History Data Research Articles

Usefulness of estimated glucose disposal rate in detecting heart failure: results from national health and nutrition examination survey 1999–2018

BackgroundEstimated glucose disposal rate (eGDR) is a novel, clinically available, and cost-effective surrogate of insulin resistance. The current study aimed to assess the association between eGDR and prevalent heart failure (HF), and further evaluate the value of eGDR in detecting prevalent HF in a general population.Methods25,450 subjects from the National Health and Nutrition Examination Survey 1999–2018 were included. HF was recorded according to the subjects’ reports. Logistic regression was employed to analyze the association between eGDR and HF, the results were summarized as Per standard deviation (SD) change. Then, subgroup analysis tested whether the main result from logistic regression was robust in several conventional subpopulations. Finally, receiver-operating characteristic curve (ROC) and reclassification analysis were utilized to evaluate the potential value of eGDR in improving the detection of prevalent HF.ResultsThe prevalence of reported HF was 2.96% (753 subjects). After adjusting demographic, laboratory, anthropometric, and medical history data, each SD increment of eGDR could result in a 43.3% (P < 0.001) risk reduction for prevalent HF. In the quartile analysis, the top quartile had a 31.1% (P < 0.001) risk of prevalent HF compared to the bottom quartile in the full model. Smooth curve fitting demonstrated that the association was linear in the whole range of eGDR (P for non-linearity = 0.313). Subgroup analysis revealed that the association was robust in age, sex, race, diabetes, and hypertension subgroups (All P for interaction > 0.05). Additionally, ROC analysis displayed a significant improvement in the detection of prevalent HF (0.869 vs. 0.873, P = 0.008); reclassification analysis also confirmed the improvement from eGDR (All P < 0.001).ConclusionOur study indicates that eGDR, a costless surrogate of insulin resistance, may have a linear and robust association with the prevalent HF. Furthermore, our findings implicate the potential value of eGDR in refining the detection of prevalent HF in the general population.

Improving spatial exposure data for everyone - lifecourse social context and ascertaining residential history.

Measuring age-specific, contextual exposures is crucial for lifecourse epidemiology research. Longitudinal residential data offers a "golden ticket" to cumulative exposure metrics and can enhance our understanding of health disparities. Residential history can be linked to myriad spatiotemporal databases to characterize environmental, socioeconomic, and policy contexts that a person experienced throughout life. However, obtaining accurate residential history is challenging in the United States due to the limitations of administrative registries and self-reports. Xu et al. (Am J Epidemiol. 2024; 193(2):348-359) detail an approach to linking residential history sourced from LexisNexis ® Accurint ® to a Wisconsin-based research cohort, offering insights into challenges with residential history collection. Researchers must analyze the magnitude of selection and misclassification biases inherent to ascertaining residential history from cohort data. A lifecourse framework can provide insights into why the frequency and distance of moves is patterned by age, birth cohort, racial/ethnic identity, socioeconomic status, and urbanicity. Historic and contemporary migration patterns of marginalized people seeking economic and political opportunities must guide interpretations of residential history data. We outline methodologic priorities for use of residential history in health disparities research, including contextualizing residential history data with determinants of residential moves, triangulating spatial exposure assessment methods, and transparently quantifying measurement error.

Impact of hypertension and lipid profile on cardiac function in an Iranian teaching hospital: A cross-sectional analysis.

Cardiovascular diseases (CVDs) pose a significant global health challenge and affect diverse populations. For conditions such as coronary artery disease, heart failure, and stroke prevalence, understanding the multifaceted factors contributing to CVDs is crucial. Hypertension and dyslipidemia, which are established risk factors, require further exploration, particularly in terms of their individual impact on cardiac function. This study aims to uncover associations, elucidate nuanced interplay, and provide insights for personalized interventions. A cross-sectional analysis, conducted at a Tehran Teaching Hospital, focused on adults admitted for suspected heart disease. The dataset included demographic information, clinical history, medications, and echocardiographic data. Statistical analysis was performed using Pearson's correlation with IBM SPSS Statistics software. In this analysis of 95 individuals suspected of heart disease, aged 51 years on average, diverse blood pressure patterns with significant percentages across various hypertension stages were observed. Lipid profile analysis revealed typical lipid levels. Correlations between blood pressure, lipid parameters, and cardiac function indicated significant associations, including a negative correlation between ejection fraction and blood pressure and significant correlations between lipid profiles and adverse cardiac volume changes. Disparities in the prevalence of obesity and diabetes have highlighted potential links to hypertension. This study sheds light on crucial clinical aspects of individuals with suspected heart disease, revealing patterns of obesity, varied blood pressure categories, and nuanced lipid profiles. The correlations between blood pressure, lipid parameters, and cardiac function highlight potential connections, emphasizing the importance of tailored interventions for improved cardiovascular outcomes.

