Clinical Profile, Intensive Care Needs and Outcome of Children with Dilated Cardiomyopathy Associated with Vitamin D Deficiency: A 5-year PICU Experience.

Aim: To describe the clinical profile, treatment details, intensive care needs, and long-term outcome of children with dilated cardiomyopathy (DCM) associated with Vitamin D deficiency (VDD). Materials and methods: Case records of 14 children with DCM associated with VDD [25(OH)D3 levels <20 ng/mL] admitted to the pediatric intensive care unit (PICU) of a tertiary care teaching hospital between January 2017 and December 2021 were retrospectively analyzed for clinical features, echocardiographic findings, treatment details, intensive care needs, and outcomes. Results: The median (IQR) age was 6 (2-9) months and 71% (n=10) were males. The common modes of presentation included respiratory distress or failure (78.6%), congestive cardiac failure (71.4%), cardiogenic shock (37.5%), and seizures and encephalopathy (14.3% each). The median (IQR) serum calcium was 8.7 (7-9.5) mg%, ionized calcium 0.7 (0.7-1.1) mmol/L, alkaline phosphatase 343 (316-415) IU/L, phosphate 3.5 (2.6-4.5) mg%, PTH 115 (66-228) pg/mL, and 25(OH)D3 5 (3-7) ng/mL. The median (IQR) left ventricular ejection fraction (LVEF) at admission was 22 (17-25)%. The treatment included intravenous calcium infusion (35.7%), vitamin D supplementation in all (57.1% parenteral and 42.9% oral), mechanical ventilation (35.7%), and vasoactive drugs (57.1%). There was no mortality. The median (IQR) duration of PICU and hospital stay was 76 (31-98) hours and 6 (4.7-10) days, respectively. Out of 14 children, 10 (71.4%) were followed-up till median (IQR) of 10 (7-58) months. All were asymptomatic and had normal LEVF (except one had residual moderate mitral regurgitation). Conclusion: Vitamin D deficiency is a potentially treatable and reversible cause of DCM in children. How to cite this article: Kumar S, Randhawa MS, Angurana SK, Nallasamy K, Bansal A, Kumar MR, et al. Clinical Profile, Intensive Care Needs and Outcome of Children with Dilated Cardiomyopathy Associated with Vitamin D Deficiency: A 5-year PICU Experience. Indian J Crit Care Med 2023;27(7):510-514.

Population modeling of oilseed brassica aphids and their biocontrol agents with weather parameters in the north-west Himalayan region of India.

We studied the impact of weather parameters on the population build-up of Brevicoryne brassicae (L.) (Cabbage aphid), Lipaphis erysimi (Kalt.) (Mustard aphid), Myzus persicae (Sulzer) (Green peach aphid) and their biocontrol agents (coccinellids, syrphids, and a parasitoid, Diaeretiella rapae M'Intosh) on oilseed brassicas in Himachal Pradesh, India, during winters from 2016-2017 to 2018-2019. The temperature and sunshine resulted in the build-up of B. brassicae and their biocontrol agents' population, while rainfall and relative humidity caused a negative influence at surveyed locations. The L. erysimi and M. persicae populations showed an inverse correlation with the density-independent factors at most locations. Correlation coefficients indicated a negative correlation of the coccinellids population with the build-up of L. erysimi and M. persicae, while the predator population was positively related to the B. brassicae population at maximum locations. Parasitization by D. rapae showed a negative relationship with the aphid population. Stepwise regression analysis showed that minimum temperature and rainfall had a significant effect on the variability in the population of aphids. The predictive model could interpret more than 90% variation by minimum temperature in the coccinellid population at the surveyed locations. Further, regression analysis with temperature could explain up to 94% variability in parasitization by D. rapae. This study will contribute to predicting the changes that may occur in a population of aphids concerning the weather.

Psychosocial issues among paediatric health-care workers posted in intensive care unit during COVID-19 pandemic: A questionnaire-based survey (Psy-Co-19 survey).

