Higher Risk Ratio Research Articles

A Survey on Perception, Knowledge and Use of Contraceptives among Females in Ikot Abasi, Akwa Ibom State

The rate of unwanted pregnancies and maternal morbidity can be significantly reduced by the use of various forms of contraception. This study assesses the perception, knowledge and use of contraceptives among women in Ikot Abasi local government area of Akwa Ibom State. A pre-tested, structured interviewer-administered questionnaire was the tool for data collection and multi-staged sampling technique was used to select 512 females of reproductive age from the five clans of Ikot Abasi. The method of multinomial logistic regression was used to determine the contraceptive methods and determinants of contraceptive use while the Chi-Square test was applied to determine the perception of contraception. The results revealed that about 97% of the women have knowledge about contraceptives and their major source of information about contraceptives were from their friends/relatives which account for about (37%). Women in the age category 33 – 38, M.Sc/Ph.D level of education and income earners of more than ₦100,000 per month have a high relative risk ratio of contraceptive use of 3.90, 2.48 and 3.32 respectively. Finally, Age group, level of education, level of income per month and relationship status were discovered to be the main determinants of contraceptives use among women in Ikot Abasi.

Combined population attributable fractions for dementia are dependent on strong assumptions of the form of interactions between risk factors: an analysis of data from the Canadian Longitudinal Study on Aging

AbstractBackgroundSeveral recent studies have used communality weights to calculate a combined population attributable fraction (PAF) of modifiable risks factors for dementia. Other research has suggested this method may be underestimating the true PAF. We applied multiple methods to calculate the combined PAF of 12 modifiable risk factors using record‐level, national Canadian data.MethodWe used baseline data (2011‐2015) from the comprehensive cohort of the Canadian Longitudinal Study on Aging (CLSA). We measured the 12 risk factors identified in the Lancet Commission on dementia prevention, intervention, and care. We calculated a combined PAF of these risk factors using the independent multiplicative method of Barnes and Yaffe (BY‐M), the additive and multiplicative methods of Welberry (W‐A and W‐M), and communality‐adjusted multiplicative method of Norton (N‐M). We also implemented a novel method (J‐MA) to mix multiplicative and additive interactivity based on the number of risk factors present. All methods incorporated sample weights and used the risk ratios from the Lancet Commission.ResultThere were 30,097 baseline participants in the CLSA ranging in age from 45 to 85 years (median 62). Combined PAFs varied widely: 78.5%(W‐M), 75.9% (BY‐M), 59.8% (J‐MA), 58.2% (W‐A), and 43.3% (N‐M). The BY‐M and W‐M methods resulted in unrealistically high combined risk ratios (RR >90) in individuals with many risk factors. The other methods produced broadly realistic results. Despite a nominally multiplicative form, N‐M produced results consistent with sub‐additive interactivity and makes arbitrary analytic choices. The J‐MA method also uses an arbitrary function to blend multiplicative and additive interactions. The W‐A approach made no assumption other than additive interactivity.ConclusionAssumptions regarding how risk factors for dementia interact highly influence combined PAFs. All multiplicative methods produce either unrealistic results or require arbitrary analytic choices. The additive method makes no arbitrary assumptions but may not reflect the actual form of interactions between risk factors. Not enough is known on how modifiable risk factors for dementia interact to estimate combined PAFs with confidence. When reporting PAFs for dementia a range of possible values, including one assuming additive interactions, should be provided and the assumptions behind each value clearly stated.

Further analysis of tuberculosis in eight high-burden countries based on the Global Burden of Disease Study 2021 data

