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Background: Clinical machine learning (ML) technologies can sometimes be biased and their use could exacerbate health disparities. The extent to which bias is present, the groups who most frequently experience bias, and the mechanism through which bias is introduced in clinical ML applications is not well described. The objective of this study was to examine instances of bias in clinical ML models. We identified the sociodemographic subgroups (using the PROGRESS-Plus framework) that experienced bias and the reported mechanisms of bias introduction METHODS: We searched MEDLINE, EMBASE, PsycINFO and Web of Science for all studies that evaluated bias on sociodemographic factors within ML algorithms created for the purpose of facilitating clinical care. The scoping review was conducted according to the JBI guide and reported using the PRISMA extension for scoping reviews., Results: We identified 6448 articles, of which 760 reported on a clinical ML model and 91 (12.0%) completed a bias evaluation and met all inclusion criteria. Most studies evaluated a single sociodemographic factor (n=56, 61.5%). The most frequently evaluated sociodemographic factor was race (n=59, 64.8%), followed by sex/gender (n=41, 45.1%), and age (n=24, 26.4%), with one study (1.1%) evaluating intersectional factors. Of all studies, 74.7% (n=68) reported that bias was present, 18.7% (n=17) reported bias was not present, and 6.6% (n=6) did not state whether bias was present. When present, 87% of studies reported bias against groups with socioeconomic disadvantage., Conclusion: Most ML algorithms that were evaluated for bias demonstrated bias on sociodemographic factors. Furthermore, most bias evaluations concentrated on race, sex/gender, and age, while other sociodemographic factors and their intersection were infrequently assessed. Given potential health equity implications, bias assessments should be completed for all clinical ML models., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

The Mediterranean fruit fly (Ceratitis capitata) is a globally invasive species and an economically significant pest of fruit crops. Understanding the evolutionary history and local climatic adaptation of this species is crucial for developing effective pest management strategies. We conducted a comprehensive investigation using whole genome sequencing to explore (i) the invasion history of C. capitata with an emphasis on historical admixture and (ii) local climatic adaptation across African, European, Central, and South American populations of C. capitata. Our results suggest a stepwise colonization of C. capitata in Europe and Latin America in which Mediterranean and Central American populations share an ancestral lineage. Conversely, South American invasion history is more complex, and our results partly suggest an old secondary invasion into South America from Europe or a colonization of South America directly from Africa, followed by admixture with an European lineage. Throughout its invasive range, C. capitata is challenged with diverse climatic regimes. A genome wide association study identified a relationship between allele frequency changes and specific bioclimatic variables. Notably, we observed a significant allele frequency shift related to adaptation to cold stress (BIO6), highlighting the species' ability to rapidly adapt to seasonal variations in colder climates., (© 2024. The Author(s).)

Background It is not known how disability, homelessness, or neighborhood marginalization influence risk-adjusted hospital performance measurement in a universal health care system. Methods We evaluated the effect of including these equity-related factors in risk-adjustment models for in-hospital mortality, and 7- and 30-day readmission in 28 hospitals in Ontario, Canada. We compared risk-adjustment with commonly-used clinical factors to models that also included homelessness, disability, and neighborhood indices of marginalization. We evaluated models in historical data using internal-external cross-validation. We calculated risk-standardized outcome rates for each hospital in a recent reporting period using mixed-effects logistic regression. Results The cohort included 544,805 admissions. Adjustment for disability, homelessness, and neighborhood marginalization had little impact on discrimination or calibration of risk-adjustment models. However, it influenced comparative hospital performance on risk-standardized 30-day readmission rates, resulting in 5 hospitals being reclassified between below-average, average, and above-average groups. No hospitals were reclassified for mortality and 7-day readmission. Conclusion In a system with universally insured hospital services, adjustment for disability, homelessness, and neighborhood marginalization influenced estimates of hospital performance for 30-day readmission but not 7-day readmission or in-hospital mortality. These findings can inform researchers and policymakers as they thoughtfully consider when to adjust for these factors in hospital performance measurement., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.)

