Statistical Classification Research Articles

Maternal Obesity and Risk of Sudden Unexpected Infant Death

Rates of maternal obesity are increasing in the US. Although obesity is a well-documented risk factor for numerous poor pregnancy outcomes, it is not currently a recognized risk factor for sudden unexpected infant death (SUID). To determine whether maternal obesity is a risk factor for SUID and the proportion of SUID cases attributable to maternal obesity. This was a US nationwide cohort study using Centers for Disease Control and Prevention National Center for Health Statistics linked birth-infant death records for birth cohorts in 2015 through 2019. All US live births for the study years occurring at 28 weeks' gestation or later from complete reporting areas were eligible; SUID cases were deaths occurring at 7 to 364 days after birth with International Statistical Classification of Diseases, Tenth Revision cause of death code R95 (sudden infant death syndrome), R99 (ill-defined and unknown causes), or W75 (accidental suffocation and strangulation in bed). Data were analyzed from October 1 through November 15, 2023. Maternal prepregnancy body mass index (BMI; calculated as weight in kilograms divided by height in meters squared). SUID. Of 18 857 694 live births eligible for analysis (median [IQR] age: maternal, 29 [9] years; paternal, 31 [9] years; gestational, 39 [2] weeks), 16 545 died of SUID (SUID rate, 0.88/1000 live births). After confounder adjustment, compared with mothers with normal BMI (BMI 18.5-24.9), infants born to mothers with obesity had a higher SUID risk that increased with increasing obesity severity. Infants of mothers with class I obesity (BMI 30.0-34.9) were at increased SUID risk (adjusted odds ratio [aOR], 1.10; 95% CI, 1.05-1.16); with class II obesity (BMI 35.0-39.9), a higher risk (aOR, 1.20; 95% CI, 1.13-1.27); and class III obesity (BMI ≥40.0), an even higher risk (aOR, 1.39; 95% CI, 1.31-1.47). A generalized additive model showed that increased BMI was monotonically associated with increased SUID risk, with an acceleration of risk for BMIs greater than approximately 25 to 30. Approximately 5.4% of SUID cases were attributable to maternal obesity. The findings suggest that infants born to mothers with obesity are at increased risk of SUID, with a dose-dependent association between increasing maternal BMI and SUID risk. Maternal obesity should be added to the list of known risk factors for SUID. With maternal obesity rates increasing, research should identify potential causal mechanisms for this association.

Fairness in Classifying and Grouping Health Equity Information.

This paper explores the balance between fairness and performance in machine learning classification, predicting the likelihood of a patient receiving anti-microbial treatment using structured data in community nursing wound care electronic health records. The data includes two important predictors (gender and language) of the social determinants of health, which we used to evaluate the fairness of the classifiers. At the same time, the impact of various groupings of language codes on classifiers' performance and fairness is analyzed. Most common statistical learning-based classifiers are evaluated. The findings indicate that while K-Nearest Neighbors offers the best fairness metrics among different grouping settings, the performance of all classifiers is generally consistent across different language code groupings. Also, grouping more variables tends to improve the fairness metrics over all classifiers while maintaining their performance.

Psychiatric morbidity across the life course and provoked vulvodynia: is it dependent upon the presence of non-stress-related immune dysfunction?

Vulvodynia impacts up to 8% of women by age 40, and these women may have a more compromised immune system than women with no vulvar pain history. Given that psychiatric morbidity is associated with vulvodynia and is known to activate immune inflammatory pathways in the brain and systemically, we sought to determine whether the association between psychiatric morbidity and vulvar pain was independent of or dependent upon the presence of immune-related conditions. Women born in Sweden between 1973 and 1996 with localized provoked vulvodynia (N76.3) and/or vaginismus (N94.2 or F52.5) diagnosed between 2001 and 2018 were matched to two women from the same birth year with no vulvar pain. International Statistical Classification of Diseases and Related Health Problems (ICD-9 or -10 codes) were used to identify women with a history of depression, anxiety, attempted suicide, neurotic disorders, stress-related disorders, behavioral syndromes, personality disorders, psychotic disorders, or chemical dependencies, as well as a spectrum of immune-related conditions. The Swedish National Prescribed Drug Register was used to identify women with filled prescriptions of antidepressants or anxiolytics. Vulvodynia, vaginismus, or both were outcomes assessed in relation to psychiatric morbidity. Women with vulvodynia, vaginismus, or both, relative to those without vulvar pain, had adjusted odds ratios between 1.4 and 2.3, with CIs highly compatible with harmful effects. When we assessed women with and those without a lifetime history of immune-related conditions separately, we also observed elevated odds ratios in both groups for mood, anxiety, and neurotic and stress disorders. Documenting psychiatric impairment as a cause or consequence of vulvodynia is critical in clinical practice because psychiatric conditions may impact treatment efficacy. Strengths of this study include a data source that represents the entire population of women in Sweden that is known to be highly accurate because Sweden provides universal healthcare. Limitations include difficulty in making an accurate assessment of temporality between psychiatric morbidity and the first onset of vulvar pain. In addition, because Swedish registry data have limited information on lifestyle, behavioral, and anthropomorphic factors such as smoking, diet, physical activity, and obesity, these conditions could not be assessed as confounders of psychiatric morbidity and vulvar pain. Immune pathways by which women with psychiatric conditions increase their risk of vulvar pain could be independent from other immune pathways.

