Effects of sedatives on diaphragm activity monitored by ultrasound: a systematic review and meta-analysis
Bibliographic record
Abstract
Current research lacks comprehensive evaluations on the inhibitory effects of sedatives on diaphragm activity under ultrasound monitoring. This meta-analysis aims to launch this problem by systematically analyzing the available evidence. The EMBASE, PubMed, and Web of Science databases were searched. Original studies that explored the effects of sedative agents on human diaphragm activity via ultrasound were eligible. The quality of the included studies was evaluated using the Revised Cochrane Risk-of-Bias tool for randomized trials (RoB 2) and the Newcastle–Ottawa Scale (NOS). The pooled assessment encompassed alterations in diaphragmatic motion (DM) and diaphragmatic thickening fraction (DTF). Mean difference (MD) with 95% confidence intervals (CI) were calculated. The trial sequential analysis (TSA) was performed to calculate the required information size (RIS). The strength of evidence was assessed using the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) Pro Guideline Development Tool (GDT). Subgroup analysis and meta-regression was conducted to explore heterogeneity. Sensitivity analysis was used to evaluate the robustness for the meta-analysis results. Six randomized controlled trials and four prospective observational studies involving 727 patients were ultimately included. In the pooled analysis, DM and DTF were measured at three time points: during sedation (T1), upon awakening (T2), and at baseline (T0). Comparisons were conducted between the values at each time point, revealing mean differences (MDs) for DM of 2.54 mm (95% CI [2.01, 3.08], P < 0.00001, I 2 = 92%) (T0 vs. T1), − 1.14 mm (95% CI [-1.90, -0.93], P < 0.00001, I 2 = 95%) (T1 vs. T2), and 1.47 mm (95% CI [ 0.90, 2.05], P < 0.00001, I 2 = 92%) (T0 vs. T2). For DTF, the corresponding MDs were 0.11 (95% CI [0.09, 0.13], P < 0.00001, I 2 = 89%), − 0.06 (95% CI [− 0.08, − 0.04], P < 0.00001, I 2 = 88%), and 0.04 (95% CI [0.03, 0.05], P < 0.00001, I 2 = 71%). Subgroup analyses further demonstrated that the MDs at T0 vs. T1 for DM and DTF were 3.62 mm (95% CI [3.15, 4.10], P < 0.00001, I 2 = 76%) and 0.13 (95% CI [0.11, 0.14], P < 0.00001, I 2 = 75%), respectively, in the propofol group, compared to 1.65 mm (95% CI [1.21, 2.09], P < 0.00001, I 2 = 73%) (DM) and 0.09 (95% CI [0.08, 0.10], P < 0.00001, I 2 = 0%) (DTF) in the group receiving propofol in combination with other sedatives. Sensitivity analysis suggested high robustness of the analysis for DTF. The TSA indicated that the sample size was sufficient. And GDT showed a low but important strength of this review. This meta-analysis reveals that sedatives can inhibit diaphragm activity, with this negative impact persisting post-awakening. Propofol alone achieves a more pronounced reduction in diaphragm activity than when combined with other sedatives. However, significant heterogeneity remains across studies due to data limitations and low evidence certainty. Further research is crucial to establish evidence-based recommendations for optimal diaphragm-protective sedation strategies. The protocol was registered at the PROSPERO international prospective register of systematic reviews (CRD42024514504).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.044 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".