Source: Scientific reports [Sci Rep] 2025 Jul 16; Vol. 15 (1), pp. 25831. Date of Electronic Publication: 2025 Jul 16.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN:

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Academic Journal

Prevalence of invasive fungal infection in critically Ill patients: a systematic review and meta-analysis.

Authors : Trelles M; SOLCA Unidad Oncológica Chimborazo, Riobamba, Ecuador.; Murillo J

Subjects: Critical Illness* ; Invasive Fungal Infections*/Invasive Fungal Infections*/Invasive Fungal Infections*/epidemiology ; Invasive Fungal Infections*/Invasive Fungal Infections*/Invasive Fungal Infections*/microbiology

Source: BMC infectious diseases [BMC Infect Dis] 2025 Jul 05; Vol. 25 (1), pp. 896. Date of Electronic Publication: 2025 Jul 05.Publisher: BioMed Central Country of Publication: England NLM ID: 100968551 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2334

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Academic Journal

Development and external validation of machine learning models for the early prediction of malnutrition in critically ill patients: a prospective observational study.

Authors : Liu Y; Department of Nursing, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.; Xu Y

Subjects: Critical Illness* ; Machine Learning*/Machine Learning*/Machine Learning*/standards ; Malnutrition*/Malnutrition*/Malnutrition*/diagnosis

Source: BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2025 Jul 03; Vol. 25 (1), pp. 248. Date of Electronic Publication: 2025 Jul 03.Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947

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Academic Journal

The modified HALP score is associated with short-term mortality in critically ill patients with sepsis - A cohort study.

Authors : Lin L; Intensive Care Unit, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou 350001, China.; Huang H

Subjects: Sepsis*/Sepsis*/Sepsis*/mortality ; Sepsis*/Sepsis*/Sepsis*/diagnosis ; Critical Illness*/Critical Illness*/Critical Illness*/mortality

Source: Journal of infection in developing countries [J Infect Dev Ctries] 2025 Jun 30; Vol. 19 (6), pp. 924-933. Date of Electronic Publication: 2025 Jun 30.Publisher: Open Learning on Enteric Pathogens Country of Publication: Italy NLM ID: 101305410 Publication Model: Electronic Cited Medium: Internet

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Academic Journal

U shaped relationship between serum glucose potassium ratio and mortality in critically ill patients with toxic encephalopathy.

Authors : Sun L; Department of Critical Care Medicine, Jingzhou Hospital Affiliated to Yangtze University, No.26 Chuyuan Avenue, Jingzhou District, Jingzhou, 434020, Hubei Province, China.; Shao F

Subjects: Critical Illness*/Critical Illness*/Critical Illness*/mortality ; Blood Glucose*/Blood Glucose*/Blood Glucose*/analysis ; Blood Glucose*/Blood Glucose*/Blood Glucose*/metabolism

Source: Scientific reports [Sci Rep] 2025 Jul 23; Vol. 15 (1), pp. 26795. Date of Electronic Publication: 2025 Jul 23.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN:

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Academic Journal

Early acetaminophen administration and mortality outcomes in critically ill patients with cirrhosis: a retrospective analysis from the MIMIC-IV database.

Authors : Fan XF; Shandong Medical College, No.5460, Second Ring South Road, Jinan, Shandong, 250002, China.; Xu SK

Subjects: Acetaminophen*/Acetaminophen*/Acetaminophen*/adverse effects ; Acetaminophen*/Acetaminophen*/Acetaminophen*/administration & dosage ; Critical Illness*/Critical Illness*/Critical Illness*/mortality

Source: BMC gastroenterology [BMC Gastroenterol] 2025 Jul 16; Vol. 25 (1), pp. 522. Date of Electronic Publication: 2025 Jul 16.Publisher: BioMed Central Country of Publication: England NLM ID: 100968547 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-230X

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Academic Journal

Interpretable prediction of hospital mortality in bleeding critically ill patients based on machine learning and SHAP.

Authors : Ren B; Department of Critical Care Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, P.R. China.; Graduate School of Peking Union Medical College, Beijing, P.R. China.

Subjects: Critical Illness*/Critical Illness*/Critical Illness*/mortality ; Machine Learning* ; Hospital Mortality*

Source: BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2025 Jul 15; Vol. 25 (1), pp. 263. Date of Electronic Publication: 2025 Jul 15.Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947

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Academic Journal

Association between hemoglobin glycation index and mortality in critically ill patients: a retrospective cohort study.

Authors : Pan L; Department of Anesthesiology, Critical Care and Pain Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.; Lu F

Subjects: Critical Illness*/Critical Illness*/Critical Illness*/mortality ; Hospital Mortality* ; Glycated Hemoglobin*/Glycated Hemoglobin*/Glycated Hemoglobin*/analysis

Source: Journal of health, population, and nutrition [J Health Popul Nutr] 2025 Jul 12; Vol. 44 (1), pp. 249. Date of Electronic Publication: 2025 Jul 12.Publisher: BioMed Central Country of Publication: Bangladesh NLM ID: 100959228 Publication Model: Electronic Cited Medium: Internet ISSN:

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Academic Journal

Machine learning-based predictive tools and nomogram for in-hospital mortality in critically ill cancer patients: development and external validation using retrospective cohorts.

Authors : Gu K; Department of Internal Medicine, Shaoxing Maternity and Child Health Care Hospital, Shaoxing, Zhejiang, China.; Lu S

Subjects: Neoplasms*/Neoplasms*/Neoplasms*/mortality ; Machine Learning* ; Nomograms*

Source: BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2025 Jul 04; Vol. 25 (1), pp. 251. Date of Electronic Publication: 2025 Jul 04.Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947

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Academic Journal

SpO2/FiO2 ratio as a better metric for assessment of RBC transfusion effectiveness in non-traumatic critically ill patients with physiologic derangements.

Authors : Choudhary T; Department of Surgery, Duke University School of Medicine, Durham, North Carolina, United States of America.; Department of Anesthesiology, Duke University School of Medicine, Durham, North Carolina, United States of America.

Subjects: Critical Illness*/Critical Illness*/Critical Illness*/therapy ; Erythrocyte Transfusion* ; Oxygen Saturation*

Source: PloS one [PLoS One] 2025 Jul 03; Vol. 20 (7), pp. e0327537. Date of Electronic Publication: 2025 Jul 03 (Print Publication: 2025).Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet

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نتائج البحث

فلترة النتائج

A non-linear association between AST/ALT ratio and 28-day mortality in critically ill elderly: evidence from a multicenter study.

Prevalence of invasive fungal infection in critically Ill patients: a systematic review and meta-analysis.

Development and external validation of machine learning models for the early prediction of malnutrition in critically ill patients: a prospective observational study.

The modified HALP score is associated with short-term mortality in critically ill patients with sepsis - A cohort study.

U shaped relationship between serum glucose potassium ratio and mortality in critically ill patients with toxic encephalopathy.

Early acetaminophen administration and mortality outcomes in critically ill patients with cirrhosis: a retrospective analysis from the MIMIC-IV database.

Interpretable prediction of hospital mortality in bleeding critically ill patients based on machine learning and SHAP.

Association between hemoglobin glycation index and mortality in critically ill patients: a retrospective cohort study.

Machine learning-based predictive tools and nomogram for in-hospital mortality in critically ill cancer patients: development and external validation using retrospective cohorts.

SpO2/FiO2 ratio as a better metric for assessment of RBC transfusion effectiveness in non-traumatic critically ill patients with physiologic derangements.

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