ArticleBMC geriatrics2024
A correlation study between blood glucose fluctuation and chronic pain in the older people with type 2 diabetes mellitus.
Article in BMC geriatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Efficacy and safety of bi-weekly cofrogliptin treatment replacing daily dipeptidyl peptidase-4 inhibitors in Chinese patients with type 2 diabetes mellitus: A multicenter, open-label, randomized controlled phase 2 trial.Diabetes, obesity & metabolism · 2026Trial
- Impact of Glycemic Trajectory and Variability on Ischemic Stroke Prognosis and Exploration of Its Mechanisms: A Comprehensive Review.Healthcare (Basel, Switzerland) · 2026Review
- Association between islet β-cell function and time in range in patients with type 2 diabetes mellitus: a retrospective cross-sectional study.Frontiers in endocrinology · 2026Observational
- The relationship between abnormal glucose metabolism and chronic pain.Cell & bioscience · 2025Review
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13 authors.
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Abstract
objectivesTo investigate the correlation between blood glucose fluctuation parameters and other clinical data with chronic pain in older patients ( ≧ 60 years) with type 2 diabetes mellitus (T2DM), as well as evaluating the predictive value of risk of these parameters for chronic pain.
methodsClinical data were collected from 60 older patients with T2DM undergoing chronic pain who were hospitalized in the Department of Geriatric Endocrinology at the First Affiliated Hospital of Anhui Medical University. Pain scores using the numeric rating scale (NRS) were administered to all study participants by a dedicated person. Based on their pain scores, patients were categorized into two groups: mild pain group (NRS ≤ 5, n = 28) and severe pain group (NRS > 5, n = 32). Blood glucose levels were continuously monitored using the Continuous Glucose Monitoring System (CGMS). Spearman correlation analysis was performed to investigate the correlation between pain scores and blood glucose fluctuation parameters, as well as other clinical data of concern. Comparing general clinical information and relevant data recorded by CGMS between the two groups. Binary logistic regression was used to identify factors influencing the severity of chronic pain in old patients with T2DM combined with chronic pain. Additionally, the predictive value of Mean Amplitude of Glycemic Excursions (MAGE), Coefficient of Variation (CV), and Time in Range (TIR) for chronic pain severity was assessed using Receiver Operating Characteristic (ROC) curve analysis.
resultsSpearman correlation analysis revealed positive correlations between pain scores and the following variables: gender, age, duration of diabetes, duration of pain, MAGE, CV, mean blood glucose (MBG), standard deviation (SD), Mean of Daily Differences (MODD), and the highest glucose level. Conversely, pain scores were negatively correlated with red blood cell (RBC) count, hemoglobin (Hb), estimated glomerular filtration rate (eGFR). There were statistically significant differences in gender, age, disease duration, pain duration, Hb, eGFR, MAGE, CV, TIR, MBG, SD, MODD, and highest blood glucose values between the two groups. The gender, age, duration of diabetes, duration of pain, Hb, eGFR, MAGE, TIR, CV, MBG, SD, and MODD were identified as the risk factors for the severity of chronic pain in older T2DM patients by using binary logistic regression analysis. ROC curve analysis showed that the area under the curve for MAGE was 0.741 (sensitivity: 53.1%, specificity: 89.3%), for CV it was 0.668 (sensitivity: 40.6%, specificity: 89.3%), and for TIR it was 0.763 (sensitivity: 67.9%, specificity: 84%).
conclusionThe chronic pain is strongly correlated with blood glucose fluctuation parameters in older patients with T2DM. This work shows that those indicators of blood glucose fluctuations can be used for predicting chronic pain level in older T2DM patients, providing a potential methodology for rapid evaluation of chronic pain. CLINICAL TRIAL NUMBER: ChiCTR1800019107.
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