Impact of homelessness on outcomes among pancreatic cancer hospitalization: Insight from the 2016-2020 National Inpatient Sample.
Bibliographic record
Abstract
e16264 Background: Homelessness is a major socio-economic issue in the United States, affecting an estimated 171 per 100,000 persons in certain states. While pancreatic cancer (PC) tends to have a poor prognosis, the disease requires an early diagnosis, proper care, and follow-ups. As there is a paucity of data highlighting differences in patient characteristics and outcomes of homeless patients with PC, a retrospective study was conducted via a national database. Methods: We used data from the 2016-2020 National Inpatient Sample (NIS), the most extensive hospital database, to identify patients with a diagnosis of pancreatic cancer. Patients with a status of “homeless” were located via the ICD-10 code “Z590”, per suggestions from HCUP and past studies. Several differences in patient characteristics were explored between homeless cases of PC and non-homeless cases via Pearson’s Chi-Square tests. Finally, the adjusted odds ratio (aOR) and 95% Confidence intervals (CI) of various outcomes such as mortality, pulmonary embolism, septicemia, and hepatic failure were calculated via multivariable logistic regression models. Results: Our study identified 544855 pancreatic cancer cases, including 1380 patients classified as homeless (0.3%). 81.5% of homeless patients were males (vs. 52.1%), and 24.6% were admitted on weekends (vs. 20.6%). Moreover, Medicaid was the prime insurer among homeless patients (47.6% vs. 8.6%) with a higher mean hospital charge ($86796 vs. $70610). Racial differences were also observed as 51.9% of homeless cases were Whites (vs. 71.2%), while 31.6% (vs. 13.8%) were Blacks, and 11.3% (vs. 8.2%) were Hispanics. A higher proportion of homeless cases had palliative care utilization (27.9% vs. 19.1%), a Do-Not-Resuscitate (DNR) order (25.7% vs. 23.1%), and required pancreatic and proximal biliary dilation/stenting (4.0% vs. 2.2%). Homeless patients admitted with pancreatic cancer also expressed higher odds of in-hospital mortality (8.7% vs. 7.4%, aOR 1.625, 95% CI 1.280-2.064, p<0.01). No statistical significance was found for events of pulmonary embolism (aOR 1.231, p=0.160), septicemia (aOR 1.044, p=0.674), and hepatic failure (aOR 0.892, p=0.549). Conclusions: Homeless patients with PC were linked with higher in-patient mortality. Various racial and socio-economic differences were also observed. Several efforts to ameliorate access to care among homeless patients and an early diagnosis may help improve the 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 | 0.004 |
| 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".