AIM: To understand the moral distress experienced by health-care workers (HCWs) in the COVID paediatric intensive care unit (PICU). We also aimed to assess the psychological well-being and the coping mechanisms used by HCWs. METHODS: A prospective observational cross-sectional study was conducted from July to September 2021, involving all HCWs who worked in the COVID PICU. Moral distress using Moral Distress for Health-care Professionals (MMD-HPs) scale, psychological well-being using Trauma Screening Questionnaire (TSQ) and coping strategies adopted by HCWs using Brief-COPE (Coping Orientation to Problems Experienced) were measured. RESULTS: One hundred and eighty-four HCW data were examined. The most common causes of moral distress among HCWs were compromised patient care caused by a lack of resources and caring for more patients than they could safely handle. Moral distress was the same regardless of the HCWs' job profile, marital status, number of children or age. The TSQ revealed psychological stress in 23.3% of HCWs with Post-traumatic Stress Disorder, significantly higher in HCWs under the age of 30 and without children. Few HCWs turned to substance use, self-blame or denial as coping mechanisms; instead, acceptance, self-distraction and emotional support were the most frequently used. CONCLUSION: The most common reasons for moral and psychological distress perceived by participants were insufficient staff and organisational support. Younger HCWs and those without children experienced higher levels of psychological distress. HCWs' typical coping mechanisms are constructive, such as seeking help and support from others, reframing situations and meditation. Health-care administrators must develop a framework to assist HCWs in dealing with such serious issues.

Severe dengue associated with Staphylococcus aureus sepsis in pediatric patients: a case series.

BACKGROUND: Staphylococcus aureus co-infection is seldom reported in children with severe dengue. METHODOLOGY: In this retrospective study, we reported five children with severe dengue and S. aureus co-infection admitted to pediatric intensive care unit (PICU) during July-December 2021. RESULTS: All children had prolonged fever, persistence of bilateral pleural effusion beyond the critical phase, thrombocytopenia and raised inflammatory markers [C-reactive protein (CRP) and procalcitonin]. S. aureus was isolated from pleural fluid (n = 2, 40%), blood (n = 2, 40%) and endotracheal aspirate (n = 1, 20%). Four children (80%) grew methicillin-sensitive S. aureus, while 1 (20%) had methicillin-resistant S. aureus. Two children (40%) had septic thromboemboli in skin, and 1 (20%) had limb cellulitis. One child required anterior thoracotomy, pericardiectomy and bilateral pleural decortication, while all other children required intercostal chest tube drainage. All children required prolonged targeted antibiotics, invasive mechanical ventilation and had prolong stay in PICU and all of them survived. CONCLUSION: In children with severe dengue, persistence of fever, persistence of pleural effusion beyond critical phase and raised CRP and procalcitonin should raise suspicion of bacterial/S. aureus co-infection.

A Composite Microfiber for Biodegradable Stretchable Electronics.

Biodegradable stretchable electronics have demonstrated great potential for future applications in stretchable electronics and can be resorbed, dissolved, and disintegrated in the environment. Most biodegradable electronic devices have used flexible biodegradable materials, which have limited conformality in wearable and implantable devices. Here, we report a biodegradable, biocompatible, and stretchable composite microfiber of poly(glycerol sebacate) (PGS) and polyvinyl alcohol (PVA) for transient stretchable device applications. Compositing high-strength PVA with stretchable and biodegradable PGS with poor processability, formability, and mechanical strength overcomes the limits of pure PGS. As an application, the stretchable microfiber-based strain sensor developed by the incorporation of Au nanoparticles (AuNPs) into a composite microfiber showed stable current response under cyclic and dynamic stretching at 30% strain. The sensor also showed the ability to monitor the strain produced by tapping, bending, and stretching of the finger, knee, and esophagus. The biodegradable and stretchable composite materials of PGS with additive PVA have great potential for use in transient and environmentally friendly stretchable electronics with reduced environmental footprint.

Damage Potential, Effect on Germination, and Development of Sitophilus oryzae (Coleoptera: Curculionidae) on Wheat Grains in Northwestern Himalayas.

The present investigation was carried out to study the biological parameters and orientation of Sitophilus oryzae (L.) toward wheat cultivar HPW-236 and mixed grains of different cultivars (HPW-155, HPW-236, HPW-249, HPW-349, HPW-360, HS-490, and VL-892). The incubation period, larval period, pupal period, and total life cycle period of S. oryzae was longer when fed on mixed grains as compared to HPW-236. Also, the weevils were more oriented toward HPW-236 and lower germination rates were observed from HPW-236 than mixed cultivars when exposed to S. oryzae. We also evaluated quantitative losses caused by S. oryzae in different cultivars of wheat recommended in the northwestern Himalayas under free-choice conditions. The weevil inflicted greater damage and weight loss in grains of HPW-236 while it was negligible in the case of HPW-360 and HPW-249. HPW-236 which is the most cultivated variety of wheat in northwestern Himalayas proved to be highly susceptible to the weevil and provided a more suitable environment for weevil's development. Therefore, this particular cultivar can be avoided for prolong storage and the farmers should prefer cultivars such as HPW-360 and HPW-249, which proved to be least affected the weevil.