Real-world anti-seizure treatment and adverse events among individuals living with drug-resistant focal epilepsy in the United States.

This study aimed to understand how people living with drug-resistant focal epilepsy (DRE) navigate through lines of antiseizure medications (ASM) and experience adverse events (AEs) in the real-world setting in the United States. A retrospective study was conducted with medical chart data from clinical practices in the United States. Eligible adults had a confirmed diagnosis of DRE and initiated a third-line ASM therapy between January 2013 and January 2020 (i.e., the index date). Subjects must have medical history data available for ≥1 year prior to (the baseline) and ≥2 years after the index date (the follow-up). Treatment patterns were captured from first to fourth lines. After the emergence of drug resistance, time to ASM discontinuation, reasons for discontinuation, AE experience and AE management were reported separately during third and fourth lines of treatment and beyond. The study included a total of 345 individuals, with an average (standard deviation) age of 23.9 (11.9) years at first diagnosis. All individuals had at least three lines of ASMs with first and second lines during baseline, and third line during follow-up. The first line for most individuals was monotherapy. As individuals progressed through additional lines of ASM therapy, they were more likely to receive polytherapy. The regimens were more individualized after meeting drug resistance criteria. The top reasons for discontinuing were uncontrolled seizure and/or intolerance/AEs for both third and subsequent lines. More than a third of individuals experienced at least one AE. Among those with at least one AE, many individuals had to manage these AEs with dose adjustment (39.4%), discontinuation of offending ASM (37.9%), de novo pharmacotherapy (25.8%), emergency room visit (13.6%), and hospitalization (12.1%). This study demonstrated that individuals living with DRE experience significant AEs, and many of these AEs lead to treatment disruption and significant healthcare resource utilization. This study examined how individuals with focal epilepsy are treated across various clinics in United States and reported the adverse events these individuals experienced during treatment, along with the consequence associated with these adverse events. We found that as individuals progressed through additional treatments, they were more and more likely to receive more than one antiseizure medication, and a significant portion of individuals experienced at least one adverse event, often manifested as headache, somnolence, dizziness, and fatigue.

Quantifying urban park use in the USA at scale: empirical estimates of realised park usage using smartphone location data

A large body of evidence connects access to greenspace with substantial benefits to physical and mental health. In urban settings where access to greenspace can be limited, park access and use have been associated with higher levels of physical activity, improved physical health, and lower levels of markers of mental distress. Despite the potential health benefits of urban parks, little is known about how park usage varies across locations (between or within cities) or over time. We estimated park usage among urban residents (identified as residents of urban census tracts) in 498 US cities from 2019 to 2021 from aggregated and anonymised opted-in smartphone location history data. We used descriptive statistics to quantify differences in park usage over time, between cities, and across census tracts within cities, and used generalised linear models to estimate the associations between park usage and census tract level descriptors. In spring (March 1 to May 31) 2019, 18·9% of urban residents visited a park at least once per week, with average use higher in northwest and southwest USA, and lowest in the southeast. Park usage varied substantially both within and between cities; was unequally distributed across census tract-level markers of race, ethnicity, income, and social vulnerability; and was only moderately correlated with established markers of census tract greenspace. In spring 2019, a doubling of walking time to parks was associated with a 10·1% (95% CI 5·6-14·3) lower average weekly park usage, adjusting for city and social vulnerability index. The median decline in park usage from spring 2019 to spring 2020 was 38·0% (IQR 28·4-46·5), coincident with the onset of physical distancing policies across much of the country. We estimated that the COVID-19-related decline in park usage was more pronounced for those living further from a park and those living in areas of higher social vulnerability. These estimates provide novel insights into the patterns and correlates of park use and could enable new studies of the health benefits of urban greenspace. In addition, the availability of an empirical park usage metric that varies over time could be a useful tool for assessing the effectiveness of policies intended to increase such activities. Google.

