Time-restricted feeding reveals a role for neural respiratory clocks in optimizing daily ventilatory-metabolic coupling in mice.

The master circadian clock, located in the suprachiasmatic nuclei (SCN), organizes the daily rhythm in minute ventilation (V̇e). However, the extent that the daily rhythm in V̇e is secondary to SCN-imposed O2 and CO2 cycles (i.e., metabolic rate) or driven by other clock mechanisms remains unknown. Here, we experimentally shifted metabolic rate using time-restricted feeding (without affecting light-induced synchronization of the SCN) to determine the influence of metabolic rate in orchestrating the daily V̇e rhythm. Mice eating predominantly at night exhibited robust daily rhythms in O2 consumption (V̇o2), CO2 production (V̇co2), and V̇e with similar peak times (approximately ZT18) that were consistent with SCN organization. However, feeding mice exclusively during the day separated the relative timing of metabolic and ventilatory rhythms, resulting in an approximately 8.5-h advance in V̇co2 and a disruption of the V̇e rhythm, suggesting opposing circadian and metabolic influences on V̇e. To determine if the molecular clock of cells involved in the neural control of breathing contributes to the daily V̇e rhythm, we examined V̇e in mice lacking BMAL1 in Phox2b-expressing respiratory cells (i.e., BKOP mice). The ventilatory and metabolic rhythms of predominantly night-fed BKOP mice did not differ from wild-type mice. However, in contrast to wild-type mice, exclusive day feeding of BKOP mice led to an unfettered daily V̇e rhythm with a peak time aligning closely with the daily V̇co2 rhythm. Taken together, these results indicate that both daily V̇co2 changes and intrinsic circadian time-keeping within Phox2b respiratory cells are predominant orchestrators of the daily rhythm in ventilation.NEW & NOTEWORTHY The master circadian clock organizes the daily rhythm in ventilation; however, the extent that this rhythm is driven by SCN regulation of metabolic rate versus other clock mechanisms remains unknown. We report that metabolic rate alone is insufficient to explain the daily oscillation in ventilation and that neural respiratory clocks within Phox2b-expressing cells additionally optimize breathing. Collectively, these findings advance our mechanistic understanding of the circadian rhythm in ventilatory control.

Potentially Modifiable Risk Factors for Dementia and Mild Cognitive Impairment: An Umbrella Review and Meta-Analysis.

INTRODUCTION: The prevalence of mild and major neurocognitive disorders (NCDs), also referred to as mild cognitive impairment and dementia, is rising globally. The prevention of NCDs is a major global public health interest. We sought to synthesize the literature on potentially modifiable risk factors for NCDs. METHODS: We conducted an umbrella review using a systematic search across multiple databases to identify relevant systematic reviews and meta-analyses. Eligible reviews examined potentially modifiable risk factors for mild or major NCDs. We used a random-effects multi-level meta-analytic approach to synthesize risk ratios for each risk factor while accounting for overlap in the reviews. We further examined risk factors for major NCD due to two common etiologies: Alzheimer's disease and vascular dementia. RESULTS: A total of 45 reviews with 212 meta-analyses were synthesized. We identified fourteen broadly defined modifiable risk factors that were significantly associated with these disorders: alcohol consumption, body weight, depression, diabetes mellitus, diet, hypertension, less education, physical inactivity, sensory loss, sleep disturbance, smoking, social isolation, traumatic brain injury, and vitamin D deficiency. All 14 factors were associated with the risk of major NCD, and five were associated with mild NCD. We found considerably less research for vascular dementia and mild NCD. CONCLUSION: Our review quantifies the risk associated with 14 potentially modifiable risk factors for mild and major NCDs, including several factors infrequently included in dementia action plans. Prevention strategies should consider approaches that reduce the incidence and severity of these risk factors through health promotion, identification, and early management.

Evaluating methods for risk prediction of Covid-19 mortality in nursing home residents before and after vaccine availability: a retrospective cohort study.

