M. S. Deepthy

Jawaharlal Institute of Post Graduate Medical Education and Research

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Kalesh M Karun

Malankara Orthodox Syrian Church Medical College Hospital

M. K. Lintu

Malankara Orthodox Syrian Church Medical College Hospital

Amitha Puranik

Glenfield Hospital

Saravanan Rajendiran

Jawaharlal Institute of Post Graduate Medical Education and Research

Girish Varma

Dean College

B. Krishnan

Jawaharlal Institute of Post Graduate Medical Education and Research

T Unnikrishnan

Central University of Kerala

N. Sreekumaran Nair

Manipal Academy of Higher Education

Kotten Thazhath Harichandrakumar

Jawaharlal Institute of Post Graduate Medical Education and Research

A. Prasad

Kerala Veterinary and Animal Sciences University

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Jawaharlal Institute of Post Graduate Medical Education and Research

Manipal Academy of Higher Education

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Kerala Veterinary and Animal Sciences University

Malankara Orthodox Syrian Church Medical College Hospital

Kasturba Medical College, Manipal

Sri Dharmasthala Manjunatheshwara College of Dental Sciences & Hospital

Dean College

National Institute Of Veterinary Epidemiology And Disease Informatics

National Institute of Animal Nutrition and Physiology

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Side Effects of COVID-19 Vaccination among Indian Population - An Online Survey

International Journal of Health Sciences and Research (2022)

M. S. Deepthy Amitha Puranik M. K. Lintu

Background: India has successfully accomplished the administration of 100 crore doses of Covid-19 vaccination. However, there are not many reports regarding the post-vaccination experience. The aim of this study was to determine the side effects of Covid-19 vaccination in southern part of India. Methods: An online cross-sectional survey was conducted to collect information related to the post vaccination experience in southern part of India. The prevalence of different side effects along with their 95% confidence intervals were reported. The association of demographic characteristics and co-morbidities with side effects of vaccine were also estimated. Results: Almost 70% of the survey participants reported at least one side effect. Pain at the site of injection was the most common side effect followed by body pain, fever, fatigue, muscle pain and head ache. The side effects were found significantly higher among the younger adults (ages 18-35 years). Female respondents experienced more side effects than males. Conclusion: The information regarding the potential side effects identified through this survey study can be useful in educating the community and easing the reluctance towards Covid-19 vaccination. Key words: Covid-19; Side effect; Vaccination; India.

Cross-sectional study

10.52403/ijhsr.20220526

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Statistical tool for the estimation of body weight of lactating cows from 2D photographs

Journal of Veterinary and Animal Sciences (2024)

M. S. Deepthy T Unnikrishnan Girish Varma A. Prasad

Estimating the body weights of animals is an arduous task in livestock management. However, it is a vital tool in developing suitable breeding programmes,calculating the nutritional requirements, determining pharmaceutical doses of drugs and assessing feed conversion efficiency and carcass quality. In this study, we made an attempt to predict the bodyweights of lactating cows using images from various angles. Seventeen lactating cows from the University Livestock Farm and Fodder Research Station, Mannuthy, were selected randomly. Different body measurements of the animals were obtained manually and photographs of the lateral, rear, and dorsal views were taken using the demo version of the CAD-KAS measure-pictures 1.0 software. The surface area was estimated using the body length along the back on the midline from the withers to the croup and the maximum stomach width from the dorsal view photographs. A stepwise multiple linear regression model was used to predict the body weight of the animals. A regression equation fitted using the surface area and perpendicular length between the Tail Head above and the plane in level with the ventral line of the abdomen below yielded an R2 of 90.5 percent. This study suggests that models built using measurements retrieved from digital image analysis techniques can be used as a promising tool for predicting the body weight of animals. Keywords: Cattle, body weight, digital image analysis, multiple linear regression

Withers

Body surface area

10.51966/jvas.2024.55.1.1-6

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Risk factors of pneumonia among elderly with robust Poisson regression - A study on mimic III data

Biomedicine (2023)

