The impact of chronic diseases on non-invasive blood glucose measurement using near-infrared spectroscopy in Republic of Korea: retrospective clinical study
- Author:
Hoonsung CHOI
1
;
Meihua JIN
;
Won Sang YOO
Author Information
- Publication Type:Original article
- From: Medical Lasers 2025;14(4):244-252
- CountryRepublic of Korea
- Language:English
-
Abstract:
Background:Self-monitoring of blood glucose is crucial for diabetes management but is often hindered by the discomfort of invasive methods such as finger-pricking. Near-infrared spectroscopy (NIRS) offers a promising non-invasive alternative by measuring glucose levels through interactions with light in interstitial fluid. However, chronic diseases may alter NIRS signals, affecting accuracy. This study aimed to evaluate how diabetes, chronic kidney disease, and liver disease influence the correlation between NIRS signals and blood glucose levels.
Methods:From April to December 2022, 697 patients at Dankook University Hospital participated. Blood glucose was measured by finger-pricking, followed by simultaneous NIRS readings. Clinical data on comorbidities were collected. Correlations between NIRS wavelengths and glucose levels were analyzed, adjusting for age, sex, and comorbidities. Regression models and Bland–Altman plots assessed predictive performance.
Results:A total of 974 paired glucose and NIRS measurements were obtained. Significant correlations were found at 660 and 1,450 nm. Wavelengths from 660 to 1,300 nm showed consistent negative correlations with glucose, whereas 1,450 nm showed a positive correlation. Multivariate regression identified age, NIR wavelengths, and chronic diseases as significant predictors. The prediction model showed good accuracy for glucose levels below 200 mg/dL (R 2 = 0.24, 3.38% outside Bland–Altman limits) but reduced accuracy at higher levels.
Conclusion:NIRS-based glucose monitoring is influenced by chronic diseases, underscoring the need to incorporate these factors into future algorithm development. Further studies are warranted to optimize NIRS for clinical application.
