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Advancing critical care recovery:The pivotal role of machine learning in early detection of intensive care unit-acquired weakness

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World Journal of Clinical Cases 2024年第21期12卷 4455-4459页

作者： Georges Khattar elie bou sanayeh Department of Medicine Staten Island University HospitalStaten IslandNY 10305United States

This editorial explores the significant challenge of intensive care unit-acquiredweakness(ICU-AW),a prevalent condition affecting critically ill patients,characterizedby profound muscle weakness and complicating patient *** paradox of modern medical advances,it emphasizes the urgent needfor early identification and intervention to mitigate ICU-AW's ***,the study by Wang et al is showcased for employing a multilayer perceptronneural network model,achieving high accuracy in predicting *** advancement underscores the potential of neural network models inenhancing patient care but also calls for continued research to address limitationsand improve model *** editorial advocates for the developmentand validation of sophisticated predictive tools,aiming for personalized carestrategies to reduce ICU-AW incidence and severity,ultimately improving patientoutcomes in critical care settings.

关键词： Critical illness myopathy Critical illness polyneuropathy Early detection Intensive care unit-acquired weakness Neural network models Patient outcomes Personalized intervention strategies Predictive modeling

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Outpatient insulin use in type 2 diabetes mellitus and acute respiratory distress syndrome outcomes:A retrospective cohort study

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World Journal of Clinical Cases 2024年第17期12卷 2966-2975页

作者： Georges Khattar Samer Asmar Laurence Aoun Fares Saliba Shaza Almardini Saif Abu Baker Catherine Hong Carolla El Chamieh Fadi Haddadin Toni Habib Omar Mourad Zeina Morcos Fatema Arafa Jonathan Mina Khalil El Gharib Mohammad Aldalahmeh Salman Khan elie bou sanayeh Department of Medicine Holy Spirit University of KaslikJounieh 00000Lebanon Department of Internal Medicine Staten Island University HospitalStaten IslandNY 10305United States Public Heath and Biostatistics Independent ResearchBeirut 0000Lebanon Department of Medicine Lebanese UniversityBeirut 00000Lebanon Department of Medicine University of BalamandBeirut 00000Lebanon Department of Medicine Lebanese American UniversityBeirut 00000Lebanon Department of Medicine Northwell Health Staten Island University HospitalNew YorkNY 10305United States

BACKGROUND The impact of type 2 diabetes mellitus(T2DM)on acute respiratory distress syndrome(ARDS)is debatable.T2DM was suspected to reduce the risk and complications of ***,during coronavirus disease 2019(COVID-19),T2DM predisposed patients to ARDS,especially those who were on insulin at *** evaluate the impact of outpatient insulin use in T2DM patients on non-COVID-19 ARDS *** We conducted a retrospective cohort analysis using the Nationwide Inpatient Sample *** patients diagnosed with ARDS were stratified into insulin-dependent diabetes mellitus(DM)(IDDM)and non-insulindependent DM(NIDDM)*** applying exclusion criteria and matching over 20 variables,we compared cohorts for mortality,duration of mechanical ventilation,incidence of acute kidney injury(AKI),length of stay(LOS),hospitalization costs,and other clinical *** Following 1:1 propensity score matching,the analysis included 274 patients in each ***,no statistically significant differences emerged between the IDDM and NIDDM groups in terms of mortality rates(32.8%vs 31.0%,P=0.520),median hospital LOS(10 d,P=0.537),requirement for mechanical ventilation,incidence rates of sepsis,pneumonia or AKI,median total hospitalization costs,or patient disposition upon *** Compared to alternative anti-diabetic medications,outpatient insulin treatment does not appear to exert an independent influence on in-hospital morbidity or mortality in diabetic patients with non-COVID-19 ARDS.

关键词： Acute respiratory distress syndrome Type 2 diabetes mellitus Insulin Length of stay Mortality Endotracheal intubation Acute kidney injury Coronavirus disease 2019

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