BACKGROUND: SARS-CoV-2 vaccines are effective in reducing hospitalization, COVID-19 symptoms, and COVID-19 mortality for nursing home (NH) residents. We sought to compare the accuracy of various machine learning models, examine changes to model performance, and identify resident characteristics that have the strongest associations with 30-day COVID-19 mortality, before and after vaccine availability. METHODS: We conducted a population-based retrospective cohort study analyzing data from all NH facilities across Ontario, Canada. We included all residents diagnosed with SARS-CoV-2 and living in NHs between March 2020 and July 2021. We employed five machine learning algorithms to predict COVID-19 mortality, including logistic regression, LASSO regression, classification and regression trees (CART), random forests, and gradient boosted trees. The discriminative performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC) for each model using 10-fold cross-validation. Model calibration was determined through evaluation of calibration slopes. Variable importance was calculated by repeatedly and randomly permutating the values of each predictor in the dataset and re-evaluating the model's performance. RESULTS: A total of 14,977 NH residents and 20 resident characteristics were included in the model. The cross-validated AUCs were similar across algorithms and ranged from 0.64 to 0.67. Gradient boosted trees and logistic regression had an AUC of 0.67 pre- and post-vaccine availability. CART had the lowest discrimination ability with an AUC of 0.64 pre-vaccine availability, and 0.65 post-vaccine availability. The most influential resident characteristics, irrespective of vaccine availability, included advanced age (≥ 75 years), health instability, functional and cognitive status, sex (male), and polypharmacy. CONCLUSIONS: The predictive accuracy and discrimination exhibited by all five examined machine learning algorithms were similar. Both logistic regression and gradient boosted trees exhibit comparable performance and display slight superiority over other machine learning algorithms. We observed consistent model performance both before and after vaccine availability. The influence of resident characteristics on COVID-19 mortality remained consistent across time periods, suggesting that changes to pre-vaccination screening practices for high-risk individuals are effective in the post-vaccination era.

Length of postpartum hospital stays during COVID-19: Findings from a convergent parallel mixed-methods study.

