68 research outputs found
Low platelet counts in pregnancy: an alarm signal for abruption!
Background: Thrombocytopenia, defined as a platelet count less than 150 million/mm3, affects 6% to 10% of all pregnant women and other than anemia is the most common hematologic disorder in pregnancy.Methods: We studied all patients with thrombocytopenia in pregnancy from June 2012 to May 2013. There were 86 patients recruited into the study. Pregnant women with preeclampsia and suspected connective tissue disorder were also screened for thrombocytopenia. All women with platelet count of <1.50,000/µl during the study period were included.Results: Patients were grouped in to mild thrombocytopenia (platelet 100,000-149,999/µl), moderate thrombocytopenia (platelet 50,000-99,999/µl) and severe thrombocytopenia (platelet <49,999/µl. Pregnancy specific cause of thrombocytopenia was in 63 (73.2%) women and non-pregnancy specific were in 23(26.7%) patients.Conclusions: Preeclampsia and HELLP syndrome is more common cause of thrombocytopenia in pregnancy. Abruption can occur in patients with severe thrombocytopenia. Though platelet count is not routinely done in pregnancy it is advisable to do so as it may help in detecting gestational thrombocytopenia or other immune related condition
Childhood Health and Growth Trends: A Cross-Sectional Study of School Children
Childhood is a pivotal phase of human development, entails rapid growth and evolving health requirements. This cross-sectional study examines the age and sex distribution of school children across five coastal localities. To address the unique health and well-being challenges faced by school children in different regions, this cross-sectional study explores the age and sex distribution of school children across five distinct localities: Koilpathu, Karaikalmedu, Nallathur, Varichikudy, and Kottucherry. It offers a comprehensive examination of school children, encompassing demographic profiles, anthropometric measurements, and a wide array of health-related data. Our analysis revealed shifting gender proportions across age groups, with females dominating in the younger years but males surpassing females as children grow older. Particularly intriguing were the 12-year age group's scarcity of females (0.3%) and the 13-year age group's exclusive female composition (6.07%). Regarding body mass index (BMI), boys generally exhibited values near reference standards in their early years, while girls displayed lower BMI values than the reference during pre-adolescence, signaling potential nutritional concerns. Malnutrition was less prevalent in younger age groups, but overweight and obesity became more common as children aged. Gender-specific health disparities were also evident, with females more susceptible to anemia, while males had a higher prevalence of color blindness and dental health issues. These findings underscore the importance of tailored interventions to address age and gender-specific health challenges among coastal school children
CORRELATES OF EXAM PERFORMANCE IN AN INTRODUCTORY STATISTICS COURSE: BASIC MATH SKILLS ALONG WITH SELF- REPORTED PSYCHOLOGICAL/BEHAVIORAL AND DEMOGRAPHIC VARIABLES
This study investigated whether basic mathematics skills are associated with undergraduate psychology statistics course performance while simultaneously considering self-reported psychological/behavioral and demographic variables. Participants (n = 460) completed a Math Assessment for College Students (MACS), which included questions ranging from calculating percentages to graphical interpretation. The researchers used a discriminant correspondence analysis to reveal differences in course performance evaluated as the average of three exam grades. For the variation in the average exam scores accounted for by our model, the MACS scores provided the largest contribution. Other variables associated with better exam grades included white ethnicity, non-transfer status, lower year in school, and low procrastination. The researchers discuss the implications for helping instructors identify areas of basic mathematical deficiency and strength
Mental health literacy in a diverse sample of undergraduate students: demographic, psychological, and academic correlates
Background: Investigating variables associated with mental health literacy in the college-age population takes us one step closer to providing intervention for this vulnerable group, where growing rates of psychological disorders are a serious public concern. This study adds to the existing literature by incorporating, within a single model, multi-faceted variables (demographic, psychological, and academic) that contribute to mental health literacy in demographically and ethnically diverse college students.
Methods: Participants were undergraduate students enrolled at nine different colleges that are part of a large, urban, public university system. A total of 1213 respondents (62.0% female, 73.3% non-white) completed an in- person assessment of mental health literacy and answered questions about demographics, college experience, and mental health experience. Data were analyzed to identify which variables best discriminated between high, mid- level, and low performers on this assessment.
