Study of behavioral and psychosocial factors relating to needle stick injuries in nursing staff of a tertiary care cancer hospital of Punjab, India.

Background and Objectives: Needle stick injury (NSI) is the most dreaded occupational health hazard affecting a healthcare worker (HCW) psychologically and physically. The risk of infection post needle stick injury ranges between 1.9% to greater than 40% for HBV infections, 2.7-10% for HCV and 0.2-0.44% for HIV infections. As per National AIDS Control Organisation (NACO) records, nursing staff is at highest risk (43%) followed by physicians (28%). The main objective of this study was to evaluate knowledge of nursing staff about needle stick injuries and to study factors leading to such incidents in their working areas, impart them knowledge regarding the same and fill gaps in knowledge. Materials and Methods: This is a cross-sectional retrospective analysis involving nursing staff and students. p values were calculated using SPSS software. Results: Overall NSI prevalence among nursing staff and students was 51.6% whereas in more exposed and less exposed group was 47.45% and 10.16% respectively (p=0.2056). The most common cause of NSI incident was recapping of needle (38.5%) followed by transferring needle to sharp container (35%). Conclusion: Consequences of NSI are serious and this study has tried to emphasize on the need to study the factors leading to NSI.

Association between calcium supplementation and gestational hypertension, and preeclampsia: A Meta-analysis of 26 randomized controlled trials.

BACKGROUND: Pre-eclampsia and eclampsia are common causes of morbidity and mortality, especially in low-income countries. Reducing adverse outcomes associated with hypertensive disorders of pregnancy has been the ultimate priority in recent years. We aim to evaluate the association between calcium supplementation and preeclampsia and gestational hypertension risk among pregnant women. METHODS: A systematic literature search was performed in electronic databases from inception to 15th July 2023, including only randomized controlled trials. Odds ratio (OR) were, and their corresponding 95% confidence interval (95% CI). RESULTS: A total of 26 studies with 20,038 patients (10,003 patients with calcium supplements and 10,035 patients with placebo group) were included in the analysis. The Pooled analysis of primary outcome shows that calcium supplements reduce the risk of preeclampsia by 49% (OR, 0.51(95%CI: 0.40-0.66), P<0.001), and reduce the risk of gestational hypertension by 30% (OR, 0.70 (95%CI: 0.58-0.85)), P<0.001) compared to placebo. There was a trend of lower incidence of preterm delivery (OR, 0.88 (95%CI: 0.71-1.09), P=0.23), labor induction (OR, 0.90 (95%CI: 0.78-1.03), P=0.13), small for gestational age (OR, 0.70 (95% CI:0.37-1.32), P = 0.27), low birth weight (OR, 0.96 (95%CI: 0.86-1.08), P=0.53), perinatal mortality (OR, 0.88 (95%CI: 0.72-1.09), P=0.24), and maternal mortality (OR, 0.48 (95%CI: 0.12-1.84), P=0.28) among calcium supplementation group compared with the placebo group, however, statistical signifance was not achieved. CONCLUSION: This study shows that calcium supplements are associated with a significant reduction in the risk of preeclampsia and gestational hypertension and a trend toward better maternal and fetal-related outcomes.

Meta-Analysis of Racial Disparity in Clinical Outcome Among Congenital Heart Disease Patients Postsurgery.

Congenital heart disease (CHD), the most prevalent congenital disorder in newborns, is a leading cause of infant mortality. Mortality rates have declined over time with advancements in knowledge and management approaches. Despite these advancements, studies on racial disparities in CHD surgical mortality have yielded inconclusive results. We aim to evaluate the disparity among the clinical outcomes post-CHD surgery. A comprehensive literature search was conducted on PubMed, Embase, and Scopus utilizing predefined MeSH terms coupled with Boolean operators "AND" and "OR." The search strategy included the terms "congenital heart disease" AND "racial disparity" OR "minorities" OR "Black" OR "White" AND "mortality." Our meta-analysis sought observational studies published from inception until 10th March 2023 reporting post-surgical incidence of mortality in Black and White patients with CHD. We identified 5 studies, including 79616 patients with CHD. Of these, 15,124 Black patients and 64,492 White patients who underwent for CHD surgery. All included patients were less than 18 years of age with a definitive diagnosis of CHD. The mean length of the hospital stay was (11.5 vs 10.10) days, respectively. The pooled analysis showed that Black patients with CHD have significantly higher odds of postoperative mortality (OR, 1.46 (95%CI: 1.31-1.62), P < 0.001) with low heterogeneity across the studies. This very first meta-analysis shows that Black patients are at increased risk of mortality post-CHD surgery compared to White patients. These disparities need to be addressed, and proper guidelines need to be made with better medical infrastructure and treatment options for racial minority groups.

Machine learning models trained on synthetic datasets of multiple sample sizes for the use of predicting blood pressure from clinical data in a national dataset.