OBJECTIVE: We examined length of postpartum hospitalization for live births during the COVID-19 pandemic and explored how pandemic circumstances influenced postpartum hospital experiences. METHODS: We conducted a cross-provincial, convergent parallel mixed-methods study in Ontario (ON) and British Columbia (BC), Canada. We included birthing persons (BPs) with an in-hospital birth in ON from 1 January to 31 March 2019, 2021, and 2022 (quantitative), and BPs (≥18 years) in ON or BC from 1 May 2020 to 1 December 2021 (qualitative). We linked multiple health administrative datasets at ICES and developed multivariable linear regression models to examine length of hospital stay (quantitative). We conducted semi-structured interviews using qualitative descriptive to understand experiences of postpartum hospitalization (qualitative). Data integration occurred during design and interpretation. RESULTS: Relative to 2019, postpartum hospital stays decreased significantly by 3.29 hours (95% CI: -3.58 to -2.99; 9.2% reduction) in 2021 and 3.89 hours (95% CI: -4.17 to -3.60; 9.0% reduction) in 2022. After adjustment, factors associated with shortened stays included: giving birth during COVID-19, social deprivation (more ethnocultural diversity), midwifery care, multiparity, and lower newborn birth weight. Postpartum hospital experiences were impacted by risk perception of COVID-19 infection, clinical care and hospital services/amenities, visitor policies, and duration of stay. CONCLUSION: Length of postpartum hospital stays decreased during COVID-19, and qualitative findings described unmet needs for postpartum services. The integration of large administrative and interview data expanded our understanding of observed differences. Future research should investigate the impacts of shortened stays on health services outcomes and personal experiences. OBJECTIF: Nous avons examiné la durée d'hospitalisation post-partum pour les cas de naissance vivante pendant la pandémie de COVID-19 et exploré comment les circonstances de la pandémie ont influencé l'expérience post-partum à l'hôpital. MéTHODES: Nous avons mené une étude interprovinciale selon un modèle mixte parallèle et convergent en Ontario (Ont.) et en Colombie-Britannique (C.-B.), au Canada. Nous avons inclus les personnes ayant accouché à l'hôpital en Ont. entre le 1 janvier et le 31 mars 2019, 2021 et 2022 (quantitatif), et celles ayant accouché (≥ 18 ans) entre le 1 mai 2020 et le 1 décembre 2021 en Ont. ou en C.-B. (qualitatif). Nous avons relié plusieurs ensembles de données de santé administratives à l'ICES et développé des modèles de régression linéaire multivariable pour examiner la durée d'hospitalisation (quantitative). Nous avons mené des entretiens semi-structurés en utilisant une méthode qualitative descriptive pour comprendre les expériences d'hospitalisation post-partum (qualitative). L'intégration des données a eu lieu pendant la conception de l'étude et l'interprétation. RéSULTATS: Par rapport à 2019, la durée de l'hospitalisation post-partum a significativement diminué de 3,29 heures (IC à 95 % : -3,58 à -2,99; réduction de 9,2 %) en 2021 et de 3,89 heures (IC à 95 % : -4,17 à -3,60; réduction de 9,0 %) en 2022. Après ajustement, les facteurs associés à la réduction de la durée d'hospitalisation étaient les suivants : accouchement pendant la pandémie de COVID-19, manque de socialisation (plus grande diversité ethnoculturelle), prise en charge en pratique sage-femme, multiparité et poids plus faible du nouveau-né à la naissance. L'expérience d'hospitalisation post-partum était influencée par la perception du risque de contracter la COVID-19, les soins cliniques et les services et commodités à l'hôpital, les politiques relatives aux visiteurs et la durée de l'hospitalisation. CONCLUSION: La durée d'hospitalisation post-partum a diminué pendant la pandémie de COVID-19, et les résultats qualitatifs ont décrit des besoins non satisfaits en matière de services post-partum. L'intégration de grands ensembles de données administratives et d'entretiens a permis de mieux comprendre les différences observées. Les recherches futures devront se pencher sur l'impact de la réduction de la durée d'hospitalisation sur les résultats des services de santé et les expériences personnelles.

The association between frailty, long-term care home characteristics and COVID-19 mortality before and after SARS-CoV-2 vaccination: a retrospective cohort study.

BACKGROUND: The relative contributions of long-term care (LTC) resident frailty and home-level characteristics on COVID-19 mortality has not been well studied. We examined the association between resident frailty and home-level characteristics with 30-day COVID-19 mortality before and after the availability of SARS-CoV-2 vaccination in LTC. METHODS: We conducted a population-based retrospective cohort study of LTC residents with confirmed SARS-CoV-2 infection in Ontario, Canada. We used multi-level multivariable logistic regression to examine associations between 30-day COVID-19 mortality, the Hubbard Frailty Index (FI), and resident and home-level characteristics. We compared explanatory models before and after vaccine availability. RESULTS: There were 11,179 and 3,655 COVID-19 cases in the pre- and post-vaccine period, respectively. The 30-day COVID-19 mortality was 25.9 and 20.0% during the same periods. The median odds ratios for 30-day COVID-19 mortality between LTC homes were 1.50 (95% credible interval [CrI]: 1.41-1.65) and 1.62 (95% CrI: 1.46-1.96), respectively. In the pre-vaccine period, 30-day COVID-19 mortality was higher for males and those of greater age. For every 0.1 increase in the Hubbard FI, the odds of death were 1.49 (95% CI: 1.42-1.56) times higher. The association between frailty and mortality remained consistent in the post-vaccine period, but sex and age were partly attenuated. Despite the substantial home-level variation, no home-level characteristic examined was significantly associated with 30-day COVID-19 mortality during either period. INTERPRETATION: Frailty is consistently associated with COVID-19 mortality before and after the availability of SARS-CoV-2 vaccination. Home-level characteristics previously attributed to COVID-19 outcomes do not explain significant home-to-home variation in COVID-19 mortality.

