Association Between Ethnicity and Mortality Outcomes in Patients with COVID-19: A Mayo Clinic VIRUS Registry Cohort Study.

Hispanic populations face significant disparities in health and healthcare. The COVID-19 pandemic highlighted and sometimes further exacerbated these disparities. We conducted a multisite, retrospective cohort study of 6494 hospitalized adult patients admitted between March 2020 and January 2022 with a diagnosis of COVID-19 from five sites including academic hospitals in MN, AZ, and FL and community hospitals in MN and WI. This is an ancillary project of the Viral Infection and Respiratory illness Universal Study (VIRUS) registry, supplemented by electronic health record data. We compared in-hospital mortality and length of stay outcomes between Hispanic and non-Hispanic populations admitted with COVID-19 using propensity matched scores to account for imbalances in demographic and clinical covariables. Among a total of 6494 patients, 512 (7.9%) patients were reported deceased and 5982 (92.1%) alive at discharge. We did not find a statistically significant difference between in-hospital mortality nor length of stay between the two groups.

Early Prevention of Critical Illness in Older Adults: Adaptation and Pilot Testing of an Electronic Risk Score and Checklist.

OBJECTIVE: Given limited critical care resources and an aging population, early interventions to prevent critical illness are vital. In this work, we measured post-implementation outcomes after introducing a novel electronic scoring system (Elders Risk Assessment-ERA) and a risk-factor checklist, Checklist for Early Recognition and Treatment of Acute Illness (CERTAIN), to detect older patients at high risk of critical illness in a primary care setting. METHODS: The study was conducted at a family medicine clinic in Kasson, MN. The ADAPT-ITT framework was used to modify the CERTAIN checklist for primary care during 2 co-design workshops involving interdisciplinary clinicians, held in April 2023. The ERA score and modified CERTAIN checklist were implemented between May and July 2023 and identify and assess all patients age ≥60 years at risk of critical illness during their primary care visits. Implementation outcomes were evaluated at the end of the study via an anonymous survey and EHR data extraction. RESULTS: Fourteen clinicians participated in 2 co-design workshops. A total of 19 clinicians participated in a post-pilot survey. All survey items were rated on a 5-point Likert type scale. Mean acceptability of the ERA score and checklist was rated 3.35 (SD = 0.75) and 3.09 (SD = 0.64), respectively. Appropriateness had a mean rating of 3.38 (SD = 0.82) for the ERA score and 3.19 (SD = 0.59) for the checklist. Mean feasibility was rated 3.38(SD = 0.85) and 2.92 (SD = 0.76) for the ERA score and checklist, respectively. The adoption rate was 50% (19/38) among clinicians, but the reach was low at 17% (49/289) of eligible patients. CONCLUSIONS: This pilot study evaluated the implementation of an intervention that introduced the ERA score and CERTAIN checklist into a primary care practice. Results indicate moderate acceptability, appropriateness, and feasibility of the ERA score, and similar ratings for the checklist, with slightly lower feasibility. While checklist adoption was moderate, reach was limited, indicating inconsistent use. RECOMMENDATIONS: We plan to use the open-ended resurvey responses to further modify the CERTAIN-FM checklist and implementation process. The ADAPT-ITT framework is a useful model for adapting the checklist to meet the primary care clinician needs.

Machine Learning for Automated Classification of Abnormal Lung Sounds Obtained from Public Databases: A Systematic Review.

Pulmonary auscultation is essential for detecting abnormal lung sounds during physical assessments, but its reliability depends on the operator. Machine learning (ML) models offer an alternative by automatically classifying lung sounds. ML models require substantial data, and public databases aim to address this limitation. This systematic review compares characteristics, diagnostic accuracy, concerns, and data sources of existing models in the literature. Papers published from five major databases between 1990 and 2022 were assessed. Quality assessment was accomplished with a modified QUADAS-2 tool. The review encompassed 62 studies utilizing ML models and public-access databases for lung sound classification. Artificial neural networks (ANN) and support vector machines (SVM) were frequently employed in the ML classifiers. The accuracy ranged from 49.43% to 100% for discriminating abnormal sound types and 69.40% to 99.62% for disease class classification. Seventeen public databases were identified, with the ICBHI 2017 database being the most used (66%). The majority of studies exhibited a high risk of bias and concerns related to patient selection and reference standards. Summarizing, ML models can effectively classify abnormal lung sounds using publicly available data sources. Nevertheless, inconsistent reporting and methodologies pose limitations to advancing the field, and therefore, public databases should adhere to standardized recording and labeling procedures.

Perioperative mortality in Colombia: perspectives of the fourth indicator in The Lancet Commission on Global Surgery - Colombian Surgical Outcomes Study (ColSOS) - a protocol for a multicentre prospective cohort study.

INTRODUCTION: Death following surgical procedures is a global health problem, accounting for 4.2 million deaths annually within the first 30 postoperative days. The fourth indicator of The Lancet Commission on Global Surgery is essential as it seeks to standardise postoperative mortality. Consequently, it helps identify the strengths and weaknesses of each country's healthcare system. Accurate information on this indicator is not available in Colombia, limiting the possibility of interventions applied to our population. We aim to describe the in-hospital perioperative mortality of the surgical procedures performed in Colombia. The data obtained will help formulate public policies, improving the quality of the surgical departments. METHODS AND ANALYSIS: An observational, analytical, multicentre prospective cohort study will be conducted throughout Colombia. Patients over 18 years of age who have undergone a surgical procedure, excluding radiological/endoscopic procedures, will be included. A sample size of 1353 patients has been projected to achieve significance in our primary objective; however, convenience sampling will be used, as we aim to include all possible patients. Data collection will be carried out prospectively for 1 week. Follow-up will continue until hospital discharge, death or a maximum of 30 inpatient days. The primary outcome is perioperative mortality. A descriptive analysis of the data will be performed, along with a case mix analysis of mortality by procedure-related, patient-related and hospital-related conditions ETHICS AND DISSEMINATION: The Fundación Cardioinfantil-Instituto de Cardiología Ethics Committee approved this study (No. 41-2021). The results are planned to be disseminated in three scenarios: the submission of an article for publication in a high-impact scientific journal and presentations at the Colombian Surgical Forum and the Congress of the American College of Surgeons. TRIAL REGISTRATION NUMBER: NCT05147623.