Background: The implementation and clinical impact of machine learning-based early warning systems for patient deterioration in hospitals have not been well described. We sought to describe the implementation and evaluation of a multifaceted, real-time, machine learning-based early warning system for patient deterioration used in the general internal medicine (GIM) unit of an academic medical centre., Methods: In this nonrandomized, controlled study, we evaluated the association between the implementation of a machine learning-based early warning system and clinical outcomes. We used propensity score-based overlap weighting to compare patients in the GIM unit during the intervention period (Nov. 1, 2020, to June 1, 2022) to those admitted during the pre-intervention period (Nov. 1, 2016, to June 1, 2020). In a difference-indifferences analysis, we compared patients in the GIM unit with those in the cardiology, respirology, and nephrology units who did not receive the intervention. We retrospectively calculated system predictions for each patient in the control cohorts, although alerts were sent to clinicians only during the intervention period for patients in GIM. The primary outcome was non-palliative in-hospital death., Results: The study included 13 649 patient admissions in GIM and 8470 patient admissions in subspecialty units. Non-palliative deaths were significantly lower in the intervention period than the pre-intervention period among patients in GIM (1.6% v. 2.1%; adjusted relative risk [RR] 0.74, 95% confidence interval [CI] 0.55-1.00) but not in the subspecialty cohorts (1.9% v. 2.1%; adjusted RR 0.89, 95% CI 0.63-1.28). Among high-risk patients in GIM for whom the system triggered at least 1 alert, the proportion of non-palliative deaths was 7.1% in the intervention period, compared with 10.3% in the pre-intervention period (adjusted RR 0.69, 95% CI 0.46-1.02), with no meaningful difference in subspecialty cohorts (10.4% v. 10.6%; adjusted RR 0.98, 95% CI 0.60-1.59). In the difference-indifferences analysis, the adjusted relative risk reduction for non-palliative death in GIM was 0.79 (95% CI 0.50-1.24)., Interpretation: Implementing a machine learning-based early warning system in the GIM unit was associated with lower risk of non-palliative death than in the pre-intervention period. Machine learning-based early warning systems are promising technologies for improving clinical outcomes., Competing Interests: Competing interests:: Amol Verma, Chloe Pou-Prom, Joshua Murray, and Muhammad Mamdani co-invented CHARTwatch, which was acquired by a start-up company, Signal1, and they have the potential to acquire minority interests in the company in the future, as does Sebnem Kuzulugil. Amol Verma received travel support from the Alberta Machine Intelligence Institute and is a parttime employee of Ontario Health, outside of the submitted work., (© 2024 CMA Impact Inc. or its licensors.)

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.)

The behavioural response of adult maize weevil, Sitophilus zeamais , to different types of semolina pasta enriched or not enriched with increasing proportions (5%, 10%, and 15%) of house cricket ( Acheta domesticus ) powder was investigated in olfactometer arena bioassays by using trap devices. In the five-choice behavioural bioassays, the number of S. zeamais adults attracted to 100% durum wheat semolina pasta was significantly higher than those attracted to the other pasta types enriched with A. domesticus powder. In the two-choice behavioural bioassays, the Response Index for each pasta type was positive and significant. However, although not significant, there was a progressive reduction in the Response Index as the cricket powder content increased. In similar experiments, there were no significant differences between cricket powder alone and the control in the number of attracted S. zeamais , indicating a neutral effect towards insects. These observations suggest that the lower attractiveness of pasta enriched with house cricket powder is mainly due to the masking of host food odours. Solid-phase microextraction coupled to gas chromatography-mass spectroscopy identified a total of 18 compounds in the head-space samples of the different types of pasta, highlighting differences in volatile composition. Some volatile compounds were only present in the pasta produced with cricket powder. In particular, 1-octen-3-ol and phenol were present in the samples containing 5%, 10%, or 15% cricket powder; pentanal, benzaldehyde, and dimethyl disulphide were present in samples containing 10% or 15% cricket powder; and 2,5-dimethyl-pyrazine was present in the sample containing 15% cricket powder. Further investigation with individual compounds and mixtures is needed to define the chemical basis of the differences in the insect olfactory preference observed in this study.

