Trends and Factors Influencing Inpatient Prolapse Surgical Costs and Length of Stay in the United States
Bibliographic record
Abstract
OBJECTIVE: This study aimed to assess trends and factors affecting inpatient hospital costs and length of stay (LOS) in surgical treatment of pelvic organ prolapse in the United States. METHODS: A retrospective cross-sectional study along with longitudinal trend analysis from the 2001 to 2011 National Inpatient Sample included subjects who underwent inpatient prolapse repairs. The primary outcomes were inpatient mean cost per admission and LOS. We compared unadjusted differences in primary outcomes for each patient and hospital characteristic using 2011 data with analysis of variance. Multivariable regression estimated proportional change in cost and LOS associated with each characteristic. RESULTS: Unadjusted analysis revealed increased LOS with age of 80 years or older, African American race, uninsured status, lower income, and lower surgical volume hospitals (≤75%) as well as increased costs in the West and public hospitals. On multivariable analyses, African Americans had 1.09 (95% confidence interval [CI], 1.05-1.13; P < 0.001) times longer LOS compared with Caucasians, and the uninsured had 1.15 (95% CI, 1.01-1.30; P = 0.032) times longer LOS compared with those privately insured. Comorbidities associated with 20% increase in LOS and costs were pulmonary circulation disorders, metastatic cancer, weight loss, coagulopathy, and electrolyte/fluid imbalance (P < 0.001). Congestive heart failure and blood loss/deficiency anemia lead to 20% longer LOS (P < 0.001). In 2001-2011, mean LOS declined from 2.42 days (95% CI, 2.37-2.47) to 1.79 days (95% CI, 1.71-1.87) (P < 0.001), whereas mean total cost increased from $6233 (95% CI, $5859-$6607) to $9035 (95% CI, $8632-$9438) (P < 0.001). CONCLUSIONS: Inpatient surgical costs for prolapse increased despite decreasing LOS. Some patient and hospital characteristics are associated with increased inpatient costs and LOS.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".