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Record W3028767330 · doi:10.1007/s00268-020-05607-x

Bellwether Procedures for Monitoring Subnational Variation of All‐cause Perioperative Mortality in Brazil

2020· article· en· W3028767330 on OpenAlexaff
Paul Truché, Lina Roa, Isabelle Citron, Luke Caddell, J. Batista Costa Neto, Matheus Reis, Eileen M. Moore, Fábio Botelho, Nivaldo Alonso, David Watters

Bibliographic record

VenueWorld Journal of Surgery · 2020
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicinePerioperativeLaparotomyMortality rateGeneral surgerySurgeryEmergency medicine

Abstract

fetched live from OpenAlex

BACKGROUND: All-cause perioperative mortality rate (POMR) is a commonly reported metric to assess surgical quality. Benchmarking POMR remains difficult due to differences in surgical volume and case mix combined with the burden of reporting and leveraging this complex and high-volume data. We seek to determine whether the pooled and individual procedure POMR of each bellwether (cesarean section, laparotomy, management of open fracture) correlate with state-level all-cause POMR in the interest of identifying benchmark procedures that can be used to make standardized regional comparisons of surgical quality. METHODS: The Brazilian National Healthcare Database (DATASUS) was queried to identify unadjusted all-cause POMR for all patient admissions among public hospitals in Brazil in 2018. Bellwether procedures were identified as any procedure involving laparotomy, cesarean section, or treatment of open long bone fracture and then classified as emergent or elective. The pooled POMR of all bellwether procedures as well as for each individual bellwether procedure was compared with the all-cause POMR in each of the 26 states, and one federal district and correlations were calculated. Funnel plots were used to compare surgical volume to perioperative mortality for each bellwether procedure. RESULTS: 4,756,642 surgical procedures were reported to DATASUS in 2018: 237,727 emergent procedures requiring laparotomy, 852,821 emergent cesarean sections, and 210,657 open, long bone fracture repairs. Pooled perioperative mortality for all of the bellwether procedures was correlated with all-procedure POMR among states (r = 0.77, p < 0.001). POMR for emergency procedures (2.4%) correlated with the all-procedure (emergent and elective) POMR (1.6%, r = 0.93, p < .001), while POMR for elective procedures (0.4%) did not (p = .247). POMR for emergency laparotomy (4.4%) correlated with all-procedure POMR (1.6%, r = 0.52, p = .005), as did the POMR for open, long bone fractures (0.8%, r = 0.61, p < .001). POMR for emergency cesarean section (0.05%) did not correlate with all-procedure POMR (p = 0.400). There was a correlation between surgical volume and emergency laparotomy POMR (r = - 0.53, p = .004), but not for emergency cesarean section or open, long bone fractures POMR. CONCLUSION: Procedure-specific POMR for laparotomy and open long bone fracture correlates modestly with all-procedure POMR among Brazilian states which is primarily driven by emergency procedure POMR. Selective reporting of emergency laparotomy and open fracture POMR may be a useful surrogate to guide subnational surgical policy decisions.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.087
GPT teacher head0.356
Teacher spread0.270 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations14
Published2020
Admission routes1
Has abstractyes

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