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.)

We compared the attractiveness of five commercially available Italian macaroni pastas of different shapes (penne, casarecce, and fusilli) made from cereals and/or legumes [100% Triticum durum ; 100% Cicer arietinum ; 100% Lens esculenta ; 50% Triticum durum + 50% Cicer arietinum ; 60% Triticum durum + 40% Lens esculenta ] to adults of Sitophilus zeamais (L.). A multiple-choice walking bioassay showed that S. zeamais adults were more attracted to cereal than legume pastas. The modified Flit-Track M 2 trap devices baited with pasta made with 100% T. durum captured an average of 61.4% of the adults released into the olfactometric arena after 7 days. Of the insects tested, pasta made with 100% C. arietinum trapped 3.8%, pasta made with 100% L. esculenta trapped 2.7%, pasta made with 50% T. durum + 50% C. arietinum trapped 4.3%, and pasta made with 60% T. durum + 40% L. esculenta trapped 4.2%. When individually compared, 79.6% of S. zeamais adults chose the Triticum durum pasta. Orientation to 100% Cicer pasta or 100% Lens pasta was not observed. In the choice test, only 37% and 25% were attracted to Triticum and Cicer pastas or Triticum and Lens pasta, respectively. Our results confirm that the low attractiveness of legume pasta is mainly due to the lack of attractant stimuli rather than the emission of repellent compounds. From a practical perspective, it is also interesting to note how mixed pasta decreases the risk of S. zeamais infestation.

