SynthesisPloS one2021
Risk prediction models for intensive care unit-acquired weakness in intensive care unit patients: A systematic review.
Synthesis in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Pooled it
- Development and Validation of an Interpretable Machine Learning Model for Predicting ICU-Acquired Weakness in Postoperative Patients.Nursing in critical care · 2026Article
- Early Measurement of Quadriceps Response to Neuromuscular Electrical Stimulation to Identify Future ICU-Acquired Weakness.Critical care medicine · 2026Observational
- Development and validation of machine learning-based risk prediction models for ICU-acquired weakness: a prospective cohort study.European journal of medical research · 2025Article
- Prospective ultrasonographic evaluation of femoral and vastus intermedius muscles as predictors of ICU-acquired weakness in critically ill patients.Journal of ultrasound · 2025Article
- Intensive care unit-acquired weakness: Unveiling significant risk factors and preemptive strategies through machine learning.World journal of clinical cases · 2024Article
- Which factors are associated with acquired weakness in the ICU? An overview of systematic reviews and meta-analyses.Journal of intensive care · 2024Review
- The knowledge, attitude and behavior of ICU nurses regarding ICU-acquired weakness: a cross-sectional survey.BMC nursing · 2024Article
- Significant risk factors for intensive care unit-acquired weakness: A processing strategy based on repeated machine learning.World journal of clinical cases · 2024Article
- Comparison of machine learning models to predict the risk of breast cancer-related lymphedema among breast cancer survivors: a cross-sectional study in China.Frontiers in oncology · 2024Article
- Development and validation of an intensive care unit acquired weakness prediction model: A cohort study.Frontiers in medicine · 2023Article
- Modern Learning from Big Data in Critical Care: Primum Non Nocere.Neurocritical care · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesIntensive care unit-acquired weakness (ICU-AW) commonly occurs among intensive care unit (ICU) patients and seriously affects the survival rate and long-term quality of life for patients. In this systematic review, we synthesized the findings of previous studies in order to analyze predictors of ICU-AW and evaluate the discrimination and validity of ICU-AW risk prediction models for ICU patients.
methodsWe searched seven databases published in English and Chinese language to identify studies regarding ICU-AW risk prediction models. Two reviewers independently screened the literature, evaluated the quality of the included literature, extracted data, and performed a systematic review.
resultsUltimately, 11 studies were considered for this review. For the verification of prediction models, internal verification methods had been used in three studies, and a combination of internal and external verification had been used in one study. The value for the area under the ROC curve for eight models was 0.7-0.923. The predictor most commonly included in the models were age and the administration of corticosteroids. All the models have good applicability, but most of the models are biased due to the lack of blindness, lack of reporting, insufficient sample size, missing data, and lack of performance evaluation and calibration of the models.
conclusionsThe efficacy of most models for the risk prediction of ICU-AW among high-risk groups is good, but there was a certain bias in the development and verification of the models. Thus, ICU medical staff should select existing models based on actual clinical conditions and verify them before applying them in clinical practice. In order to provide a reliable basis for the risk prediction of ICU-AW, it is necessary that large-sample, multi-center studies be conducted in the future, in which ICU-AW risk prediction models are verified.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.