INTRODUCTION: The potential for synthetic data to act as a replacement for real data in research has attracted attention in recent months due to the prospect of increasing access to data and overcoming data privacy concerns when sharing data. The field of generative artificial intelligence and synthetic data is still early in its development, with a research gap evidencing that synthetic data can adequately be used to train algorithms that can be used on real data. This study compares the performance of a series machine learning models trained on real data and synthetic data, based on the National Diet and Nutrition Survey (NDNS). METHODS: Features identified to be potentially of relevance by directed acyclic graphs were isolated from the NDNS dataset and used to construct synthetic datasets and impute missing data. Recursive feature elimination identified only four variables needed to predict mean arterial blood pressure: age, sex, weight and height. Bayesian generalised linear regression, random forest and neural network models were constructed based on these four variables to predict blood pressure. Models were trained on the real data training set (n = 2408), a synthetic data training set (n = 2408) and larger synthetic data training set (n = 4816) and a combination of the real and synthetic data training set (n = 4816). The same test set (n = 424) was used for each model. RESULTS: Synthetic datasets demonstrated a high degree of fidelity with the real dataset. There was no significant difference between the performance of models trained on real, synthetic or combined datasets. Mean average error across all models and all training data ranged from 8.12 To 8.33. This indicates that synthetic data was capable of training equally accurate machine learning models as real data. DISCUSSION: Further research is needed on a variety of datasets to confirm the utility of synthetic data to replace the use of potentially identifiable patient data. There is also further urgent research needed into evidencing that synthetic data can truly protect patient privacy against adversarial attempts to re-identify real individuals from the synthetic dataset.

Levelling up health: A practical, evidence-based framework for reducing health inequalities.

There are substantial inequalities in health across society which have been exacerbated by the COVID-19 pandemic. The UK government have committed to a programme of levelling-up to address geographical inequalities. Here we undertake rapid review of the evidence base on interventions to reduce such health inequalities and developed a practical, evidence-based framework to 'level up' health across the country. This paper overviews a rapid review undertaken to develop a framework of guiding principles to guide policy. To that end and based on an initial theory, we searched one electrotonic database (MEDLINE) from 2007 to July 2021 to identify published umbrella reviews and undertook an internet search to identify relevant systematic reviews, primary studies, and grey literature. Titles and abstracts were screened according to the eligibility criteria. Key themes were extracted from the included studies and synthesised into an overarching framework of guiding principles in consultation with an expert panel. Included studies were cross checked with the initial theoretical domains and further searching undertaken to fill any gaps. We identified 16 published umbrella reviews (covering 667 individual studies), 19 grey literature publications, and 15 key systematic reviews or primary studies. Based on these studies, we develop a framework applicable at national, regional and local level which consisted of five principles - 1) healthy-by-default and easy to use initiatives; 2) long-term, multi-sector action; 3) locally designed focus; 4) targeting disadvantaged communities; and 5) matching of resources to need. Decision-makers working on policies to level up health should be guided by these five principles.

Generative adversarial networks and synthetic patient data: current challenges and future perspectives.

Artificial intelligence (AI) has been heralded as one of the key technological innovations of the 21st century. Within healthcare, much attention has been placed upon the ability of deductive AI systems to analyse large datasets to find patterns that would be unfeasible to program. Generative AI, including generative adversarial networks, are a newer type of machine learning that functions to create fake data after learning the properties of real data. Artificially generated patient data has the potential to revolutionise clinical research and protect patient privacy. Using novel techniques, it is increasingly possible to fully anonymise datasets to the point where no datapoint is traceable to any real individual. This can be used to expand and balance datasets as well as to replace the use of real patient data in certain contexts. This paper focuses upon three key uses of synthetic data: clinical research, data privacy and medical education. We also highlight ethical and practical concerns that require consideration.

Clinical characteristic and epidemiological features of SARS CoV -2 disease patients from a COVID 19 designated Hospital in New Delhi.

SARS CoV -2 infection is rapidly evolving as a serious global pandemic. The present study describes the clinical characteristics of SARS CoV-2 infection patients. The Samples were subjected to RT - PCR or Rapid Antigen test for diagnosis of SARS CoV- 2. A cohort of 3745 patients with confirmed diagnosis of SARS CoV -2 infection in a tertiary care center in New Delhi, India were included in this study. Data was collected from offline and online medical records over a period of six months. Amongst 3745 SARS CoV -2 infected patients, 2245 (60%) were symptomatic and 1500 (40%) were asymptomatic. Most common presenting symptom was cough (49.3%) followed febrile episodes (47.1%), breathlessness (42.7%) and sore throat (35.1%). Cough along with breathlessness (24.1) was the most common combination of symptoms followed by fever with cough (22.7). The most common comorbidity found among symptomatic group was diabetes (42.5%) followed by hypertension (21.4%) and chronic kidney disease (18%). Comorbidities like diabetes mellitus, chronic diseases of lungs, heart and kidneys were found to be common in symptomatic group and this was found to be statistically significant (p<0.05). COVID-19 is an evolving disease and data from our study help in understanding the clinic-epidemiological profile of patients. This article is protected by copyright. All rights reserved.

