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Record W2434605785 · doi:10.1111/pan.12939

Preoperative warming and undesired surgical and anesthesia outcomes in pediatric spinal surgery—a retrospective cohort study

2016· article· en· W2434605785 on OpenAlexaff
Matthias Görges, Nicholas West, Wesley Cheung, Guohai Zhou, Firoz Miyanji, Simon D. Whyte

Bibliographic record

VenuePediatric Anesthesia · 2016
Typearticle
Languageen
FieldMedicine
TopicThermal Regulation in Medicine
Canadian institutionsChild and Family Research InstituteUniversity of British Columbia
Fundersnot available
KeywordsMedicinePerioperativePropensity score matchingOdds ratioRetrospective cohort studyAnesthesiaIncidence (geometry)Packed red blood cellsSurgeryBlood transfusionInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Underbody forced air warming is a method commonly used for intraoperative temperature maintenance in children. We previously reported that preoperative forced air warming of children undergoing spinal surgery substantially reduces the incidence and duration of intraoperative hypothermia (<36°C). OBJECTIVE: The aim of this study was to evaluate the effects of preoperative warming before spinal deformity surgery on surgical site infection rate, length of hospitalization, and bleeding (estimated blood loss and incidence of cell salvaged and/or allogeneic packed red blood cell transfusions). METHODS: Demographic, anesthetic, and surgical data of all patients who underwent spinal deformity surgery between December 2009 and December 2012 were obtained by retrospective chart review. Temperature data were abstracted from an existing repository; the incidence and duration of hypothermic episodes were identified. For each outcome, logistic regression models and propensity score analysis were used to estimate the effect of prewarming, adjusted for potential confounders. The issue of missing data was handled by a multiple imputation method. Data from 334 procedures were used in modeling and propensity score stratification. RESULTS: Adjusted odds ratios for the effects of prewarming were 0.47 (95% CI 0.15-1.49) for surgical site infections; 0.89 (95% CI 0.55-1.41) for cell salvaged blood transfusion; 0.43 (95% CI 0.22-0.83) for allogeneic packed red blood cell transfusion; and 1.24 (95% CI 0.77-1.99) for a length of hospitalization >6 days. Adjusted mean decrease in estimated blood loss for prewarming was 72 (95% CI -29 to 173) ml. CONCLUSION: In this study, prewarming was associated with a reduction in allogeneic packed red blood cell transfusion. However, no causal relationship between prewarming and reduced allogeneic blood transfusion should be assumed. Prewarming was not associated with reductions in estimated blood loss, length of hospitalization, or the incidence of surgical site infection.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.280
Teacher spread0.262 · 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 designObservational
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

Citations31
Published2016
Admission routes1
Has abstractyes

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