Identification of reversible OATP1B1 and time-dependent CYP3A4 inhibition as the major risk factors for drug-induced cholestasis (DIC).

Hepatic bile acid regulation is a multifaceted process modulated by several hepatic transporters and enzymes. Drug-induced cholestasis (DIC), a main type of drug-induced liver injury (DILI), denotes any drug-mediated condition in which hepatic bile flow is impaired. Our ability in translating preclinical toxicological findings to human DIC risk is currently very limited, mainly due to important interspecies differences. Accordingly, the anticipation of clinical DIC with available in vitro or in silico models is also challenging, due to the complexity of the bile acid homeostasis. Herein, we assessed the in vitro inhibition potential of 47 marketed drugs with various degrees of reported DILI severity towards all metabolic and transport mechanisms currently known to be involved in the hepatic regulation of bile acids. The reported DILI concern and/or cholestatic annotation correlated with the number of investigated processes being inhibited. Furthermore, we employed univariate and multivariate statistical methods to determine the important processes for DILI discrimination. We identified time-dependent inhibition (TDI) of cytochrome P450 (CYP) 3A4 and reversible inhibition of the organic anion transporting polypeptide (OATP) 1B1 as the major risk factors for DIC among the tested mechanisms related to bile acid transport and metabolism. These results were consistent across multiple statistical methods and DILI classification systems applied in our dataset. We anticipate that our assessment of the two most important processes in the development of cholestasis will enable a risk assessment for DIC to be efficiently integrated into the preclinical development process.

The course of COVID-19 infection in patients with cardiovascular diseases

Abstract Background Certainly, the COVID-19 pandemic has changed the paths of modern medicine. Elevated morbidity and mortality that was observed especially during first and second year focused health care providers on highlighting the high risk group of patients. Many results have showed the influence of comorbidities on the course of COVID-19. Purpose The aim of the study was to demonstrate whether cardiovascular diseases correlate to severity of coronavirus disease 2019 infection. Methods The study group contained 70 patients admitted to the hospital from the 1st of January 2021 to the 10th of November 2022 due to symptoms indicating respiratory infection. The survey's inclusion criteria was U07.1 COVID-19, virus identified (code from Chapter XXII: Codes for special purposes of The International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) – WHO, Version 2019: COVID expanded). The used research method was the analysis of patients' medical records. Subsequently the data were subjected to quantitative and statistical analysis. Results There were 16 different cardiovascular diseases diagnosed in the study group. The most common were: I10 Essential (primary) hypertension (46/70 patients; 65,71%), I50.9 Heart failure, unspecified (16/70 patients; 22,86%), I48 Atrial fibrillation and flutter (16/70 patients; 22,86%). The data of concerning hospitalizations of groups of patients with the most commonly observed cardiovascular diseases, along with a comparison to the entire study group, are presented in Table 1. Furthermore, there was statistically significant correlation between at least one cardiovascular comorbidity and the need to transfer the patient to continue the treatment of COVID-19 in the intensive care unit (p<0,001). Conclusions The results of this study showed that patients with most common cardiovascular diseases stayed hospitalized for longer time, were older and more often needed antibiotic and anticoagulant therapy compared to the entire study group. That provide a basis to conclude that patients with cardiovascular diseases are at higher risk of severe COVID-19 and the special management to this group should be applied into common medical practice.

Recent temporal trends, characteristics and outcomes of patients with non-COVID-19 community-acquired pneumonia at two tertiary hospitals in Australia: an observational study.

Community-acquired pneumonia (CAP) leads to considerable morbidity and mortality globally. However, data on CAP burden in Australia, especially during the coronavirus disease 2019 (COVID-19) pandemic, are limited. We characterised and assessed clinical outcomes of non-COVID-19 CAP hospitalisations over a 6-year period at two major hospitals in South Australia. All non-COVID-19 CAP hospitalisations were identified using the International Statistical Classification of Diseases and Related Health Problems, Tenth revision, Australian modification (ICD-10-AM) codes, between 1 January 2018 and 31 December 2023, at two tertiary hospitals in Adelaide. Clinical outcomes included in-hospital and 30-day mortality, length of stay (LOS) in, intensive care unit (ICU) admission and 30-day readmissions. Multilevel regression models were utilised to identify predictors of clinical outcomes. Over the 6-year period, there were 7853 non-COVID-19 CAP hospitalisations, with a temporal increase from 100 per 100 000 population in 2018 to 208 per 100 000 population in 2023 (P < 0.001). The mean (SD) age was 75.1 (17.6) years, and 54.6% were males. The mean age declined over time (P < 0.05), while other characteristics remained stable. Streptococcus pneumoniae was the most commonly identified bacterium (21.8% of cases). In-hospital mortality occurred in 7.8% of patients, with 30-day mortality and readmission rates of 14.3% and 16.9% respectively. LOS declined significantly during the pandemic years; however, mortality remained stable over time. Frailty status, malnutrition and number of comorbidities significantly predicted 30-day mortality and LOS, in addition to pneumonia severity and ICU admission. There has been an increasing trend of hospitalisations for non-COVID-19 CAP during the COVID-19 pandemic, with a concomitant trend towards shorter LOS and no significant shift in other clinical outcomes.

