scholarly journals The Patient Health Questionnaire-9 as a Screening Tool for Depression in Individuals with Type 2 Diabetes Mellitus: The Maastricht Study

2016 ◽  
Vol 64 (11) ◽  
pp. e201-e206 ◽  
Author(s):  
Eveline P. C. J. Janssen ◽  
Sebastian Köhler ◽  
Coen D. A. Stehouwer ◽  
Nicolaas C. Schaper ◽  
Pieter C. Dagnelie ◽  
...  
Author(s):  
VENKATESAN S. ◽  
SUSILA S. ◽  
SUTHANTHIRAN S. ◽  
MADHUSUDHAN S. ◽  
PAARI N.

Objective: To identify and prevent the vulnerable prediabetic population becoming diabetic patients in the future using the Indian Diabetic Risk Score (IDRS) and to evaluate the performance of the IDRS questionnaire for detecting prediabetes and predicting the risk of Type 2 Diabetes Mellitus in Chidambaram rural Indian population. Methods: A cross-sectional descriptive study was carried out among patients attending a master health check-up of RMMCH hospital located at Chidambaram. The IDRS was calculated by using four simple measures of age, family history of diabetes, physical activity, and waist measurement. The relevant blood test, like Fasting plasma glucose (FBS), Glycated hemoglobin (HbA1C) test, were observed for identifying prediabetes. Subjects were classified as Normoglycemic, prediabetics, and diabetics based on the questionnaire and diagnostic criteria of the Indian Council of Medical Research (ICMR) guidelines. Results: In the study, sensitivity and specificity of IDRS score were found to be 84.21% and 63.4% respectively for detecting prediabetes in community with the positive predictive value of 51.6% and negative predictive value of 89.6% and prevalence of prediabetes in the Chidambaram rural population is 31.6% among the 60 participants. Conclusion: The Indian diabetic risk score questionnaire designed by Ma­dras diabetic research federation is a useful screening tool to identify unknown type 2 diabetes mellitus. The question­naire is a reliable, valuable, and easy to use screening tool which can be used in a primary care setup. 


Author(s):  
Surya Roca ◽  
María Luisa Lozano ◽  
José García ◽  
Álvaro Alesanco

Virtual assistants are programs that interact with users through text or voice messages simulating a human-based conversation. The development of healthcare virtual assistants that use messaging platforms is rapidly increasing. Still, there is a lack of validation of these assistants. In particular, this work aimed to validate the effectiveness of a healthcare virtual assistant, integrated within messaging platforms, with the aim of improving medication adherence in patients with comorbid type 2 diabetes mellitus and depressive disorder. For this purpose, a nine-month pilot study was designed and subsequently conducted. The virtual assistant reminds patients about their medication and provides healthcare professionals with the ability to monitor their patients. We analyzed the medication possession ratio (MPR), measured the level of glycosylated hemoglobin (HbA1c), and obtained the patient health questionnaire (PHQ-9) score in the patients before and after the study. We also conducted interviews with all participants. A total of thirteen patients and five nurses used and evaluated the proposed virtual assistant using the messaging platform Signal. Results showed that on average, the medication adherence improved. In the final interview, 69% of the patients agreed with the idea of continuing to use the virtual assistant after the study.


2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Mohamad Adam Bujang ◽  
Pei Xuan Kuan ◽  
Xun Ting Tiong ◽  
Fatin Ellisya Saperi ◽  
Mastura Ismail ◽  
...  

Aims. This study aims to determine the all-cause mortality and the associated risk factors for all-cause mortality among the prevalent type 2 diabetes mellitus (T2DM) patients within five years’ period and to develop a screening tool to determine high-risk patients. Methods. This is a cohort study of T2DM patients in the national diabetes registry, Malaysia. Patients’ particulars were derived from the database between 1st January 2009 and 31st December 2009. Their records were matched with the national death record at the end of year 2013 to determine the status after five years. The factors associated with mortality were investigated, and a prognostic model was developed based on logistic regression model. Results. There were 69,555 records analyzed. The mortality rate was 1.4 persons per 100 person-years. The major cause of death were diseases of the circulatory system (28.4%), infectious and parasitic diseases (19.7%), and respiratory system (16.0%). The risk factors of mortality within five years were age group (p<0.001), body mass index category (p<0.001), duration of diabetes (p<0.001), retinopathy (p=0.001), ischaemic heart disease (p<0.001), cerebrovascular (p=0.007), nephropathy (p=0.001), and foot problem (p=0.001). The sensitivity and specificity of the proposed model was fairly strong with 70.2% and 61.3%, respectively. Conclusions. The elderly and underweight T2DM patients with complications have higher risk for mortality within five years. The model has moderate accuracy; the prognostic model can be used as a screening tool to classify T2DM patients who are at higher risk for mortality within five years.


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