Influence of Different Plant Powders as Grain Protectants on Sitophilus oryzae (L.) (Coleoptera: Curculionidae) in Stored Wheat.

ABSTRACT: Sitophilus oryzae (L.) is the most widespread and destructive insect of stored wheat throughout the world. The main aim of the study was to find ecofriendly alternatives to chemical fumigants and synthetic insecticides for the control of weevils in stored wheat. The leaf powder of Ageratum conyzoides proved to be the best treatment against the weevil that resulted in maximum mean cumulative mortality (96.67%), the lowest monthly population increase (18.33), and the least grain damage (12.61%) and weight loss (1.75%) during 6 months of storage. The next best treatments were the drupe powder of Melia azedarach, followed by Vitex negundo and Ocimum sanctum. A. conyzoides, Melia azedarach, and O. sanctum were found effective even 3 months after preparation. The leaf powder of Murraya koenigii resulted into the lowest mean cumulative adult mortality (14.23%), the highest monthly population increase (132.78), and the highest grain damage (47.50%) and weight loss (11.07%), thus proving to be the least effective.

Prediction of Skin Disease Using Ensemble Data Mining Techniques and Feature Selection Method-a Comparative Study.

Nowadays, skin disease is a major problem among peoples worldwide. Different machine learning techniques are applied to predict the various classes of skin disease. In this research paper, we have applied six different machine learning algorithm to categorize different classes of skin disease using three ensemble techniques and then a feature selection method to compare the results obtained from different machine learning techniques. In the proposed study, we present a new method, which applies six different data mining classification techniques and then developed an ensemble approach using bagging, AdaBoost, and gradient boosting classifiers techniques to predict the different classes of skin disease. Further, the feature importance method is used to select important 15 features which play a major role in prediction. A subset of the original dataset is obtained after selecting only 15 features to compare the results of used six machine learning techniques and ensemble approach as on the whole dataset. The ensemble method used on skin disease dataset is compared with the new subset of the original dataset obtained from feature selection method. The outcome shows that the dermatological prediction accuracy of the test dataset is increased compared with an individual classifier and a better accuracy is obtained as compared with subset obtained from feature selection method. The ensemble method and feature selection used on dermatology datasets give better performance as compared with individual classifier algorithms. Ensemble method gives more accurate and effective skin disease prediction.

Classification of Skin Disease using Ensemble Data Mining Techniques.

Objective: Skin diseases are a major global health problem associated with high number of people. With the rapid development of technologies and the application of various data mining techniques in recent years, the progress of dermatological predictive classification has become more and more predictive and accurate. Therefore, development of machine learning techniques, which can effectively differentiate skin disease classification, is of vast importance. The machine learning techniques applied to skin disease prediction so far, no techniques outperforms over all the others. Methods: In this research paper, we present a new method, which applies five different data mining techniques and then developed an ensemble approach that consists all the five different data mining techniques as a single unit. We use informative Dermatology data to analysis different data mining techniques to classify the skin disease and then, an ensemble machine learning method is applied. Results: The proposed ensemble method, which is based on machine learning was tested on Dermatology datasets and classify the type of skin disease in six different classes like include C1: psoriasis, C2: seborrheic dermatitis, C3: lichen planus, C4: pityriasis rosea, C5: chronic dermatitis, C6: pityriasis rubra. The results show that the dermatological prediction accuracy of the test data set is increased compared to a single classifier. Conclusion: The ensemble method used on Dermatology datasets give better performance as compared to different classifier algorithms. Ensemble method gives more accurate and effective skin disease prediction.

Plasma Hepcidin Levels in Healthy Children: Review of Current Literature Highlights Limited Studies.

BACKGROUND: There are few studies that highlight pediatric hepcidin reference ranges especially from Asian subcontinent. In current study, plasma from 131 children (72 boys and 59 girls; 1 to 12 y) was analyzed for hepcidin-25 by enzyme-linked immunosorbent assay. OBSERVATIONS: The median (interquartile range) plasma hepcidin in boys was 21.89 ng/mL (16.50 to 51.70 ng/mL) and girls was 21.95 ng/mL (19.20 to 47.70 ng/mL). No statistically significant difference (P=0.937) of plasma hepcidin levels in sex was noted. However, multiple regression analysis revealed a significant correlation between plasma hepcidin levels and ferritin (P=0.000). CONCLUSIONS: Our study results highlight relatively lower median hepcidin values in children 1 to 12 years of age as compared with western data. This may be attributed to either lack of a harmonized and standard enzyme-linked immunosorbent assay detection methodology or to presence of clinically significant polymorphisms in hepcidin gene in our population.