Mathematical Model of Logistic Regression for Binary Classification. Part 1. Regression Models of Data Generalization

In this article, the mathematical justification of logistic regression as an effective and simple to implement method of machine learning is performed. A review of literary sources was conducted in the direction of statistical processing, analysis and classification of data using the logistic regression method, which confirmed the popularity of this method in various subject areas. The logistic regression method was compared with the linear and probit regression methods regarding the possibility of predicting the probabilities of events. In this context, the disadvantages of linear regression and the advantages and affinity of logit and probit regression methods are noted. It is indicated that the possibility of forecasting probabilities and binary classification by the method of logistic regression is provided by the use of a sigmoid function with the property of compressive transformation of an argument with an unlimited numerical value into a limited range from 0 to 1 real value of the function. The derivation of the sigmoid function in two different ways is described: based on the model of the logarithm of the odds of events and the model of logistic population growth. Based on the method of maximum likelihood, the construction of a logarithmic loss function was demonstrated, the use of which made it possible to move from a multi-extremal nonlinear regression problem to a unimodal optimization problem. Methods of regularization of the loss function are presented to control the complexity and prevent retraining of the logistic regression model.

Pediatric Complex Chronic Condition System Version 3

Since implementation of the International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) in the US, thousands of new or related codes have been added to represent clinical conditions. The widely used pediatric complex chronic condition (CCC) system required a major update from version 2 (V2) to version 3 (V3) to capture the range of clinical conditions represented in the ICD-10-CM. To update the CCC V3 system, creating V3, with new, missing, or retired codes; to reconceptualize the system's use of technology codes; and to compare CCC V3 with V2. This repeated cross-sectional study examined US hospitalization data from the Pediatric Health Information System (PHIS) and the Medicaid Merative MarketScan Research Databases from January 1, 2009, to December 31, 2019, for all patients aged 0 to 18 years. Data were analyzed from March 1, 2023, to April 1, 2024. The CCCs were identified in both data sources using the CCC V2 and V3 systems. The (1) percentage of pediatric hospitalizations associated with a CCC, (2) numbers of CCC body-system categories per patient, and (3) explanatory power for hospital length of stay and in-hospital mortality were compared over time for V3 vs V2. Among 7 186 019 hospitalizations within PHIS, 54.3% patients were male, the median age was 4 years (IQR, 1-11 years), and 51.2% were aged 0 to 4 years). The CCC V2 identified 2 878 476 (40.1%) patients as having any CCC compared with 2 753 412 (38.3%) identified by V3. In addition, V2 identified 100 065 (1.4%) patients with transplant status compared with 146 683 (2.0%) by V3, and V2 identified 914 835 (12.7%) as having technology codes compared with 805 585 (11.2%) by V3. The 2 systems were similar in accounting for the number of CCC body-system categories per patient and in explaining variation in hospital length of stay and in-hospital mortality. For both V2 and V3, 10.0% of the variance in hospital length of stay and 12.0% of the variance in in-hospital mortality was explained by the presence of a CCC. Similar patterns were observed when analyzing the 2 999 420 Medicaid Merative MarketScan Research Databases' hospitalizations (52.3% of patients were male, the median age was 1 year [IQR, 0-12 years], and 62.0% were 0 to 4 years old), except that the percentages of identified CCCs were all lower: V2 identified 758 110 hospitalizations (25.3%) with any CCC compared with 718 100 (23.9%) identified by V3. These results suggest that, moving forward, V3 should be used to identify CCCs, and ongoing, frequent updates to V3, using a transparent, structured process, will enable V3 to accurately reflect the evolving spectrum of clinical conditions represented in the ICD-10-CM.

Seabed characterization based on the statistical classification using the seabed reflection amplitudes of sub-bottom profiler data

The seabed reflection amplitudes (SRAs) extracted from the sub-bottom profile have a strong correlation with the types and physical properties of the seabed sediments. In this paper, the SRAs distribution of classified seabed sediments is statistically obtained by calibration with seabed sampling results, discovering that SRAs on different seafloor sediment types exhibit Rayleigh distributions with varying parameters. Firstly, SRAs are compensated and enhanced, to improve their identification. Then, a novel classification method based on K–S test was proposed. This method measures the maximum distance between the cumulative distribution functions (CDF) of the unknown seabed and the calibrated sediment SRAs to check whether unknown samples belong to any of the known types. This proposed method only requires a small amount of seabed samples to automatically classify the seabed with high accuracy, and the model is simple, robust, and provides classification confidence.