Background: Methods to accurately predict the risk of in-hospital mortality are important for applications including quality assessment of healthcare institutions and research., Objective: To update and validate the Kaiser Permanente inpatient risk adjustment methodology (KP method) to predict in-hospital mortality, using open-source tools to measure comorbidity and diagnosis groups, and removing troponin which is difficult to standardize across modern clinical assays., Design: Retrospective cohort study using electronic health record data from GEMINI. GEMINI is a research collaborative that collects administrative and clinical data from hospital information systems., Participants: Adult general medicine inpatients at 28 hospitals in Ontario, Canada, between April 2010 and December 2022., Main Measures: The outcome was in-hospital mortality, modeled by diagnosis group using 56 logistic regressions. We compared models with and without troponin as an input to the laboratory-based acute physiology score. We fit and validated the updated method using internal-external cross-validation at 28 hospitals from April 2015 to December 2022., Key Results: In 938,103 hospitalizations with 7.2% in-hospital mortality, the updated KP method accurately predicted the risk of mortality. The c-statistic at the median hospital was 0.866 (see Fig. 3) (25th-75th 0.848-0.876, range 0.816-0.927) and calibration was strong for nearly all patients at all hospitals. The 95th percentile absolute difference between predicted and observed probabilities was 0.038 at the median hospital (25th-75th 0.024-0.057, range 0.006-0.118). Model performance was very similar with and without troponin in a subset of 7 hospitals, and performance was similar with and without troponin for patients hospitalized for heart failure and acute myocardial infarction., Conclusions: An update to the KP method accurately predicted in-hospital mortality for general medicine inpatients in 28 hospitals in Ontario, Canada. This updated method can be implemented in a wider range of settings using common open-source tools., (© 2023. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Importance: A diagnosis of diabetes is considered when a patient has hyperglycemia with a random plasma glucose ≥200 mg/dL. However, in the inpatient setting, hyperglycemia is frequently non-specific, especially among patients who are acutely unwell. As a result, patients with transient hyperglycemia may be incorrectly labeled as having diabetes, leading to unnecessary treatment, and potential harm., Design, Setting, and Participants: We conducted a multicenter cohort study of patients hospitalized at six hospitals in Ontario, Canada, and identified those with a glucose value ≥200 mg/dL (including standing measurements and randomly drawn). We validated a definition for diabetes using manual chart review that included physician notes, pharmacy notes, home medications, and hemoglobin A1C. Among patients with a glucose value ≥200 mg/dL (11.1 mmol/L), we identified patients without diabetes who received a diabetes medication, and the number who experienced hypoglycemia during the same admission., Main Outcomes and Measures: To determine the diagnostic value of using random blood glucose to diagnose diabetes in the inpatient setting, and its impact on patient outcomes., Results: We identified 328,786 hospitalizations from hospital between 2010 and 2020. A blood glucose value of ≥200 mg/dL (11.1 mmol/L) had a positive predictive value of 68% and a negative predictive value of 90% for a diagnosis of diabetes. Of the 76,967 patients with an elevated glucose value reported, 16,787 (21.8%) did not have diabetes, and of these, 5375 (32%) received a diabetes medication. Hypoglycemia was frequently reported among the 5375 patients that received a diabetes medication, with 1406 (26.2%) experiencing hypoglycemia and 405 (7.5%) experiencing severe hypoglycemia., Conclusions and Relevance: Hyperglycemia in hospital is common but does not necessarily indicate a patient has diabetes. Furthermore, it can lead to treatment with diabetes medications with potential harm. Our findings highlight that clinicians should be cautious when responding to elevated random plasma glucose tests in the inpatient setting., (© 2023. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Objectives: Diabetes has been reported to be associated with an increased risk of death among patients with COVID-19. However, the available studies lack detail on COVID-19 illness severity and measurement of relevant comorbidities., Methods: We conducted a multicentre, retrospective cohort study of patients 18 years of age and older who were hospitalized with COVID-19 between January 1, 2020, and November 30, 2020, in Ontario, Canada, and Copenhagen, Denmark. Chart abstraction emphasizing comorbidities and disease severity was performed by trained research personnel. The association between diabetes and death was measured using Poisson regression. The main outcome measure was in-hospital 30-day risk of death., Results: Our study included 1,133 hospitalized patients with COVID-19 in Ontario and 305 in Denmark, of whom 405 and 75 patients, respectively, had pre-existing diabetes. In both Ontario and Denmark, patients with diabetes were more likely to be older; have chronic kidney disease, cardiovascular disease, and higher troponin levels; and be receiving antibiotics, when compared with adults without diabetes. In Ontario, 24% (n=96) of adults with diabetes died compared with 15% (n=109) of adults without diabetes. In Denmark, 16% (n=12) of adults with diabetes died in hospital compared with 13% (n=29) of those without diabetes. In Ontario, the crude mortality ratio among patients with diabetes was 1.60 (95% confidence interval [CI], 1.24 to 2.07) and in the adjusted regression model it was 1.19 (95% CI, 0.86 to 1.66). In Denmark, the crude mortality ratio among patients with diabetes was 1.27 (95% CI, 0.68 to 2.36) and in the adjusted model it was 0.87 (95% CI, 0.49 to 1.54). Meta-analysis of the 2 rate ratios from each region resulted in a crude mortality ratio of 1.55 (95% CI, 1.22 to 1.96) and an adjusted mortality ratio of 1.11 (95% CI, 0.84 to 1.47)., Conclusion: The presence of diabetes was not strongly associated with in-hospital COVID-19 mortality independent of illness severity and other comorbidities., (Copyright © 2023 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.)