A Case of Tizanidine Withdrawal and Road to Recovery.

This case report highlights the complexities of tizanidine withdrawal in a 68-year-old woman with chronic pain. Tizanidine, a widely used imidazole-derived muscle relaxant, poses challenges due to the absence of standardized withdrawal protocols. The patient's presentation included hypertension and tachycardia following a gradual reduction in her outpatient tizanidine dose. During the de-escalation of tizanidine, the patient experienced withdrawal symptoms, including severe body aches, hypertension, and tachycardia. Management during withdrawal involved a unique approach using a one-time dose of phenobarbital, a measure that allowed the resolution of hemodynamic instability and pain with complete discontinuation of tizanidine. The ultimate decision to transition the patient to methocarbamol and stop taking tizanidine for pain control highlights the importance of individualized care. The patient has responded to this therapy upon follow-up.

Measures of retention in HIV care: A protocol for a mixed methods study.

INTRODUCTION: Retention in HIV care is necessary to achieve adherence to antiretroviral therapy, viral load suppression, and optimal health outcomes. There is no standard definition for retention in HIV care, which compromises consistent and reliable reporting and comparison of retention across facilities, jurisdictions, and studies. OBJECTIVE: The objective of this study is to explore how stakeholders involved in HIV care define retention in HIV care and their preferences on measuring retention. METHODS: We will use an exploratory sequential mixed methods design involving HIV stakeholder groups such as people living with HIV, people involved in providing care for PLHIV, and people involved in decision-making about PLHIV. In the qualitative phase of the study, we will conduct 20-25 in-depth interviews to collect the perspectives of HIV stakeholders on using their preferred retention measures. The findings from the qualitative phase will inform the development of survey items for the quantitative phase. Survey participants (n = 385) will be invited to rate the importance of each approach to measuring retention on a seven-point Likert scale. We will merge the qualitative and quantitative findings phase findings to inform a consensus-building framework for a standard definition of retention in care. ETHICAL ISSUES AND DISSEMINATION: This study has received ethics approval from the Hamilton Integrated Research Ethics Board. The findings will be disseminated through peer-reviewed publications, conference presentations, and among stakeholder groups. LIMITATIONS: This study has limitations; we won't be able to arrive at a standard definition; a Delphi technique amongst the stakeholders will be utilized using the framework to reach a consensus globally accepted definition.

Reshaping Wound Care: Evaluation of an Artificial Intelligence App to Improve Wound Assessment and Management.

This study evaluated the usability and effectiveness of an artificial intelligence application for wound assessment and management from a clinician-and-patient perspective. A quasi-experimental design was conducted in four settings in an Australian health service. Data were collected from patients in the standard (n=166,243 wounds) and intervention (n=124,184 wounds) group, at baseline and post-intervention. Clinicians completed a survey (n=10) and focus group (n=13) and patients were interviewed (n=4). Wound documentation were analysed descriptively, bivariate statistics determined between-group differences, and interviews were thematically analysed. Compared with the standard group, wound documentation in the intervention group improved significantly (<2 items documented 24% vs 70%, P < .001). During the intervention, 101/132 wounds improved (mean wound size reduction=53.99%). Positive evaluations included instantaneous objective wound assessment, shared wound plans increased patient adherence and enhanced efficiency in providing virtual care. Application use facilitated remote patient monitoring and reduced patient travel time while maintaining optimal wound care.

Short-term mortality and palliative care use after delayed hospital discharge: a population-based retrospective cohort study.