A DPC Database Study on the Safety of Atezolizumab/Bevacizumab/Carboplatin/Paclitaxel in Non-small Cell Lung Cancer in Japanese Patients.

Atezolizumab, bevacizumab, carboplatin, and paclitaxel (ABCP) combination therapy is a standard of care for advanced non-squamous non-small cell lung cancer (NSQ-NSCLC); however, the lack of safety data limits its clinical application in Japan. This study compared the safety of ABCP with that of bevacizumab, carboplatin, and paclitaxel (BCP) combination for the treatment of advanced NSQ-NSCLC in Japanese patients by evaluating the clinical background and incidence of adverse events (AEs) based on data extracted from the Diagnosis Procedure Combination (DPC) database. Incidence rates and restricted mean survival times (RMSTs) for up to 1 year were analyzed for 19 clinically important AEs. Covariates were adjusted using the inverse probability weighting method. A search conducted using the International Statistical Classification of Diseases and Related Health Problems 10th Revision codes identified 350,987 patients, of whom 202 were included in the ABCP cohort and 232 in the BCP cohort. Among the 19 AEs, the incidence of skin disorder and febrile neutropenia (FN) was significantly higher in the ABCP cohort versus the BCP cohort. The adjusted incidence rate ratios were 2.65 [95%confidence interval (CI) 1.43-4.91] for skin disorder and 1.70 (95% CI 1.01-2.85) for FN. The adjusted RMST differences were-64.2 days (95% CI-93.0 to-35.4 days) and-46.0days (95% CI-73.5 to-18.5 days) for skin disorder and FN, respectively. These results were comparable to those of other pivotal clinical trials. The findings of this DPC database study highlight the safety of ABCP in Japanese clinical practice, and this methodology may facilitate more efficient research in real-world settings. UMIN Clinical Trials Registry ID UMIN000041507.

Neuroimage Analysis Methods and Artificial Intelligence Techniques for Reliable Biomarkers and Accurate Diagnosis of Schizophrenia: Achievements Made by Chinese Scholars Around the Past Decade.

Schizophrenia (SZ) is characterized by significant cognitive and behavioral disruptions. Neuroimaging techniques, particularly magnetic resonance imaging (MRI), have been widely utilized to investigate biomarkers of SZ, distinguish SZ from healthy conditions or other mental disorders, and explore biotypes within SZ or across SZ and other mental disorders, which aim to promote the accurate diagnosis of SZ. In China, research on SZ using MRI has grown considerably in recent years. The article reviews advanced neuroimaging and artificial intelligence (AI) methods using single-modal or multimodal MRI to reveal the mechanism of SZ and promote accurate diagnosis of SZ, with a particular emphasis on the achievements made by Chinese scholars around the past decade. Our article focuses on the methods for capturing subtle brain functional and structural properties from the high-dimensional MRI data, the multimodal fusion and feature selection methods for obtaining important and sparse neuroimaging features, the supervised statistical analysis and classification for distinguishing disorders, and the unsupervised clustering and semi-supervised learning methods for identifying neuroimage-based biotypes. Crucially, our article highlights the characteristics of each method and underscores the interconnections among various approaches regarding biomarker extraction and neuroimage-based diagnosis, which is beneficial not only for comprehending SZ but also for exploring other mental disorders. We offer a valuable review of advanced neuroimage analysis and AI methods primarily focused on SZ research by Chinese scholars, aiming to promote the diagnosis, treatment, and prevention of SZ, as well as other mental disorders, both within China and internationally.

Plantas medicinais utilizadas pela população do município de Mangaratiba (Rio de Janeiro, Brasil): uma revisão integrativa

Work's aim was to carry out an integrative review of the literature on medicinal plants used by the population of Mangaratiba, Rio de Janeiro, Brazil. This review was prepared from online databases. Subsequently, the health problems cited in the selected articles were classified according to the International Statistical Classification of Diseases and Related Health Problems (ICD-10) and the plants were studied. Three studies were selected, two of which were carried out on islands and the ethnobotanical knowledge of the elderly predominated. The Asteraceae and Lamiaceae families were the most cited, with the leaves and the decoction being most used as parts of the plant and form of preparation, respectively. In addition, there was an agreement of the plants used by the population, regarding the therapeutic indication with the diseases that cause illness. In view of the results obtained, it can be concluded that the municipality has a lack of study of ethnobotany, knowledge among younger people tends to disappear and the species studied can be used, minimizing the population’s illness. Literature review works such as this are important tools for the design of new projects for Primary Health Care and for the development of medicines of plant origin.