BackgroundsMost significant findings from the Global Tuberculosis (TB) Report 2023 indicate that India, Indonesia, China, the Philippines, Pakistan, Nigeria, Bangladesh, and the Democratic Republic of the Congo (DRC) collectively contribute to approximately two-thirds of global TB cases. This study aims to provide crucial data-driven insights and references to improve TB control measures through a comprehensive analysis of these eight high-burden countries.MethodsThe eight high-burden TB countries analyzed in this study include India, Indonesia, China, the Philippines, Pakistan, Nigeria, Bangladesh, and the DRC. Age-standardized incidence rates (ASIR) of TB were derived from the Global Burden of Diseases Study 2021 data. Temporal trends were analyzed using Joinpoint regression. An age-period-cohort model was applied to examine the risk ratios (RR) of TB across diverse age groups, periods, and birth cohorts. A Bayesian age-period-cohort framework was employed to predict the ASIR of TB by 2030.ResultsThe study found that the Philippines (average annual percentage change = 3.1%, P < 0.001) exhibited an upward trend from 1990 to 2021. In India, the Philippines, Pakistan, and Bangladesh, the RR of TB incidence exceeded 1 after individuals reached 25 years old. Notably, the RR has shown a consistent upward trend since 2001, peaking during the period of 2017–2021 with an estimated RR of 1.5 (P < 0.001) in the Philippines. Similarly, the highest RR was observed during the period of 2017–2021 reaching 1.1 (P < 0.001) in the DRC. In the Philippines, the markedly increasing RR values for TB have been observed among individuals born after 1997–2001. Projections suggest that the ASIR of TB is expected to follow a continued upward trajectory, with an estimated rate of 392.9 per 100,000 by 2030 in the Philippines; India and Indonesia are projected to achieve less than 20.0% of the target set by the World Health Organization (WHO).ConclusionsAmong the eight high-burden countries, the Philippines, India and Indonesia are diverging from the goals set by the WHO, and the risk of TB in the Philippines and the DRC shows a trend toward affecting younger populations, which suggests that the management strategies for TB patients need to be further strengthened.Graphical

Identification of prognostic biomarkers and tumor immune microenvironment about Uveal melanoma

Uveal melanoma (UM) is a malignant eye cancer that has a high mortality rate and is notoriously difficult to diagnose clinically. Identifying prognostic biomarkers and evaluating the tumor immune microenvironment for UM in order to improve diagnosis, treatment decisions and even overall survival for patients. The study involved a comprehensive analysis of transcriptome profiling from the TCGA-UVM project, with the aim of identifying biomarkers and exploring the relationship between the tumor immune microenvironment and UM. A total of 32 differentially expressed genes and 25 RNAs associated with the overall survival (OS) of UM patients were identified. The fusion gene HSPE1-MOB4 was found to have the highest risk ratio, indicating it plays a key role in the survival rate of these individuals. Through similarity analysis of RNAs expression levels in UM, two subtypes were identified, and the survival rate for Type 1 was notably greater compared to Type 2. Using LASSO regression, a risk model was developed to identify five genes as potential biomarkers for the diagnosis and prediction of overall survival (OS) in patients with UM. Additionally, an association between the risk score and the fraction of immune cells in the Tumor Immune Microenvironment (TIME) was proposed. The observations revealed a significant contrast in both immune score and clustering between high-risk and low-risk groups. These findings offer new insights into approaches for immunotherapy and suggest potential therapeutic targets for individual UM patients.

Comprehensive analysis of multiple sclerosis hospitalization trends in Spain (1998–2022)

ObjectiveTo analyse the trends in MS hospitalization rates in Spain (1998–2022) considering age, period, and birth cohort (A-P-C) effects. MethodsThis retrospective study used data on MS hospitalizations from the Spanish National Health System Minimum Basic Data Set (CMBD). Age-Standardized Hospitalization Rates (ASHRs) and Joinpoint analysis were used to assess trends. A-P-C analysis was performed to estimate age-specific rates, period and cohort effects. ResultsFrom 1998 to 2022, MS hospital admissions in Spain declined annually by -2.1 %, with women showing a slightly greater decrease (-2.3 %) than men (-1.7 %). Joinpoint analysis revealed non-parallel trends, with three inflection points indicating distinct periods of stabilization and decline. ASHR showed an overall decrease, with -2.0 % for men and -2.2 % for women annually. Risk of hospitalization peaked in the 25–29-year age group for men and 30–34-year age group for women, declining with age. Women consistently had higher risk ratios across age groups. Cohort analysis showed periods of stabilization and decline in MS hospitalization risk, aligning with joinpoint analysis findings. Risk increased for cohorts born in the early 20th century, peaking around 1938, followed by a progressive decline in later cohorts. ConclusionsDespite an aging population, MS hospitalization rates in Spain decreased. The risk of hospitalization for MS is affected by a person's age, the time period they were born in, the historical context of healthcare received, and potentially their sex.