The Mediterranean fruit fly (medfly), Ceratitis capitata , is a key pest of fruit crops in a wide range of climatic zone. Its economic importance is increasing due to its invasion and establishment in new geographical areas caused by global warming. Generally, the management of medfly infestation has been carried out with the use of synthetic pyrethroids and phosphorganic insecticides. Other containment approaches include attract-and-kill, biological control, and the sterile insect technique. The mass trapping technique can be considered an eco-friendly method to use in combination with other control systems. The present study reported the trapping effectiveness of commercially available devices (Decis Trap, Tephri Trap Ecological, and Conetrap) baited with different types of female attractants (Econex Trypack and Biodelear) under different thermal conditions. The performance of trapping systems was evaluated in semi-field cages. Our results showed that the combination of Conetrap with Biodelear was not proven effective, while the Tephri Trap baited with Trypack or Biodelear and the Decis Trap reported the same performance in capturing females and could be used for medfly mass trapping.

Background: There is wide variation in mortality among patients hospitalized with COVID-19. Whether this is related to patient or hospital factors is unknown., Objective: To compare the risk of mortality for patients hospitalized with COVID-19 and to determine whether the majority of that variation was explained by differences in patient characteristics across sites., Design, Setting, and Participants: An international multicenter cohort study of hospitalized adults with laboratory-confirmed COVID-19 enrolled from 10 hospitals in Ontario, Canada and 8 hospitals in Copenhagen, Denmark between January 1, 2020 and November 11, 2020., Main Outcomes and Measures: Inpatient mortality. We used a multivariable multilevel regression model to compare the in-hospital mortality risk across hospitals and quantify the variation attributable to patient-level factors., Results: There were 1364 adults hospitalized with COVID-19 in Ontario (n = 1149) and in Denmark (n = 215). In Ontario, the absolute risk of in-hospital mortality ranged from 12.0% to 39.8% across hospitals. Ninety-eight percent of the variation in mortality in Ontario was explained by differences in the characteristics of the patients. In Denmark, the absolute risk of inpatients ranged from 13.8% to 20.6%. One hundred percent of the variation in mortality in Denmark was explained by differences in the characteristics of the inpatients., Conclusion: There was wide variation in inpatient COVID-19 mortality across hospitals, which was largely explained by patient-level factors, such as age and severity of presenting illness. However, hospital-level factors that could have affected care, including resource availability and capacity, were not taken into account. These findings highlight potential limitations in comparing crude mortality rates across hospitals for the purposes of reporting on the quality of care., (© 2022 Society of Hospital Medicine.)