OBJECTIVES: In Canada, patients whose acute medical issues have been resolved but are awaiting discharge from hospital are designated as alternate level of care (ALC). We investigated short-term mortality and palliative care use following ALC designation in Ontario, Canada. METHODS: We conducted a population-based retrospective cohort study of adult, acute care hospital admissions in Ontario with an ALC designation between January and December 2021. Our follow-up window was until 90 days post-ALC designation or death. Setting of discharge and death was determined using admission and discharge dates from multiple databases. We measured palliative care using physician billings, inpatient palliative care records and palliative home care records. We compared the characteristics of ALC patients by 90-day survival status and compared palliative care use across settings of discharge and death. RESULTS: We included 54 839 ALC patients with a median age of 80 years. Nearly one-fifth (18.4%) of patients died within 90 days. Patients who died were older, had more comorbid conditions and were more likely to be male. Among those who died, 35.1% were never discharged from hospital and 20.3% were discharged but ultimately died in the hospital. The majority of people who died received palliative care following their ALC designation (68.1%). CONCLUSIONS: A significant proportion of patients experiencing delayed discharge die within 3 months, with the majority dying in hospitals despite being identified as ready to be discharged. Future research should examine the adequacy of palliative care provision for this population.

Primary care quality for older adults: Practice-based quality measures derived from a RAND/UCLA appropriateness method study.

We established consensus on practice-based metrics that characterize quality of care for older primary care patients and can be examined using secondary health administrative data. We conducted a two-round RAND/UCLA Appropriateness Method (RAM) study and recruited 10 Canadian clinicians and researchers with expertise relevant to the primary care of elderly patients. Informed by a literature review, the first RAM round evaluated the appropriateness and importance of candidate quality measures in an online questionnaire. Technical definitions were developed for each endorsed indicator to specify how the indicator could be operationalized using health administrative data. In a virtual synchronous meeting, the expert panel offered feedback on the technical specifications for the endorsed indicators. Panelists then completed a second (final) questionnaire to rate each indicator and corresponding technical definition on the same criteria (appropriateness and importance). We used statistical integration to combine technical expert panelists' judgements and content analysis of open-ended survey responses. Our literature search and internal screening resulted in 61 practice-based quality indicators for rating. We developed technical definitions for indicators endorsed in the first questionnaire (n = 55). Following the virtual synchronous meeting and second questionnaire, we achieved consensus on 12 practice-based quality measures across four Priority Topics in Care of the Elderly. The endorsed indicators provide a framework to characterize practice- and population-level encounters of family physicians delivering care to older patients and will offer insights into the outcomes of their care provision. This study presented a case of soliciting expert feedback to develop measurable practice-based quality indicators that can be examined using administrative data to understand quality of care within population-based data holdings. Future work will refine and operationalize the technical definitions established through this process to examine primary care provision for older adults in a particular context (Ontario, Canada).

Trends of Peanut-Induced Anaphylaxis Rates Before and After the 2017 Early Peanut Introduction Guidelines in Montreal, Canada.

BACKGROUND: Food allergies, particularly peanut, represent the predominant cause of anaphylaxis. Whereas early allergen introduction has emerged as a potential preventive strategy, the precise impact of recent guidelines on peanut-induced anaphylaxis rates in Canada remains unclear. OBJECTIVE: To assess the impact of the 2017 Addendum Guidelines for the Prevention of Peanut Allergy on peanut-induced anaphylaxis rates in Canada. METHODS: Using a comprehensive longitudinal registry capturing pediatric anaphylaxis presentations to the Montreal's Children's Hospital, we compared children with and without known peanut allergy who presented with peanut-induced anaphylaxis between 2011 and 2019 inclusive, excluding data beyond 2019 owing to the Coronavirus disease 2019 (COVID-19) pandemic. We calculated rates of peanut-induced anaphylaxis presentations per 100,000 age-adjusted all-cause emergency department visits using 4-month intervals. Interrupted time series analysis was used to compare anaphylaxis rate trends before and after 2017 for children ages 0 to 2 and 3 to 17 years. RESULTS: We examined 2,011 cases of pediatric anaphylaxis, including 429 (21%) triggered by peanuts. Compared with pre-guideline estimates, the yearly rate of change of peanut anaphylaxis rates decreased by 7.96 (95% confidence interval -14.57 to -1.36; P = .018) after 2017 among patients with new-onset anaphylaxis in children 2 years of age or younger (n = 109). No significant changes were identified for older patients ages 3 to 17, or in patients with known peanut allergy. CONCLUSIONS: Early introduction guidelines in Canada are associated with a reduced risk of new-onset peanut-induced anaphylaxis in young children within a single center in Montreal. Further research is required to assess the impact on a wider population and other food allergens.

