Novel Prognostic Predictor for Primary Pulmonary Hypertension: Focus on Blood Urea Nitrogen
Bibliographic record
Abstract
Background: Primary pulmonary hypertension (PPH) is a life-threatening disease associated with increased mortality. The urea cycle pathway plays a major role in PPH severity and treatment response. Little is known about the association of the blood urea nitrogen (BUN) and PPH prognosis. Methods: Clinical data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Adult patients (≥18 years) patients with primary pulmonary hypertension (PPH) in the database were enrolled. Spearman correlation was used to analyze the association of BUN with length of hospital and intensive care unit (ICU) stays. The chi-square test was used to analyze the association of BUN with mortality rate. Survival curves were estimated using the Kaplan-Meier method and compared by the log-rank test. Multivariable logistic regression was used to identify the BUN as an independent prognostic factor of mortality. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to analyze the sensitivity and specificity for mortality. Results: In total, 263 patients who met the selection criteria were enrolled. BUN was significantly positively associated with length of hospital stay and ICU stay (hospital stay: ρ = 0.282, ICU stay: ρ = 0.276; all P < 0.001). Higher hospital, 90-day and 4-year mortality rates were observed in the higher BUN quartile of PPH patients (hospital: P = 0.002; 90-day: P = 0.025; 4-year: P < 0.001). The Kaplan-Meier survival curves showed that patients in higher BUN quartile tended to have lower 4-year survival (Q1:7.65%, Q2: 10.71%; Q3: 14.80%, Q4: 16.84%; P < 0.0001). Logistic regression analyses found a significant association of BUN and mortality (hospital: OR = 1.05, 95% CI = 1.02–1.08, P = 0.001; 90-day: OR = 1.02, 95% CI = 1.00–1.05, P = 0.027; 4-year: OR = 1.05, 95% CI = 1.02–1.08, P = 0.001). Results of ROC and AUC showed that the diagnostic performance of BUN for mortality was moderately good. Conclusion: BUN was positively correlated with the length of hospital stay and ICU stay of PPH patients. Higher BUN was associated with higher hospital, 90-day and 4-year mortality and lower 4-year survival of PPH patients. These findings indicate that BUN can be a novel potential prognostic predictor for PPH.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".