Data-driven continuum damage mechanics with built-in physics

Soft materials such as rubbers and soft tissues often undergo large deformations and experience damage degradation that impairs their function. This energy dissipation mechanism can be described in a thermodynamically consistent framework known as continuum damage mechanics. Recently, data-driven methods have been developed to capture complex material behaviors with unmatched accuracy due to the high flexibility of deep learning architectures. Initial efforts focused on hyperelastic materials, and recent advances now offer the ability to satisfy physics constraints such as polyconvexity of the strain energy density function by default. However, modeling inelastic behavior with deep learning architectures and built-in physics has remained challenging. Here we show that neural ordinary differential equations (NODEs), which we used previously to model arbitrary hyperelastic materials with automatic polyconvexity, can be extended to model energy dissipation in a thermodynamically consistent way by introducing an inelastic potential: a monotonic yield function. We demonstrate the inherent flexibility of our network architecture in terms of different damage models proposed in the literature. Our results suggest that our NODEs re-discover the true damage function from synthetic stress-deformation history data. In addition, they can accurately characterize experimental skin and subcutaneous tissue data.

A 72-year-old Woman with Dyspnea and Thrombocytosis

&lt;p&gt;原發性血小板增多症的臨床表徵並不典型且早期診斷不易，往往多數病人於診斷前已發生動靜脈血栓形成及出血併發症。本個案一位72歲女性，有高血壓及胃食道逆流病史並按時門診追蹤服藥，五天前注射新冠疫苗後，呼吸喘、乾咳併胸悶至診所就醫未改善，於急診初步診斷急性支氣管炎。入院後感心悸且胸悶，藉由病史詢問、檢驗及理學檢查，顯示心肌酵素正常但心電圖呈現陣發性心室上心搏過速，安排冠狀動脈血管攝影攝影後排除急性心肌梗塞，但呼吸急促未見好轉呈現低血氧，經胸腔電腦斷層為肺栓塞。疑似新冠疫苗後引起的免疫併發症，直到右手食指及中指末梢腫、痛且發紺症狀出現，筆者再次重新檢視病史資料，發現血小板異常，透過骨髓穿刺切片是發現巨核細胞（megakaryocyte）增生，病理報告判斷為骨髓增生性腫瘤，基因檢測結果為JAK2V617F 突變，最後確診是原發性血小板增多症併發肺栓塞，接受Hydroxyurea合併口服抗凝血劑治療，症狀改善且血小板數值趨於穩定。藉此案例分享提醒當發現病人有不明血栓產生時須考慮將相關血液疾病列入鑑別診斷，期能及早發現疾病，掌握治療時機。&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;The clinical symptoms of essential thrombocythemia are not typical and early diagnosis is difficult.Most patients have arteriovenous thrombosis and bleeding complications before diagnosis. In this case, a 72-year-old woman had a history of hypertension and gastroesophageal reflux and was taking medication regularly at the outpatient clinic. After being injected with the COVID-19 vaccine five days ago, her breathing, dry cough, and chest tightness did not improve when she went to the clinic. She was initially diagnosed with acute bronchitis in the emergency department. After being admitted to the hospital, she felt palpitations and chest tightness. The medical history, examination and physical examination showed that myocardial enzymes were normal, but the electrocardiogram showed Parox-ysmal supraventricular tachycardia. Coronary angiography was arranged to rule out acute myocardial infarction, but the shortness of breath persisted with hypoxemia, and the computed tomography of the chest showed pulmonary embolism. Immune complications caused by the COVID-19 vaccine were suspected, symptoms of swelling, pain and cyanosis appeared in the distal part of the right index fin-ger and middle finger appeared. The author re-examined the medical history data and found abnormal platelets. Through bone marrow aspiration and sectioning, megakaryocyte hyperplasia was found. Pa-thology report determined that the patient suffered from myeloproliferative neoplasm, and the genetic test result was the JAK2V617F mutation. The patient was finally diagnosed with essential thrombocythe-mia complicated by pulmonary embolism. She was treated with Hydroxyurea combined with oral an-ticoagulants. The symptoms improved and the platelet level stabilized. This case serves as a reminder that when a patient is found to have unknown thrombosis, related blood diseases must be considered in the differential diagnosis, so that the disease can be detected early and proper treatments can be pro-vided.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Sexual Orientation Differences in Age of First Treatment for a Mental Health Diagnosis: A Population-Based Study of Childhood and Adolescence