Evaluating the Association between the Implementation of the PoET (Prevention of Error-Based Transfers) Southwest Spread Project and Palliative Care Provision: A Quasi-Experimental Matched Cohort Study Using Population-Level Health Administrative Data.

OBJECTIVES: The PoET (Prevention of Error-based Transfers) project seeks to align long-term care (LTC) home informed consent practices to existing legislation, thereby reducing consent-related error-based transfers to acute care. We sought to measure changes in resident-level palliative care provision after participating in the PoET Southwest Spread Project (PSSP), and to identify patient and LTC home characteristics associated with palliative care provision. DESIGN: Quasi-experimental matched (1:1 ratio) cohort study design using linked population-based health administrative data. SETTING: Sixty LTC homes (PSSP = 30; Control = 30) in Ontario, Canada, from November 2019 to December 2021. METHODS: We matched 30 PSSP to 30 control homes and described incidence rates for resident-level palliative care provision (ie, physician palliative care encounters and palliative medication prescriptions) during the 7-month postimplementation period. We used generalized linear mixed models to evaluate the association between PSSP implementation and palliative care provision during the postimplementation period. We adjusted for resident-level characteristics (ie, age, sex, comorbidity status) and home-level characteristics (ie, rurality status, profit model, COVID-19 impact). We identified a decedent subcohort to measure palliative care provision patterns during the last 2 months of life. RESULTS: We captured a matched cohort of 8894 residents (PSSP = 4103; Control = 4791). Incidence rates of palliative care encounters increased during the postimplementation period for PSSP (82.6 to 85.4 per 100 person-months) but not for control residents (68.8 to 65.3 per 100 person-months). After adjusting for key covariates, PSSP exposure was associated increased palliative care provision (incidence rate ratio 2.47, 95% CI 2.31-2.64) and palliative care medication prescription (1.16, 95% CI 1.12-1.20). Larger home size, certain health regions, and higher number of comorbidities were associated with increased physician palliative care encounters. CONCLUSIONS AND IMPLICATIONS: By promoting correct informed consent practices in LTC, PSSP participation increased palliative care provision for PSSP LTC residents across all settings.

Using Patient-Specific 3D Modeling and Simulations to Optimize Microwave Ablation Therapy for Liver Cancer.

Microwave ablation (MWA) of liver tumors presents challenges like under- and over-ablation, potentially leading to inadequate tumor destruction and damage to healthy tissue. This study aims to develop personalized three-dimensional (3D) models to simulate MWA for liver tumors, incorporating patient-specific characteristics. The primary objective is to validate the predicted ablation zones compared to clinical outcomes, offering insights into MWA before therapy to facilitate accurate treatment planning. Contrast-enhanced CT images from three patients were used to create 3D models. The simulations used coupled electromagnetic wave propagation and bioheat transfer to estimate the temperature distribution, predicting tumor destruction and ablation margins. The findings indicate that prolonged ablation does not significantly improve tumor destruction once an adequate margin is achieved, although it increases tissue damage. There was a substantial overlap between the clinical ablation zones and the predicted ablation zones. For patient 1, the Dice score was 0.73, indicating high accuracy, with a sensitivity of 0.72 and a specificity of 0.76. For patient 2, the Dice score was 0.86, with a sensitivity of 0.79 and a specificity of 0.96. For patient 3, the Dice score was 0.8, with a sensitivity of 0.85 and a specificity of 0.74. Patient-specific 3D models demonstrate potential in accurately predicting ablation zones and optimizing MWA treatment strategies.

Long-Term Functional Limitations and Predictors of Recovery After COVID-19: A Multicenter Prospective Cohort Study.