Objectives: To assess the effectiveness of prone positioning to reduce the risk of death or respiratory failure in non-critically ill patients admitted to hospital with covid-19., Design: Multicentre pragmatic randomised clinical trial., Setting: 15 hospitals in Canada and the United States from May 2020 until May 2021., Participants: Eligible patients had a laboratory confirmed or a clinically highly suspected diagnosis of covid-19, needed supplemental oxygen (up to 50% fraction of inspired oxygen), and were able to independently lie prone with verbal instruction. Of the 570 patients who were assessed for eligibility, 257 were randomised and 248 were included in the analysis., Intervention: Patients were randomised 1:1 to prone positioning (that is, instructing a patient to lie on their stomach while they are in bed) or standard of care (that is, no instruction to adopt prone position)., Main Outcome Measures: The primary outcome was a composite of in-hospital death, mechanical ventilation, or worsening respiratory failure defined as needing at least 60% fraction of inspired oxygen for at least 24 hours. Secondary outcomes included the change in the ratio of oxygen saturation to fraction of inspired oxygen., Results: The trial was stopped early on the basis of futility for the pre-specified primary outcome. The median time from hospital admission until randomisation was 1 day, the median age of patients was 56 (interquartile range 45-65) years, 89 (36%) patients were female, and 222 (90%) were receiving oxygen via nasal prongs at the time of randomisation. The median time spent prone in the first 72 hours was 6 (1.5-12.8) hours in total for the prone arm compared with 0 (0-2) hours in the control arm. The risk of the primary outcome was similar between the prone group (18 (14%) events) and the standard care group (17 (14%) events) (odds ratio 0.92, 95% confidence interval 0.44 to 1.92). The change in the ratio of oxygen saturation to fraction of inspired oxygen after 72 hours was similar for patients randomised to prone positioning and standard of care., Conclusion: Among non-critically ill patients with hypoxaemia who were admitted to hospital with covid-19, a multifaceted intervention to increase prone positioning did not improve outcomes. However, wide confidence intervals preclude definitively ruling out benefit or harm. Adherence to prone positioning was poor, despite multiple efforts to increase it. Subsequent trials of prone positioning should aim to develop strategies to improve adherence to awake prone positioning., Study Registration: ClinicalTrials.gov NCT04383613., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: the study was funded by St Michael’s Hospital Innovation Fund, the Sinai Health Research Fund, and Sunnybrook Health Sciences Centre Alternate Funding Plan Innovation Fund; JZ has received payments for medicolegal opinions regarding the safety and effectiveness of drugs outside the submitted work; AV is provincial clinical lead for quality improvement in general internal medicine at Ontario Health and an AMS healthcare fellow in compassion and artificial intelligence and has received funding for covid related research from CIHR, Canadian Frailty Network, St Michael's Hospital, Sinai Health System, and St Michael's Hospital Foundation; MF is a consultant for a start-up company (ProofDx) that has developed a point-of-care diagnostic test for covid-19 using CRISPR; FR has received an award from the Mak Pak Chiu and Mak-Soo Lai Hing chair in general internal medicine, University of Toronto, outside the submitted work and is an employee of Ontario Health; no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: The magnitude and precision regarding the risk of diabetic ketoacidosis (DKA) with sodium-glucose cotransporter-2 (SGLT2) inhibitors is unclear. Thus, we examined the risk of DKA with SGLT2 inhibitors in both observational studies and large clinical trials., Methods: Searches were performed in PubMed, Embase, CENTRAL and Google Scholar (from inception to April 15, 2019) without language restrictions, including conference proceedings and reference lists. Study selection consisted of randomized controlled trials and observational studies that quantified the rate of DKA with an SGLT2 inhibitor in comparison to other diabetes medications or placebo. Two independent investigators abstracted the study data and assessed the quality of evidence. Data were pooled using random effects models with the Hartung-Knapp-Sidik-Jonkman method. Absolute event rates and hazard ratios for DKA were extracted from each study., Results: Seven randomized trials encompassing 42,375 participants and 5 cohort studies encompassing 318,636 participants were selected. Among the 7 randomized controlled trials, the absolute rate of DKA among patients randomized to an SGLT2 inhibitor ranged from 0.6 to 2.2 events per 1,000 person years. Four randomized trials were included in the meta-analysis and, compared with placebo or comparator medication, SGLT2 inhibitors had a 2.5-fold higher risk of DKA (relative risk [RR], 2.46; 95% confidence interval [CI], 1.16 to 5.21]; I 2 =0%; p=0.54). Among the 5 observational studies, the absolute rate of DKA associated with SGLT2 inhibitor use ranged from 0.6 to 4.9 per 1,000 person years and a 1.7-fold higher rate of DKA compared with another diabetes medication (RR, 1.74; 95% CI, 1.07 to 2.83; I 2 =45%; p=0.12)., Conclusions: In adults with type 2 diabetes, SGLT2 inhibitors were found to increase the risk of DKA in both observational studies and large randomized clinical trials., (Copyright © 2021 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.)

