Hyperlactacidemia as a risk factor for intensive care unit-acquired weakness in critically ill adult patients

Growth differentiation factor-15 as a biomarker for intensive care unit-acquired weakness: a meta-analysis

Background

Growth differentiation factor-15 (GDF-15) may be a potential biomarker for intensive care unit-acquired weakness (ICU-AW). In this study, we aimed to quantitative analysis the levels of GDF-15 in patients with ICU-AW and in non-ICU-AW, and then to determine its potential diagnostic utility.

Methods

Two researchers separately conducted a systematic search of the relevant studies up to May 2023 in various literature databases (PubMed, Cochrane, Web of Science, Embase, and CINAHL). Studies were selected according to the inclusion and exclusion criteria, and quality evaluation of the included studies was conducted by using QUADAS-2 provided by Review Manager 5.3. The software packages Meta Disc (C1.4) and Stata17.0 were used for the meta-analysis. The data were combined with fixed-effects model, and the summary receiver operating characteristic curve was drawn to evaluate the overall diagnostic accuracy of GDF-15.

Results

We identified 6 eligible studies comprising 401 patients with ICU-AW. The sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) for the discriminative performance of GDF-15 as a diagnostic biomarker were 0.82 (95% confidence interval (CI):0.78-0.86), 0.83 (95% CI: 0.61-0.88), 21.39 (95% CI: 13.36-34.24), and 0.88 (95% CI: 0.85-0.91), respectively.

Conclusion

GDF-15 is a candidate biomarker in diagnosing of ICU-AW from non-ICU-AW.

Risk factors for acquired weakness in intensive care unit patients: An umbrella review

OBJECTIVE

This umbrella review aims to summarize and synthesize the evidence on risk factors related to intensive care unit-acquired weakness in systematic reviews to create prevention strategies and intervention measures for intensive care unit-acquired weakness.

METHODOLOGY

Eight databases were searched systematically from inception to 1st November 2023. Two researchers independently screened and extracted data based on predefined inclusion and exclusion criteria. The methodological quality, risk of bias and certainty of evidence of reviews included were evaluated using version 2 of the Measurement Tool for Evaluation System Review (AMSTAR-2) and the Risk of Bias in Systematic Reviews (ROBIS), and the Grading of Recommendations Assessment, Development and Evaluation(GRADE) respectively.

RESULTS

This review included 10 systematic reviews, reporting a total of 42 factors and 22 associations with meta-analysis. Overall, among these associations, the methodological and evidence quality of the majority ofstudies was rated as low or extremely low. Most systematic reviews and/or meta-analyses exhibited a high risk of bias.

CONCLUSION

This umbrella review comprehensively summarized the risk factors related to intensive care unit-acquired weakness and evaluated the methodological quality, risk of bias, and evidence quality of reviews included. Future studies with high-quality research such as cohort studies are needed, to better update and synthesize the risk factors of intensive care unit-acquired weakness.

IMPLICATIONS FOR CLINICAL PRACTICE

Inconsistent or even contradictory findings exist among multiple systematic reviews regarding intensive care unit-acquired weakness. The present study offers a comprehensive and readily comprehensible overview of the risk factors linked to intensive care unit-acquired weakness, which is conducive to develop assessment tools for the condition and identify intervention targets.

Predictive modeling of ICU-AW inflammatory factors based on machine learning

BACKGROUND

ICU-acquired weakness (ICU-AW) is a common complication among ICU patients. We used machine learning techniques to construct an ICU-AW inflammatory factor prediction model to predict the risk of disease development and reduce the incidence of ICU-AW.

METHODS

The least absolute shrinkage and selection operator (LASSO) technique was used to screen key variables related to ICU-AW. Eleven indicators, such as the presence of sepsis, glucocorticoids (GC), neuromuscular blocking agents (NBAs), length of ICU stay, Acute Physiology and Chronic Health Evaluation (APACHE II) II score, and the levels of albumin (ALB), lactate (LAC), glucose (GLU), interleukin-1β (IL-1β), interleukin-6 (IL-6), and interleukin-10 (IL-10), were used as variables to establish the prediction model. We divided the data into a dataset that included inflammatory factors and a dataset that excluded inflammatory factors. Specifically, 70% of the participants in both datasets were used as the training set, and 30% of the participants were used as the test set. Three machine learning methods, logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB), were used in the 70% participant training set to construct six different models, which were validated and evaluated in the remaining 30% of the participants as the test set. The optimal model was visualized for prediction using nomograms.

