TY - JOUR
T1 - SYmptom-Based STratification of DiabEtes Mellitus by Renal Function Decline (SYSTEM)
T2 - A Retrospective Cohort Study and Modeling Assessment
AU - Chan, Kam Wa
AU - Chow, Tak Yee
AU - Yu, Kam Yan
AU - Xu, Yulong
AU - Zhang, Nevin Lianwen
AU - Wong, Vivian Taam
AU - Li, Saimei
AU - Tang, Sydney Chi Wai
N1 - This project was made possible in part through the support of Fu Tak Iam Foundation, Health and Medical Research Fund (Ref: 12133341, 14151731) and Hong Kong Society of Nephrology Research Grant.
Publisher Copyright:
© Copyright © 2021 Chan, Chow, Yu, Xu, Zhang, Wong, Li and Tang.
PY - 2021/6/14
Y1 - 2021/6/14
N2 - Background: Previous UK Biobank studies showed that symptoms and physical measurements had excellent prediction on long-term clinical outcomes in general population. Symptoms and signs could intuitively and non-invasively predict and monitor disease progression, especially for telemedicine, but related research is limited in diabetes and renal medicine. Methods: This retrospective cohort study aimed to evaluate the predictive power of a symptom-based stratification framework and individual symptoms for diabetes. Three hundred two adult diabetic patients were consecutively sampled from outpatient clinics in Hong Kong for prospective symptom assessment. Demographics and longitudinal measures of biochemical parameters were retrospectively extracted from linked medical records. The association between estimated glomerular filtration rate (GFR) (independent variable) and biochemistry, epidemiological factors, and individual symptoms was assessed by mixed regression analyses. A symptom-based stratification framework of diabetes using symptom clusters was formulated by Delphi consensus method. Akaike information criterion (AIC) and Bayesian information criterion (BIC) were compared between statistical models with different combinations of biochemical, epidemiological, and symptom variables. Results: In the 4.2-year follow-up period, baseline presentation of edema (−1.8 ml/min/1.73m2, 95%CI: −2.5 to −1.2, p < 0.001), epigastric bloating (−0.8 ml/min/1.73m2, 95%CI: −1.4 to −0.2, p = 0.014) and alternating dry and loose stool (−1.1 ml/min/1.73m2, 95%CI: −1.9 to −0.4, p = 0.004) were independently associated with faster annual GFR decline. Eleven symptom clusters were identified from literature, stratifying diabetes predominantly by gastrointestinal phenotypes. Using symptom clusters synchronized by Delphi consensus as the independent variable in statistical models reduced complexity and improved explanatory power when compared to using individual symptoms. Symptom-biologic-epidemiologic combined model had the lowest AIC (4,478 vs. 5,824 vs. 4,966 vs. 7,926) and BIC (4,597 vs. 5,870 vs. 5,065 vs. 8,026) compared to the symptom, symptom-epidemiologic and biologic-epidemiologic models, respectively. Patients co-presenting with a constellation of fatigue, malaise, dry mouth, and dry throat were independently associated with faster annual GFR decline (−1.1 ml/min/1.73m2, 95%CI: −1.9 to −0.2, p = 0.011).Conclusions: Add-on symptom-based diagnosis improves the predictive power on renal function decline among diabetic patients based on key biochemical and epidemiological factors. Dynamic change of symptoms should be considered in clinical practice and research design.
AB - Background: Previous UK Biobank studies showed that symptoms and physical measurements had excellent prediction on long-term clinical outcomes in general population. Symptoms and signs could intuitively and non-invasively predict and monitor disease progression, especially for telemedicine, but related research is limited in diabetes and renal medicine. Methods: This retrospective cohort study aimed to evaluate the predictive power of a symptom-based stratification framework and individual symptoms for diabetes. Three hundred two adult diabetic patients were consecutively sampled from outpatient clinics in Hong Kong for prospective symptom assessment. Demographics and longitudinal measures of biochemical parameters were retrospectively extracted from linked medical records. The association between estimated glomerular filtration rate (GFR) (independent variable) and biochemistry, epidemiological factors, and individual symptoms was assessed by mixed regression analyses. A symptom-based stratification framework of diabetes using symptom clusters was formulated by Delphi consensus method. Akaike information criterion (AIC) and Bayesian information criterion (BIC) were compared between statistical models with different combinations of biochemical, epidemiological, and symptom variables. Results: In the 4.2-year follow-up period, baseline presentation of edema (−1.8 ml/min/1.73m2, 95%CI: −2.5 to −1.2, p < 0.001), epigastric bloating (−0.8 ml/min/1.73m2, 95%CI: −1.4 to −0.2, p = 0.014) and alternating dry and loose stool (−1.1 ml/min/1.73m2, 95%CI: −1.9 to −0.4, p = 0.004) were independently associated with faster annual GFR decline. Eleven symptom clusters were identified from literature, stratifying diabetes predominantly by gastrointestinal phenotypes. Using symptom clusters synchronized by Delphi consensus as the independent variable in statistical models reduced complexity and improved explanatory power when compared to using individual symptoms. Symptom-biologic-epidemiologic combined model had the lowest AIC (4,478 vs. 5,824 vs. 4,966 vs. 7,926) and BIC (4,597 vs. 5,870 vs. 5,065 vs. 8,026) compared to the symptom, symptom-epidemiologic and biologic-epidemiologic models, respectively. Patients co-presenting with a constellation of fatigue, malaise, dry mouth, and dry throat were independently associated with faster annual GFR decline (−1.1 ml/min/1.73m2, 95%CI: −1.9 to −0.2, p = 0.011).Conclusions: Add-on symptom-based diagnosis improves the predictive power on renal function decline among diabetic patients based on key biochemical and epidemiological factors. Dynamic change of symptoms should be considered in clinical practice and research design.
KW - diabetes
KW - diabetic kidney disease
KW - diagnosis
KW - epidemiology
KW - integrative medicine
KW - renal medicine
KW - symptom
KW - traditional chinese medicine
UR - http://www.scopus.com/inward/record.url?scp=85114806994&partnerID=8YFLogxK
U2 - 10.3389/fmed.2021.682090
DO - 10.3389/fmed.2021.682090
M3 - Journal article
AN - SCOPUS:85114806994
SN - 2296-858X
VL - 8
JO - Frontiers in Medicine
JF - Frontiers in Medicine
M1 - 682090
ER -