Authors. Journal of the American Geriatrics Society published by Wiley Periodicals LLC on behalf of The American Geriatrics Society.)

Objectives: Diabetic ketoacidosis (DKA) occurring after diabetes diagnosis is often associated with risk factors for other diabetes-related complications. In this study we aimed to determine the prognostic implications of DKA on all-cause mortality and complications in type 1 diabetes (T1D)., Methods: Previously collected data from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study were obtained through the the National Institute of Diabetes and Digestive and Kidney Diseases Central Repository. Using Cox proportional hazards models with time-dependent covariates, we examined age- and sex-adjusted, glycated hemoglobin-adjusted, and fully adjusted associations of DKA with all-cause mortality, cardiovascular disease, microvascular, and acute complications over 34 years., Results: Of the 1,441 study participants, 297 had 488 DKA events. Prior DKA was associated with a higher risk of age- and sex-adjusted all-cause mortality (hazard ratio [HR] 8.28, 95% confidence interval [CI] 3.74 to 18.32, p<0.001), major adverse cardiovascular events (MACEs) (HR 2.05, 95% CI 1.34 to 3.13, p<0.001), and all advanced microvascular and acute complications compared with no prior DKA. Most associations except retinopathy were significant even after adjustment for covariates. In our fully adjusted analysis, prior DKA was associated with a significantly higher risk of subsequent all-cause mortality (HR 9.13, 95% CI 3.87 to 21.50, p<0.001), MACEs (HR 1.66, 95% CI 1.07 to 2.59, p=0.03), advanced kidney disease (HR 2.10, 95% CI 1.00 to 4.22, p=0.049), advanced neuropathy (HR 1.49, 95% CI 1.05 to 2.13, p=0.03), severe hypoglycemia (HR 1.53, 95% CI 1.28 to 1.81, p<0.001), and recurrent DKA (HR 3.24, 95% CI 2.41 to 4.36, p<0.001) compared with person-time without DKA., Conclusions: DKA is a prognostic marker for diabetes complications, including excess all-cause mortality. Intensified clinical interventions, such as cardiovascular prevention strategies, may be warranted after diagnosis of DKA., (Copyright © 2024 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.)

