Hospitalization Outcomes and Comorbidities of Bulimia Nervosa: A Nationwide Inpatient Study
Bibliographic record
Abstract
Objective To evaluate inpatient outcomes and the prevalence of psychiatric and medical comorbidities in bulimia nervosa. Methods We used the Nationwide Inpatient Sample (NIS) from the Healthcare Cost and Utilization Project (HCUP). We identified bulimia nervosa as the primary diagnosis and medical and psychiatric comorbidities using ICD-9-CM codes. The differences in comorbidities were quantified using the Chi-square (χ2) test, and a multinomial logistic regression model was used to quantify associations among comorbidities (odds ratio (OR)). Results The sample consisted of 3,319 inpatient admissions with bulimia nervosa between 2010-2014. Overall, 88% patients were younger than 40 years of age (p < 0.001). Bulimia nervosa was seen in a higher proportion of females (92.5%). The mean inpatient stay was 9.15 days and had a variable trend, whereas inpatient charges have been increasing (p < 0.001), averaging $34,398 (USD). The odds of having a longer hospitalization > 7 days (median) was seen in patients with comorbid fluid/electrolyte disorders (OR = 1.816; p < 0.001) and comorbid depression (OR = 1.745; p < 0.001). The most prevalent psychiatric comorbidities were psychosis (52.4%), followed by depression (23.5%). Females had three times higher odds of comorbid diabetes (OR = 3.374; p < 0.001), hypertension (OR = 2.548; p-value < 0.001), comorbid depression (OR = 1.670; p = 0.002), and drug abuse (OR = 2.008; p < 0.001). Conclusion Our study established psycho-socio-demographic characteristics, hospitalization outcomes, and comorbidities of bulimia nervosa patients. We believe that medical and psychiatric comorbidities of bulimia nervosa should be carefully investigated by clinicians as they can further complicate the management of bulimia nervosa and result in adverse inpatient outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".