Standardized follow-up program may reduce emergency room and urgent care visits for patients undergoing radical prostatectomy
Bibliographic record
Abstract
INTRODUCTION: The objective of the current study was to determine the impact of a standardized follow-up program on the morbidity and rates of hospital visits following radical prostatectomy (RP) in a tertiary, non-teaching urologic centre. METHODS: Patients who underwent a RP in 2008 were retrospectively evaluated in this study. Postoperative morbidity for the entire cohort was assessed using the Modified Clavien Scale (MCS). Those patients readmitted to hospital or who visited an urban or rural emergency department (ED) within 90 days of surgery were further evaluated to determine the reason for readmission. RESULTS: At our centre, 321 patients underwent RP in 2008 by 11 surgeons. Of the 321 patients, 77 (24.0%) visited an ED within 90 days, and 14 were readmitted to hospital, with an additional patient readmitted directly (with a total 15 readmissions, 4.7% overall). No patients died within the study period. In 2009 we launched a pilot study wherein 115 RP patients received scheduled and on-demand follow-up care by a dedicated nurse between May and November. We found that 90-day readmission rates among this cohort dropped to 5% and 2.6% for ED visits and hospital readmission, respectively. CONCLUSIONS: At our tertiary non-teaching centre, a significant number of patients presented back to hospital within 90 days following RP. Most of these patients (80.8%) were managed entirely through an outpatient ED, and many visits were for routine postoperative care. Only 18.2% (4.7% of the 321 prostatectomy patients) were readmitted to hospital. These data point to a need for enhanced postoperative support of patients to reduce costly and often unnecessary visits to acute care EDs. This conclusion is supported by our early experience. Limitations include retrospective design, and variability in practice of surgeons in this study.
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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 | 0.005 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".