Reliability and Predictive Validity of Inlow’s 60-Second Diabetic Foot Screen Tool
Bibliographic record
Abstract
OBJECTIVE: : The purpose of this study was to assess Inlow's 60-Second Diabetic Foot Screen Tool to ascertain consistency of risk recognition for development of ulceration independent of specific assessor and practice setting. Screening tools that assist clinicians in identifying risk require validation. The objectives were to determine the intrarater reliability, interrater reliability, and predictive validity of Inlow's 60-Second Diabetic Foot Screen Tool in 2 healthcare settings. DESIGN: : Following ethics board approval, a prospective observational study was completed. SETTING AND PARTICIPANTS: : A convenience sample of 69 persons with diabetes was recruited: n = 26 from an acute care setting (dialysis) and n = 43 from long-term-care (LTC) setting. MAIN OUTCOME MEASURES: : The screening tool was administered by 2 assessors independently to determine interrater reliability and later the same day by one of the assessors to determine intrarater reliability. Occurrence of foot ulcers or amputation was noted 1 to 5 months later to determine predictive validity. MAIN RESULTS: : Reliability is reported per setting using the intraclass correlation coefficient (2.1) and 95% confidence intervals. Intrarater reliability: LTC 0.96 (0.93-0.98) right foot, 0.97 (0.95-0.98) left foot; dialysis 1.00 right and 1.00 left foot. Interrater reliability: LTC 0.92 (0.86-0.96) right foot, 0.93 (0.87-0.96) left foot; dialysis 0.83 (0.65-0.92) right foot and left foot. Predictive validity: Two subjects had events-1 ulcer and 1 amputation-that were associated with high Inlow's screening tool scores. CONCLUSION: : This study demonstrates excellent interrater and intrarater reliability and provides preliminary information about predictive validity.
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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 | 0.015 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".