Kalesh M Karun Amitha Puranik M. K. Lintu M. S. Deepthy

Introduction and Aim: Pneumonia is a common and serious illness among the elderly. Early identification of the risk factors for pneumonia is essential for improving the survival outcomes among elderly. The present study aimed to identify an optimal regression approach to determine the risk factors for pneumonia among elderly patients. Materials and Methods: The present study utilized data from the Medical Information Mart for Intensive Care (MIMIC III) to evaluate the use of alternative generalized linear models to identify the risk factors for pneumonia. The regression model with the smallest AIC, BIC and SE was considered as the appropriate regression model for the data. Robust Poisson model was considered the best fit for the current data as it had the lowest AIC, BIC and standard error compared to other regression models. Results: Variables such as BMI, renal failure, hypertension, diabetes and asthma were identified as the significant risk factors for pneumonia. The risk of pneumonia was found to be significantly higher in the underweight category of BMI [RRadj=1.70; 95% CI=1.38, 2.08]; diabetic patients [RRadj =1.29; 95% CI=1.03, 1.61); asthmatic patients [RRadj =1.35; 95% CI=1.15, 1.58] and patients with renal failure [RRadj =1.16; 95% CI= 1.05, 1.29]. Conclusion: Among various binary regression models, Poisson regression with robust variance (sandwich Poisson regression) provided unbiased estimates of the relationship. In the present study, variables such as BMI, renal failure, diabetics, hypertension and asthma were identified as the significant risk factors for pneumonia in the elderly using robust Poisson regression.

Underweight

10.51248/.v43i02.2250

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Generalized Estimating Equations in Longitudinal Studies: A Non-Parametric Alternative for Two-Way Repeated Measures Mixed ANOVA

Research Journal of Pharmacy and Technology (2023)

Kalesh M Karun M. S. Deepthy

Two group pre-post designs are very commonly used in medical research to study the effect of interventions on numerical outcome variables. Sometimes these measurements don’t follow the fundamental statistical assumption of normality and two-way repeated measures mixed ANOVA cannot be used. Generalized Estimating Equation (GEE) with Gamma log link function is a non-parametric analogue that can be used when data is skewed. When compared to other methods GEE has fewer assumptions and provides precise estimates.In the present study, the application of GEE is demonstrated using a simulated data. Different steps involved in the GEE analysis using SPSS software were also provided as an easy guide to researchers. This study could serve medical researchers understand, perform and interpret GEE in a better way.

Gee

Repeated measures design

Estimating equations

Mixed model

Marginal model

10.52711/0974-360x.2023.00392

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The Local Route of Administration of Dexamethasone in Impacted Mandibular Third Molar Surgery: A Systematic Review and Meta-analysis of Randomised Controlled Trials and a Critical Narrative Review on the Claimed Advantages of the Local Route

Journal of Maxillofacial and Oral Surgery (2023)

Saravanan Rajendiran B. Krishnan M. S. Deepthy

10.1007/s12663-023-02011-5

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Investigation of the Utility of Multivariate Meta-Analysis Methods in Estimating the Summary Dose Response Curve

Journal of Research in Health Sciences (2022)

M. S. Deepthy Kalesh M Karun Kotten Thazhath Harichandrakumar N. Sreekumaran Nair

Traditional meta-analyses often assess the effectiveness of different doses of the same intervention separately or examine the overall differences between intervention and placebo groups. The present study aimed to model the effect sizes obtained from different doses in multiple studies using a two-stage dose-response meta-analytic approach while taking dose variations into account.Different dose-response meta-analysis models using linear, quadratic, and restricted cubic spline (RCS) functions were fitted. A two-stage approach utilizing multivariate meta-analysis was performed and the obtained results were compared with those of the univariate meta-analysis. A random effect dose-response meta-analysis was performed using data from an existing systematic review on combination therapy with zonisamide and anti-Parkinson drugs for Parkinson's disease. The effective or optimum dose for producing maximum response was also investigated. Moreover, a sensitivity analysis was performed by changing the knots of the RCS model.Dose-response meta-analysis was performed using data from four double-blinded randomized controlled trials with 724 and 309 patients with Parkinson's disease in dose and placebo arms, respectively. The quadratic model yielded the smallest Akaike information criterion (AIC), compared to the linear and RCS models, indicating it to be the best fit for the data.Compared to the traditional approach, the two-stage approach could model the dose-dependent effect of zonisamide on the Unified Parkinson's Disease Rating Scale (UPRDS) part III score and predict the outcome for different doses through a single analysis.

Akaike information criterion

Univariate

10.34172/jrhs.2022.96

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