Biomedical subjects

Sanjay Mehrotra

Publications and source records attributed to Sanjay Mehrotra.

6 recordsLinked to original sources

PubMed2025

A Systematic Review of Spatial Epidemiological Modeling Approaches Applied During the COVID-19 Pandemic.

BACKGROUND: A wide range of epidemiological modeling approaches have been applied to the SARS-CoV-2 pandemic, which presents an opportunity to assess common approaches applied to specific research questions. Spatial models interrogate how heterogeneities and host movement dynamics influence local and regional patterns of disease, issues that were of great interest for understanding and controlling SARS-CoV-2. OBJECTIVE: Here we present a systematic review of spatial epidemiological modeling approaches of SARS-CoV-2. We describe common themes and highlight unique strategies, providing a foundation for researchers to devise spatial models most appropriate for future pathogens and epidemics. Our review also categorizes the research questions that were addressed with spatial models, highlights parameter estimation techniques, and describes the cyber infrastructure used for model development. METHODS: We conducted a systematic review using Web of Science and a standardized set of keywords, followed by thorough examination of abstracts and full texts to determine which studies met our inclusion criteria. To guide our description and comparisons of models, we developed a Geography, Population, Movement (GPM) framework that conceptualizes the interactions between three distinct subcomponents of any spatial model. The geographic model represents the physical arena in which the model is implemented, the intra-population model describes the transmission and disease processes that occur within distinct spatial units of the geography, and the movement model describes the algorithms that dictate how hosts move among spatial units within the geography. RESULTS: The search identified a total of 193 articles, of which 109 were included in our review. The most abundant intra-population modeling methods were agent-based (47.7%) and compartmental modeling (29.4%) approaches. Movement models ranged in complexity, with the most complex models implementing commuter movement among many points of interest in the geographic arena, which were sometimes parameterized by fine-scale mobility data. Geographic models ranged from describing microcosms, such as single classrooms, all the way up to multi-country models. Of the 63.3% of models studies that specified the programming language used, we detected ten different languages, with Matlab and Python being the most frequent, although only 30.6% of studies provided open-access code for their models. We also described eight specialized software systems that were used to construct agent-based or compartment models of COVID-19. CONCLUSIONS: Our review identified and characterized a variety of spatial modeling strategies and software that were usefully employed to address many relevant epidemiological questions for COVID-19. Future research is needed to quantitatively assess which modeling approaches are most appropriate in specific situations, to answer specific questions, or to apply to certain disease systems. Moreover, future cyberinfrastructure could help to modularize and standardize modeling approaches, which would increase transparency and reproducibility, and which would facilitate a detailed examination of which model attributes relate to model performance in a variety of contexts.

COVID-19↗

PubMed2006

Esthesioneuroblastoma treated with non-craniofacial resection surgery followed by combined chemotherapy and radiotherapy: An alternative approach in limited resources.

BACKGROUND: Esthesioneuroblastoma (ENB) is a rare and aggressive malignant tumor arising from olfactory epithelium. Surgical excision in the form of craniofacial surgical resection (CFR) has shown encouraging results. The purpose of the study is to analyze the outcome of this disease when managed by non-craniofacial resection (NCFR) surgery in limited resources. METHODS: Between October 1998 and January 2004, eight patients with ENB were treated in the Department of Radiotherapy at KGMU, Lucknow. None of these eight patients underwent CFR surgery. All patients received six cycles of vincristine, adriamycin and cyclophosphamide (VAC) based chemotherapy followed by radiotherapy. RESULTS: All the patients registered during this period had undergone operative procedures in the form of NCFR surgery except two. Complete response was present in five (62.5%) patients and three (37.5%) patients had partial response. Locoregional relapse-free survival at 3 years was 62.5% and median survival time was 38 months. Disease-free survival and overall survival at 3 years was 72.9 and 71.4%, respectively, and median disease-free survival time was 43 months, while mean overall survival time was 40.7 months as median overall survival time was not reached. CONCLUSION: Patients in developing countries often present with advanced stages and because of non-availability of technical advances and surgical expertise one tends to approach these patients with palliative intent. Most of the patients in our series were of stage C disease (75%) and still our response rate and survival were encouraging despite the fact that surgery was not optimal. This combination chemoradiotherapy schedule can be used outside the protocol setting where resources are limited.

Adolescent↗

PubMed2006

Idiopathic chylopericardium: an unusual cause of cardiac tamponade.

Chylous pericardial effusion is an uncommon condition, and the treatment is difficult. We report a case of massive chylous pericardial effusion with tamponade in a 22-year-old man, managed successfully. Lymphoscintigraphy confirmed the communication between the lymphatic trunk and the pericardial space, which was surgically ligated. There are relatively few published reports of idiopathic chylopericardium, and its pathogenesis remains unknown. The most effective treatment is surgical ligation of the thoracic duct and creation of a pericardial window.

Adult↗

PubMed2004

A model-based optimization framework for the inference on gene regulatory networks from DNA array data.

MOTIVATION: Identification of the regulatory structures in genetic networks and the formulation of mechanistic models in the form of wiring diagrams is one of the significant objectives of expression profiling using DNA microarray technologies and it requires the development and application of identification frameworks. RESULTS: We have developed a novel optimization framework for identifying regulation in a genetic network using the S-system modeling formalism. We show that balance equations on both mRNA and protein species led to a formulation suitable for analyzing DNA-microarray data whereby protein concentrations have been eliminated and only mRNA relative concentrations are retained. Using this formulation, we examined if it is possible to infer a set of possible genetic regulatory networks consistent with observed mRNA expression patterns. Two origins of changes in mRNA expression patterns were considered. One derives from changes in the biophysical properties of the system that alter the molecular-interaction kinetics and/or message stability. The second is due to gene knock-outs. We reduced the identification problem to an optimization problem (of the so-called mixed-integer non-linear programming class) and we developed an algorithmic procedure for solving this optimization problem. Using simulated data generated by our mathematical model, we show that our method can actually find the regulatory network from which the data were generated. We also show that the number of possible alternate genetic regulatory networks depends on the size of the dataset (i.e. number of experiments), but this dependence is different for each of the two types of problems considered, and that a unique solution requires fewer datasets than previously estimated in the literature. This is the first method that also allows the identification of every possible regulatory network that could explain the data, when the number of experiments does not allow identification of unique regulatory structure.

