A20 DIAGNOSTIC ACCURACY OF A LOW COST, WIDELY AVAILABLE TEST STRIP FOR PREDICTING A POSITIVE FECAL CALPROTECTIN TEST
Bibliographic record
Abstract
Abstract Background Fecal calprotectin is a non-invasive test of colonic inflammation used for monitoring inflammatory bowel disease activity and for risk stratifying non-specific colonic symptoms. Calprotectin is a leukocyte specific enzyme. A similar test, leukocyte esterase is used to detect leukocytes in urine and is widely available as a low-cost point-of-care test strip. We hypothesize that an unmodified version of the urine test strip would be highly accurate in predicting a positive fecal calprotectin test in a real world sample of patients. Aims To explore a low cost, rapid alternative to the fecal calprotectin test Methods All inpatient and outpatient stool samples tested for calprotectin by the Vancouver General Hospital laboratory from February 2020 to November 2020 were included prospectively. Samples were simultaneously tested for fecal leukocyte esterase using an unmodified Roche Cobas Chemstrip urinalysis test strip by central lab personnel. An identical aliquot was sent to LifeLabs for calprotectin as per standard protocol. All samples were suspended in buffer using established laboratory protocols prior to testing. Fecal leukocyte esterase results were reported as 0–4+ based on visual interpretation, calprotectin results were reported as mcg/g of stool. REB review and approval was obtained prior to data collection. Sensitivity, Specificity and AUROC were calculated using Microsoft Excel and JROCFIT. Results 26 samples were collected. Using a fecal calprotectin greater than 120 mcg/g as a gold standard an AUROC of 0.89 (SE= .06) was calculated. A leukocyte esterase reading of 2+ or greater had the best test characteristics based on ROC curve analysis. Using this cutoff, 21/26 samples were concordant, giving an accuracy of 80.8%, sensitivity of 90.9% and specificity of 73.3%. Positive likelihood ratio was 8.07 and negative likelihood ratio was 0.29. Assuming an AUROC of 0.8, the sample size N=26 is 90% powered (β=0.9) to predict the true AUROC within 0.1 with a type I error rate of .05 (α<.05). Conclusions This study suggests application of a prepared stool sample to a urinalysis test strip gives a result highly predictive of a positive fecal calprotectin test. Further results are being collected prospectively to improve the robustness of these preliminary data. Secondary outcomes including comparison to endoscopy and biopsy results where available are planned if an adequate sample size can be accrued. Future studies justifying independent clinical use of leukocyte esterase would require a common gold standard comparator such as endoscopy. Fecal calprotectin testing is not universally insured and is not available as a rapid test strip. Use of fecal leukocyte esterase may reduce costs and shorten time to results if proven to be independently reliable. Funding Agencies None
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".