Diagnostic Accuracy of Point of Care Tests for Diagnosing Celiac Disease: A Systematic Review and Meta-Analysis.

GOALS: To perform a systematic review and meta-analysis to estimate the overall diagnostic accuracy of point of care tests (POCTs) for diagnosing celiac disease (CD). BACKGROUND: Recently, POCTs for CD have been developed and are commercially available. Studies have reported significant variability in their sensitivity (70% to 100%) and specificity (85% to 100%). STUDY: We searched MEDLINE, EMBASE databases, and the Cochrane library through June 2017. Positive reference test was defined as villous atrophy along with positive celiac-specific serology and/or clinical improvement after gluten-free diet. Normal duodenal biopsy was defined as negative reference test. Bivariate random-effect model was used to present the summary estimates of sensitivities and specificities along with 95% confidence regions We assessed methodologic quality using the quality assessment of diagnostic accuracy studies-2 tool. RESULTS: The pooled sensitivity and specificity of all POCTs (based on tTG or DGP or tTG+Anti-gliadin antibodies) for diagnosing CD were 94.0% [95% confidence interval (CI), 89.9-96.5] and 94.4% (95% CI, 90.9-96.5), respectively. The pooled positive and negative likelihood ratios for POCTs were 16.7 and 0.06, respectively. The pooled sensitivity and specificity for IgA-tTG-based POCTs were 90.5% (95% CI, 82.3-95.1) and 94.8% (95% CI, 92.5-96.4), respectively. CONCLUSIONS: The pooled sensitivity and specificity of POCTs in diagnosing CD are high. POCTs may be used to screen for CD, especially in areas with limited access to laboratory-based testing. Further research assessing the diagnostic accuracy of individual POCTs and comparing it with other available POCTs is needed.

Global Prevalence of Celiac Disease: Systematic Review and Meta-analysis.

BACKGROUND & AIMS: Celiac disease is a major public health problem worldwide. Although initially it was reported from countries with predominant Caucasian populations, it now has been reported from other parts of the world. The exact global prevalence of celiac disease is not known. We conducted a systematic review and meta-analysis to estimate the global prevalence of celiac disease. METHODS: We searched Medline, PubMed, and EMBASE for the keywords celiac disease, celiac, celiac disease, tissue transglutaminase antibody, anti-endomysium antibody, endomysial antibody, and prevalence for studies published from January 1991 through March 2016. Each article was cross-referenced with the words Asia, Europe, Africa, South America, North America, and Australia. The diagnosis of celiac disease was based on European Society of Pediatric Gastroenterology, Hepatology, and Nutrition guidelines. Of 3843 articles, 96 articles were included in the final analysis. RESULTS: The pooled global prevalence of celiac disease was 1.4% (95% confidence interval, 1.1%-1.7%) in 275,818 individuals, based on positive results from tests for anti-tissue transglutaminase and/or anti-endomysial antibodies (called seroprevalence). The pooled global prevalence of biopsy-confirmed celiac disease was 0.7% (95% confidence interval, 0.5%-0.9%) in 138,792 individuals. The prevalence values for celiac disease were 0.4% in South America, 0.5% in Africa and North America, 0.6% in Asia, and 0.8% in Europe and Oceania; the prevalence was higher in female vs male individuals (0.6% vs 0.4%; P < .001). The prevalence of celiac disease was significantly greater in children than adults (0.9% vs 0.5%; P < .001). CONCLUSIONS: In a systematic review and meta-analysis, we found celiac disease to be reported worldwide. The prevalence of celiac disease based on serologic test results is 1.4% and based on biopsy results is 0.7%. The prevalence of celiac disease varies with sex, age, and location. There is a need for population-based prevalence studies in many countries.

Predictors of death in infants with probable serious bacterial infection.

BackgroundBacterial infections account for a significant proportion of neonatal and infant mortality globally. We aimed to identify predictors of death in infants with probable serious bacterial infection (PSBI) defined as signs/symptoms of possible serious bacterial infection along with baseline C-reactive protein (CRP) ≥12 mg/l.MethodsWe did a secondary analysis using the data collected from 700 infants with PSBI who participated in a randomized controlled trial in India in which zinc or placebo was given in addition to the standard antibiotics. Logistic regression was used to estimate the associations between relevant variables and death within 21 days.ResultsThose infants who were fed cow's milk or formula before the illness episode had 3.7-fold (95% confidence interval (CI) 1.5-9.3) and 5.3-fold (95% CI 2.0-13.6) higher odds of death, respectively. Lethargy (odds ratio (OR) 2.4, 95% CI 1.1-5.4) and CRP (OR 1.9, 95% CI 1.1-3.3) were also independent predictors of death. In the model including only clinical features, female gender (OR 2.25, 95% CI 1.0-5.0), abdominal distention (3.7, 95% CI 1.1-12.3), and bulging fontanelle (5.8, 95% CI 1.1-30.5) were also independent predictors for death.ConclusionFormula or cow milk feeding prior to the illness, lethargy at the time of presentation, and high serum CRP levels predicted death in infants with PSBI.