Observational studyBMC anesthesiology2025
Predicting early diagnosis of intensive care unit-acquired weakness in septic patients using critical ultrasound and biological markers.
Observational study in BMC anesthesiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Early prediction of intensive care unit-acquired weakness using quadriceps ultrasound and routine clinical variables: development and temporal validation of a prospective multicentre machine-learning model.Journal of intensive care · 2026Article
- Correction: Predicting early diagnosis of intensive care unit-acquired weakness in septic patients using critical ultrasound and biological markers.BMC anesthesiology · 2026Article
- ICU-Acquired Weakness: An Unsolved Clinical Problem: A Narrative Review.Journal of clinical medicine · 2026Review
- Ultrasound assessment of muscle atrophy and its association with functional outcomes in critically ill patients: a systematic review and meta-analysis.Critical care (London, England) · 2026Review
- Serum Gelsolin Combined with Albumin Might Be a Promising Marker for the Intensive Care Unit-Acquired Weakness-A Pilot Study.Diagnostics (Basel, Switzerland) · 2026Article
- Integrating sarcopenia into ICU-acquired weakness risk stratification: a machine learning-based prediction model for critical care.Frontiers in nutrition · 2026Article
- Development and Validation of a Prediction Model for Intensive Care Unit-Acquired Weakness in Adult Patients with Sepsis: A Prospective, Observational, Single-Center Study.International journal of general medicine · 2026Article
- Machine Learning-Based Classification of ICU-Acquired Neuromuscular Weakness: A Comparative Study in Survivors of Critical Illness.Life (Basel, Switzerland) · 2025Article
- Artificial Intelligence-Assisted Muscular Ultrasonography for Assessing Inflammation and Muscle Mass in Patients at Risk of Malnutrition.Nutrients · 2025Observational
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
Abstract
objectiveEarly diagnosis of intensive care unit-acquired weakness (ICUAW) is crucial for improving the outcomes of critically ill patients. Hence, this study was designed to identify predisposing factors for ICUAW and establish a predictive model for the early diagnosis of ICUAW.
methodsThis prospective observational multicenter study included septic patients from the comprehensive ICUs of West China Hospital of Sichuan University and 10 other hospitals between September and November 2023. Inclusion criteria were as follows: age over 18 years; expected ICU stay longer than 3 days; and voluntary informed consent. Patients were classified into ICUAW (MRC score < 48) and non-ICUAW (MRC score ≥ 48) groups based on muscle strength assessments. The analyzed key predictive factors encompassed demographic data, SOFA and APACHE II scores, inflammatory markers (PCT, IL-6, and CRP), and ultrasound measurements of muscle thickness and cross-sectional area. Logistic regression analysis was conducted for variable selection and nomogram model construction.
resultsA total of 116 septic patients were included, comprising 77 males and 39 females (mean age: 56.94 ± 19.90 years). A nomogram model predicting ICUAW probability was developed, which involved vastus intermedius diameter, rectus femoris cross-sectional area, IL-6, and CRP. The AUC of the composite diagnostic ROC curve was 0.966 (95%CI: 0.936 - 0.996), with a sensitivity of 88% and a specificity of 95.8%.
conclusionsConclusively, a nomogram model is constructed for diagnosing ICUAW in septic patients, which is simple and rapid and allows for visual representation, with excellent diagnostic capability.
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