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Record W1955545978 · doi:10.1111/jgs.13630

Response to Xue and Colleagues

2015· letter· en· W1955545978 on OpenAlexaff
Dallas Seitz, Sudeep S. Gill, Chaim M. Bell, Peter C. Austin, Andrea Gruneir, George Anderson, Paula A. Rochon

Bibliographic record

VenueJournal of the American Geriatrics Society · 2015
Typeletter
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsWomen's College HospitalUniversity of TorontoMount Sinai HospitalInstitute for Clinical Evaluative SciencesQueen's University
Fundersnot available
KeywordsMedicineObservational studyConfoundingHip fractureRandomized controlled trialAdverse effectDementiaClinical trialMEDLINEIntensive care medicinePhysical therapySurgeryInternal medicineOsteoporosisDisease

Abstract

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To the Editor: We thank Dr. Xue et al.1 for their interest in our article and appreciate the opportunity to respond to their questions regarding our study.2 Individuals with dementia are frequently excluded from surgical clinical trials. Observational studies such as ours provide important information for clinicians about the effect of anesthesia on early postoperative outcomes that would otherwise be unavailable. In response to the specific questions that Xue and colleagues raise, we would like first to address the questions regarding blood transfusions and acute kidney injury. Previous meta-analyses of randomized controlled trials have failed to find a significant difference in the risk of red blood cell transfusions or acute kidney injury associated with anesthetic technique for hip fracture surgery.3, 4 Therefore, although both of these adverse outcomes after hip fracture are potentially important, it was decided not to include them in the analysis. Functional status preceding surgery is a known risk factor for poor postoperative outcomes after hip fracture surgery.5, 6 Most administrative databases, including the ones used for the current study, do not contain detailed measures of functional impairment. A previous study that examined the effect of functional impairment measures on predicting hip fracture outcomes found that measures of functional impairment can improve prediction of adverse outcomes after hip fracture surgery but that the magnitude of improved predictive ability is less than in a model that includes only age, sex, and medical comorbidities.5 Therefore, although there may have been confounding due to unmeasured functional impairment in our study, functional impairment is unlikely to have had a significant effect on outcomes observed in our study.2 It was hypothesized that anesthetic technique might lead to some intraoperative complications that Xue and colleagues mentioned (e.g., hypotension, hypoxemia), which would then act as mediators of major postoperative complications such as mortality and intensive care unit admission. Therefore, adjusting for these intraoperative complications, which are in the causal pathway between anesthesia and outcomes, would obscure any associations between anesthetic technique and major early postoperative outcomes, which was the focus of our study.2 Although Xue and colleagues raised several important points regarding our study, the results of the study are valid, and there appears to be little difference in early major postoperative adverse outcomes associated between general anesthesia and regional anesthesia in older adults with dementia undergoing hip fracture surgery.

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)0.006
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.032
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.059
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0050.005
Open science0.0050.003
Research integrity0.0320.039
Insufficient payload (model declined to judge)0.0260.023

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 head0.059
GPT teacher head0.378
Teacher spread0.319 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2015
Admission routes1
Has abstractyes

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