Epidemiological Pattern and Case Fatality Rate among COVID-19 Patients during First and Second Wave of Pandemic in Madhesh Province, Nepal

Background &amp; Objectives: Evaluating multi-wave patterns of COVID-19 infection, hospitalization, and mortality across spatial scales can inform public health strategies for future pandemics. However, there is limited understanding of these patterns in developing countries, including Nepal. This study aimed to analyze epidemiological patterns, fatality rates, and factors associated with severe outcomes during the first and second waves of COVID-19 in Madhesh Province, Nepal. Materials and Methods: This retrospective cross-sectional study used provincial health records from Madhesh Province, covering April 9, 2020, to December 15, 2021, to analyze 37,551 positive COVID-19 cases and 1,037 deaths across two waves. The study examined changes in COVID-19-related deaths, with data on demographics, residence, isolation sites, treatment hospitals, care levels, and testing laboratories. The frequency and percentage of the variables were presented. The case fatality rate (CFR) for different categories were calculated. Additionally, the case fatality rate ratio (CFRR) for the first wave against second wave was obtained. Finally, case fatality risk ratios with 95% confidence intervals were presented. A p-value of &lt;0.05 was set as statistically significant. Results: The case fatality rate (CFR) for COVID-19 was significantly higher in the second wave, especially among the elderly (≥47 years), and in institutional isolation (7.82%). Tertiary level care and private hospitals consistently showed higher CFRs. Furthermore, the multivariable analysis of risk ratios (RR) for COVID-19 case fatality in revealed that the 25–34 year age group had the highest RR (2.39). Similarly, males had a higher RR (1.42) than females, and institutional isolation had a substantially higher RR (93.33) compared to home isolation. Primary level care RR (28.11) and government hospitals RR (4.32) showed a higher risk. Place of residence also impacted the RR, with Sarlahi (7.68) having higher. Conclusion: A significant increase in COVID-19 case fatality rates during the second wave, particularly among the elderly and those in institutional isolation. Higher mortality was observed in tertiary hospitals and among those who were tested in private laboratories, with substantial variations in risk ratios based on age, isolation type, and place of residence.

Outcomes of Muscle versus Fasciocutaneous Free Flap Reconstruction in Acute Burns: A Systematic Review and Meta-analysis.

Free flap reconstruction in acute burns is high risk but often required for limb salvage and coverage of vital structures. Prior studies have shown a flap loss rate up to 44%. This study aimed to compare the complications associated with muscle and fasciocutaneous free flaps in acute burn reconstruction. A systematic review and meta-analysis was conducted according to PRISMA guidelines and registered on the PROSPERO database (CDR42023471088). The databases accessed were Embase, PubMed, Web of Science, and Cochrane Library. The primary outcome was free flap failure rate based on flap type. Secondary outcomes included venous congestion, arterial thrombosis, amputation, and need for reintervention. Twelve studies with 181 free flaps were included: 87 muscle flaps and 94 fasciocutaneous flaps. Muscle flaps had a higher risk ratio (RR) for total flap loss [RR: 2.32, 95% confidence interval (CI): 1.01-5.32, P = 0.04], arterial thrombosis (RR: 3.13, 95% CI: 1.17-8.42, P = 0.02), and amputations (RR: 8.89, 95% CI: 1.27-70.13, P = 0.03) compared with fasciocutaneous flaps. No significant differences were found in venous thrombosis (RR: 1.33, 95% CI: 0.37-4.78, P = 0.65) or need for reinterventions (RR: 1.34, 95% CI: 0.77-2.32, P = 0.29). Muscle flaps in burn injuries are associated with higher risks of flap failure, arterial thrombosis, and amputations. Fasciocutaneous free flaps in acute burns seem to be safer with better outcomes, though further research is needed to confirm these findings.

