MétaCan
Menu
Back to cohort
Record W1964905091 · doi:10.1097/sla.0b013e318296c732

The Comprehensive Complication Index

2013· article· en· W1964905091 on OpenAlexaff
Ksenija Slankamenac, Rolf Graf, Jeffrey Barkun, Milo A. Puhan, Pierre-Alain Clavien

Bibliographic record

VenueAnnals of Surgery · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineContext (archaeology)ComplicationSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop and validate a comprehensive complication index (CCI) that integrates all events with their respective severity. BACKGROUND: Reporting of surgical complications is inconsistent and often incomplete. Most studies fail to provide information about the severity of complications, or inform only on the most severe event, ignoring events of lesser severity. METHODS: We used an established classification of complications, adopting methods from operation risk index analysis in marketing research to develop a formula that considers all complications that may occur in a patient. The weights of each grade of complication, defined as median reference values, were obtained from 472 participants, who rated 30 different complications. Validation to assess sensitivity to treatment effects and validity of the CCI was performed by 4 different approaches, based on 1299 patients. RESULTS: The CCI is calculated as the sum of all complications that are weighted for their severity (multiplication of the median reference values from patients and physicians). The final formula yields a continuous scale to rank the severity of any combination of complications from 0 to 100 in a single patient. The CCI was highly sensitive in detecting treatment effect differences in the context of a randomized trial (effect size detected by CCI vs conventional standardized morbidity outcomes). It also showed a negative correlation with postoperative health status (r = -0.24, P = 0.002), and high correlation with the results of patient-rated single and multiple complications on conjoint analysis (r = 0.94, P < 0.001). CONCLUSIONS: The CCI summarizes all postoperative complications and is more sensitive than existing morbidity endpoints. It may serve as a standardized and widely applicable primary endpoint in surgical trials and other interventional fields of medicine. The CCI can be readily computed on the basis of tabulated complications according to the Clavien-Dindo classification (available at www.assessurgery.com).

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)0.015
metaresearch head score (Gemma)0.078
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.078
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0120.007
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.217
GPT teacher head0.353
Teacher spread0.136 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations1,729
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of SurgerySame topicCardiac, Anesthesia and Surgical OutcomesFrench-language works237,207