Iron deficiency is a highly prevalent condition, which contributes to unnecessary morbidity, mortality, and health inequity. A serum ferritin concentration of less than 30 μg/L has a high specificity and sensitivity for diagnosing iron deficiency in adults, but the laboratory reported lower limit of normal (LLN) is typically lower. These LLNs might not be rooted in rigorous scientific evidence and might be contributing to structural underdiagnosis of iron deficiency. A systematic review was done per systematic reviews and meta-analysis guidelines with the use of medical literature databases from inception of each database to Nov 30, 2021, to identify studies that determined ferritin reference intervals in healthy adults and grey literature search for the five most common ferritin assays (registration number CRD42022268844). The objectives were to systematically summarise the ferritin reference intervals and to do a methodological quality assessment of the included studies. 2306 studies were screened and 61 full texts were included. 37 studies were eligible for analysis of the ferritin LLN in the general population. The population the sample was comprised of was a total of 21 882 females and 23 650 males participants. The ferritin LLN was a median of 8 μg/L (IQR 5-15) and mean of 9 μg/L (SD 11) in females and a median of 25 μg/L (IQR 16-44) and mean of 25 μg/L (SD 29) in males. 30 (49%) of 61 studies did not explicitly screen for patients at risk of iron deficiency, and 32 (52%) did not refer to a reference interval establishment guideline (eg, guideline recommended by Clinical and Laboratory Standards Institute). The five most used commercial ferritin laboratory assays reported reference intervals with a median LLN of 11 (IQR 9-12) and mean of 9 μg/L (SD 4) for females and median of 22 (IQR 22-24) and mean of 23 μg/L (SD 4) for males. In the literature, serum ferritin reference intervals in healthy adults consistently report a LLN of less than 30 μg/L. Data driving these ferritin reference intervals are at high risk of bias, given no exclusion of individuals at risk for iron deficiency in the presumed normal population sample and no adherence to reference interval establishment standards. We suggest the use of evidence-based laboratory clinical decision limits to diagnose iron deficiency., Competing Interests: Declaration of interests MS has unrestricted research funding (to institution) from Octapharma, CSL Behring, and Pfizer; and has received honoraria for advisory boards from Octapharma and Pfizer. MF was a consultant for ProofDx, a start-up company creating a point of care diagnostic test for COVID-19 (paid position); MF is an advisor for SIGNAL1, a start-up company deploying machine learned models to improve inpatient care (stock options). All other authors declared no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Objectives: International Classification of Diseases (ICD) codes are commonly used to identify cases of diabetic ketoacidosis (DKA) in health services research, but they have not been validated. Our aim in this study was to assess the accuracy of ICD, 10th revision (ICD-10) diagnosis codes for DKA., Methods: We conducted a multicentre, cross-sectional study using data from 5 hospitals in Ontario, Canada. Each hospitalization event has a single most responsible diagnosis code. We identified all hospitalizations assigned diagnosis codes for DKA. A true case of DKA was defined using laboratory values (serum bicarbonate ≤18 mmol/L, arterial pH ≤7.3, anion gap ≥14 mEq/L, and presence of ketones in urine or blood). Chart review was conducted to validate DKA if laboratory values were missing or the diagnosis of DKA was unclear. Outcome measures included positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity of ICD-10 codes in patients with laboratory-defined DKA., Results: We identified 316,517 hospitalizations. Among these, 312,948 did not have an ICD-10 diagnosis code for DKA and 3,569 had an ICD-10 diagnosis code for DKA. Using a combination of laboratory and chart review, we identified that the overall PPV was 67.0%, the NPV was 99.7%, specificity was 99.6%, and sensitivity was 74.9%. When we restricted our analysis to hospitalizations in which DKA was the most responsible discharge diagnosis (n=3,374 [94.5%]), the test characteristics were PPV 69.8%, NPV 99.7%, specificity 99.7%, and sensitivity 71.9%., Conclusion: ICD-10 codes can identify patients with DKA among those admitted to general internal medicine., (Copyright © 2024 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.)

Classroom and staffroom floor swabs across six elementary schools in Ottawa, Canada were tested for SARS-CoV-2. Environmental test positivity did not correlate with student grade groups, school-level absenteeism, pediatric COVID-19-related hospitalizations, or community SARS-CoV-2 wastewater levels. Schools in neighbourhoods with historically elevated COVID-19 burden showed a negative but non-significant association with lower swab positivity., Competing Interests: ED works for DNA Genotek that provided sampling swabs in-kind for this study in an unrestricted fashion. DNA Genotek had no control over the findings, interpretations, or conclusions published in this paper. MF is a consultant for ProofDx, a start-up company that has created a point of care testing device for adults with COVID-19 using CRISPR. DM is a consultant for wastewater surveillance, World Bank. All other authors have no relevant conflicts to disclose. “This does not alter our adherence to PLOS ONE policies on sharing data and materials.”, (Copyright: © 2024 Thampi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Competing Interests: Intérêts concurrents:: Shohinee Sarma déclare avoir reçu une aide du Programme de cliniciens-chercheurs et du Programme de formation des cliniciens-chercheurs de l’Université de Toronto et des honoraires de conférencière de l’Association américaine du diabète. Susan Tran déclare avoir reçu des honoraires de la société Novo Nordisk pour du contenu relatif aux traitements contre l’obésité. Michael Fralick a été consultant pour la société ProofDx, une société en démarrage qui conçoit un appareil portable pour la COVID-19 tiré de la technologie CRISPR et il est conseiller auprès de la société SIGNAL1, une société en démarrage qui applique des solutions inspirées de l’apprentissage-machine à la pratique clinique. Aucun autre intérêt n’a été déclaré.