Disability severity and risk of new or recurrent intimate partner violence – Evidence from a cohort study in rural Pakistan

BackgroundPeople with disabilities are more likely to experience intimate partner violence (IPV) than those without. Most research examining the relationship between disability and IPV, however, is cross-sectional and approaches disability as a binary variable. This relationship is also important to consider in a South Asian context, where it may be affected by cultural norms surrounding IPV, and resources for people with disabilities. ObjectiveTo estimate the degree to which disability severity increases the risk of subsequent IPV among a cohort of mothers living in rural Pakistan. MethodsMothers from the Bachpan study (N = 869) with data for at least two consecutive waves between 1-, 2-, 3-, and 6-years postpartum were included in this study. Modified Poisson regression models were used to estimate the relationship between disability level in the preceding wave and psychological, physical, and sexual IPV in the following wave. ResultsFor psychological IPV, the risk ratio (RR) for medium severity was 1.27 (95 % CI: 1.10, 1.46) and the RR for high severity was 1.23 (95 % CI: 1.02, 1.48), relative to low severity. Physical IPV had a medium severity RR of 1.44 (95 % CI: 1.00, 2.06) and high severity RR of 1.60 (95 % CI: 1.02, 2.53). For sexual IPV, the medium severity RR was 1.35 (95 % CI: 1.05, 1.75) and the high severity RR was 1.53 (95 % CI: 1.11, 2.10). ConclusionsThis study supports that, in a low-income, rural South Asian context, mothers with disabilities are particularly susceptible to future psychological, physical, and sexual IPV.

Candida Albicans Candidalysin ECE1 Gene - A Potent Virulence Factor for Oral Squamous Cell Carcinoma and Oral Potentially Malignant Disorders.

Candidalysin has been isolated initially from a pathogenic human fungus. The extent of cell elongation 1 (ECE1) gene codes for candidalysin of Candida albicans (C. albicans). This toxin is most important for epithelial immune activation, invasiveness and infection of the oral mucosa. This study is aimed at detecting the ECE1 gene in C. albicans isolates from oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMDs). A total of 60 C. albicans isolates from OSCC (n = 23), OPMDs (n = 23) and healthy subjects (n = 14) were subjected to a polymerase chain reaction (PCR) for the detection of ECE1 gene. A high prevalence of the ECE1 gene was observed among the C. albicans isolates from OSCC and OPMD compared to the isolates from healthy subjects. Statistical significance was observed for both OSCC and OPMD groups compared to the healthy group. The results suggest the significant role of candidalysin in oral oncogenesis. The high odds and risk ratio specify a strong association between candidalysin and these conditions. Screening this gene in a large number of isolates would further reinforce their role in oncogenesis. Future studies in characterizing their virulence on normal cell lines would clarify the importance of candidalysin in promoting oncogenesis.

An investigation of the longitudinal trajectory patterns of health-related quality of life among Australians with disabilities: explaining disability types and properties

BackgroundResearch on health-related quality of life (HRQoL) trajectory patterns for people with disabilities (PwD) is scant. Understanding the HRQoL trajectory patterns for PwDs and investigating their relationship with disability types and socioeconomic factors can have important implications for Australia’s welfare policy.MethodsWe analysed data from waves 11 to 21 of the Household, Income and Labour Dynamics in Australia (HILDA) survey of respondents aged 15 + years of the PwDs. The analytic sample consists of 3724 self-reported disabled individuals and 34,539 observations in total. The SF-6D utility score is our HRQoL measure. Group-based trajectory modelling was utilised to identify trajectory groups, and multinomial logistic regression was employed to determine the baseline factors associated with trajectory group membership.ResultsThe study identified four distinct types of HRQoL trajectories (high, moderate improving, moderate deteriorating and low HRQoL trajectories). Psychosocial disability types followed by physical disability types had a high Relative Risk Ratio (RRR) in the low group compared with high trajectory group membership of PwDs (psychosocial: 6.090, physical: 3.524). Similar, results followed for the moderate improving group albeit with lower RRR (psychosocial: 2.868, Physical: 1.820). In the moderate deteriorating group, the disability types were not significant as this group has a similar profile to high group at the baseline. Compared with males, females had a higher RRR in low and moderate versus high improving HRQoL trajectories (low: 1.532, moderate improving: 1.237). Comparing the richest class to the poorest class, socioeconomic factors (income and education) predicted significantly lower exposure for the richer class to the low and medium HRQoL trajectories groups (RRR < 1).ConclusionDifferent forms of disability, demographic and socioeconomic factors have distinct effects on the HRQoL trajectories of disabled individuals. Healthcare and economic resource efficiency might be improved with targeted government policy interventions based on disability trajectories.

