Healthcare Costs and Utilization among Patients Hospitalized for Malignant Pleural Effusion
Bibliographic record
Abstract
BACKGROUND: Malignant pleural effusion (MPE) poses a considerable healthcare burden, but little is known about trends in directly attributable hospital utilization. OBJECTIVE: We aimed to study national trends in healthcare utilization and outcomes among hospitalized MPE patients. METHODS: We analyzed adult hospitalizations attributable to MPE using the Healthcare Cost and Utilization Project - National Inpatient Sample (HCUP-NIS) databases from 2004, 2009, and 2014. Cases were included if MPE was coded as the principal admission diagnosis or if unspecified pleural effusion was coded as the principal admission diagnosis in the setting of metastatic cancer. Annual hospitalizations were estimated for the entire US hospital population using discharge weights. Length of stay (LOS), hospital charges, and hospital mortality were also estimated. RESULTS: We analyzed 92,034 hospital discharges spanning a decade (2004-2014). Yearly hospitalizations steadily decreased from 38,865 to 23,965 during this time frame, the mean LOS decreased from 7.7 to 6.3 days, and the adjusted hospital mortality decreased from 7.9 to 4.5% (p = 0.00 for all trend analyses). The number of pleurodesis procedures also decreased over time (p = 0.00). The mean inflation-adjusted charge per hospitalization rose from USD 41,252 to USD 56,951, but fewer hospitalizations drove the total annual charges down from USD 1.51 billion to USD 1.37 billion (p = 0.00 for both analyses). CONCLUSIONS: The burden of hospital-based resource utilization associated with MPE has decreased over time, with a reduction in attributable hospitalizations by one third in the span of 1 decade. Correspondingly, the number of inpatient pleurodesis procedures has decreased during this time frame.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".