A56 LEVELS OF AGREEMENT BETWEEN PATIENT AND PRACTITIONER LED MALUTRITION SCREENING TOOLS IN CIRRHOSIS
Bibliographic record
Abstract
Malnutrition is prevalent in cirrhosis, and tools to screen for nutrition risk are available, however, screening is seldom implemented in clinical practice. Time constraints in a clinic setting may provide one explanation for this omission. Accurate, easy to use patient-led nutrition screening tools may increase use of nutrition screening. Research objectives: 1. To identify the agreement between a patient-led and health practitioner led nutrition-screening tool, the nutrition prioritizing tool (NPT). 2. To identify agreement between the patient led NPT and registered dietitian (RD) assigned gold-standard royal free hospital subjective global assessment score (RFH-SGA assessment tool). A cross-sectional survey and RD-led interview were completed on 68 patients with diagnosed cirrhosis from Edmonton and Calgary cirrhosis clinics and inpatients. Patients completed the online patient led NPT, and were subsequently interviewed by a research assistant and a RD to determine the practitioner led NPT and RFH-SGA gold standard assessment score. Proportions of patients in each category were examined and kappa measure of agreement analyses were conducted to identify if there was a statistically significant difference between assessment methods. See Table 1 for a comparison of the results from the 3 scales. Both the practitioner led NPT (Kappa = 0.37, p<0.001) and RFH-SGA (0.07, p=0.173) were not in agreement with the patient led NPT results. Considering that patients with any degree of nutrition risk should be referred for further assessment, all screens were collapsed into two categories, low risk and increased risk. While this did not improve the kappa levels the sensitivity of the patient led NPT compared to the RFH-SGA was 69% and the specificity was 87%. Many patients with cirrhosis (67% using RFH-SGA) would likely benefit from consultation with a RD. Patients in the 3 nutrition risk categories identified by the patient-led NPT screening tool were not in agreement with the practitioner led screening NPT categories or the gold-standard RFH-SGA, although the sensitivity and specificity of the test was acceptable. Further examination of other patient led measures with higher levels of agreement with the RFH-SGA is warranted. Table 1. Malnutrition scores on three different scales in cirrhosis NPT Nutrition prioritizing tool, RFH-SGA Royal free hospital-subjective global assessment None
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".