The attractiveness of ten commercially available Italian macaroni pastas made from different cereals [ Triticum durum ; Triticum durum (whole wheat); Triticum dicoccum ; mixture of five cereals; Triticum turgidum ; Triticum turanicum ] or legumes ( Cicer arietinum ; Lens culinaris ; Pisum sativum ; Vicia faba ) to Sitophilus granarius , was compared. S. granarius adults were more attracted to cereal pastas than legume pastas, but the differences in attractiveness were not always significant. Consistent with the results of behavioural bioassays, the mortality of adults over 20 days exposed to pasta samples was 100% with the legume pasta samples and only 8% with the T. turanicum pasta. GC-MS analysis of HS-SPME extracts from the different pasta samples highlighted marked qualitative and quantitative differences, with aliphatic aldehydes and aliphatic alcohols being the most abundant volatile components of cereal- and legume-pastas, respectively. In two-choice behavioural bioassays, insect attraction to a 1:1 combination of T. turanicum and C. arietinum pastas (80%) was even higher than that observed in T. turanicum pasta alone (64%) and in C. arietinum pasta alone (20%). This strongly suggested that the low attractiveness of legume pasta is mainly due to the lack of attractant stimuli rather than emission of repellent compounds.

It is not known whether non-ABO antibodies confer any protective effect against SARS-CoV-2 infection or COVID-19 severe illness alone or in conjunction with O blood group. This cohort study included 413 576 persons in Ontario, Canada with known ABO blood group and non-ABO antibody screen status, who subsequently underwent SARS-CoV-2 viral RNA polymerase chain reaction testing between January and November 2020. The risk of SARS-CoV-2 infection or COVID-19 severe illness was not associated with the presence of non-ABO antibodies, even among persons with O blood group., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Aims: To analyse the rate of heart failure hospitalization for older adults prescribed a sodium-glucose co-transporter-2 (SGLT2) inhibitor., Materials and Methods: The study cohort included adults aged 66 years and older diagnosed with diabetes mellitus in Ontario, Canada, between July 2015 and March 2019, who received either an SGLT2 inhibitor or a dipeptidyl peptidase-4 (DPP-4) inhibitor. The primary outcome was a composite of heart failure hospitalization and all-cause mortality. Secondary outcomes included diabetic ketoacidosis and hypoglycaemia., Results: A total of 29 916 adults prescribed an SGLT2 inhibitor were compared with 29 916 adults prescribed a DPP-4 inhibitor. The mean age was 72 years, 60% were men, the baseline glycated haemoglobin concentration was 8.2% and the baseline creatinine was 89 μmol/L. The incidence rate of the primary outcome was 19/1000 person-years for adults prescribed an SGLT2 inhibitor compared to 38/1000 person-years in those prescribed a DPP-4 inhibitor. This resulted in a hazard ratio (HR) of 0.49 (95% confidence interval [CI] 0.45, 0.54) and a rate difference (RD) of 19 fewer events per 1000 person-years (RD -19 [95% CI -22, -17]). Patients prescribed an SGLT2 inhibitor also had a lower rate of hypoglycaemia (HR 0.61 [95% CI 0.46, 0.81); RD -1.6 [95% CI -2.4, -0.8]), but a higher rate of diabetic ketoacidosis (HR 1.84 [95% CI 1.26, 2.70]; RD 1.0 [95% CI 0.4, 1.6])., Conclusions: Older adults prescribed an SGLT2 inhibitor had a lower rate of heart failure hospitalization or death, and a lower rate of hypoglycaemia, but an increased rate of diabetic ketoacidosis compared to older adults prescribed a DPP-4 inhibitor., (© 2020 John Wiley & Sons Ltd.)

