Polyneuropathy associated with chronic hemodialysis: Clinical and electrophysiological study

Distinguish different sensorimotor performance of the hand between the individuals with diabetes mellitus and chronic kidney disease through deep learning models

Diabetes mellitus and chronic kidney disease represent escalating global epidemics with comorbidities akin to neuropathies, resulting in various neuromuscular symptoms that impede daily performance. Interestingly, previous studies indicated differing sensorimotor functions within these conditions. If assessing sensorimotor features can effectively distinguish between diabetes mellitus and chronic kidney disease, it could serve as a valuable and non-invasive indicator for early detection, swift screening, and ongoing monitoring, aiding in the differentiation between these diseases. This study classified diverse diagnoses based on motor performance using a novel pinch-holding-up-activity test and machine learning models based on deep learning. Dataset from 271 participants, encompassing 3263 hand samples across three cohorts (healthy adults, diabetes mellitus, and chronic kidney disease), formed the basis of analysis. Leveraging convolutional neural networks, three deep learning models were employed to classify healthy adults, diabetes mellitus, and chronic kidney disease based on pinch-holding-up-activity data. Notably, the testing set displayed accuracies of 95.3% and 89.8% for the intra- and inter-participant comparisons, respectively. The weighted F1 scores for these conditions reached 0.897 and 0.953, respectively. The study findings underscore the adeptness of the dilation convolutional neural networks model in distinguishing sensorimotor performance among individuals with diabetes mellitus, chronic kidney disease, and healthy adults. These outcomes suggest discernible differences in sensorimotor performance across the diabetes mellitus, chronic kidney disease, and healthy cohorts, pointing towards the potential of rapid screening based on these parameters as an innovative clinical approach.

The formation of SCEs as an effect of occupational exposure to formaldehyde

Formaldehyde (FA) is a ubiquitous toxic chemical employed worldwide due to its disinfectant and preservative properties. Despite being classified as a human carcinogen, FA is still employed as formalin in pathology wards as standard fixative. We evaluated its relationship with the formation of sister-chromatid exchanges (SCEs) in cultured peripheral blood lymphocytes on 57 pathologists and 48 controls and the risk/protective role played by several genetic polymorphisms. All subjects were assessed for SCEs and genotyped for the most common cancer-associated gene polymorphisms: CYP1A1 exon 7 (A > G), CYP1A1*2A (T > C), CYP2C19*2 (G > A), GSTT1 (presence/absence), GSTM1 (presence/absence), GSTP1 (A > G), XRCC1 (G399A), XRCC1 (C194T), XRCC1 (A280G), XPC exon 15 (A939C), XPC exon 9 (C499T), TNFα − 308 G > A), IL10 − 1082 (G > A), and IL6 − 174 (G > C). Air-FA concentration was assessed through passive personal samplers. Pathologists, exposed to 55.2 μg/m³ of air-FA, showed a significantly higher SCEs frequency than controls, exposed, respectively, to 18.4 μg/m³. Air-FA was directly correlated with SCEs frequency and inversely with the replication index (RI). Regression models showed FA exposure as a significant predictor in developing SCEs, while did not highlight any role of the selected polymorphisms. Our study confirms the role of low air-FA levels as genotoxicity inductor, highlighting the importance to define exposure limits that could be safer for exposed workers.

Shear Wave Elastography in the Diagnosis of Peripheral Neuropathy in Patients With Chronic Kidney Disease Stage 5

OBJECTIVE

To observe the feasibility of shear wave elastography (SWE) in the diagnosis of peripheral neuropathy in patients undergoing hemodialysis [chronic kidney disease stage 5 dialysis (CKD5D)].

METHODS

Forty patients with CKD5D were divided into a uremic peripheral neuropathy (UPN) group (n = 25) and a non-UPN group (n = 15) according to the results of a neuro-electrophysiological examination. Sixteen healthy control subjects were also enrolled in this study. Two-dimensional ultrasound examination was conducted, and SWE was then performed to measure Young's modulus of the tibial nerve. The left and right diameters (D1), anterior and posterior diameters (D2), perimeter (C), cross-sectional area (CSA), and Young's modulus (E) were measured three times at the same non-entrapment site. The average values were recorded and calculated. The following evaluation indices were also analyzed: sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC).

RESULTS

D1, D2, C, and CSA were not significantly different among the three groups (P > 0.05). However, the difference in the E value among the three groups was statistically significant (P < 0.05). The AUC was 0.889 based on the E value. Using a tibial nerve E value of 48.35 kPa as the cutoff value, the sensitivity, specificity, PPV, and NPV were 86.0%, 84.0%, 81.1%, and 88.1%, respectively.

CONCLUSIONS

SWE is useful for the diagnosis of peripheral neuropathy in patients with CKD5D. Young's modulus of 48.35 kPa for the tibial nerve is the optimal cutoff value and has the best diagnostic efficiency for peripheral neuropathy in CKD5D patients.