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Purpose <p>Skin biopsy (SB) is considered the gold standard for detecting Small Fiber Neuropathy (SFN), a common complication of Diabetes Mellitus Type 1 (DM1). However, its invasive nature makes it less accessible for routine screening. Therefore, this study aims to analyze the diagnostic accuracy of Quantitative Sensory Testing (QST) in detecting SFN, using SB as reference.</p> Methods <p>A cross-sectional study was performed based on a sample of 49 adult patients with DM1 and 11 Healthy Controls. All participants underwent QST and SB. Associations between z-scores of QST parameters and SFN classified by SB were estimated by logistic regression. The cut-offs for SFN were defined by Receiver Operating Characteristic (ROC) analysis using the Youden index criterion.</p> Results <p>SFN was present in a large majority of patients with DM1, particularly among those with painful diabetic neuropathy (94.7%, <i>p</i> &lt; 0.001). Among QST parameters, Cold Detection Threshold (CDT), Warm Detection Threshold (WDT), Cold Pain Threshold (CDT), Heat Pain Threshold (HPT), Thermal Sensory Limen (TSL), Mechanical Detection Threshold, Mechanical Pain Threshold (MPT) and Vibration Detection Threshold were associated with the diagnosis of SFN. The predictive model including z-scores of CDT, WDT, CDT, HPT, TSL and MPT had the best accuracy (area under the ROC curve: 0.876; cut-off: 0.541; sensitivity: 90%; specificity: 81%).</p> Conclusion <p>Several QST parameters were associated with SFN and their combination demonstrated a good diagnostic accuracy. This non-invasive method may help identify and track SFN, ultimately improving patient management and early intervention strategies. Future studies should integrate nerve conduction studies to provide a comprehensive assessment of large fiber involvement in diabetic neuropathy.</p>

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Quantitative sensory testing and skin biopsy for neuropathy assessment in Portuguese patients with type 1 diabetes: an exploratory study

  • 期刊论文

  • 发表日期：

    2025年12月29日

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  • Mariana Jorge Santos,
  • Ana Rute Costa,
  • Carmen Lisboa,
  • Miguel Luz Soares,
  • Reinhard Sittl,
  • Davide M. Carvalho,
  • Margarida Barbosa

摘要

Purpose

Skin biopsy (SB) is considered the gold standard for detecting Small Fiber Neuropathy (SFN), a common complication of Diabetes Mellitus Type 1 (DM1). However, its invasive nature makes it less accessible for routine screening. Therefore, this study aims to analyze the diagnostic accuracy of Quantitative Sensory Testing (QST) in detecting SFN, using SB as reference.

Methods

A cross-sectional study was performed based on a sample of 49 adult patients with DM1 and 11 Healthy Controls. All participants underwent QST and SB. Associations between z-scores of QST parameters and SFN classified by SB were estimated by logistic regression. The cut-offs for SFN were defined by Receiver Operating Characteristic (ROC) analysis using the Youden index criterion.

Results

SFN was present in a large majority of patients with DM1, particularly among those with painful diabetic neuropathy (94.7%, p < 0.001). Among QST parameters, Cold Detection Threshold (CDT), Warm Detection Threshold (WDT), Cold Pain Threshold (CDT), Heat Pain Threshold (HPT), Thermal Sensory Limen (TSL), Mechanical Detection Threshold, Mechanical Pain Threshold (MPT) and Vibration Detection Threshold were associated with the diagnosis of SFN. The predictive model including z-scores of CDT, WDT, CDT, HPT, TSL and MPT had the best accuracy (area under the ROC curve: 0.876; cut-off: 0.541; sensitivity: 90%; specificity: 81%).

Conclusion

Several QST parameters were associated with SFN and their combination demonstrated a good diagnostic accuracy. This non-invasive method may help identify and track SFN, ultimately improving patient management and early intervention strategies. Future studies should integrate nerve conduction studies to provide a comprehensive assessment of large fiber involvement in diabetic neuropathy.