Demographic factors, outcomes, and patient access to transsphenoidal surgery for Cushing's disease: analysis of the Nationwide Inpatient Sample from 2002 to 2010
Bibliographic record
Abstract
OBJECT Cushing's disease (CD) is a potentially lethal neuroendocrinopathy that often requires specialized multidisciplinary treatment to achieve optimized outcomes. The authors analyzed data pertaining to patient, hospital, and admission characteristics as they relate to outcomes following transsphenoidal surgery (TSS) in more than 5500 patients treated for CD. METHODS The Nationwide Inpatient Sample (NIS) database was used to identify all patients admitted with CD between 2002 and 2010. A variety of patient demographic data (e.g., age, sex, race, payer status), hospital variables (e.g., bed size, TSS volume, teaching status), and admission subtypes (e.g., elective, emergency) were tested for association with postoperative endocrine and nonendocrine complications, mortality, nonroutine discharge, length of stay, and total hospital charges. All tests were performed using univariate analysis followed by multivariate analysis, with 4 models tested via an additive methodology. Statistical significance was defined as a p value < 0.05 for all analyses. RESULTS From 2002 to 2010, 5527 individuals who were admitted for TSS (54 biopsies, 4254 partial resections, and 1271 total resections; 5579 total TSS procedures) were identified as patients with CD. There were 25 deaths following TSS, resulting in a mortality incidence rate of 0.45%. Nonendocrine and endocrine complications were reported in 22.4% and 11.1% of patients, respectively. The most common nonendocrine complications were postoperative neurological complications (6.98%) and mechanical ventilation (1.71%). Diabetes insipidus was reported in 14.79% of patients. In a multivariate analysis, patients with Medicare were at increased risk of nonendocrine complications (relative risk [RR] 2.24, 95% CI 1.15-4.38; p = 0.02). Patients with Medicare had increased risk of higher charges (RR 1.89, 95% CI 1.04-3.45; p = 0.04), as did those with Medicaid (RR 1.93, 95% CI 1.10-3.41; p = 0.02). Additionally, as compared with white patients, Hispanic patients had an increased rate of higher charges (RR 1.86, 95% CI 1.12-3.10; p = 0.02). Patients whose age was less than 40 years had a higher risk of developing diabetes insipidus (RR 1.39, 95% CI 1.0-1.93; p = 0.05). When compared with those in northeast hospitals, patients in western hospitals were more likely to experience nonendocrine complications (RR 1.85, 95% CI 0.99-3.46; p = 0.05) and endocrine complications (RR 1.98, 95% CI 1.28-3.07; p < 0.01). Patients treated in teaching hospitals were at significantly lower risk of incurring higher hospital charges (RR 0.49, 95% CI 0.28-0.85; p = 0.01). Patients with emergency admissions had a risk of higher hospital charges (RR 3.06, 95% CI 1.26-7.46; p = 0.01) and nonendocrine complications (RR 3.18, 95% CI 1.22-8.28; p = 0.02). CONCLUSIONS This review of NIS data in more than 5500 patients treated surgically for CD pointed to major outcome disparities predicted primarily by payer status, admission type, and hospital region. Identification and targeting of such barriers to quality health care in patients with CD may help optimize patient outcomes on a national level and present an opportunity to improve access of high-risk patient subgroups to specialty centers of excellence.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".