Nabil Awan

Traumatic brain injury (TBI) and subsequent post-traumatic epilepsy (PTE) often impair daily activities and mental health (MH), which contribute to long-term TBI-related disability. PTE also affects driving capacity, which impacts functional independence, community participation, and satisfaction with life (SWL). However, studies evaluating the collective impact of PTE on multidimensional outcomes are lacking. Thus, we generated a model to investigate how PTE after moderate-to-severe (ms)TBI affects TBI-associated impairments, limits activities and participation, and influences SWL. Of 5108 participants with msTBI enrolled into the National Institute for Disability, Independent Living, and Rehabilitation Research TBI Model Systems between 2010 and 2018 and with seizure-event data available at year-1 post-TBI, 1214 had complete outcome data and 1003 had complete covariate data used for analysis. We constructed a conceptual framework illustrating hypothesized interrelationships between year-1 PTE, driving status, functional independence measure (FIM), depression and anxiety, as well as year-2 participation, and SWL. We performed univariate and multivariable linear and logistic regressions. A covariate-adjusted structural equation model (SEM), using the lavaan package (R), assessed the conceptual framework's suitability in establishing PTE links with outcomes 1-2 years post-injury. Multiple parameters were evaluated to assess SEM fit. Year-1 PTE was correlated with year-1 FIM motor (standardized coefficient, β_std = -0.112, p = 0.007) and showed a trend level association with year-1 FIM cognition (β_std = -0.070, p = 0.079). Individuals with year-1 PTE were less likely to drive independently at year 1 (β_std = -0.148, p < 0.001). In addition, FIM motor (β_std = 0.323, p < 0.001), FIM cognition (β_std = 0.181, p = 0.012), and anxiety (β_std = -0.135, p = 0.024) influenced driving status. FIM cognition was associated with year-1 depression (β_std = 0.386, p < 0.001) and year-1 anxiety (β_std = 0.396, p < 0.001), whereas year-1 FIM motor (β_std = 0.186, p = 0.003), depression (β_std = -0.322, p = 0.011), and driving status (β_std = 0.233, p < 0.001) directly affected year-2 objective life participation metrics. Moreover, year-1 depression (β_std = -0.382, p = 0.001) and year-2 participation (β_std = 0.160, p < 0.001) had direct effects on year-2 SWL. SWL was influenced indirectly by year-1 variables, including functional impairment, anxiety, and driving status-factors that impacted year-2 participation directly or indirectly, and consequently year-2 SWL, forming a complex relationship with year-1 PTE. A sensitivity analysis SEM showed that the number of MH disorders was associated with participation and SWL (p < 0.001), and this combined MH variable was directly related to driving status (p < 0.02). Developing PTE during year-1 after msTBI affects multiple aspects of life. PTE effects extend to motor and cognitive abilities, driving capabilities, and indirectly, to life participation and overall SWL. The implications underscore the crucial need for effective PTE management strategies during the first year post-TBI to minimize the adverse impact on factors influencing multidimensional year-2 participation and SWL outcomes. Addressing transportation barriers is warranted to enhance the well-being of those with PTE and msTBI, emphasizing a holistic approach. Further research is recommended for SEM validation studies, including testing causal inference pathways that might inform future prevention and treatment trials.

Objective: Although traumatic brain injury (TBI) and post‐traumatic epilepsy (PTE) are common, there are no prospective models quantifying individual epilepsy risk after moderate‐to‐severe TBI (msTBI). We generated parsimonious prediction models to quantify individual epilepsy risk between acute inpatient rehabilitation for individuals 2 years after msTBI.Methods: We used data from 6089 prospectively enrolled participants (≥16 years) in the TBI Model Systems National Database. Of these, 4126 individuals had complete seizure data collected over a 2‐year period post‐injury. We performed a case‐complete analysis to generate multiple prediction models using least absolute shrinkage and selection operator logistic regression. Baseline predictors were used to assess 2‐year seizure risk (Model 1). Then a 2‐year seizure risk was assessed excluding the acute care variables (Model 2). In addition, we generated prognostic models predicting new/recurrent seizures during Year 2 post‐msTBI (Model 3) and predicting new seizures only during Year 2 (Model 4). We assessed model sensitivity when keeping specificity ≥.60, area under the receiver‐operating characteristic curve (AUROC), and AUROC model performance through 5‐fold cross‐validation (CV).Results: Model 1 (73.8% men, 44.1 ± 19.7 years, 76.1% moderate TBI) had a model sensitivity = 76.00% and average AUROC = .73 ± .02 in 5‐fold CV. Model 2 had a model sensitivity = 72.16% and average AUROC = .70 ± .02 in 5‐fold CV. Model 3 had a sensitivity = 86.63% and average AUROC = .84 ± .03 in 5‐fold CV. Model 4 had a sensitivity = 73.68% and average AUROC = .67 ± .03 in 5‐fold CV. Cranial surgeries, acute care seizures, intracranial fragments, and traumatic hemorrhages were consistent predictors across all models. Demographic and mental health variables contributed to some models. Simulated, clinical examples model individual PTE predictions.Significance: Using information available, acute‐care, and year‐1 post‐injury data, parsimonious quantitative epilepsy prediction models following msTBI may facilitate timely evidence‐based PTE prognostication within a 2‐year period. We developed interactive web‐based tools for testing prediction model external validity among independent cohorts. Individualized PTE risk may inform clinical trial development/design and clinical decision support tools for this population.

