Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study

Article Health Policy & Services

Development and validation of nonattendance predictive models for scheduled adult outpatient appointments in different medical specialties

Diego Hernan Giunta et al.

Summary: This study aimed to build and validate predictive models for nonattendance in different outpatient appointments. The results showed that the predictive models had adequate accuracy and calibration for each subgroup.

INTERNATIONAL JOURNAL OF HEALTH PLANNING AND MANAGEMENT (2023)

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Review Emergency Medicine

Prediction models for severe manifestations and mortality due to COVID-19: A systematic review

Jamie L. Miller et al.

Summary: This systematic review evaluates the published reports of prediction models for severe COVID-19. Seventy-nine articles were included in the qualitative analysis, with nine studies having prediction models rated as low risk of bias and low concerns for applicability. The most promising and well-validated scores include Clift et al. and Knight et al.

ACADEMIC EMERGENCY MEDICINE (2022)

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Article Virology

Vaccination provides protection from respiratory deterioration and death among hospitalized COVID-19 patients: Differences between vector and mRNA vaccines

Nikolina Busic et al.

Summary: COVID-19 patients who received at least one vaccine dose before the disease onset showed significantly lower 30-day mortality, less need for high flow oxygen therapy and mechanical ventilation compared to unvaccinated patients. Patients receiving vector vaccine types had more favorable survival outcomes compared to unvaccinated patients in the study.

JOURNAL OF MEDICAL VIROLOGY (2022)

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Article Medicine, General & Internal

The role of emergency department triage early warning score (TREWS) and modified early warning score (MEWS) to predict in-hospital mortality in COVID-19 patients

Huseyin Aygun et al.

Summary: MEWS and TREWS scores calculated in the emergency department are effective in predicting 28-day mortality in COVID-19 patients requiring hospitalization. In this study, out of 339 patients, 30 (8.8%) were hospitalized in the intensive care unit, 4 (1.2%) died in the emergency room, and the number of patients who died within 28 days was 57 (16.8%).

IRISH JOURNAL OF MEDICAL SCIENCE (2022)

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Article Biology

Development and evaluation of a machine learning-based in-hospital COVID-19 disease outcome predictor (CODOP): A multicontinental retrospective study

Riku Klen et al.

Summary: Researchers have developed a machine learning-based tool called CODOP, which can predict the clinical outcome of hospitalized COVID-19 patients. The tool uses 12 clinical parameters and achieves high discriminative ability up to 9 days before clinical resolution. Furthermore, CODOP maintains its predictive ability independently of the virus variant and vaccination status, and offers online calculators for different scenarios.

ELIFE (2022)

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Article Multidisciplinary Sciences

Development of lab score system for predicting COVID-19 patient severity: A retrospective analysis

Arnab Sarkar et al.

Summary: The aim of this study was to develop an accurate lab score based on clinical and biological parameters for predicting the severity of COVID-19 in hospitalized patients. Five routine biomarkers and three clinical parameters were identified and used to develop the lab score. The lab score was validated and found to be effective in predicting patient risk and improving survivability.

PLOS ONE (2022)

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Article Public, Environmental & Occupational Health

Effectiveness of Pfizer/BioNTech and Sinopharm COVID-19 vaccines in reducing hospital admissions in prince Hamza hospital, Jordan

Hafez Al-Momani et al.

Summary: The study found that Pfizer and Sinopharm vaccines were effective in reducing COVID-19-related hospitalizations among patients in Jordan, especially among those with comorbidities.

FRONTIERS IN PUBLIC HEALTH (2022)

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Review Public, Environmental & Occupational Health

COVID-19 prediction models: a systematic literature review

Sheikh Muzaffar Shakeel et al.

Summary: This paper presents a systematic literature review on COVID-19 prediction models, offering critical insights for healthcare managers and prediction model developers. Healthcare managers can benefit from choosing the best prediction model output, while developers can identify and improve the shortcomings in their data-driven approaches.

OSONG PUBLIC HEALTH AND RESEARCH PERSPECTIVES (2021)

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Article Infectious Diseases

Early predictors and screening tool developing for severe patients with COVID-19

Le Fang et al.

Summary: A screening tool for severe patients with COVID-19 was developed in a retrospective study, with seven early predictors identified such as chronic kidney disease and age above 60, showing high sensitivity and specificity. The tool can be a good choice for early prediction and alert for severe cases, especially in the condition of overload health service.

BMC INFECTIOUS DISEASES (2021)

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Article Critical Care Medicine

The performance of the National Early Warning Score and National Early Warning Score 2 in hospitalised patients infected by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

Ina Kostakis et al.

Summary: The study showed that NEWS or NEWS2 had good and similar performance in predicting death or intensive care unit admission in patients with COVID-19 and other groups, indicating that amendments to NEWS or NEWS2 may not be necessary for COVID-19 patients.

RESUSCITATION (2021)

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Article Health Care Sciences & Services

Early Warning Scores in Patients with Suspected COVID-19 Infection in Emergency Departments

Francisco Martin-Rodriguez et al.

Summary: This study evaluated different early warning scores to predict mortality in COVID-19 patients, with NEWS2 showing the best predictive power.

JOURNAL OF PERSONALIZED MEDICINE (2021)

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Article Biochemical Research Methods

Stable Iterative Variable Selection

Mehrad Mahmoudian et al.

Summary: This study presents a feature selection method named SIVS, which can reduce the feature space by 41% on average without impacting model performance, and is applicable to both omics and clinical data.

BIOINFORMATICS (2021)

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Article Infectious Diseases

Predicting critical illness on initial diagnosis of COVID-19 based on easily obtained clinical variables: development and validation of the PRIORITY model

Miguel Martinez-Lacalzada et al.

Summary: A predictive model was developed and validated to identify COVID-19 patients at risk of critical outcomes based on clinical history and examination findings. The PRIORITY model, utilizing easily obtained clinical information, showed high discrimination and generalizability in predicting critical outcomes for COVID-19 patients.

CLINICAL MICROBIOLOGY AND INFECTION (2021)

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Editorial Material Critical Care Medicine