Predictors of Activities of Daily Living in Intensive Care Unit Survivors: A          Propensity Score Matching Analysis

Matsumoto, Tsuyoshi; Yoshikawa, Ryo; Harada, Risa; Fujii, Yasumitsu; Adachi, Akimasa; Onishi, Hideaki; Imamura, Ai; Takamiya, Daiki; Makiura, Daisuke; Komaki, Kodai; Ogawa, Masato; Sakai, Yoshitada

doi:10.2490/prm.20230010

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…In our study, ROC curve analysis was used to demonstrate the predictive value of MAC, and TSF as regards the mortality in ICU patients and hand grip strength as regards the mortality in ICU patients. This was in agreement with a recent study by Tsuyoshi Matsumoto, et al [19] who reported that, ROC analysis determined 27cm as the cut-off value of the relative change in the MAC as a predictor of mortality in ICU individuals with a p-value <0.001 sensitivity of 77.8%, a specificity of 55.6%, and the area under the curve (AUC) was 0.681.…”

Section: Aki: Acute Kidney Injurysupporting

confidence: 92%

Impact of Malnutrition in Critically Ill Patients on Intensive Care Unit

Eldehily,

Tawfik,

Elkholy

et al. 2023

The Egyptian Journal of Intensive Care and Emergency Medicine

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Background: Malnutrition is one of the major problems during the stay in the intensive care units (ICUs). Critically ill patients are at high risk of developing malnutrition, associated with worse clinical outcomes. This work aimed to detect the severity of malnutrition in critically ill patients by using the Subjective Global Assessment score (SGA) and its association with the length of ICU stay and mortality. Methods: This prospective cohort observational study was carried out on 50 patients aged >18 years old, both sexes, with clinical criteria of malnutrition, involuntary weight loss, low body mass index, decreased mass of muscles, history of decreased food intake or absorption and inflammation or acute disease or injury with severe inflammation. All patients were subjected to mid-arm circumference (MAC), triceps skin fold (TSF) and hand grip strength . Results: The mean length of stay in ICU was 13.5±11.2 days. 18 patients needed mechanical ventilation (MV) representing 36% of cases with mean ventilation days 10.7±7.1, and the mortality proportion 34%. A statistically substantial correlation existed between mortality, smaller MAC (P = 0.001), and TSF (P = 0.001). In addition, the Handgrip was lower in mortality but didn't reach statistical significance (P = 0.091). A substantial association existed between the advanced grade of SGA (grade C) and mortality (P = 0.001). Conclusions: There was a strong association between mortality in critically ill patients and smaller triceps skin fold, MAC. Severe malnutrition in critically ill patients SGA (grade C) was significantly associated with mortality and the need for MV .

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Section: Aki: Acute Kidney Injurysupporting

confidence: 92%

Impact of Malnutrition in Critically Ill Patients on Intensive Care Unit

Eldehily,

Tawfik,

Elkholy

et al. 2023

The Egyptian Journal of Intensive Care and Emergency Medicine

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Development and validation of early prediction models for new-onset functional impairment in patients after being transferred from the ICU

Xiao,

Zeng,

Chen

et al. 2024

Sci Rep

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A significant number of intensive care unit (ICU) survivors experience new-onset functional impairments that impede their activities of daily living (ADL). Currently, no effective assessment tools are available to identify these high-risk patients. This study aims to develop an interpretable machine learning (ML) model for predicting the onset of functional impairment in critically ill patients. Data for this study were sourced from a comprehensive hospital in China, focusing on adult patients admitted to the ICU from August 2022 to August 2023 without prior functional impairments. A least absolute shrinkage and selection operator (LASSO) model was utilized to select predictors for inclusion in the model. Four models, logistic regression, support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost), were constructed and validated. Model performance was assessed using the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Additionally, the DALEX package was employed to enhance the interpretability of the final models. The study ultimately included 1,380 patients, with 684 (49.6%) exhibiting new-onset functional impairment on the seventh day after leaving the ICU. Among the four models evaluated, the SVM model demonstrated the best performance, with an AUC of 0.909, accuracy of 0.838, sensitivity of 0.902, specificity of 0.772, PPV of 0.802, and NPV of 0.886. ML models are reliable tools for predicting new-onset functional impairments in critically ill patients. Notably, the SVM model emerged as the most effective, enabling early identification of patients at high risk and facilitating the implementation of timely interventions to improve ADL.

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Predictors of Activities of Daily Living in Intensive Care Unit Survivors: A Propensity Score Matching Analysis

Cited by 2 publications

References 23 publications

Impact of Malnutrition in Critically Ill Patients on Intensive Care Unit

Impact of Malnutrition in Critically Ill Patients on Intensive Care Unit

Development and validation of early prediction models for new-onset functional impairment in patients after being transferred from the ICU

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