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Mechanical versus manual chest compressions for cardiac arrest

2011· reference-entry· en· W3121604495 on OpenAlexaff
Steven C. Brooks, Blair L. Bigham, Laurie J. Morrison

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2011
Typereference-entry
Languageen
Field
Topic
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineCardiopulmonary resuscitationCochrane LibraryRelative riskConfidence intervalMEDLINEMeta-analysisRandomized controlled trialEmergency medicineResuscitationInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Mechanical chest compression devices have been proposed to improve the effectiveness of cardiopulmonary resuscitation (CPR). OBJECTIVES: To assess the effectiveness of mechanical chest compressions versus standard manual chest compressions with respect to neurologically intact survival in patients who suffer cardiac arrest. SEARCH STRATEGY: We searched the Cochrane Central Register of Controlled Studies (CENTRAL) on The Cochrane Library, MEDLINE, EMBASE, Science Citation abstracts, Biotechnology and Bioengineering abstracts and Clinicaltrials.gov in November 2009. No language restrictions were applied. Experts in the field of mechanical chest compression devices and manufacturers were contacted. SELECTION CRITERIA: We included randomised controlled trials (RCTs), cluster RCTs and quasi-randomised studies comparing mechanical chest compressions to manual chest compressions during CPR for patients with atraumatic cardiac arrest. DATA COLLECTION AND ANALYSIS: Two authors (SCB and LJM) abstracted data independently. Disagreement between reviewers was resolved by consensus and a third author (BB) if consensus could not be reached. The methodologies of selected studies were evaluated for risk of bias by a single author (SCB). The primary outcome was survival to hospital discharge with good neurologic outcome. We used the DerSimonian & Laird method (random-effects model) to provide a pooled estimate for relative risk with 95% confidence intervals. MAIN RESULTS: Four trials, including data from 868 patients, were included in the review. The overall quality of included studies was poor and significant clinical heterogeneity was observed. Only one study (N = 767) reported survival to hospital discharge with good neurologic function (as defined as a Cerebral Performance Category score of 1 or 2), demonstrating reduced survival with mechanical chest compressions when compared with manual chest compressions (RR 0.41 (95% CI 0.21- 0.79). Data from other studies included in this review were used to calculate relative risks for having a return of spontaneous circulation (2 studies, N = 51, pooled RR 2.81, 95% CI 0.96 to 8.22) and survival to hospital admission (1 study, N = 17, RR 4.13, 95% CI 0.19 to 88.71) in patients who received mechanical chest compressions versus those who received manual chest compressions. AUTHORS' CONCLUSIONS: There is insufficient evidence from human RCTs to conclude that mechanical chest compressions during cardiopulmonary resuscitation for cardiac arrest is associated with benefit or harm. Widespread use of mechanical devices for chest compressions during cardiac is not supported by this review. More RCTs that measure and account for CPR process in both arms are needed to clarify the potential benefit from this intervention.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.194
GPT teacher head0.388
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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".

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Citations54
Published2011
Admission routes1
Has abstractyes

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