Algorithms↗

PubMedDate not supplied

Third heart sound revisited: a correlation with N-terminal pro brain natriuretic peptide and echocardiography to detect left ventricular dysfunction.

BACKGROUND: Auscultation of the third heart sound is an age-old sign for predicting ventricular dysfunction. New technology and biomarkers like two-dimensional echocardiography and N-terminal pro brain natriuretic peptide, respectively, have sidelined the utility of this sign, which does not involve any cost and is readily accessible. We sought to find the predictive accuracy of third heart sound and its correlation with N-terminal pro brain natriuretic peptide and ejection fraction using two-dimensional echocardiography to detect left ventricular dysfunction in patients of acute coronary syndrome. METHODS AND RESULTS: One hundred and ten patients presenting with acute coronary syndrome [acute ST elevation myocardial infarction (n=74) and non-ST elevation myocardial infarction (n=36)] were prospectively studied. A senior cardiologist, blinded to N-terminal pro brain natriuretic peptide and ejection fraction results auscultated for a left ventricular third heart sound in each patient. Ejection fraction was measured using modified Simpson's technique on two-dimensional echocardiography and N-terminal pro brain natriuretic peptide was measured using electrochemiluminiscence assay. Median levels of N-terminal pro brain natriuretic peptide were used to provide a dichotomous approach for analysis of the data. Third heart sound was present in 40 patients (acute ST elevation myocardial infarction: n=27, non-ST elevation myocardial infarction: n=13) and absent in 70 patients (acute ST elevation myocardial infarction: n=47, non-ST elevation myocardial infarction: n=23). The sensitivity and specificity of third heart sound for predicting N-terminal pro brain natriuretic peptide above median was 65.5% and 92.7%, respectively. The positive and negative predictive value was 90% and 73%, respectively. The N-terminal pro brain natriuretic peptide of those having third heart sound was 4081 +/- 2705 pg/ml compared to 1239.3 +/- 1169 pg/ml in those without third heart sound (p < 0.001). The sensitivity of third heart sound to detect ejection fraction <45% was 67.9% while the specificity was 74.4%. The positive and the negative predictive values were 47.5% and 87.1%, respectively. The ejection fraction of patients having third heart sound was 47.5 +/- 11.3% compared to 56 +/- 10.4% without third heart sound (p < 0.001). CONCLUSIONS: Auscultation of third heart sound has a good specificity and predictive value for predicting elevated N-terminal pro brain natriuretic peptide and left ventricular dysfunction. Thus age-old clinical cardiology still holds its forte in this new era of technology-driven cardiology.

Heart Sounds↗

PubMedDate not supplied

N-terminal probrain natriuretic peptide as a predictor of short-term outcomes in acute myocardial infarction.

BACKGROUND: Risk stratification and prediction of high risk for mortality in patients with acute coronary syndromes is based on clinical evaluation, electrocardiogram, biochemical markers and various risk assessment scores. There is emerging evidence that N-terminal probrain natriuretic peptide possesses several characteristics of an ideal biomarker. In this study we looked into the role of N-terminal probrain natriuretic peptide in risk stratification and prediction of short-term events including mortality in patients presenting with acute coronary syndrome. METHODS AND RESULTS: A total of 120 consecutive patients admitted with a diagnosis of acute myocardial infarction, including both ST elevation myocardial infarction (n=80) and non-ST elevation myocardial infarction (n=40) were enrolled. Serum N-terminal probrain natriuretic peptide was measured using electrochemiluminiscence assay (Roche Diagnostics), on the Elecsys 2010 system. On two-dimentional echocardiography, modified Simpson's technique was used to measure the ejection fraction along with end-systolic volume. Various other demographic variables, echocardiographic parameters and risk scores were also assessed. Follow-up at day 30 included a two-dimentional echocardiographic evaluation and assessment for worsening heart failure, recurrent ischemia, and repeat hospitalization. Death due to cardiovascular cause by 30 days was also noted. The mean value of N-terminal probrain natriuretic peptide for the whole cohort was 2307 +/- 2287 pg/ml (271.4 +/- 269.1 pmol/L). For the purpose of comparative analysis, the median value was determined [1403 pg/ml (165 pmol/L)]. In patients having N-terminal probrain natriuretic peptide above median, the end-systolic volume was higher while ejection fraction was significantly lower at baseline (p<0.05). At 30 days follow-up, there was a further decline in ejection fraction from 47.7 +/- 11.4 to 43.9 +/- 9.9 (p<0.05), and clinical outcomes were worse in this group. There was a 5% mortality in the entire study group and all patients who died had N-terminal probrain natriuretic peptide above median. On multivariate logistic regression analysis, N-terminal probrain natriuretic peptide above median (OR=32.79, 95% CI 8.74-123.1, p<0.001) emerged as the strongest predictors of adverse outcomes, including 30-day mortality (p<0.001). CONCLUSIONS: N-terminal probrain natriuretic peptide emerged as a strong prognostic tool across the spectrum of acute myocardial infarction and had the strongest predictive value for short-term adverse outcomes including death.

Adult↗