Introduction: Leiomyoma is one of the most common benign smooth muscle tumor of the uterus which on rare occasions may grow into the vessels and extend up till the Inferior Vena cava or the heart and hence be referred to as Intra-Venous Leiomyomatosis and Intra-Cardiac Leiomyomatosis respectively. Case Report: We herein report a rare presentation of leiomyoma in a 46 year old female who presented with complaints of shortness of breath on exertion associated with palpitations for the past 1 year with a history of irregular menstrual bleeding. Ultrasonography of the abdomen and pelvis revealed an enlarged, distorted uterus with multiple intramural fibroids. A trans-thoracic echocardiography was then performed which showed a large right atrial mass. To investigate further, a contrast enhanced computed tomography was performed covering entire chest and upper abdomen. It showed a large lesion in right atrium of heart measuring 6x5cm.

Mitral valve pathology in rheumatic heart disease patients is a common cause of secondary pulmonary hypertension (PH). Our aim was to evaluate pulmonary hypertension severity as a predictor of in-hospital mortality and early complications following mitral valve replacement. A retrospective review of rheumatic heart disease patients who underwent mitral valve replacement between January 2017 and August 2020 was performed. Systolic pulmonary artery pressure (sPAP) was used to classify patients as no PH (60 mmHg). Patients subjected to additional cardiac procedures (such as aortic valve replacement and coronary artery bypass grafting) were excluded from the study sample. The study group was composed of 159 patients (mean age: 40; 73 male, 86 female) categorized as no PH (n = 32; 20.1%), mild PH (n = 14; 8.8%), moderate PH (n = 65, 40.9%) and severe PH (n = 48, 30.2%) groups. Patient demographic data and preoperative comorbidities were comparable among the four groups. Use of intraoperative and postoperative blood products was similar in all the groups. Severe PH patients had similar in-hospital mortality (4.2%; p = 0.74) as in groups with lesser degrees of pulmonary hypertension. Likewise, increasing severity of pulmonary hypertension did not confer any significant increase in early postoperative complications, namely prolonged ICU stay (10.4%; p = 0.41), prolonged ventilation (2.1%; p = 0.70), reintubation (4.2%; p = 0.90), reopening for bleeding tamponade (6.3%; p = 0.39), new-onset renal failure (6.3%; p = 0.91), postoperative stroke (4.2%; p = 0.52) or prolonged length of stay (mean: 5.6 + 2.8 days; p = 0.49). Increasing severity of pulmonary hypertension does not appear to have a significant impact on in-hospital mortality or early postoperative outcomes of patients undergoing mitral valve replacement.

Coastal morphology makes Bangladesh vulnerable to environmental hazards and climate change. Therefore, environmental characteristics may shape population health, including child health. The prevalence of stunting among under-five aged (U5) children is high in Bangladesh. However, there is a lack of research on environmental predictors of stunting. This study aimed to assess the association between community-level environmental characteristics and stunting using pooled data from the three latest Bangladesh demographic and health surveys (BDHS). According to the multilevel model, rainfall, distance to protected areas, and vegetation index showed a nonlinear association with stunting. The temperature was inversely, and distance to water bodies was positively related to stunting. Overall, results evidence the environmental characteristics are predictive of stunting, and these characteristics should be taken into account during intervention design to minimise the negative effects of environmental change on child health. Further research is also necessary to comprehend the causal pathways between environmental characteristics and stunting in Bangladesh.

