Leapfrog volume thresholds and perioperative complications after radical prostatectomy
Bibliographic record
Abstract
BACKGROUND: The authors explored the effect of Leapfrog volume thresholds (LVTs) on 5 short-term radical prostatectomy (RP) outcomes. METHODS: Within the Health Care Utilization Project Nationwide Inpatient Sample (NIS), the authors focused on RPs performed within the 7 most contemporary years (2001-2007). They tested rates of in-hospital mortality, intraoperative complications, postoperative complications, and blood transfusions as well as the mean length of stay (LOS), stratified according to the number of LVTs that were met. Multivariable regression analyses were adjusted further for potential confounders. RESULTS: Overall, 36.2%, 17.3%, 14.9%, 15.7%, 12.9%, and 3% of RPs were performed at institutions that reached 0 LVT, 1 LVT, 2 LVTs, 3 LVTs, 4 LVTs, and 5 LVTs, respectively. Relative to patients who underwent RP at institutions that reached 0 LVTs, patients who underwent RP at institutions that reached 5 LVTs had fewer comorbidities, were younger, were more likely to hold private insurance, and were more likely to undergo concomitant pelvic lymphadenectomy (all P < .001). In multivariable analyses adjusted for hospital volume (HV), age, race, year of surgery, Charlson Comorbidity Index, hospital region and location, pelvic lymphadenectomy, and insurance status, LVT status was related inversely to LOS and the likelihood of receiving blood transfusions (both P < .001). CONCLUSIONS: The current results indicated that LVTs can provide a highly accurate prediction of the probability of 2 important, detrimental, short-term outcomes after RP, even after accounting for HV. The benefit at institutions that meet LVTs may exceed that at other institutions when short-term RP outcomes are considered. This observation should be taken into consideration when treatment decisions are made, especially because most RPs were performed at institutions that did not meet any LVTs.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".