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Record W4411902048 · doi:10.1186/s12871-025-03187-8

Effects of sedatives on diaphragm activity monitored by ultrasound: a systematic review and meta-analysis

2025· review· en· W4411902048 on OpenAlexaboutno aff
Luhao Wang, Bilin Wei, Zhikun Huang, Huifang Zheng, Bin Guo, ZeNan Chang, Yang Liu, Xiangdong Guan, Xuyu Zhang, Zimeng Liu

Bibliographic record

VenueBMC Anesthesiology · 2025
Typereview
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAnesthesiologyMedicineMeta-analysisPain medicineMedical physicsAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

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, I2 = 92%) (T0 vs. T1), − 1.14 mm (95% CI [-1.90, -0.93], P < 0.00001, I2 = 95%) (T1 vs. T2), and 1.47 mm (95% CI [ 0.90, 2.05], P < 0.00001, I2 = 92%) (T0 vs. T2). For DTF, the corresponding MDs were 0.11 (95% CI [0.09, 0.13], P < 0.00001, I2 = 89%), − 0.06 (95% CI [− 0.08, − 0.04], P < 0.00001, I2 = 88%), and 0.04 (95% CI [0.03, 0.05], P < 0.00001, I2 = 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, I2 = 76%) and 0.13 (95% CI [0.11, 0.14], P < 0.00001, I2 = 75%), respectively, in the propofol group, compared to 1.65 mm (95% CI [1.21, 2.09], P < 0.00001, I2 = 73%) (DM) and 0.09 (95% CI [0.08, 0.10], P < 0.00001, I2 = 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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.896
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0160.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.069
GPT teacher head0.400
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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