The Joint Effects of Thunderstorms and Power Outages on Respiratory-Related Emergency Visits and Modifying and Mediating Factors of This Relationship.

While limited studies have evaluated the health impacts of thunderstorms and power outages (POs) separately, few have assessed their joint effects. We aimed to investigate the individual and joint effects of both thunderstorms and POs on respiratory diseases, to identify disparities by demographics, and to examine the modifications and mediations by meteorological factors and air pollution. Distributed lag nonlinear models were used to examine exposures during three periods (i.e., days with both thunderstorms and POs, thunderstorms only, and POs only) in relation to emergency department visits for respiratory diseases (2005-2018) compared to controls (no thunderstorm/no PO) in New York State (NYS) while controlling for confounders. Interactions between thunderstorms and weather factors or air pollutants on health were assessed. The disparities by demographics and seasons and the mediative effects by particulate matter with aerodynamic diameter () and relative humidity (RH) were also evaluated. Thunderstorms and POs were independently associated with total and six subtypes of respiratory diseases in NYS [highest risk ratio (RR) = 1.12; 95% confidence interval (CI): 1.08, 1.17], but the impact was stronger when they co-occurred (highest RR = 1.44; 95% CI: 1.22, 1.70), especially during grass weed, ragweed, and tree pollen seasons. The stronger thunderstorm/PO joint effects were observed on chronic obstructive pulmonary diseases, bronchitis, and asthma (lasted 0-10 d) and were higher among residents who lived in rural areas, were uninsured, were of Hispanic ethnicity, were 6-17 or over 65 years old, and during spring and summer. The number of comorbidities was significantly higher by 0.299-0.782/case. Extreme cold/heat, high RH, , and ozone concentrations significantly modified the thunderstorm-health effect on both multiplicative and additive scales. Over 35% of the thunderstorm effects were mediated by and RH. Thunderstorms accompanied by POs showed the strongest respiratory effects. There were large disparities in thunderstorm-health associations by demographics. Meteorological factors and air pollution levels modified and mediated the thunderstorm-health effects. https://doi.org/10.1289/EHP13237.

Healthcare resource utilisation and direct medical cost for individuals with 5q spinal muscular atrophy in Sweden.

Spinal muscular atrophy (SMA) is a rare, progressive, neuromuscular disorder. Recent advances in treatment require an updated assessment of burden to inform reimbursement decisions. To quantify healthcare resource utilisation (HCRU) and cost of care for patients with SMA. Cohort study of patients with SMA identified in the Swedish National Patient Registry (2007-2018), matched to a reference cohort grouped into four SMA types (1, 2, 3, unspecified adult onset [UAO]). HCRU included inpatient admissions, outpatient visits, procedures, and dispensed medications. Direct medical costs were estimated by multiplying HCRU by respective unit costs. Average annual HCRU and medical costs were modelled for SMA versus reference cohorts to estimate differences attributable to the disease (i.e., average treatment effect estimand). The trajectory of direct costs over time were assessed using synthetic cohorts. We identified 290 SMA patients. Annualised HCRU was higher in SMA patients compared with reference cohorts. Highest risk ratios were observed for inpatient overnight stays for type 1 (risk ratio [RR]: 29.2; 95% confidence interval [CI]: 16.0, 53.5) and type 2 (RR: 23.3; 95% CI: 16.4,33.1). Mean annual direct medical costs per patient for each year since first diagnosis were greatest for type 1 (€114,185 and SMA-attributable: €113,380), type 2 (€61,876 and SMA-attributable: €61,237), type 3 (€45,518 and SMA-attributable: €44,556), and UAO (€4046 and SMA-attributable: €2098). Costs were greatest in the 2-3years after the first diagnosis for all types. The economic burden attributable to SMA is significant. Further research is needed to understand the burden in other European countries and the impact of new treatments.

