Milestones in Surgical Complication Reporting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To provide improved guidance for the consistent application of the Clavien-Dindo classification (CDC) and Comprehensive Complication Index (CCI ® ) in challenging clinical scenarios. BACKGROUND: Standardized outcome reporting is key for the proper assessment of surgical procedures. A recent consensus conference recommended the CDC and the CCI ® for assessing postoperative morbidity. Several challenging scenarios for grading complications still require evidence-based guidance, and the use of the 2 metrics in randomized controlled trials (RCTs) remains unexplored. METHODS: We assessed the use of the CDC and CCI ® as an outcome measure in a systematic literature search. In addition, we asked 163 international surgeons to critically evaluate and independently grade complications in 20 complex clinical scenarios. Finally, a Core Group of 5 experts used this information to develop consistent recommendations. RESULTS: Until July 2023, 1327 RCTs selected the CDC and/or CCI ® to assess morbidity. Annual use was steadily increasing with now over 200 new RCTs per year. However, only a third (n = 335) of published RCTs provided the complete range of CDC grades, including all subgrades. Eighty-nine out of 163 surgeons (response rate: 55%) completed the questionnaire that served as a basis for the recommendations: repetitive interventions that are required to treat one complication, complications followed by further complications, complications occurring before referral, and expected and unrelated complications to the original procedure should all be counted separately and included in the CCI ® . Invasive blank diagnostic interventions should not be considered a complication. CONCLUSIONS: The increasing use of the CDC and CCI ® in RCTs highlights the importance of their standardized application. The current consensus on various difficult scenarios may offer novel guidance for the consistent use of the CDC and CCI ® , aiming to improve complication reporting and better quality control, ultimately benefiting all health care stakeholders and, first and foremost, all patients.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it