Results: Discriminant correspondence analysis revealed that the difference between high and low performers (accounting for 90.27% of the total variance) was driven by participants who had taken at least one course related to clinical psychology and who typically majored in psychology and applied health science fields. These participants were more likely to report being white, female, between the ages of 28–32, and in the fourth year or later of their undergraduate program. In addition, high performers were more likely to have been diagnosed and/or treated for a psychological disorder, have more experience with psychological disorders through personal, family, or peer history, and have families who are open to discussing mental health issues.
Conclusion: The main contributor to variation in mental health literacy scores was having taken a clinical psychology course, followed by majoring in psychology. Importantly, our findings identified not only the high performers, but also the low performers, for whom an increase in knowledge and awareness of mental health is crucial to overall psychological well-being. These results have important implications for the design of educational interventions aimed at improving mental health literacy at the college level, especially for students who otherwise would not have been exposed to this information from coursework or their major
Quantifying Cerebral Contributions to Pain beyond Nociception
Cerebral processes contribute to pain beyond the level of nociceptive input and mediate psychological and behavioural influences. However, cerebral contributions beyond nociception are not yet well characterized, leading to a predominant focus on nociception when studying pain and developing interventions. Here we use functional magnetic resonance imaging combined with machine learning to develop a multivariate pattern signature—termed the stimulus intensity independent pain signature-1 (SIIPS1)—that predicts pain above and beyond nociceptive input in four training data sets (Studies 1–4, N¼137). The SIIPS1 includes patterns of activity in nucleus accumbens, lateral prefrontal and parahippocampal cortices, and other regions. In cross-validated analyses of Studies 1–4 and in two independent test data sets (Studies 5–6, N¼46), SIIPS1 responses explain variation in trial-by-trial pain ratings not captured by a previous fMRI-based marker for nociceptive pain. In addition, SIIPS1 responses mediate the pain-modulating effects of three psychological manipulations of expectations and perceived control. The SIIPS1 provides an extensible characterization of cerebral contributions to pain and specific brain targets for interventions
Somatic and Vicarious Pain are Represented by Dissociable Multivariate Brain Patterns
Understanding how humans represent others’ pain is critical for understanding pro-social behavior. ‘Shared experience’ theories propose common brain representations for somatic and vicarious pain, but other evidence suggests that specialized circuits are required to experience others’ suffering. Combining functional neuroimaging with multivariate pattern analyses, we identified dissociable patterns that predicted somatic (high versus low: 100%) and vicarious (high versus low: 100%) pain intensity in out-of-sample individuals. Critically, each pattern was at chance in predicting the other experience, demonstrating separate modifiability of both patterns. Somatotopy (upper versus lower limb: 93% accuracy for both conditions) was also distinct, located in somatosensory versus mentalizing-related circuits for somatic and vicarious pain, respectively. Two additional studies demonstrated the generalizability of the somatic pain pattern (which was originally developed on thermal pain) to mechanical and electrical pain, and also demonstrated the replicability of the somatic/vicarious dissociation. These findings suggest possible mechanisms underlying limitations in feeling others’ pain, and present new, more specific, brain targets for studying pain empathy
Group-regularized individual prediction: theory and application to pain
Multivariate pattern analysis (MVPA) has become an important tool for identifying brain representations of psychological processes and clinical outcomes using fMRI and related methods. Such methods can be used to predict or ‘decode’ psychological states in individual subjects. Single-subject MVPA approaches, however, are limited by the amount and quality of individual-subject data. In spite of higher spatial resolution, predictive accuracy from single-subject data often does not exceed what can be accomplished using coarser, group-level maps, because single-subject patterns are trained on limited amounts of often-noisy data. Here, we present a method that combines population-level priors, in the form of biomarker patterns developed on prior samples, with single-subject MVPA maps to improve single-subject prediction. Theoretical results and simulations motivate a weighting based on the relative variances of biomarker-based prediction—based on population-level predictive maps from prior groups—and individual-subject, cross-validated prediction. Empirical results predicting pain using brain activity on a trial-by-trial basis (single-trial prediction) across 6 studies (N = 180 participants) confirm the theoretical predictions. Regularization based on a population-level biomarker—in this case, the Neurologic Pain Signature (NPS)—improved single-subject prediction accuracy compared with idiographic maps based on the individuals' data alone. The regularization scheme that we propose, which we term group-regularized individual prediction (GRIP), can be applied broadly to within-person MVPA-based prediction. We also show how GRIP can be used to evaluate data quality and provide benchmarks for the appropriateness of population-level maps like the NPS for a given individual or study