The aim of the current study was to identify the age at which sexual orientation disparity in mental health diagnoses can be first identified, as well as gender and sexual identity subgroup differences in such treatment, in a population-based sample. Young people aged 16 to 25 (N= 10,365) participating in the probability-based Swedish National Public Health Survey in 2018 were included. This sample was linked to physician-assessed mental health care treatment history data starting when all participants were 8 years old using national health care registries. Participants reporting a sexual minority identity in adolescence and young adulthood were more than 3 times as likely to have been treated for an internalizing disorder diagnosis (eg, depression, anxiety) and more than twice as likely to have been treated for a neurodevelopmental disorder diagnosis during childhood than participants reporting a heterosexual identity. Sexual minority participants overall and women in particular were more likely to have been treated for an internalizing disorder diagnosis at an early age compared with heterosexual participants, with this disparity starting at age 13. The sexual orientation disparity in likelihood of treatment for a neurodevelopmental disorder diagnosis was particularly elevated among bisexual/pansexual women with this disparity starting in early/middle adolescence. This population-based study linked to physician-assessed mental health diagnoses during childhood and adolescence identifies the age at which sexual orientation differences in treatment for common mental disorders emerge. The early emergence of this disparity suggests a potential benefit of interventions that facilitate social belonging for all youth.

Optimization of typical structural components of composite materials based on fatigue life

Abstract Optimizing the fatigue life of reinforced composite panels in hypersonic aircraft is crucial for enhancing performance and reliability. Employing the rainflow counting method and a linear cumulative damage model, we process stress-time history data under random loading. The optimization model, with structural fatigue life as the objective function and parameters as constraints, is tackled using genetic algorithms. This efficient approach, exemplified with needle-punched C/SiC composite reinforced panels, significantly improves fatigue life, offering substantial benefits to hypersonic aircraft.

Incremental value of multidomain risk factors for dementia prediction: A machine learning approach

ObjectiveThe current evidence regarding how different predictor domains contribute to predicting incident dementia remains unclear. This study aims to assess the incremental value of five predictor domains when added to a simple dementia risk prediction model (DRPM) for predicting incident dementia in older adults. DesignPopulation-based, prospective cohort study SettingUK Biobank study ParticipantsIndividuals aged 60 or older without dementia. Measurements55 dementia-related predictors were gathered and categorized into clinical and medical history, questionnaire, cognition, polygenetic risk, and neuroimaging domains. Incident dementia (all-cause) and the subtypes, Alzheimer's disease (AD) and vascular dementia (VaD), were determined through hospital and death registries. Ensemble machine learning (ML) DRPMs were employed for prediction. The incremental values of risk predictors were assessed using the percent change in Area Under the Curve (∆AUC%) and the net reclassification index (NRI). ResultsThe simple DRPM which included age, body mass index, sex, education, diabetes, hyperlipidaemia, hypertension, depression, smoking, and alcohol consumption yielded an AUC of 0.711 (± 0.008 SD). The five predictor domains exhibited varying levels of incremental value over the basic model when predicting all-cause dementia and the two subtypes. Neuroimaging markers provided the highest incremental value in predicting all-cause dementia (∆AUC% +9.6%) and AD (∆AUC% +16.5%) while clinical and medical history data performed the best at predicting VaD (∆AUC% +12.2%). Combining clinical and medical history, and questionnaire data synergistically enhanced ML DRPM performance. ConclusionCombining predictors from different domains generally results in better predictive performance. Selecting predictors entails trade-offs, and while neuroimaging markers can significantly enhance predictive accuracy, they may pose challenges in terms of cost or accessibility.

Research on personal credit scoring model based on deep learning

The increasing integration of internet technology and the financial industry has led to the gradual replacement of traditional credit evaluation models with those based on deep learning, which have demonstrated excellent accuracy. This has become a prominent area of research. Nevertheless, the credit scoring model based on a deep neural network encounters significant challenges in terms of its applicability in the field of credit scoring, largely due to the opaque nature of its learning and decision-making processes. The application of deep learning to personal credit scoring has been shown to enhance the accuracy of the resulting scores by leveraging large amounts of data. The model employs a deep neural network (DNN) architecture that integrates multiple input features, including the user's transaction history, social behaviour and other relevant data. The model is trained using supervised learning, with a large amount of labelled data used to optimise its prediction performance. Experimental results demonstrate that the deep learning-based model exhibits a notable improvement in accuracy and robustness compared to traditional credit scoring models.