Pandemic Stringency Measures and Hospital Admissions for Eating Disorders

Hospitalizations for eating disorders rose dramatically during the COVID-19 pandemic. Public health restrictions, or stringency, are believed to have played a role in exacerbating eating disorders. Few studies of eating disorders during the pandemic have extended to the period when public health stringency restrictions were lifted. To assess the association between hospitalization rates for eating disorders and public health stringency during the COVID-19 pandemic and after the easing of public health restrictions. This Canadian population-based cross-sectional study was performed from April 1, 2016, to March 31, 2023, and was divided into pre-COVID-19 and COVID-19-prevalent periods. Data were provided by the Canadian Institute for Health Information and the Institut National d'Excellence en Santé et Services Sociaux for all Canadian provinces and territories. Participants included all children and adolescents aged 6 to 20 years. The exposure was public health stringency, as measured by the Bank of Canada stringency index. The primary outcome was hospitalizations for a primary diagnosis of eating disorders (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision code F50), stratified by region, age group, and sex. Interrupted time series analyses based on Poisson regression were used to estimate the association between the stringency index and the rate of hospitalizations for eating disorders. During the study period, there were 11 289 hospitalizations for eating disorders across Canada, of which 8726 hospitalizations (77%) were for females aged 12 to 17 years. Due to low case counts in other age-sex strata, the time series analysis was limited to females within the 12- to 17-year age range. Among females aged 12 to 17 years, a 10% increase in stringency was associated with a significant increase in hospitalization rates in Quebec (adjusted rate ratio [ARR], 1.05; 95% CI, 1.01-1.07), Ontario (ARR, 1.05; 95% CI, 1.03-1.07), the Prairies (ARR, 1.08; 95% CI, 1.03-1.13), and British Columbia (ARR, 1.11; 95% CI, 1.05-1.16). The excess COVID-19-prevalent period hospitalizations were highest at the 1-year mark, with increases in all regions: Quebec (RR, 2.17), Ontario (RR, 2.44), the Prairies (RR, 2.39), and British Columbia (RR, 2.02). In this cross-sectional study of hospitalizations for eating disorders across Canada, hospitalization rates for eating disorders in females aged 12 to 17 years were associated with public health measure stringency. The findings suggest that future pandemic preparedness should consider implications for youths at risk for eating disorders and their resource and support needs.

Temporal relationship between sarcoidosis and malignancies in a nationwide cohort of 1942 patients.

To investigate the phenotype of sarcoidosis according to the time when a malignancy is diagnosed (preexisting to the diagnosis of sarcoidosis, concomitant, or sequential) and to identify prognostic factors associated with malignancies in a large cohort of patients with sarcoidosis. We searched for malignancies in the SARCOGEAS cohort, a multicenter nationwide database of consecutive patients diagnosed with sarcoidosis according to the ATS/ESC/WASOG criteria. Solid malignancies were classified using the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) nomenclature, and hematological malignancies using the 2016 WHO classification. We excluded patients with a biopsy-proven diagnosis of sarcoidosis based exclusively on demonstrating granulomas in tissues also involved by malignant cells. Out of 1942 patients with sarcoidosis, 233 (12%) developed 250 malignancies, including solid (n= 173), hematological (n= 57), and both types of malignancies (n= 3). Concerning the time interval between the diagnoses of both conditions, 83 (36%) patients were diagnosed with malignancy at least 1 year before sarcoidosis diagnosis, 22 (9%) had s synchronous diagnosis of both diseases, and 118 (51%) developed malignancies at least 1 year after the diagnosis of sarcoidosis (the remaining cases developed malignancies in different time intervals). The multivariate-adjusted model showed that individuals with sarcoidosis who developed a malignancy had an hazard ratio (HR) of 2.27 [95% confidence interval (CI), 1.62-3.17] for having an asymptomatic clinical phenotype at diagnosis of sarcoidosis and that spleen (presence vs. absence: HR = 2.06; 95% CI, 1.21-3.51) and bone marrow (presence vs. absence: HR = 3.04; 95% CI, 1.77-5.24) involvements were independent predictors for the development of all-type malignancies. No predictive factors were identified when the analysis was restricted to the development of solid malignancies. The analysis limited to the development of hematological malignancies confirmed the presence of involvement in the spleen (HR = 3.73; 95% CI, 1.38-10.06) and bone marrow (presence vs. absence: HR = 8.00; 95% CI, 3.15-20.35) at the time of sarcoidosis diagnosis as predictive factors. It is essential to consider the synchronous or metachronous timing of the diagnosis of malignancies in people with sarcoidosis. We found that half of the malignancies were diagnosed after a diagnosis of sarcoidosis, with spleen and bone marrow involvement associated with a four to eight times higher risk of developing hematological malignancies. Key messages What is already known on this topic Malignancies are one of the comorbidities more frequently encountered in people with sarcoidosis What this study adds Malignancies occur in 12% of patients with sarcoidosis Malignancy may precede, coincide with, or follow the diagnosis of sarcoidosis One-third were identified before sarcoidosis, and half were diagnosed after Spleen and bone marrow involvement are risk factors for developing hematological malignancies How this study might affect research, practice or policy Patients with sarcoidosis should be regularly monitored for neoplasms, informed of the increased risk, and educated on early detection. Those with spleen or bone marrow involvement must be closely followed.