Objective: To determine whether presence of a psychiatric comorbidity impacts use of inpatient imaging tests and subsequent wait times., Methods: This was a retrospective cohort study of all patients admitted to General Internal Medicine (GIM) at five academic hospitals in Toronto, Ontario from 2010 to 2019. Exposure was presence of a coded psychiatric comorbidity on admission. Primary outcome was time to test, as calculated from the time of test ordering to time of test completion, for computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, or peripherally inserted central catheter (PICC) insertion. Multilevel mixed-effects models were used to identify predictors of time to test, and marginal effects were used to calculate differences in absolute units (h). Secondary outcome was the rate of each type of test included. Subgroup analyses were performed according to type of psychiatric comorbidity: psychotic, mood/anxiety, or substance use disorder., Results: There were 196,819 GIM admissions from 2010to 2019. In 77,562 admissions, ≥1 advanced imaging test was performed. After adjusting for all covariates, presence of any psychiatric comorbidity was associated with increased time to test for MRI (adjusted difference: 5.3 h, 95% confidence interval [CI]: 3.9-6.8), PICC (adjusted difference: 3.7 h, 95% CI: 1.6-5.8), and ultrasound (adjusted difference: 3.0 h, 95% CI: 2.3-3.8), but not for CT (adjusted difference: 0.1 h, 95% CI: -0.3 to 0.5). Presence of any psychiatric comorbidity was associated with lower rate of ordering for all test types (adjusted difference: -17.2 tests per 100 days hospitalization, interquartile range: -18.0 to -16.3)., Conclusions: There was a lower rate of ordering of advanced imaging among patients with psychiatric comorbidity. Once ordered, time to test completion was longer for MRI, ultrasound, and PICC. Further exploration, such as quantifying rates of cancelled tests and qualitative studies evaluating hospital, provider, and patient barriers to timely advanced imaging, will be helpful in elucidating causes for these disparities., (© 2024 The Authors. Brain and Behavior published by Wiley Periodicals LLC.)

Rationale: Outcomes for people with respiratory failure in the United States vary by patient race and ethnicity. Invasive ventilation is an important treatment initiated based on expert opinion. It is unknown whether the use of invasive ventilation varies by patient race and ethnicity. Objectives: To measure 1 ) the association between patient race and ethnicity and the use of invasive ventilation; and 2 ) the change in 28-day mortality mediated by any association. Methods: We performed a multicenter cohort study of nonintubated adults receiving oxygen within 24 hours of intensive care admission using the Medical Information Mart for Intensive Care IV (MIMIC-IV, 2008-2019) and Phillips eICU (eICU, 2014-2015) databases from the United States. We modeled the association between patient race and ethnicity (Asian, Black, Hispanic, White) and invasive ventilation rate using a Bayesian multistate model that adjusted for baseline and time-varying covariates, calculated hazard ratios (HRs), and estimated 28-day hospital mortality changes mediated by differential invasive ventilation use. We reported posterior means and 95% credible intervals (CrIs). Results: We studied 38,258 patients, 52% (20,032) from MIMIC-IV and 48% (18,226) from eICU: 2% Asian (892), 11% Black (4,289), 5% Hispanic (1,964), and 81% White (31,113). Invasive ventilation occurred in 9.2% (3,511), and 7.5% (2,869) died. The adjusted rate of invasive ventilation was lower in Asian (HR, 0.82; CrI, 0.70-0.95), Black (HR, 0.78; CrI, 0.71-0.86), and Hispanic (HR, 0.70; CrI, 0.61-0.79) patients compared with White patients. For the average patient, lower rates of invasive ventilation did not mediate differences in 28-day mortality. For a patient on high-flow nasal cannula with inspired oxygen fraction of 1.0, the odds ratios for mortality if invasive ventilation rates were equal to the rate for White patients were 0.97 (CrI, 0.91-1.03) for Asian patients, 0.96 (CrI, 0.91-1.03) for Black patients, and 0.94 (CrI, 0.89-1.01) for Hispanic patients. Conclusions: Asian, Black, and Hispanic patients had lower rates of invasive ventilation than White patients. These decreases did not mediate harm for the average patient, but we could not rule out harm for patients with more severe hypoxemia.