Changes in the Language of the Reformed Church in the Second Half of the 20th Century: The Convergence of Oral History and Big Data

The author’s journey begins with a deep immersion in his traditional Protestant faith, where he was taught to thoroughly know both the Old and the New Testament. As he reflects on his faith, the concept of being a “stranger and sojourner” comes to the forefront, highlighting the feeling of alienation within the secular world. The narrative takes an interesting turn when the author discusses the impact of changing political language on his perspective. The introduction of new political ideas and discourse challenges the previously straightforward worldview, leading to a sense of uncertainty in decision-making. Believers find themselves in a world with a multiplicity of perspectives that require a re-evaluation of what it means to “deny” or to make choices. In a changing social and political context, the narrative continually explores the intricate connection between faith and language. The author’s experiences and reflections provide a compelling insight into the complexities of navigating a shifting spiritual landscape while grappling with the ever-evolving meaning of words and beliefs. The second half of the article presents the results of a computer analysis of the vocabulary of two Bible translations that defined the language usage of the Reformed Church in the second half of the 20th century: the 1908 Károli and the 1975 New Translation. The analysis focuses on words that present difficulties in understanding due to their archaic or religious nature. As a point of comparison, it also showcases the vocabulary of the Gospel of John, where a mere 199 word roots constitute 80% of word occurrences. Keywords: language of the church, Bible translation, vocabulary of the Bible, letter and soul, protestant language use

The first record of ants as potential pollinators of a Neotropical tree species (Lomatia hirsuta Diels ex J.F.Macbr., Proteaceae)

AbstractWe provide evidence that Camponotus chilensis (Spinola) visit flowers of the Radal tree (Lomatia hirsuta Diels ex J.F.Macbr.), possibly acting as pollinators of this important tree of the Proteaceae family in the Andean Patagonian forests of Argentina. We found several ant workers transporting pollen from different trees during the blooming season. Pollen transported by workers varied in amount, with some individuals observed fully coated with pollen grains. This note constitutes the first observation of ant activity on the flowers of this plant species and also the first potential example of a tree pollinated by ants in the Neotropics. This note highlights the importance of natural history data in the emergent study field of ant‐pollination.

A sensitive fluorescence assay of serum dipeptidyl peptidase IV activity to predict the suitability of its inhibitors in patients with type 2 diabetes mellitus

DPP-IV inhibitors, which are close to the natural hypoglycemic pathway of human physiology and have few side effects, have been extensively employed in the management of type 2 diabetes mellitus (T2DM). However, there are currently no specific blood indicators that can indicate or predict a patient's suitability for DPP-IV inhibitors. In this study, based on the self-developed high-specificity fluorescent substrate glycyl-prolyl-N-butyl-4-amino-1, 8-naphthimide (GP-BAN), a detection method of human serum DPP-IV activity was established and optimized. The method demonstrates a favorable lower limit of detection (LOD) at 0.32 ng/mL and a satisfactory lower limit of quantification (LOQ) of 1.12 ng/mL, and can be used for the detection of DPP-IV activity in trace serum (2 μL). In addition, Vitalliptin and Sitagliptin showed similar IC50 values when human recombinant DPP-IV and human serum were used as enzyme sources, and the intra-day and inter-day precision obtained by the microplate analyzer were less than 15 %. These results indicate that the microplate reader based detection technique has good accuracy, repeatability and reproducibility. A total of 700 volunteers were recruited, and 646 serum samples were tested for DPP-IV activity. The results showed that serum DPP-IV activity was higher in patients with T2DM than in controls (P < 0.01). However, the statistical data of family history of diabetes, gender and age of diabetic patients showed no statistical significance, and there was no contrast difference. The DPP-IV activity of serum in T2DM patients ranged from 2.4 μmol/min/L to 78.6 μmol/min/L, with a huge difference of up to 32-fold. These results suggest that it is necessary to test DPP-IV activity in patients with T2DM when taking DPP-IV inhibitors to determine the applicability of DPP-IV inhibitors in T2DM patients. These results suggest that it is necessary to detect the activity of DPP-IV in blood before taking DPP-IV inhibitors in patients with T2DM to judge the applicability of DPP-IV inhibitors in patients with T2DM.