Driver Fatigue Detection Using Heart Rate Variability Features from 2-Minute Electrocardiogram Signals While Accounting for Sex Differences.

Traffic accidents due to fatigue account for a large proportion of road fatalities. Based on simulated driving experiments with drivers recruited from college students, this paper investigates the use of heart rate variability (HRV) features to detect driver fatigue while considering sex differences. Sex-independent and sex-specific differences in HRV features between alert and fatigued states derived from 2 min electrocardiogram (ECG) signals were determined. Then, decision trees were used for driver fatigue detection using the HRV features of either all subjects or those of only males or females. Nineteen, eighteen, and thirteen HRV features were significantly different (Mann-Whitney U test, p < 0.01) between the two mental states for all subjects, males, and females, respectively. The fatigue detection models for all subjects, males, and females achieved classification accuracies of 86.3%, 94.8%, and 92.0%, respectively. In conclusion, sex differences in HRV features between drivers' mental states were found according to both the statistical analysis and classification results. By considering sex differences, precise HRV feature-based driver fatigue detection systems can be developed. Moreover, in contrast to conventional methods using HRV features from 5 min ECG signals, our method uses HRV features from 2 min ECG signals, thus enabling more rapid driver fatigue detection.

Risk of Nonarteritic Anterior Ischemic Optic Neuropathy in Patients Prescribed Semaglutide

Anecdotal experience raised the possibility that semaglutide, a glucagon-like peptide 1 receptor agonist (GLP-1 RA) with rapidly increasing use, is associated with nonarteritic anterior ischemic optic neuropathy (NAION). To investigate whether there is an association between semaglutide and risk of NAION. In a retrospective matched cohort study using data from a centralized data registry of patients evaluated by neuro-ophthalmologists at 1 academic institution from December 1, 2017, through November 30, 2023, a search for International Statistical Classification of Diseases and Related Health Problems, Tenth Revision code H47.01 (ischemic optic neuropathy) and text search yielded 16 827 patients with no history of NAION. Propensity matching was used to assess whether prescribed semaglutide was associated with NAION in patients with type 2 diabetes (T2D) or overweight/obesity, in each case accounting for covarying factors (sex, age, systemic hypertension, T2D, obstructive sleep apnea, obesity, hyperlipidemia, and coronary artery disease) and contraindications for use of semaglutide. The cumulative incidence of NAION was determined with the Kaplan-Meier method and a Cox proportional hazards regression model adjusted for potential confounding comorbidities. Data were analyzed from December 1, 2017, through November 30, 2023. Prescriptions for semaglutide vs non-GLP-1 RA medications to manage either T2D or weight. Cumulative incidence and hazard ratio of NAION. Among 16 827 patients, 710 had T2D (194 prescribed semaglutide; 516 prescribed non-GLP-1 RA antidiabetic medications; median [IQR] age, 59 [49-68] years; 369 [52%] female) and 979 were overweight or obese (361 prescribed semaglutide; 618 prescribed non-GLP-1 RA weight-loss medications; median [IQR] age, 47 [32-59] years; 708 [72%] female). In the population with T2D, 17 NAION events occurred in patients prescribed semaglutide vs 6 in the non-GLP-1 RA antidiabetes cohort. The cumulative incidence of NAION for the semaglutide and non-GLP-1 RA cohorts over 36 months was 8.9% (95% CI, 4.5%-13.1%) and 1.8% (95% CI, 0%-3.5%), respectively. A Cox proportional hazards regression model showed higher risk of NAION for patients receiving semaglutide (hazard ratio [HR], 4.28; 95% CI, 1.62-11.29); P < .001). In the population of patients who were overweight or obese, 20 NAION events occurred in the prescribed semaglutide cohort vs 3 in the non-GLP-1 RA cohort. The cumulative incidence of NAION for the semaglutide vs non-GLP-1 RA cohorts over 36 months was 6.7% (95% CI, 3.6%-9.7%) and 0.8% (95% CI, 0%-1.8%), respectively. A Cox proportional hazards regression model showed a higher risk of NAION for patients prescribed semaglutide (HR, 7.64; 95% CI, 2.21-26.36; P < .001). This study's findings suggest an association between semaglutide and NAION. As this was an observational study, future study is required to assess causality.

Gender-Affirming Hormone Treatment and Metabolic Syndrome Among Transgender Veterans.