Importance: Influenza vaccination is associated with a reduced risk of mortality in patients with diabetes, but vaccination rates remain suboptimal., Objective: To assess the effect of electronic nudges on influenza vaccination uptake according to diabetes status., Design, Setting, and Participants: The NUDGE-FLU (Nationwide Utilization of Danish Government Electronic Letter System for Increasing Influenza Vaccine Uptake) trial was a nationwide clinical trial of Danish citizens 65 years or older that randomized participants at the household level to usual care or 9 different electronic nudge letters during the 2022 to 2023 influenza season. End of follow-up was January 1, 2023. This secondary analysis of the NUDGE-FLU trial was performed from May to July 2023., Intervention: Nine different electronic nudge letters designed to boost influenza vaccination were sent in September to October 2022. Effect modification by diabetes status was assessed in a pooled analysis of all intervention arms vs usual care and for individual letters., Main Outcomes and Measures: The primary end point was receipt of a seasonal influenza vaccine., Results: The trial included 964 870 participants (51.5% female; mean [SD] age, 73.8 [6.3] years); 123 974 had diabetes. During follow-up, 83.5% with diabetes vs 80.2% without diabetes received a vaccine (P < .001). In the pooled analysis, nudges improved vaccination uptake in participants without diabetes (80.4% vs 80.0%; difference, 0.37 percentage points; 99.55% CI, 0.08 to 0.66), whereas there was no evidence of effect in those with diabetes (83.4% vs 83.6%; difference, -0.19 percentage points; 99.55% CI, -0.89 to 0.51) (P = .02 for interaction). In the main results of NUDGE-FLU, 2 of the 9 behaviorally designed letters (cardiovascular benefits letter and a repeated letter) significantly increased uptake of influenza vaccination vs usual care; these benefits similarly appeared attenuated in participants with diabetes (cardiovascular gain letter: 83.7% vs 83.6%; difference, 0.04 percentage points; 99.55% CI, -1.52 to 1.60; repeated letter: 83.5% vs 83.6%; difference, -0.15 percentage points; 99.55% CI, -1.71 to 1.41) vs those without diabetes (cardiovascular gain letter: 81.1% vs 80.0%; difference, 1.06 percentage points; 99.55% CI, 0.42 to 1.70; repeated letter: 80.9% vs 80.0%; difference, 0.87 percentage points; 99.55% CI, 0.22 to 1.52) (P = .07 for interaction)., Conclusions and Relevance: In this exploratory subgroup analysis, electronic nudges improved influenza vaccination uptake in persons without diabetes, whereas there was no evidence of an effect in persons with diabetes. Trials are needed to investigate the effect of digital nudges specifically tailored to individuals with diabetes., Trial Registration: ClinicalTrials.gov Identifier: NCT05542004.

Competing Interests: Competing interests: Shohinee Sarma reports support from the Clinician Investigator Program and the Clinician Scientist Training Program at the University of Toronto, and has received honoraria for presentations from the American Diabetes Association. Susan Tran reports honoraria from Novo Nordisk for content unrelated to obesity treatments. Michael Fralick was a consultant for ProofDx, a start-up company creating a point-of-care device for COVID-19 using CRISPR. and is an advisor for SIGNAL1, a start-up company that implements machine-learned solutions into clinical practice. No other competing interests were declared.

Objective: Rather than during illness while diabetic ketoacidosis (DKA) is developing, we aimed to determine if levels of routine point-of-care capillary blood ketones could predict future DKA., Research Design and Methods: We examined previously collected data from placebo-assigned participants in an adjunct-to-insulin medication trial program that included measurement of fasted capillary blood ketone levels twice per week in a 2-month baseline period. The outcome was 6- to 12-month trial-adjudicated DKA., Results: DKA events occurred in 12 of 484 participants at a median of 105 (interquartile range 43, 199) days. Maximum ketone levels were higher in patient cases compared with in control patients (0.8 [0.6, 1.2] vs. 0.3 [0.2, 0.7] mmol/L; P = 0.002), with a nonparametric area under the receiver operating characteristic curve of 0.77 (95% CI 0.66-0.88). Ketone levels ≥0.8 mmol/L had a sensitivity of 64%, a specificity of 78%, and positive and negative likelihood ratios of 2.9 and 0.5, respectively., Conclusions: This proof of concept that routine capillary ketone surveillance can identify individuals at high risk of future DKA implies a role for future technologies including continuous ketone monitoring., (© 2023 by the American Diabetes Association.)