Comprehensive periodic health evaluations of 454 Norwegian Paralympic and Olympic athletes over 8 years: what did we learn?

ObjectiveA periodic health evaluation (PHE) is a comprehensive and multidisciplinary investigation of athlete health widely used in elite sport, but its contents and benefits can be questioned. This study aimed...

Medication Adherence and Treatment Satisfaction With Lipid-Lowering Drugs Among Patients With Diabetes and Dyslipidemia.

Poor adherence to lipid-lowering drugs in diabetic patients with dyslipidemia increases has been linked with an increased cardiovascular risk. A better understanding of the determinants of adherence to lipid-lowering drugs and treatment satisfaction among people with diabetes and dyslipidemia is crucial. We aimed to assess the prevalence of adherence to lipid-lowering drugs, identify its determinant factors, and evaluate treatment satisfaction among users of lipid-lowering drugs who have diabetes and dyslipidemia. We surveyed 398 adult patients with diabetes and dyslipidemia, using a validated medication adherence survey (Adherence to Refills and Medications Scale) and a validated treatment satisfaction survey (Treatment Satisfaction Questionnaire for Medication, TSQM). Sociodemographic and medical history data were collected through questionnaires. The prevalence of poor medication adherence was 36%. Factors associated with poor adherence included adverse reactions to medications, lack of medication availability, and lack of family support. Adherent patients reported lower low-density lipoprotein-cholesterol (LDL-C) and total cholesterol levels, higher treatment satisfaction, and a higher prevalence of cardiovascular disease and comorbidities. Having a family history of dyslipidemia was negatively associated with adherence, while the number of comorbidities positively influenced it. The scores of TSQM components such as effectiveness, global satisfaction, and convenience were significantly higher in people who were adherent or achieved the LDL-C target. Our findings highlight the need for interventions targeting several factors impacting adherence to lipid-lowering drugs in patients with diabetes and dyslipidemia. Managing adverse effects, leveraging family support, and ensuring medication access represent crucial aspects of improving adherence and potentially mitigating cardiovascular risks in this high-risk population.

Hypothermia in preterm infants admitted to low-resource neonatal units in northern Nigeria: an observational study of occurrence and risk factors

BackgroundHypothermia is an important cause of morbidity and mortality among preterm and low-birth-weight neonates. In resource-constrained settings, limited referral infrastructure and technologies for temperature control potentiate preterm hypothermia. While there is some documentation on point-of-admission hypothermia from single center studies, there are limited multicenter studies on the occurrence of hypothermia among preterm infants in resource-limited-settings. Therefore, we conducted a multicenter study to determine the prevalence and risk factors for hypothermia at the time of admission and during the first 72 h after admission in northern Nigeria.MethodWe carried out a prospective cohort study on preterm infants admitted to four referral hospitals in northern Nigerian between August 2020 and July 2021. We documented temperature measurements at admission and the lowest and highest temperatures in the first 72 h after admission. We also collected individual baby-level data on sociodemographic and perinatal history data. We used the World Health Organization classification of hypothermia to classify the babies’ temperatures into mild, moderate, and severe hypothermia. Poisson regression analysis was used to identify risk factors for moderate-severe hypothermia.ResultsOf the 933 preterm infants enrolled, 682 (72.9%) had hypothermia at admission although the prevalence of hypothermia varied across the four hospitals. During the first 24 h after admission, 7 out of every 10 babies developed hypothermia. By 72 h after admission, between 10 and 40% of preterm infants across the 4 hospitals had at least one episode of moderate hypothermia. Gestational age (OR = 0.86; CI = 0.82–0.91), birth weight (OR = 8.11; CI = 2.87–22.91), presence of a skilled birth attendant at delivery (OR = 0.53; CI = 0.29–0.95), place of delivery (OR = 1.94 CI = 1.13–3.33) and resuscitation at birth (OR = 1.79; CI = 1.27–2.53) were significant risk factors associated with hypothermia.ConclusionThe prevalence of admission hypothermia in preterm infants is high and hypothermia is associated with low-birth-weight, place of delivery and presence of skilled birth attendant. The prevalence of hypothermia while in care is also high and this has important implications for patient safety and quality of patient care. Referral services for preterm infants need to be developed while hospitals need to be better equipped to maintain the temperatures of admitted small and sick newborns.