Beneficial impacts of goat milk on the nutritional status and general well-being of human beings: Anecdotal evidence
Goats provide an essential food supply in the form of milk and meat. Goat milk has distinct qualities, but it shares many similarities with human and bovine milk regarding its nutritional and therapeutic benefits. Because of their different compositions, goat and cow milk products could have different tastes, nutrients, and medicinal effects. Modification in composition aid of goat milk determining the viability of goat milk processing methods. Comparatively, goat's milk has higher calcium, magnesium, and phosphorus levels than cow's or human milk but lower vitamin D, B12, and folate levels. Goat milk is safe and healthy for infants, the old, and healing ailments. Capric, caprylic, and capric acid are three fatty acids that have shown promise as potential treatments for various medical issues. Considering the benefits and drawbacks of goat milk over cow milk is essential; goat milk is more digestible, has unique alkalinity, has a better buffering capacity, and has certain medicinal benefits. Acidifying goat milk shrinks fat globules and makes protein friable (with less αs1-casein and more αs2-casein). Goat milk treats malabsorption illnesses because it has more short- and medium-chain triglycerides that give developing children energy. In wealthy countries, goat milk and its products—yoghurt, cheeses, and powdered goods—are popular with connoisseurs and persons with allergies and gastrointestinal issues who need alternative dairy products. A food product category containing fermented goat milk with live probiotic microbes appears promising nutritionally and medicinally. This article presents anecdotal evidence of the therapeutic effects of consuming goat milk for human health and its nutritional value
Establishing a core outcome set for peritoneal dialysis : report of the SONG-PD (standardized outcomes in nephrology-peritoneal dialysis) consensus workshop
Outcomes reported in randomized controlled trials in peritoneal dialysis (PD) are diverse, are measured inconsistently, and may not be important to patients, families, and clinicians. The Standardized Outcomes in Nephrology-Peritoneal Dialysis (SONG-PD) initiative aims to establish a core outcome set for trials in PD based on the shared priorities of all stakeholders. We convened an international SONG-PD stakeholder consensus workshop in May 2018 in Vancouver, Canada. Nineteen patients/caregivers and 51 health professionals attended. Participants discussed core outcome domains and implementation in trials in PD. Four themes relating to the formation of core outcome domains were identified: life participation as a main goal of PD, impact of fatigue, empowerment for preparation and planning, and separation of contributing factors from core factors. Considerations for implementation were identified: standardizing patient-reported outcomes, requiring a validated and feasible measure, simplicity of binary outcomes, responsiveness to interventions, and using positive terminology. All stakeholders supported inclusion of PD-related infection, cardiovascular disease, mortality, technique survival, and life participation as the core outcome domains for PD
Cost-Effectiveness of HIV Testing Referral Strategies among Tuberculosis Patients in India
Background: Indian guidelines recommend routine referral for HIV testing of all tuberculosis (TB) patients in the nine states with the highest HIV prevalence, and selective referral for testing elsewhere. We assessed the clinical impact and cost-effectiveness of alternative HIV testing referral strategies among TB patients in India. Methods and Findings: We utilized a computer model of HIV and TB disease to project outcomes for patients with active TB in India. We compared life expectancy, cost, and cost-effectiveness for three HIV testing referral strategies: 1) selective referral for HIV testing of those with increased HIV risk, 2) routine referral of patients in the nine highest HIV prevalence states with selective referral elsewhere (current standard), and 3) routine referral of all patients for HIV testing. TB-related data were from the World Health Organization. HIV prevalence among TB patients was 9.0% in the highest prevalence states, 2.9% in the other states, and 4.9% overall. The selective referral strategy, beginning from age 33.50 years, had a projected discounted life expectancy of 16.88 years and a mean lifetime HIV/TB treatment cost of US10; the incremental cost-effectiveness ratio was US730/YLS compared to the current standard. For HIV-infected patients cured of TB, receiving antiretroviral therapy increased survival from 4.71 to 13.87 years. Results were most sensitive to the HIV prevalence and the cost of second-line antiretroviral therapy. Conclusions: Referral of all patients with active TB in India for HIV testing will be both effective and cost-effective. While effective implementation of this strategy would require investment, routine, voluntary HIV testing of TB patients in India should be recommended
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