BACKGROUND: Limited data exist on post-severe COVID-19 functional trajectory, particularly considering premorbid status. We characterized 1-year functional recovery post-hospitalization for COVID-19, highlighting predictors of long-term recovery. METHODS: We enrolled adult patients with lab-confirmed SARS-CoV-2 infection and hospitalized for COVID-19 sequelae, from five major Ontario, Canada hospitals in a prospective cohort study. Assessments included telephone interviews on admission followed by telephone and in-person assessments at 3-, 6-, 9-, and 12-months post-discharge. The Activity-Measure for Post-Acute Care (AM-PAC) Mobility and Cognition scales were administered at baseline and every 3 months for 1 year. Secondary outcomes included symptoms, spirometry, physical performance, dyspnea, fatigue, distress, anxiety and depression, and quality of life. RESULTS: A total of 254 patients (57.1% male) with a mean age of 60.0 (±13.1) years and an average hospital stay of 14.3 (±19.7) days agreed to participate. At 12 months, 55.3% demonstrated clinically important deficits in mobility and 38.8% had cognitive deficits compared to premorbid levels. Fatigue was reported in 44.2%, followed by difficulty walking long distances in 35.8% and dyspnea in 33.0%. Almost 40% of patients had an FEV1(% Pred) < 80% at 12 months, 60.3% had impairments in physical performance, and 44.5% had problems with anxiety or depression. Predictors of better mobility at 12 months included higher premorbid mobility status, male sex, shorter hospital stay, fewer comorbidities, and higher FEV1 (% pred) at the 3-month follow-up. CONCLUSIONS: Our study provides compelling evidence of the long-term impact of COVID-19 on functional and cognitive status 1-year post-infection.

The Viability and Acceptability of a Virtual Wound Care Command Centre in Australia.

The objective of this study was to assess the viability and acceptability of an innovative Virtual Wound Care Command Centre where patients in the community, and their treating clinicians, have access to an expert wound specialist service that comprises a digital wound application (app) for wound analysis, decision-making, remote consultation, and monitoring. Fifty-one patients with chronic (42.6%) wounds were healed, with a median time to healing of 66 (95% CI: 56-88) days. All patients reported high satisfaction with their wound care, 86.4% of patients recommended the Virtual Wound Care Command Centre with 84.1% of patients reporting the app as easy to use. The data revealed that the Virtual Wound Care Command Centre was a viable and acceptable patient-centred expert wound consultation service for chronic wound patients in the community.

Prevalence and population attributable fractions of potentially modifiable risk factors for dementia in Canada: A cross-sectional analysis of the Canadian Longitudinal Study on Aging.

OBJECTIVES: We investigated the prevalence and population attributable fraction (PAF) of 12 potentially modifiable risk factors for dementia in middle-aged and older Canadians. METHODS: We conducted a cross-sectional study of 30,097 adults aged 45 to 85 with baseline data from the Canadian Longitudinal Study on Aging (2011‒2015). Risk factors and associated relative risks were taken from a highly cited systematic review. We calculated the prevalence of each risk factor using sampling weights. Individual PAFs were calculated both crudely and weighted for communality, and combined PAFs were calculated using both multiplicative and additive assumptions. Analyses were stratified by household income and repeated at CLSA's first follow-up (2015‒2018). RESULTS: The most prevalent risk factors were physical inactivity (63.8%; 95% CI, 62.8-64.9), hypertension (32.8%; 31.7-33.8), and obesity (30.8%; 29.7-31.8). The highest crude PAFs were physical inactivity (19.9%), traumatic brain injury (16.7%), and hypertension (16.6%). The highest weighted PAFs were physical inactivity (11.6%), depression (7.7%), and hypertension (6.0%). We estimated that the 12 risk factors combined accounted for 43.4% (37.3‒49.0) of dementia cases assuming weighted multiplicative interactions and 60.9% (55.7‒65.5) assuming additive interactions. There was a clear gradient of increasing prevalence and PAF with decreasing income for 9 of the 12 risk factors. CONCLUSION: The findings of this study can inform individual- and population-level dementia prevention strategies in Canada. Differences in the impact of individual risk factors between this study and other international and regional studies highlight the importance of tailoring national dementia strategies to the local distribution of risk factors.

