Impact of obesity on admissions for COVID-19 with concurrent prostate cancer.
Bibliographic record
Abstract
e17110 Background: Obesity is a significant risk factor for prostate cancer and its associated mortality. Recent studies have shown that a five-point rise in BMI can lead to a 10% rise in death among these patients. Since the pandemic of COVID-19, obesity has also been associated with poorer outcomes among the general population. As there is a paucity of data on the impact of obesity among prostate cancer admissions with COVID-19, we conducted a retrospective study to provide a novel perspective. Methods: Patients with a diagnosis of COVID-19 were used for our study from the 2020 National Inpatient Sample. We included cases between April 2020 to December 2020. Hospitalization records with prostate cancer and obesity were also identified via their respective ICD-10 codes. The differences in outcomes, including non-invasive ventilation, use of mechanical ventilation, pulmonary embolism, events of Acute Kidney Injury(AKI) and in-hospital mortality were compared between obese and non-obese patients with a history of prostate cancer, admitted for COVID-19. We also compared the mean lengths of stay, mean ages between the two groups, and their overall mean hospitalization charge. Results: A total of 7165 prostate cancer patients were hospitalized with COVID-19 between 1st April 2020 to 31st December 2020 in the United States. 1065 (14.9%) were obese. Prostate cancer patients admitted with COVID-19 who were obese were also younger (mean age 71.75 years) than those who were not obese (77.50 years) and recorded a more extended stay (mean LOS 9.68 days vs. 7.93 days). Obese patients also recorded a higher adjusted odds ratio for needing non-invasive ventilation (aOR 1.736, 95% CI 1.331-2.263, p < 0.01), mechanical ventilation (aOR 1.894, 95% CI 1.533-2.340, p < 0.01), events of acute kidney injury (aOR 1.328, 95% CI 1.137-1.550, p < 0.01), and in-hospital mortality (aOR 1.246, 95% CI 1.033-1.502, p = 0.021). While more patients with obesity developed pulmonary embolism (4.2% vs. 3.6%) after adjusting for confounders, the result was not statistically significant (aOR 1.258, 95% CI 0.879-1.800, p = 0.209). Obese patients also recorded a higher mean hospital charge compared to non-obese cases ($117200.50 vs. $81028.15). Conclusions: Obesity in prostate cancer patients admitted with COVID-19 is linked with several poor outcomes and complications, including AKI, mechanical ventilation, non-invasive ventilation, and mortality. Thus, physicians must identify such cases as higher-risk and encourage closer monitoring during their hospitalizations.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".