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Risk of GERD with Diabetes Mellitus, Hypertension and Bronchial Asthma – A Hospital based Retrospective Cohort Study.

ABSTRACT: IntroductionThe rise in Gastro-Esophageal Reflux Disease (GERD) prevalence appears to have coincided with a simultaneous increase in the prevalence of diabetes mellitus, hypertension and bronchial asthma amongst the Indian population. Despite being evaluated extensively for their role as a risk factor for GERD, till date this relationship has remained a debatable one. Moreover, literature available on such studies conducted within Indian population remains scarce.AimThe aim of the present study was to examine the risk of developing GERD in patients suffering from diabetes mellitus, hypertension and asthma in a Southern Indian population. The present retrospective, triple cohort and hospital based study was conducted by accessing the patient records from the medical records department of a tertiary care hospital in Southern India.Materials and MethodsThe patient’s records were accessed from the year 2011 onwards. Relative Risk (RR) was calculated to determine the risk of development of GERD with every disease. Chi-square test was used to determine the statistical significance of the relationship between each disease and the development of GERD. A p-value of <0.05 was considered statistically significant.ResultsIn view of the time constraints as well as the limitations of the inclusion and exclusion criteria, data pertaining to only 40, 71 and 53 patients in Cohort 1 (diabetics), 2 (hypertensives) and 3 (bronchial asthmatics) respectively could be analyzed in the present study. The relative risk of GERD development was greater than 1 for patients belonging to Cohort 2 and 3, suggesting that the risk of GERD development is higher amongst hypertensives and asthmatics. Surprisingly, the diabetics (Cohort 1) were not associated with a high risk of GERD development. However, the relationship between any of the disease and GERD development was not statistically significant.ConclusionThe present study found an increased risk of GERD development amongst patients suffering from hypertension and bronchial asthma, but not with diabetes mellitus.

SUBMITTER: Nandyal S

PROVIDER: S-EPMC5583783 | biostudies-other | 2017 Jul

REPOSITORIES: biostudies-other

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Project description:BackgroundAsthma hospital encounters impose a heavy burden on the health care system. To improve preventive care and outcomes for patients with asthma, we recently developed a black-box machine learning model to predict whether a patient with asthma will have one or more asthma hospital encounters in the succeeding 12 months. Our model is more accurate than previous models. However, black-box machine learning models do not explain their predictions, which forms a barrier to widespread clinical adoption. To solve this issue, we previously developed a method to automatically provide rule-based explanations for the model's predictions and to suggest tailored interventions without sacrificing model performance. For an average patient correctly predicted by our model to have future asthma hospital encounters, our explanation method generated over 5000 rule-based explanations, if any. However, the user of the automated explanation function, often a busy clinician, will want to quickly obtain the most useful information for a patient by viewing only the top few explanations. Therefore, a methodology is required to appropriately rank the explanations generated for a patient. However, this is currently an open problem.ObjectiveThe aim of this study is to develop a method to appropriately rank the rule-based explanations that our automated explanation method generates for a patient.MethodsWe developed a ranking method that struck a balance among multiple factors. Through a secondary analysis of 82,888 data instances of adults with asthma from the University of Washington Medicine between 2011 and 2018, we demonstrated our ranking method on the test case of predicting asthma hospital encounters in patients with asthma.ResultsFor each patient predicted to have asthma hospital encounters in the succeeding 12 months, the top few explanations returned by our ranking method typically have high quality and low redundancy. Many top-ranked explanations provide useful insights on the various aspects of the patient's situation, which cannot be easily obtained by viewing the patient's data in the current electronic health record system.ConclusionsThe explanation ranking module is an essential component of the automated explanation function, and it addresses the interpretability issue that deters the widespread adoption of machine learning predictive models in clinical practice. In the next few years, we plan to test our explanation ranking method on predictive modeling problems addressing other diseases as well as on data from other health care systems.International registered report identifier (irrid)RR2-10.2196/5039.

Project description:To evaluate the association between incidence of any kidney cancer and type 2 diabetes mellitus.A random sample of 1,000,000 subjects covered by the National Health Insurance was recruited. A total of 998728 people (115655 diabetes and 883073 non-diabetes) without kidney cancer at recruitment were followed from 2003 to 2005. The cumulative incidence of kidney cancer from 2003 to 2005 in diabetic patients and non-diabetic people in all ages and in age <40, 40-64, 65-74 and ? 75 years were calculated in the diabetic patients and the non-diabetic people, respectively. Logistic regression was used to estimate the odds ratios comparing diabetic patients to non-diabetic people in the respective age groups. Multivariable-adjusted odds ratios for kidney cancer with regards to diabetes status and diabetes duration (as a continuous variable or categorized into subgroups of non-diabetes, diabetes duration <1 year, 1-2.9 years, 3-4.9 years and ? 5 years) were estimated after multivariable adjustment. The multivariable-adjusted odds ratios for all baseline variables were also estimated for diabetic patients and non-diabetic people, respectively.The 3-year cumulative incidence of kidney cancer in the diabetic patients and the non-diabetic people was 166.9 and 33.1 per 100,000 person-years, respectively. The incidence increased with regards to increasing age in both the diabetic patients and the non-diabetic people, but a higher risk of kidney cancer for the diabetic patients compared to the non-diabetic people was consistently observed in different age groups. After multivariable adjustment, the odds ratio for diabetic patients versus non-diabetic people was 1.7 (95% confidence interval: 1.3-2.1, P<0.01). While compared to the non-diabetic people, the odds ratio (95% confidence interval) for diabetes duration <1, 1-2.9 years, 3-4.9 years and ? 5 years was 1.5 (0.8-2.7), 1.6 (1.0-2.4), 1.6 (1.1-2.4) and 1.7 (1.3-2.3), respectively (P-trend <0.01). Analyses conducted in the diabetic patients and the non-diabetic people, respectively, consistently showed age, nephropathy and end-stage renal disease as significant risk factors of kidney cancer. Additionally, living in metropolitan Taipei region might also be associated with a higher risk of kidney cancer in the non-diabetic people, indicating a potential link between kidney cancer and some factors related to urbanization.Patients with type 2 diabetes mellitus have a significantly higher risk of kidney cancer.

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Risk of GERD with Diabetes Mellitus, Hypertension and Bronchial Asthma – A Hospital based Retrospective Cohort Study.

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