Developing a Screening Algorithm for Type II Diabetes Mellitus in the Resource-Limited Setting of Rural Tanzania
| Autor: | Virginia A. Fonner, David W. Ploth, Francis Fredrick, Caroline West, Michael D. Sweat, Jessie Mbwambo |
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| Rok vydání: | 2016 |
| Předmět: |
Rural Population
Gerontology medicine.medical_specialty Population 030209 endocrinology & metabolism Risk management tools Tanzania Article Type ii diabetes 03 medical and health sciences 0302 clinical medicine Humans Mass Screening Medicine 030212 general & internal medicine education Intensive care medicine Mass screening Cause of death education.field_of_study biology business.industry General Medicine biology.organism_classification Diabetes Mellitus Type 2 Latin hypercube sampling Health Resources Risk assessment business Algorithms Follow-Up Studies |
| Zdroj: | The American Journal of the Medical Sciences. 351:408-415 |
| ISSN: | 0002-9629 |
| DOI: | 10.1016/j.amjms.2016.01.012 |
| Popis: | Background Noncommunicable diseases are on pace to outnumber infectious disease as the leading cause of death in sub-Saharan Africa, yet many questions remain unanswered with concern toward effective methods of screening for type II diabetes mellitus (DM) in this resource-limited setting. We aim to design a screening algorithm for type II DM that optimizes sensitivity and specificity of identifying individuals with undiagnosed DM, as well as affordability to health systems and individuals. Methods Baseline demographic and clinical data, including hemoglobin A1c (HbA1c), were collected from 713 participants using probability sampling of the general population. We used these data, along with model parameters obtained from the literature, to mathematically model 8 purposed DM screening algorithms, while optimizing the sensitivity and specificity using Monte Carlo and Latin Hypercube simulation. Results An algorithm that combines risk assessment and measurement of fasting blood glucose was found to be superior for the most resource-limited settings (sensitivity 68%, sensitivity 99% and cost per patient having DM identified as $2.94). Incorporating HbA1c testing improves the sensitivity to 75.62%, but raises the cost per DM case identified to $6.04. The preferred algorithms are heavily biased to diagnose those with more severe cases of DM. Conclusions Using basic risk assessment tools and fasting blood sugar testing in lieu of HbA1c testing in resource-limited settings could allow for significantly more feasible DM screening programs with reasonable sensitivity and specificity. |
| Databáze: | OpenAIRE |
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