RéSUMé: OBJECTIFS: Nous avons étudié la prévalence et la fraction attribuable dans la population (FAP) de 12 facteurs de risque de démence potentiellement modifiables chez les Canadiens d'âge moyen et plus âgés. MéTHODE: Nous avons mené une étude transversale de 30 097 adultes de 45 à 85 ans à l'aide des données de référence de l'Étude longitudinale canadienne sur le vieillissement (ELCV) (2011‒2015). Les facteurs de risque et les risques relatifs associés ont été extraits d'une revue systématique fréquemment citée. Nous avons calculé la prévalence de chaque facteur de risque à l'aide de poids d'échantillonnage. Les FAP individuelles ont été calculées à la fois sous forme brute et pondérées selon leurs points communs; les FAP combinées ont été calculées à l'aide d'hypothèses multiplicatives et additives. Les analyses ont été stratifiées selon le revenu du ménage et répétées au premier suivi de l'ELCV (2015‒2018). RéSULTATS: Les facteurs de risque les plus prévalents étaient la sédentarité (63,8 %; IC de 95%, 62,8­64,9), l'hypertension artérielle (32,8 %; 31,7­33,8) et l'obésité (30,8 %; 29,7­31,8). Les FAP brutes les plus élevées étaient la sédentarité (19,9 %), les traumatismes cranio-cérébraux (16,7 %) et l'hypertension artérielle (16,6 %). Les FAP pondérées les plus élevées étaient la sédentarité (11,6 %), la dépression (7,7 %) et l'hypertension artérielle (6,0 %). Selon nos estimations, les 12 facteurs de risque combinés représentaient 43,4 % (37,3‒49,0) des cas de démence en supposant des interactions multiplicatives pondérées et 60,9 % (55,7‒65,5) en supposant des interactions additives. Il y avait clairement un gradient d'accroissement de la prévalence et de la FAP avec la diminution du revenu pour 9 des 12 facteurs de risque. CONCLUSION: Les constats de l'étude peuvent éclairer les stratégies individuelles et populationnelles de prévention de la démence au Canada. Les différences d'impact des facteurs de risque individuels entre cette étude et d'autres études internationales et régionales montrent l'importance d'adapter les stratégies nationales de prévention de la démence à la répartition locale des facteurs de risque.

Fully automated deep learning based auto-contouring of liver segments and spleen on contrast-enhanced CT images.

Manual delineation of liver segments on computed tomography (CT) images for primary/secondary liver cancer (LC) patients is time-intensive and prone to inter/intra-observer variability. Therefore, we developed a deep-learning-based model to auto-contour liver segments and spleen on contrast-enhanced CT (CECT) images. We trained two models using 3d patch-based attention U-Net ([Formula: see text] and 3d full resolution of nnU-Net ([Formula: see text] to determine the best architecture ([Formula: see text]. BA was used with vessels ([Formula: see text] and spleen ([Formula: see text] to assess the impact on segment contouring. Models were trained, validated, and tested on 160 ([Formula: see text]), 40 ([Formula: see text]), 33 ([Formula: see text]), 25 (CCH) and 20 (CPVE) CECT of LC patients. [Formula: see text] outperformed [Formula: see text] across all segments with median differences in Dice similarity coefficients (DSC) ranging 0.03-0.05 (p < 0.05). [Formula: see text], and [Formula: see text] were not statistically different (p > 0.05), however, both were slightly better than [Formula: see text] by DSC up to 0.02. The final model, [Formula: see text], showed a mean DSC of 0.89, 0.82, 0.88, 0.87, 0.96, and 0.95 for segments 1, 2, 3, 4, 5-8, and spleen, respectively on entire test sets. Qualitatively, more than 85% of cases showed a Likert score [Formula: see text] 3 on test sets. Our final model provides clinically acceptable contours of liver segments and spleen which are usable in treatment planning.