Prior traumatic brain injury is a risk factor for in-hospital mortality in moderate to severe traumatic brain injury: a TRACK-TBI cohort study

ObjectivesAn estimated 14–23% of patients with traumatic brain injury (TBI) incur multiple lifetime TBIs. The relationship between prior TBI and outcomes in patients with moderate to severe TBI (msTBI) is...

Crosstalk between skeletal muscle ratio and cholesterol metabolism disorders: a cross-section study

BackgroundDysfunction of cholesterol metabolism may be associated with low skeletal muscle mass. This study aimed to explore the relationship between skeletal muscle mass and cholesterol metabolic disorders in adults.MethodsThe data of a total of 5949 people with complete medical history data, biochemical data and body composition analysis were recruited. According to the serum cholesterol, low density lipoprotein (LDL), high density lipoprotein (HDL) and nonHDL, the population was divided into a disorder group and a normal group. Independent sample t tests, chi-square tests, Pearson's correlation analyses and binary logistic regression analyses were used to study the effect of body composition on abnormal cholesterol metabolism. According to BMI and sex, the population was divided into different subgroups, and binary logistic regression analysis was used to study the effect of the skeletal mass ratio on cholesteral metabolic disorders in different subgroups.ResultsThere were significant differences in sex, alcohol consumption, body weight, BMI, skeletal muscle mass index (SMI) [total skeletal muscle mass (kg)/height 2 (m2)] and skeletal muscle mass ratio (SMR) [total skeletal muscle mass (kg)/weight (kg) *100] between the disorder group (hypercholesterolemia, hyper-LDL, lower-HDL and hyper-nonHDL) and the normal group. Pearson correlation analysis revealed that the SMR was negatively correlated, while the SMI was positively correlated with cholesterol metabolic disorders in both sexes. The overweight group was older and had a greater SMI, abnormal cholesteral metabolism ratio and lower SMR than the normal-weight group. In the normal-weight group, the SMR was an independent protective factor against different kinds of cholesteral metabolic disorders in both sexes, while the SMI was a risk factor. In the overweight subgroup, the protective effect on HDL and nonHDL metabolism remained in the male subgroup but disappeared in the female subgroup. However, the SMI was an independent risk factor for different kinds of cholesteral metabolic disorders in both sexes.ConclusionsSMR was an independent protective factor against cholesterol metabolic disorders in both males and females, especially in the normal weight group. SMI was an independent risk factor, especially in the overweight group.

Retinal Sensitivity in Macular Subfields and Their Association with Contrast Sensitivity in Early and Intermediate Age-Related Macular Degeneration.

The objective of this study was to evaluate retinal sensitivity in subfields and its association with the novel quantitative contrast sensitivity function (qCSF) in patients with early age-related macular degeneration (eAMD), in patients with intermediate AMD (iAMD), and in healthy controls. In this prospective longitudinal study, retinal sensitivity of a customized 24-point grid was assessed by microperimetry Macular Integrity Assessment (MAIA, CenterVue, Padova, Italy) and divided into different subfields. The Multiple Contrast Vision Meter (Adaptive Sensory Technology, San Diego, CA, USA) was used for qCSF testing. Linear models were used to test the association of functional metrics with variables of interest. 92 study eyes from 92 participants were analyzed (13 eAMD, 31 iAMD, and 48 controls). Microperimetry subfield comparison showed significant differences (p &lt; 0.0001) in the control group between superior and inferior hemifield as well as between central and peripheral subfields. For eAMD, significant differences were found between central and peripheral subfields (p &lt; 0.001) and specific subfields (p &lt; 0.05) and finally for iAMD between specific quadrants (p &lt; 0.05) and specific squares (p &lt; 0.05). Significant associations of retinal sensitivity with qCSF metrics were found for the area underneath the logarithmic contrast sensitivity function, contrast acuity and for the contrast sensitivity at specific spatial frequencies. This study showed significant differences in the evaluated retinal sensitivity subfields, providing localized natural history data for retinal sensitivity in healthy controls and patients with eAMD and iAMD.