Employing machine learning to predict the occurrence and spatial variability of high fluoride groundwater in intensively irrigated areas

Groundwater serves as a vital source of drinking water in the Hetao Basin of northwestern China. However, the occurrence and intense spatial variability of high fluoride (F−>1.5 mg/L) groundwater poses a significant health threat to local residents. In this study, the Random Forest (RF) machine learning algorithm was employed to develop two prediction models for high fluoride groundwater in Qiantao and Houtao plain, northwestern China, based on 650 groundwater samples. The models incorporated hydrochemical and geospatial datasets (climatic factors, topographic factors, and soil properties) to predict the probability of fluoride in groundwater exceeding 1.5 mg/L at a 250 m spatial resolution. The results show that the high-risk areas of the Qiantao Plain and Houtao Plain cover 33.0 % and 6.7 % of the total area of the plains, respectively. The ratio of high risk (F > 1.5 mg/L) samples correctly detected in Qiantao plain and Houtao plain were 86.7% and 94.5%, indicated an increased sensitivity to high fluoride category. Hydrochemical parameters were proven to be the most effective predictors. The spatial variability of high fluoride groundwater in two plains was dominated by the lithology, tectonic evolution, and hydrogeologic settings. Hyper-parameter optimized RF models demonstrate an outstanding performance in predicting the risk of high fluoride groundwater. This research presents a cooperative and successful effort to integrate hydrochemical and geospatial variables for prediction model, which can enhance the understanding of the geological origin and anthropogenic causes, and facilitate decision-making to identify potential risks in the areas affected by high levels of fluoride in groundwater.

Prevalence and clinical impact of sarcopenia in liver transplant recipients: A meta-analysis.

The prevalence of sarcopenia in patients undergoing liver transplantation (LT) remains to be determined partly because of different diagnostic criteria. Sarcopenia has recently been recognized as a new prognostic factor for predicting outcomes in LT candidates. To estimate the prevalence of sarcopenia and evaluate its clinical effect on LT candidates. This systematic search was conducted in PubMed, Web of Science, Embase, and Cochrane Library for original English-language articles that investigated the prevalence and influence of sarcopenia in patients undergoing LT from database inception to November 30, 2022. Cohort studies of the definition of sarcopenia that estimate sarcopenia prevalence and evaluate its effect on clinical outcomes and the risk of mortality were included. Twenty-five studies involving 7760 patients undergoing LT were included. The pooled prevalence of sarcopenia in patients undergoing LT was 40.7% [95% confidence intervals (95%CI): 32.1-49.6]. The 1-, 3-, and 5-year cumulative probabilities of post-LT survival in patients with preoperative sarcopenia were all lower than those without sarcopenia (P < 0.05). Sarcopenia was associated with an increased risk of post-LT mortality in patients undergoing LT (adjusted hazard ratio: 1.58; 95%CI: 1.21-2.07). Patients with preoperative sarcopenia had a longer intensive care unit stay, a high risk ratio of sepsis, and serious post-LT complications than those without sarcopenia. Sarcopenia is prevalent in a substantial proportion of patients undergoing LT and is strongly and independently associated with higher a risk of mortality risk.

