Nutritional risk score predicts the length of stay in patients undergoing coronary angiography
Bibliographic record
Abstract
AIM: Nutritional status is a factor that impacts the clinical outcomes of various medical conditions, including cardiovascular disease and surgical procedures; however, little is known about its role in percutaneous procedures. This study aimed to assess the association between nutritional status and risk in patients undergoing coronary angiography and in-hospital mortality and length of stay to improve risk stratification and peri-procedural care. METHODS: Patients who underwent coronary angiography between January 2022 and August 2023. Nutritional status was assessed with body mass index, and nutritional risk was assessed with the Nutritional Risk Screening 2002 score. Multivariate regression models assessed independent predictors of in-hospital mortality, adjusting for age, sex, coronary event, Canadian Cardiovascular Society class, and cardiac arrest at admission. Subgroup analyses were performed based on coronary event type to evaluate whether the associations differed across clinical presentations. RESULTS: Patients who underwent angiography (n = 1343) were aged 69.2 ± 11.1 years, 51% male, and 49% had acute coronary syndrome. The mean length of stay at the hospital was 4.5 ± 4.8 days; 38% of patients stayed ≥5 days. The in-hospital mortality rate was 1.3%. Regression analyses revealed that the Nutritional Risk Screening 2002 score independently predicted the length of stay (β = 0.63, p = 0.002), and this relationship was strongest in the non-ST segment elevation myocardial infarction subgroup (β = 1.26, p = 0.02). Body mass index did not predict the length of stay. There was no significant relationship between in-hospital mortality and body mass index or the Nutritional Risk Screening 2002 score. CONCLUSION: Nutritional risk significantly predicts the length of stay after coronary angiography, independent of age, sex, and coronary event type. Clinicians should consider routine nutritional risk assessment preceding coronary angiography to help individualise post-procedure, in-hospital care.
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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 | 0.001 |
| 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".