Infant and young child feeding (IYCF) is crucial for the growth, development, and survival of a child. This study aims to examine the factors associated with IYCF practices among the under-2 aged children in Bangladesh and spatial variability. A total of 2336 children aged 6–23 months were selected from the 2014 Bangladesh Demographic and Health Survey (BDHS). A multi-level logistic regression was used to determine the association between socio-demographic and health-related factors accounting for the cluster effects. An adaptive bandwidth kernel density estimator (KDE) was used to investigate the spatial variability of IYCF practices in Bangladesh. The prevalence of minimum dietary diversity (MDD), minimum meal frequency (MMF), and minimum acceptable diet (MAD) were 29%, 47%, and 19% respectively, where the suboptimal IYCF practice was 96% among them. The study findings show that higher maternal age at childbirth and maternal education level are positively associated with MDD, MMF, and MAD. The likelihood of MMF and MAD was higher for children whose mothers had the decision-making abilities (adjusted odds ratio, [AOR] 1.23 and 1.26, respectively) and had exposure to media (AOR 1.43 and 1.38, respectively). Four or more antenatal care (ANC) visits positively associated with the MDD (AOR 1.47; 95% confidence interval [CI] 1.07–2.02) and ICFI (AOR 3.06; 95% CI 1.24–7.54). The heatmap shows Northern parts of Bangladesh performed better than South-West parts in child feeding practices. Overall, age-appropriate IYCF practices are not satisfactory, and many maternal characteristics contribute significantly to this. Geospatial inequalities are also notable across Bangladesh. The current scenario reinforces the need for programmes and interventions that address the spectrum of IYCF practices and help reduce spatial disparities.

Determining the optimal lineup and batting order have ever been a challenge in ODI cricket for the Bangladesh team management. Over the years, we have seen them trying different batsmen in various positions and the process is still going on. While a stable batting order is crucial for long-term success in the game, this is understandably a difficult problem to decide because there are so many determinants that a team needs to consider. These determinants are usually correlated and optimally mapping them into a single dimension can help us make the problem easier and comment about what’s best on statistical grounds. In this article, we propose a sequential principal component-based algorithm to evaluate the players’ performances in batting and bowling, and to order the batting positions of the recent Bangladesh national cricket team players to find the best squad. In particular, the first principal component explains a substantial portion of the variation in a linear combination of some commonly used measures of cricket prowess. The algorithm focuses on obtaining the best batting line-up using successive principal components for each position. We also layout different strategies of team formation based on the bowling performances for different conditions and pitches.

While there is a plethora of research on people management and high-commitment management, most are focused on commercial enterprises. Even the high-commitment management literature on commercial organisations argues that we need to move beyond the confines of financial performance. There are relatively few studies of high-commitment management which focus on hospitals. This is despite the fact that human resources are a major cost and source of performance leverage in hospitals.

Low birth weight (LBW) remains a leading global cause of childhood morbidity and mortality. This study leverages a large national survey to determine current prevalence and socioeconomic, demographic and heath related factors associated with LBW in Bangladesh. Data from the Multiple Indicator Cluster Survey (MICS) 2012–13 of Bangladesh were analyzed. A total of 2319 women for whom contemporaneous birth weight data was available and who had a live birth in the two years preceding the survey were sampled for this study. However, this analysis only was able to take advantage of 29% of the total sample with 71% missing birth weight for newborns. The indicator, LBW (< 2500 g) of infants, was examined as the outcome variable in association with different socioeconomic, demographic and health-related covariates. Mixed-effects logistic regression was performed to identify possible factors related to LBW. In the selected sub-sample, about 20% of infants were born with LBW, with lowest rates observed in Rajshahi (11%) and highest rates in Rangpur (28%). Education of mothers (adjusted odds ratio [AOR] 0.52, 95% confidence interval [CI] 0.39–0.68 for secondary or higher educated mother) and poor antenatal care (ANC) (AOR 1.40, 95% CI 1.04–1.90) were associated with LBW after adjusting for mother’s age, parity and cluster effects. Mothers from wealthier families were less likely to give birth to an LBW infant. Further indicators that wealth continues to play a role in LBW were that place of delivery, ANC and delivery assistance by quality health workers were significantly associated with LBW. However there has been a notable fall in LBW prevalence in Bangladesh since the last comparable survey (prevalence 36%), and an evidence of possible elimination of rural/urban disparities. Low birth weight remains associated with key indicators not just of maternal poverty (notably adequate maternal education) but also markers of structural poverty in health care (notably quality ANC). Results based on this sub-sample indicate LBW is still a public health concern in Bangladesh and an integrated effort from all stakeholders should be continued and interventions based on the study findings should be devised to further reduce the risk of LBW.