New-onset autoimmune disease after COVID-19.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) may trigger autoimmune disease (AD) through initial innate immune activation with subsequent aberrations in adaptive immune cells leading to AD. While there are multiple reports of incident AD diagnosed after COVID-19, the risk in the context of key circulating strains is unknown. TriNetX, a global, federated, health research network providing access to electronic medical records across 74 healthcare organizations, was utilized to define an adult cohort between January 1, 2020, and March 3, 2023. Exposure was defined as COVID-19 diagnosis (ICD-10 code or positive laboratory test). Age- and sex-propensity score-matched controls never had COVID-19 diagnosed. Outcomes were assessed 1 month to 1 year after the index date. Patients with AD prior to or within 1 month after the index date were excluded from the primary analysis. Incidence and risk ratios of each AD were assessed. A total of 3,908,592 patients were included. Of 24 AD patients assessed, adjusted risk ratios for eight AD patients who had COVID-19 were higher compared to those who had no COVID-19. Cutaneous vasculitis (adjusted hazard ratio (aHR): 1.82; 95% CI 1.55-2.13), polyarteritis nodosa (aHR: 1.76; 95% CI 1.15-2.70), and hypersensitivity angiitis (aHR: 1.64; 95% CI 1.12-2.38) had the highest risk ratios. Overall, psoriasis (0.15%), rheumatoid arthritis (0.14%), and type 1 diabetes (0.13%) had the highest incidence during the study period, and of these, psoriasis and diabetes were more likely after COVID-19. The risk of any AD was lower if COVID-19 was diagnosed when Omicron variants were the predominant circulating strains. A positive antinuclear antibody was more likely and predictive of AD after COVID-19. SARS-CoV-2 may be a potential trigger for some AD, but the risk for AD may decrease with time given the apparent lower risk after infection with Omicron variants.

Spatio-temporal epidemiology and associated indicators of COVID-19 (wave-I and II) in India

The spatio-temporal distribution of COVID-19 across India’s states and union territories is not uniform, and the reasons for the heterogeneous spread are unclear. Identifying the space–time trends and underlying indicators influencing COVID-19 epidemiology at micro-administrative units (districts) will help guide public health strategies. The district-wise daily COVID-19 data of cases and deaths from February 2020 to August 2021 (COVID-19 waves-I and II) for the entire country were downloaded and curated from public databases. The COVID-19 data normalized with the projected population (2020) and used for space–time trend analysis shows the states/districts in southern India are the worst hit. Coastal districts and districts adjoining large urban regions of Mumbai, Chennai, Bengaluru, Goa, and New Delhi experienced > 50,001 cases per million population. Negative binomial regression analysis with 21 independent variables (identified through multicollinearity analysis, with VIF < 10) covering demography, socio-economic status, environment, and health was carried out for wave-I, wave-II, and total (wave-I and wave-II) cases and deaths. It shows wealth index, derived from household amenities datasets, has a high positive risk ratio (RR) with COVID-19 cases (RR: 3.577; 95% CI: 2.062–6.205) and deaths (RR: 2.477; 95% CI: 1.361–4.506) across the districts. Furthermore, socio-economic factors such as literacy rate, health services, other workers’ rate, alcohol use in men, tobacco use in women, overweight/obese women, and rainfall have a positive RR and are significantly associated with COVID-19 cases/deaths at the district level. These positively associated variables are highly interconnected in COVID-19 hotspot districts. Among these, the wealth index, literacy rate, and health services, the key indices of socio-economic development within a state, are some of the significant indicators associated with COVID-19 epidemiology in India. The identification of district-level space–time trends and indicators associated with COVID-19 would help policymakers devise strategies and guidelines during public health emergencies.

Sober up: Time from last drink to a road traffic injury

PurposeThere is no intervention that quickly reduces a person's blood alcohol content (BAC). “Sober up before you drive” may prevent road traffic injury (RTI) caused by alcohol consumption. The aim of this study was to analyze the risk of RTI on an hourly basis (1–6 h) after the last drink and the determinants of this risk. MethodsThis was a case-crossover study of alcohol consumption among 430 patients who suffered an RTI and arrived at an emergency department in a large hospital in Mexico City from January to April 2022. ResultsOf the 430 patients studied, 46 reported drinking within 1 h before the RTI, for a risk ratio (RR) of 7.7 (95% CI [5.6, 10.4]). This RR decreased to 2.2 (95% CI [1.3, 3.7]) for the 12 patients drinking in the second hour before the RTI and was null for those drinking earlier (p ≤ 0.001 for the trend). The induction time was 3 h among those with higher BAC and intoxication levels. The RR for an RTI decreases 71% from the first to second hour from the last drink and 32% from the second to third hour. This decrease was similar among those intoxicated and those with increased BACs. In multiple regression models, higher levels of intoxication and higher BACs remained associated with higher RRs. DiscussionPeople should avoid driving after drinking. Waiting to drive, walking, or riding after drinking reduces the risk of an RTI, especially for people with higher BAC and intoxication levels.