Gender-affirming hormone treatment (GAHT) is a common therapy for transgender individuals to reduce gender dysphoria and improve quality of life. Clarifying the long-term effects of GAHT remains a priority in transgender health research. To explore whether sex hormones (estradiol and testosterone) are associated with the development of metabolic syndrome in transgender veterans compared with cisgender veterans. This retrospective, longitudinal cohort study used International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis codes for gender dysphoria from the Veterans Health Administration national database to identify transfeminine and transmasculine veterans receiving documented feminizing (estradiol) or masculinizing (testosterone) treatment from January 1, 2006, to December 31, 2019, and for whom the GAHT initiation date and metabolic syndrome component-related data were available. Transgender veterans were matched to cisgender referents. Gender-affirming hormone treatment. Metabolic syndrome z-scores were calculated based on body mass index, systolic blood pressure, and levels of high-density lipoprotein cholesterol, triglycerides, and blood glucose. Changes in mean z-scores were compared among the transgender and cisgender groups before and after the index date (corresponding to GAHT initiation) using a repeated-measures analysis of variance model. The cohort included 1290 participants: 645 transgender (494 [38.3%] transfeminine, 151 [11.7%] transmasculine) and 645 cisgender (280 [21.7%] female, 365 [28.3%] male). Mean (SD) age at the index date was 41.3 (13.2) years. Metabolic syndrome z-scores changed significantly over time and differed significantly across groups. Overall, transmasculine veterans had the greatest percentage increase in mean (SEM) z-scores after vs before the index date (298.0% [57.0%]; P < .001), followed by cisgender females (108.3% [27.5%]; P < .001), cisgender males (49.3% [27.5%]; P = .02), and transfeminine persons (3.0% [10.7%]; P = .77). In this cohort study, in both cisgender and transgender veterans, estradiol was associated with reduced metabolic syndrome risk, whereas testosterone was associated with increased risk. However, transmasculine individuals had the greatest risk and transfeminine individuals had the lowest risk of metabolic syndrome associated with these hormones. This is relevant for the management of metabolic syndrome risk factors in cisgender and transgender individuals and to potentially predict the risk of atherosclerotic cardiovascular disease, type 2 diabetes, systolic hypertension, insulin resistance, and nonalcoholic fatty liver disease.

Diagnostic Accuracy of Mental Health Screening Tools After Mild Traumatic Brain Injury.

Mental health disorders are common after mild traumatic brain injury (mTBI) and likely exacerbate postconcussive symptoms and disability. Early detection could improve clinical outcomes, but the accuracy of mental health screening tools in this population has not been well established. To determine the diagnostic accuracy of the Patient Health Questionnaire-9 (PHQ-9), Generalizaed Anxiety Disorder-7 (GAD-7), and Primary Care PTSD (Posttramatic Stress Disorder) Screen for Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) (PC-PTSD-5) in adults with mTBI. This diagnostic study was performed as a secondary analysis of a cluster randomized clinical trial. Self-report mental health screening tools (PHQ-9, GAD-7, and PC-PTSD-5) were administered online 12 weeks after mTBI and compared against a structured psychodiagnostic interview (Mini-International Neuropsychiatric Interview for DSM-5 (MINI) over videoconference at the same time. Adults with mTBI (N = 537) were recruited from February 1, 2021, to October 25, 2022. Presence of a major depressive episode, anxiety disorders, and PTSD were determined by a blinded assessor with the MINI. Diagnostic accuracy statistics were derived for the PHQ-9, GAD-7, and PC-PTSD-5. Findings were disaggregated for participants with and without persistent postconcussion symptoms (PPCS) by International and Statistical Classification of Diseases, Tenth Revision criteria. Data were available for 499 of 537 trial participants, 278 (55.7%) of whom were female; the mean (SD) age was 38.8 (13.9) years. Each screening questionnaire had strong diagnostic accuracy in the overall sample for optimal cut points (area under the curve [AUC], ≥0.80; sensitivity, 0.55-0.94; specificity, 0.64-0.94). The AUC (difference of 0.01-0.13) and specificity (difference, 5-65 percentage points) were lower in those with PPCS present compared with PPCS absent, but the prevalence of at least 1 mental health disorder was 3 to 5 times higher in patients with PPCS present. The GAD-7 had slightly better performance than the PC-PTSD-5 for detecting PTSD (AUC, 0.85 [95% CI, 0.80-0.89] vs 0.80 [95% CI, 0.72-0.87]). The optimal cutoff on the PHQ-9 was 5 or more symptoms experienced on more than half of days; on the GAD-7, a total score of at least 7. The findings of this diagnostic study suggest that the PHQ-9, GAD-7 and PC-PTSD-5 accurately screen for mental health disorders in patients with mTBI. Future research should corroborate optimal test cutoffs for this population.