RESULTS

The logistic regression model including the inflammatory factors demonstrated excellent performance on the test set, with an area under the curve (AUC) of 82.1% and the best calibration curve fit, outperforming the other five models. The optimal model is represented visually in the nomograms.

CONCLUSION

This study used easily accessible clinical characteristics and laboratory data that can aid in early clinical recognition of ICU-AW. The inflammatory factors IL-1β, IL-6, and IL-10 have high value for predicting ICU-AW.

TRIAL REGISTRATION

The trial was registered at the Chinese Clinical Trial Registry with the registration number ChiCTR2300077968.

Which factors are associated with acquired weakness in the ICU? An overview of systematic reviews and meta-analyses

RATIONALE

Intensive care unit-acquired weakness (ICUAW) is common in critically ill patients, characterized by muscle weakness and physical function loss. Determining risk factors for ICUAW poses challenges due to variations in assessment methods and limited generalizability of results from specific populations, the existing literature on these risk factors lacks a clear and comprehensive synthesis.

OBJECTIVE

This overview aimed to synthesize risk factors for ICUAW, categorizing its modifiable and nonmodifiable factors.

METHODS

An overview of systematic reviews was conducted. Six relevant databases were searched for systematic reviews. Two pairs of reviewers selected reviews following predefined criteria, where bias was evaluated. Results were qualitatively summarized and an overlap analysis was performed for meta-analyses.

RESULTS

Eighteen systematic reviews were included, comprising 24 risk factors for ICUAW. Meta-analyses were performed for 15 factors, while remaining reviews provided qualitative syntheses. Twelve reviews had low risk of bias, 4 reviews were unclear, and 2 reviews exhibited high risk of bias. The extent of overlap ranged from 0 to 23% for the corrected covered area index. Nonmodifiable factors, including advanced age, female gender, and multiple organ failure, were consistently associated with ICUAW. Modifiable factors, including neuromuscular blocking agents, hyperglycemia, and corticosteroids, yielded conflicting results. Aminoglycosides, renal replacement therapy, and norepinephrine were associated with ICUAW but with high heterogeneity.

CONCLUSIONS

Multiple risk factors associated with ICUAW were identified, warranting consideration in prevention and treatment strategies. Some risk factors have produced conflicting results, and several remain underexplored, emphasizing the ongoing need for personalized studies encompassing all potential contributors to ICUAW development.

A meta-analysis of the association between vasopressor use and intensive care unit-acquired weakness

OBJECTIVE

This study aims to clarify the uncertain association between vasopressor administration and the development of intensive care unit-acquired weakness (ICUAW) in critically ill adult patients.

METHODS

We conducted a comprehensive search of PubMed, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials up to October 10, 2023. Titles and abstracts were independently screened by two authors, who then reviewed full texts and extracted relevant data from the studies that met the inclusion criteria. This review included prospective and retrospective cohort studies that explored the relationship between vasopressor use and ICUAW utilizing univariate or multivariate analysis in adult ICU patients.

RESULTS

A total of 15 studies were included in our review, collectively indicating a statistically significant association between the use of vasopressors and the occurrence of ICUAW (odds ratio [OR], 3.43; 95% confidence intervals [CI], 1.95-6.04), including studies utilizing multivariate analysis (OR, 3.43; 95% CI, 1.76-6.70). Specifically, the use of noradrenaline was significantly associated with ICUAW (OR, 4.42; 95% CI, 1.69-11.56). Subgroup and sensitivity analyses further underscored the significant relationship between vasopressor use and ICUAW, particularly in studies focusing on patients with clinical weakness, varying study designs, different sample sizes, and relatively low risk of bias. However, this association was not observed in studies limited to patients with abnormal electrophysiology.

CONCLUSIONS

Our review underscores a significant link between the use of vasopressors and the development of ICUAW in critically ill adult patients. This finding helps better identify patients at higher risk of ICUAW and suggests considering targeted therapies to mitigate this risk.

A Predictive Nomogram for Intensive Care-Acquired Weakness after Cardiopulmonary Bypass

PURPOSE

Intensive care unit-acquired weakness (ICUAW) affects patient prognosis after cardiopulmonary bypass (CPB) surgery, but its risk factors remain unclear. We investigated these risk factors and developed a nomogram for predicting ICUAW after CPB.

METHODS

Baseline characteristics, preoperative laboratory data, and intra- and postoperative variables of 473 patients after CPB were determined in this prospective cohort study. Lower limb muscles on bedside ultrasound images were compared 1 day before and 7 days after CPB. Risk factors were assessed using logistic regression models.