Brain health scores to predict neurological outcomes from electronic health records

BackgroundPreserving brain health is a critical priority in primary care, yet screening for these risk factors in face-to-face primary care visits is challenging to scale to large populations. We aimed to develop automated brain health risk scores calculated from data in the electronic health record (EHR) enabling population-wide brain health screening in advance of patient care visits. MethodsThis retrospective cohort study included patients with visits to an outpatient neurology clinic at Massachusetts General Hospital, between January 2010 and March 2021. Survival analysis with an 11-year follow-up period was performed to predict the risk of intracranial hemorrhage, ischemic stroke, depression, death and composite outcome of dementia, Alzheimer’s disease, and mild cognitive impairment. Variables included age, sex, vital signs, laboratory values, employment status and social covariates pertaining to marital, tobacco and alcohol status. Random sampling was performed to create a training (70%) set for hyperparameter tuning in internal 5-fold cross validation and an external hold-out testing (30%) set of patients, both stratified by age. Risk ratios for high and low risk groups were evaluated in the hold-out test set, using 1000 bootstrapping iterations to calculate 95% confidence intervals (CI). ResultsThe cohort comprised 17,040 patients with an average age of 49 ± 15.6 years; majority were males (57 %), White (78 %) and non-Hispanic (80 %). The low and high groups average risk ratios [95 % CI] were: intracranial hemorrhage 0.46 [0.45–0.48] and 2.07 [1.95–2.20], ischemic stroke 0.57 [0.57–0.59] and 1.64 [1.52–1.69], depression 0.68 [0.39–0.74] and 1.29 [0.78–1.38], composite of dementia 0.27 [0.26–0.28] and 3.52 [3.18–3.81] and death 0.24 [0.24–0.24] and 3.96 [3.91–4.00]. ConclusionsSimple risk scores derived from routinely collected EHR accurately quantify the risk of developing common neurologic and psychiatric diseases. These scores can be computed automatically, prior to medical care visits, and may thus be useful for large-scale brain health screening.

Software Reliability Growth Model for N-Version Fault Tolerant Software with Common and Independent Faults

Research and development teams have become increasingly focused on developing highly reliable software for safety-critical systems. It is a major challenge for real-time control systems to achieve high reliability software to meet safety standards. A reliability evaluation focuses primarily on analytical and modeling techniques for fault prediction. In safety-critical systems like nuclear plant controls, aircraft controls and railroad signalization systems, N-version programming (NVP) is an effective technique for raising software’s reliability, particularly in areas with high-risk ratios because small errors can result in hazardous incidents. It allows the software to be fault-tolerant, aiding it to produce accurate results even when the software has faults. We present an analytical method for assessing the reliability of N-version software systems. Analysis of the system’s reliability and other performance metrics is provided with closed-form expressions. As an additional extension, we conduct numerical analyses of two cases, the 2VP system and 3VP system, in which suitable parameters are used. We conduct numerical simulations using MATLAB to generate the analytical results and compare the analytical results by using numerical results and neuro-fuzzy results using fuzzy interference systems.

Vehicle leasing credit risk assessment modeling by applying extended logistic regression

In vehicle leasing industry which presents a great business opportunity, information completed by applicants was assessed and judged by leasing associates manually in most cases; therefore, assessment results would be affected by their personal experience of leasing associates and decisions would be further affected accordingly. There are few researches on applicant credit risk assessment due to not easy to obtain of vehicle leasing data. Further, the difficulty in vehicle leasing risk assessment is increased due to class imbalance problems in vehicle leasing data. In order to address such issue, a research on credit risk assessment in vehicle leasing industry was conducted in this study. The great disparity in the ratio of high risk and low risk data was addressed by applying synthetic minority over-sampling technique (SMOTE). Then, classification effect of risk assessment model was improved by applying logistic regression in a two-phase manner. In the section of empirical analysis, the feasibility and effectiveness of the approach proposed in this study was validated by using data of actual vehicle leasing application cases provided by a financial institution in Taiwan. It is found that the proposed approach provided a simple yet effective way to build a credit risk assessment model for companies that provide vehicle leasing.