High rate of thiamine deficiency among inpatients with cancer referred for psychiatric consultation: results of a single site prevalence study
Bibliographic record
Abstract
OBJECTIVE: Thiamine deficiency (TD) is increasingly recognized in medically ill patients. The prevalence of TD among cancer patients is unknown. This study aims to characterize the prevalence of TD among inpatients with cancer. METHODS: Retrospective chart review of patients admitted to a large cancer center who were referred for psychiatric consultation and whose serum thiamine concentration was measured. Patients with alcohol use were excluded. RESULTS: Among 217 patients with various cancer types, TD was found in 55.3%. Risk factors included fluorouracil-based chemotherapy, significant weight loss, and undergoing active cancer treatment. Almost all patients were normal weight, overweight, or obese, and few had concomitant vitamin B12 or folate deficiency. A total of 17.5% were receiving multivitamin supplementation. Nearly half (49.8%) did not receive empiric treatment with thiamine and among those who did, treatment delay occurred in the majority of cases (59.6%). Measurement of serum thiamine concentration preceded psychiatric consultation in only 10.6% of cases. CONCLUSIONS: Our findings suggest that TD is highly prevalent among inpatients with cancer, even among normal and overweight individuals, in the absence of other vitamin deficiencies, and while receiving multivitamin supplements. Several potential risk factors were identified, including active cancer treatment. Evaluation of TD was most commonly not initiated by oncologists. Failure to treat and treatment delay were common. Given these findings, oncologists must be vigilant about detecting TD among inpatients with cancer. Copyright © 2016 John Wiley & Sons, Ltd.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".