Background: The management of type 2 diabetes predominantly focuses on reducing hemoglobin A1C (HbA1c). We examined the association between the magnitude of reduction in HbA1c and cardiovascular outcomes for new diabetes medications: sodium-glucose cotransporter-2 [SGLT2] inhibitors, glucagon-like peptide-1 [GLP1] agonists, and dipeptidyl peptidase-4 [DPP4] inhibitors., Methods: We reviewed all published, placebo-controlled, randomized cardiovascular outcome trials. Meta-regression was performed to evaluate the association between HbA1c reduction (i.e., [post-intervention HbA1c for active drug - pre-intervention HbA1c for active drug] - [post-intervention HbA1c for placebo - pre-intervention HbA1c for placebo]) and the composite cardiovascular outcome (i.e., stroke, myocardial infarction, or cardiovascular death)., Results: We identified 14 cardiovascular outcome clinical trials, the median sample size was 9401, the median age was 64 years, the median time since diagnosis of diabetes was 12 years, and the median duration of trial follow-up was 120 weeks. Within individual medication classes, each additional 0.5% reduction in HbA1c in the active drug arm, relative to placebo, was associated with a lower incidence of cardiovascular events for GLP1 agonists (0.82, 0.68-0.98) but not for SGLT2 (0.97, 0.69-1.36) or DPP4 (1.03, 0.39-2.74) inhibitors., Discussion: Our study provides further support that reducing the risk of cardiovascular events for adults with diabetes is partly explained by a reduction in HbA1c., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Apixaban and rivaroxaban are the most commonly prescribed direct oral anticoagulants for adults with atrial fibrillation, but head-to-head data comparing their safety and effectiveness are lacking., Objective: To compare the safety and effectiveness of apixaban versus rivaroxaban for patients with nonvalvular atrial fibrillation., Design: New-user, active-comparator, retrospective cohort study., Setting: A U.S. nationwide commercial health care claims database from 28 December 2012 to 1 January 2019., Patients: Adults newly prescribed apixaban (n = 59 172) or rivaroxaban (n = 40 706)., Measurements: The primary effectiveness outcome was a composite of ischemic stroke or systemic embolism. The primary safety outcome was a composite of intracranial hemorrhage or gastrointestinal bleeding., Results: 39 351 patients newly prescribed apixaban were propensity score matched to 39 351 patients newly prescribed rivaroxaban. Mean age was 69 years, 40% of patients were women, and mean follow-up was 288 days for new apixaban users and 291 days for new rivaroxaban users. The incidence rate of ischemic stroke or systemic embolism was 6.6 per 1000 person-years for adults prescribed apixaban compared with 8.0 per 1000 person-years for those prescribed rivaroxaban (hazard ratio [HR], 0.82 [95% CI, 0.68 to 0.98]; rate difference, 1.4 fewer events per 1000 person-years [CI, 0.0 to 2.7]). Adults prescribed apixaban also had a lower rate of gastrointestinal bleeding or intracranial hemorrhage (12.9 per 1000 person-years) compared with those prescribed rivaroxaban (21.9 per 1000 person-years), corresponding to an HR of 0.58 (CI, 0.52 to 0.66) and a rate difference of 9.0 fewer events per 1000 person-years (CI, 6.9 to 11.1)., Limitation: Unmeasured confounding, incomplete laboratory data., Conclusion: In routine care, adults with atrial fibrillation prescribed apixaban had a lower rate of both ischemic stroke or systemic embolism and bleeding compared with those prescribed rivaroxaban., Primary Funding Source: Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital.

Competing Interests: Competing interests: None declared.

Caterpillars of the pine processionary moths, Thaumetopoea complex, cause serious defoliation to Cedrus , Pinus, and Pseudotsuga trees. Thaumetopoea caterpillars also have fine hairs on their abdominal tergites that contain a protein that can severely irritate and cause dermatitis in humans and domestic animals. The control of the T. pityocampa pine processionary moth has become necessary in many European countries because of the sanitary risks that are related to larval urtication and the defoliation threat to pine forests and plantations. New research activities have been aimed at the development of eco-friendly, innovative technologies for Integrated Pest Management (IPM) of these moths, particularly in urban parks and woodland recreational areas. This paper describes the recent advances in the use of pheromones in monitoring, mass trapping, and mating disruption related to management of processionary moths T. hellenica and T. pityocampa . According to the results, the use of pheromones may provide a practical alternative to insecticide sprays, as they can be safe and simple as compared to other control methods.