Prevalence and Risk Factors of Heart Failure with Preserved Ejection Fraction in Middle-Aged Maintenance Haemodialysis Patients on a Twice-Weekly Schedule: Experience from a Single Indian Centre.

Background. Data on the prevalence of cardiac failure with preserved ejection in the haemodialysis population, which impacts treatment strategy, mortality, and morbidity, are scarce. Aims and Objectives. Estimate the prevalence of heart failure with preserved ejection fraction (HFpEF) in haemodialysis patients Classify cardiac failure and ascertain the risk factors influencing HFpEF in haemodialysis patients. Methods. All consenting individuals on haemodialysis over 18 years of age were included. Lung ultrasound was performed as per the LUST study protocol, and the labs were documented. Echocardiographic parameters were measured using two-dimensional (2D ECHO). Results. A total of 102 patients consented to participate in the study, which included 63 males (61.8%) and 39 females (38.2%). The mean patient age was 53 ± 13.1 years. The dialysis vintage of the participants was 38.92 ± 6.947 months. 47 (46.1%) patients had diabetes and 88 (80.4%) had hypertension. ECG findings included sinus rhythm (51/102, 50%), sinus tachycardia (22/102, 21.6%), ST-T wave abnormalities (18/102, 17.6%), and atrial fibrillation (11/102, 10.8%). Heart failure with preserved ejection fraction (HFpEF) was present in 44/102 (43.14%), heart failure with mid-range EF in 14/102 (13.72%), and heart failure with reduced EF in 13/102 (12.7%) patients. The ejection fraction was positively associated with haemoglobin (r = 0.23; p = 0.044), and calcium levels (r = 0.25; p =0 .03). E/lateral e' ratio was positively correlated with NT pro-BNP (r = 0.63; p < 0.001), systolic blood pressure (r = 0.44; p = 0.003) and age (r = 0.353; p = 0.003) and negatively correlated with transferrin saturation (r = -0.353; p = 0.027) and diastolic blood pressure (r = -0.31; p = 0.040). Binary logistic regression analysis revealed that the odds of diastolic dysfunction increased by 2.3 times with each unit increase of creatinine, and diabetics have 7.66 times higher risk for diastolic dysfunction. Binary logistic regression involving ejection fraction (EF) and all laboratory and clinical parameters revealed odds of HFpEF increased by 1.93 times with each unit increase in age, odds of HFpEF increases by 1.53 times with each unit increase in phosphorous and odds of HFpEF increased by 1.1 times with a unit increase of systolic blood pressure. Conclusion. HFpEF is the predominant form of heart failure in haemodialysis patients. Haemoglobin and calcium were positively associated with ejection fraction. Advancing age, elevated creatinine and diabetes mellitus levels are independent predictors of diastolic dysfunction in haemodialysis patients.

Syndromic surveillance during religious mass gatherings, southern India 2015-2018.

BACKGROUND: Mass gathering events carry a risk of public health emergencies such as outbreaks of infectious diseases, stampedes, and injuries and pose an increased risk for individuals with non-communicable diseases. India celebrates many festivals mass gatherings. However, operational research on syndromic surveillance during such events is limited. In this context, we documented the use of information technology tools for syndromic surveillance during selected mass gatherings in South India during 2015-2018. METHOD: We collaborated with health systems for syndromic surveillance during selected religious mass gatherings. We finalized priority syndromes and their surveillance definitions through stakeholder meetings. We used open-source software for surveillance data collection and trained the health care professionals and volunteers for data capture and collation. We consolidated, analyzed, generated near-real-time daily reports and shared them with health authorities for action. RESULTS: The number of participants in these mass gatherings ranged from 100 thousand to 3 million, and recorded out-patients seeking care for syndromic illness ranged from 4,000 to 25,000 per event. We used more than five platforms and captured information on 17 syndromes. We captured a total of 61,523 patient details during syndromic surveillance. The most frequently reported syndromes were injuries, fever, and diarrhea of the reported illness. CONCLUSIONS: These cost-effective open-source technologies are intuitive, adaptable, and inexpensive to maintain and operate in real-time. Therefore, enhanced syndromic surveillance could detect diseases early in mass gatherings.