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Record W4403058460 · doi:10.1101/2024.10.01.24314731

Alternative per-protocol estimates: secondary analyses of data from the Balanced randomised controlled trial

2024· preprint· en· W4403058460 on OpenAlexaff
Jim Young, Timothy G. Short, Luzius A. Steiner, Salome Dell‐Kuster

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsMcGill University
FundersHealth Research Council of New ZealandNational Health and Medical Research CouncilMedical Research CouncilNational Institutes of Health
KeywordsProtocol (science)StatisticsMedicineMathematicsAlternative medicine

Abstract

fetched live from OpenAlex

Background The Balanced trial was designed to answer the question of whether anaesthetic depth affects postoperative mortality when a vulnerable patient undergoes major surgery. Patients were recruited between 2012 and 2017 at 73 centres in seven countries. In the intention-to-treat analysis (n=6644), there was no significant difference in one year mortality between patients randomised to surgery under deep (target BIS 35) or light anaesthesia (target BIS 50). However the separation between randomised groups was only 8.4 BIS units and the trial was criticised for being underpowered. Methods In a secondary analysis of this trial's data, we made alternative per-protocol estimates designed to improve the power of the trial. We added an additional covariate - each patient's deviation from target BIS - to the original analysis, statistically recreating the desired separation of 15 BIS units between randomised groups. We used multiple imputation to recover missing BIS values. We also assessed whether a proportional hazards Cox model was appropriate for the analysis of one year mortality. Results Our alternative per-protocol estimates did not differ materially from the original per-protocol estimate. The gain in precision through using all intent-to-treat patients for our per-protocol estimates was offset by the additional variance introduced when modelling missing BIS values. When modelling missing BIS, we found regional differences: in China, the separation between randomised groups was far higher (13.6 BIS units) than in any other region. Estimates and plots assessing proportional hazards suggested increasing late mortality under deep anaesthesia, most notably in China. Conclusion Our hypothesis is that deep anaesthesia in the Balance trial led to higher postoperative delirium, which in turn led to an increase in late mortality. In future trials, patients should be followed for more than a year and cause of death recorded.

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)0.460
metaresearch head score (Gemma)0.651
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.460
Threshold uncertainty score0.666

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4600.651
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0150.027
Bibliometrics0.0060.007
Science and technology studies0.0010.005
Scholarly communication0.0060.009
Open science0.0060.005
Research integrity0.0090.012
Insufficient payload (model declined to judge)0.0190.002

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 head0.518
GPT teacher head0.516
Teacher spread0.002 · 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.

Study designNon-randomized trial
Domainnot available
GenreEmpirical

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

Citations1
Published2024
Admission routes1
Has abstractyes

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