11-OR: Combined DPNCheck and SUDOSCAN as a Screening Tool for DPN—The Sheffield Prospective Study
Bibliographic record
Abstract
Introduction & Objective: Diabetic peripheral neuropathy (DPN) is often diagnosed late. Point-of-care-devices (POCDs, ‘DPN-Check’ a handheld device which measures sural-nerve conduction-velocity/amplitude and SUDOSCAN a test of sudomotor-function) are objective, quick tests that when combined; accurately diagnose DPN. However, the ability of POCDs to predict incident DPN is unknown, and was examined in this prospective study. Methods: 229 consecutive participants with diabetes who attended one-stop microvascular screening service were re-called for follow-up evaluation at 7 years. Baseline assessments were repeated including: clinical and neurophysiological assessments of DPN [Toronto Clinical Neuropathy Score (TCNS),10g monofilament (10g-MFT), POCDs and nerve conduction studies (NCS). Risk of developing incident DPN was assessed using the odds-ratio for the diagnosis of DPN using clinical (TCNS, 10gMFT) and NCS. Results: 90 participants have completed follow up visits. Patients attending follow up were significantly younger [57.8(11.9)vs62.5(14.2)years; (p<0.001(95%CI 4.1:11.4)] than those who did not (n=139), and had lower number of co-morbidities [3.0vs5.5; P<0.001] and Q-risk (20.3(13.1)vs29.3(13.5); p<0.001). Thirty-four (37.8%) patients had incident 10g MFT abnormality at follow-up. Patients with abnormal POCDs had a OR 7.1(p<0.001;95%CI:2.3:22.8) times greater risk of 10g-MFT abnormality compared to those with normal POCDs at baseline. Similar increased risk of incident DPN were found when DPN was diagnosed using TCNS [OR 4.0(95%CI1.0:15.2, p=0.03)] and NCS [OR 11.9(95%CI:1.5:96.0, p=0.005)]. Conclusions: We have demonstrated significantly increased risk of incident clinical DPN in patients with abnormal baseline POCDs (microalbuminuria equivalent). These findings support the use of POCDs as a screening tool for early DPN diagnosis, when cardio-metabolic control may halt the progressive neuropathic process. Disclosure M. Goonoo: None. D. Selvarajah: Research Support; Abbott. Speaker's Bureau; Grunenthal. Research Support; Impeto medical. G.P. Sloan: Other Relationship; Procter & Gamble, Lilly Diabetes. S. Tesfaye: Advisory Panel; Angelini Pharma, AstraZeneca, Bayer Inc., Worwag Pharma, Nevro Corp. Other Relationship; GlaxoSmithKline plc, Novo Nordisk Foundation. Speaker's Bureau; Procter & Gamble, Viatris Inc. Research Support; Withings, Viatris Inc., Procter & Gamble. Funding Proctor & Gamble Health (STH SPONSOR ID STH22196)
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".