RESULTS

Approximately 50.95% of the patients developed ICUAW after CPB. The body mass index (BMI), New York Heart Association (NYHA) class, lactate, albumin, aortic clamping time, operation time, and acute physiological and chronic health evaluation II were determined as independent risk factors. The average absolute error of coincidence was 0.019; the area under the curve, sensitivity, and specificity were 0.811, 0.727, and 0.733, respectively, for the predictive nomogram.

CONCLUSION

A high BMI, poor NYHA class, preoperative high serum lactate, low serum albumin, long surgical duration, aortic clamping, and high acute physiological and chronic health evaluation II score are risk factors for ICUAW after CPB. This robust and easy-to-use nomogram was developed for clinical decision-making.

Construction and evaluation of acquired weakness nomogram model in patients with mechanical ventilation in intensive care unit

Objective

The incidence of intensive care unit acquired weakness (ICU-AW) has shown an increasing trend with still a lack of effective treatment options. The early assessment of the risk of developing ICU-AW can provide patients with targeted interventions. This study aimed to determine the independent risk factors of ICU-AW in patients receiving mechanical ventilation (MV) and develop a nomogram and verify its predictive efficacy.

Methods

This observational study included patients receiving MV therapy in the ICU of our hospital between January 2020 and January 2023. They were divided into the ICU-AW and non-ICU-AW groups. The training cohort (n = 264) and the validation cohort (n = 143) were constructed. Multivariate logistic regression analyses were used to select the risk factors, and a nomogram model was established. Calibration, receiver operating characteristic (ROC), and decision curves were used to evaluate the effectiveness of the model.

Results

The MV duration (OR = 1.24, 95%CI[1.11, 1.38]), APACHE II score (OR = 1.34, 95%CI[1.20, 1.50]), SOFA score (OR = 1.36, 95%CI[1.21, 1.53]), age (OR = 1.05, 95%CI[1.00, 1.10]), nerve blockers (OR = 3.26, 95%CI[1.34, 7.92]), and diabetes mellitus (OR = 3.12, 95%CI[1.10, 8.87]) were independent risk factors for ICU-AW. The nomogram had good predictive efficacy for both the training (area under the curve (AUC) = 0.950, 95%CI [0.93, 0.97]) and validation cohorts (AUC = 0.823, 95%CI [0.75, 0.89]).

Conclusion

The MV duration, APACHE II, SOFA, age, use of nerve blockers, and diabetes mellitus are independent risk factors for ICU-AW. The nomogram model based on them had good predictive efficacy and may be clinically useful.

SEPSIS LEADS TO IMPAIRED MITOCHONDRIAL CALCIUM UPTAKE AND SKELETAL MUSCLE WEAKNESS BY REDUCING THE MICU1:MCU PROTEIN RATIO

ABSTRACT

Purpose: Intensive care unit-acquired weakness (ICUAW) is a severe neuromuscular complication that frequently occurs in patients with sepsis. The precise molecular pathophysiology of mitochondrial calcium uptake 1 (MICU1) and mitochondrial calcium uniporter (MCU) in ICUAW has not been fully elucidated. Here, we speculate that ICUAW is associated with MICU1:MCU protein ratio-mediated mitochondrial calcium ([Ca 2+ ] m ) uptake dysfunction. Methods: Cecal ligation and perforation (CLP) was performed on C57BL/6J mice to induce sepsis. Sham-operated animals were used as controls. Lipopolysaccharide (LPS) (5 μg/mL) was used to induce inflammation in differentiated C2C12 myoblasts. Compound muscle action potential (CMAP) was detected using a biological signal acquisition system. Grip strength was measured using a grip-strength meter. Skeletal muscle inflammatory factors were detected using ELISA kits. The cross-sectional area (CSA) of the tibialis anterior (TA) muscle was detected by hematoxylin and eosin staining. Cytosolic calcium ([Ca 2+ ] c ) levels were measured using Fluo-4 AM. Adeno-associated virus (AAV) was injected into TA muscles for 4 weeks to overexpress MICU1 prophylactically. A lentivirus was used to infect C2C12 cells to increase MICU1 expression prophylactically. Findings: The results suggest that sepsis induces [Ca 2+ ] m uptake disorder by reducing the MICU1:MCU protein ratio, resulting in skeletal muscle weakness and muscle fiber atrophy. However, MICU1 prophylactic overexpression reversed these effects by increasing the MICU1:MCU protein ratio. Conclusions: ICUAW is associated with impaired [Ca 2+ ] m uptake caused by a decreased MICU1:MCU protein ratio. MICU1 overexpression improves sepsis-induced skeletal muscle weakness and atrophy by ameliorating the [Ca 2+ ] m uptake disorder.