Diagnostic accuracy of nerve ultrasonography for the detection of peripheral neuropathy in type 2 diabetes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Nerve conduction studies (NCS) are the current objective measure for diagnosis of peripheral neuropathy in type 2 diabetes but do not assess nerve structure. This study investigated the utility of peripheral nerve ultrasound as a marker of the presence and severity of peripheral neuropathy in type 2 diabetes. METHODS: A total of 156 patients were recruited, and nerve ultrasound was undertaken on distal tibial and distal median nerves. Neuropathy severity was graded using the modified Toronto Clinical Neuropathy Scale (mTCNS) and Total Neuropathy Score (TNS). Studies were undertaken by a single ultrasonographer blinded to nerve conduction results. RESULTS: A stepwise increase in tibial nerve cross-sectional area (CSA) was noted with increasing TNS grade (p < 0.001) and each mTCNS quartile (p < 0.001). Regression analysis demonstrated a correlation between tibial nerve CSA and neuropathy severity (p < 0.001). Using receiver operator curve analysis, tibial nerve CSA of >12.88 mm yielded a sensitivity of 70.5% and specificity of 85.7% for neuropathy detection. Binary logistic regression revealed that tibial nerve CSA was a predictor of abnormal sural sensory nerve action potential amplitude (odds ratio = 1.239, 95% confidence interval [CI] = 1.142-1.345) and abnormal neuropathy score (odds ratio = 1.537, 95% confidence interval [CI] = 1.286-1.838). CONCLUSIONS: Tibial nerve ultrasound has good specificity and sensitivity for neuropathy diagnosis in type 2 diabetes. The study demonstrates that tibial nerve CSA correlates with neuropathy severity. Future serial studies using both ultrasound and NCS may be useful in determining whether changes in ultrasound occur prior to development of nerve conduction abnormalities and neuropathic symptoms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 |
| 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 it