Mental Health Diagnoses Risk Among Children and Young Adults With Cerebral Palsy, Chronic Conditions, or Typical Development

Mental health (MH) issues in children with cerebral palsy (CP) are poorly understood compared with other pediatric populations. To examine MH diagnosis code assignment among children and young adults with CP and compare with typically developing (TD) and chronic condition (CC) pediatric populations. This case-control study used International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes to create a CP case set and CC and TD control sets using electronic health record data of children and young adults from a large tertiary care children's hospital in the midwestern United States between 2010 and 2022. Case-control matching was performed to control for demographic factors. Data were analyzed from June to December 2023. All MH diagnosis codes were mapped to ICD-10-CM and categorized using Clinical Classifications Software Refined (CCSR). The incidence rates of MH CCSR categories were calculated. Descriptive and comparative statistics were used to evaluate the significance and odds associated with factors. Data from 216 794 individuals (mean [SD] baseline age, 4.3 [5.1] years; 118 562 [55%] male) were analyzed, including 3544 individuals with CP, 142 160 individuals with CC, and 71 080 TD individuals. The CP cohort spread across Gross Motor Function Classification System (GMFCS) levels I (981 individuals [28%]), II (645 individuals [18%]), III (346 individuals [10%]), IV (502 individuals [14%]), and V (618 individuals [17%]). Rates varied significantly for anxiety (824 individuals with CP [23%]; 25 877 individuals with CC [9%]; 6274 individuals with TD [18%]), attention-deficit/hyperactivity disorder (534 individuals with CP [15%]; 22 426 individuals with CC [9%]; 6311 individuals with TD [16%]); conduct or impulse disorder (504 individuals with CP [14%]; 13 209 individuals with CC [5%]; 3715 individuals with TD [9%]), trauma or stress disorders (343 individuals with CP [10%]; 18 229 individuals with CC [8%]; 5329 individuals with TD [13%]), obsessive-compulsive disorder (251 individuals with CP [7%]; 3795 individuals with CC [1%]; 659 individuals with TD [3%]), depression (108 individuals with CP [3%]; 12 224 individuals with CC [5%]; 4007 individuals with TD [9%]), mood disorders (74 individuals with CP [2%]; 4355 individuals with CC [2%]; 1181 individuals with TD [3%]), and suicidal ideation (72 individuals with CP [2%]; 7422 individuals with CC [5%]; 3513 individuals with TD [5%]). There was significant variation in odds of MH diagnoses by GMFCS level (I-II vs III-V: odds ratio [OR], 1.23; 95% CI, 1.09-1.40; P = .001). Among individuals with CP, males were more likely than females to have diagnosis codes for conduct or impulse disorders (OR, 1.41; 95% CI, 1.16-1.73) and attention-deficit/hyperactivity disorder (OR, 1.41 [95% CI, 1.15-1.73]). Black individuals, compared with White individuals, were more likely to have diagnoses for obsessive-compulsive disorder (OR, 1.57 [95% CI, 1.14-2.16]), other mood disorders (OR, 1.85 [95% CI, 1.01-3.38]), and trauma or stress disorders (OR, 1.94 [95% CI, 1.44-2.63]). Odds for trauma or stress disorders were elevated for individuals who identified as other races compared with White individuals (OR, 2.80 [95% CI, 2.03-3.87]). In this case-control study of children and young adults with CP and matched comparisons, anxiety and conduct or impulse diagnoses were higher in individuals with CP. The lower diagnosis rates of depression and suicidal ideation may indicate underdiagnosis among individuals with CP. There is likely a need for assessment tools that are more suitable for children with CP.

Changes in outpatient antibiotic prescriptions by U.S. physicians and advanced practice providers, 2011 and 2022

Background: The number of advanced practice providers (APPs)—nurse practitioners (NPs) and physician assistants (PAs)—continues to expand across the United States. Several studies suggest differences in antibiotic prescribing rates and appropriateness by APPs compared to physicians. The objective of this analysis is to characterize population- and provider-specific outpatient antibiotic prescribing rates among physicians and APPs nationally, by state, and within urban versus rural counties. Methods: We estimated outpatient oral antibiotic prescription rates for 2011 and 2022 using county-level prescription dispensing data from IQVIA Xponent® (numerator) and population census estimates (denominator). Provider specialty denominators were provided by IQVIA, based on data from the American Medical Association. Counties were classified as urban or rural per the 2013 National Center for Health Statistics classification. National and state-level prescription volume, rates per 1000 population, and average number of prescriptions per provider were calculated for physicians, NPs, and PAs. We assessed the degree to which provider-specific rates explained the variance of the overall rate by state, using the coefficient of determination (r2) from Pearson’s correlation. Results: Between 2011 and 2022, overall U.S. antibiotic prescribing declined from 877 to 709 per 1000 population, a 19.2% relative reduction. The provider-specific proportion of the overall prescribing rate relatively decreased by 32% for physicians but increased by 157% for APPs (NPs 229%, PAs 86%; Figure 1). State-level antibiotic prescribing rates varied by provider type for both years, shifting towards proportionally greater APP prescribing in 2022 (Figure 2). For 2011 and 2022, physician prescribing rate strongly correlated with the overall state rate (r2 = 0.83 in 2011 versus 0.80 in 2022), whereas the correlation of the NP prescribing rate increased (r2 = 0.20 in 2011 versus 0.76 in 2022). A total of 60,327 (7.2%) physicians practiced in rural settings in contrast to 42,876 (12%) NPs and 14,495 (9.4%) PAs in 2022. Providers in rural counties prescribed more antibiotics per provider on average compared to urban counties; rural physicians prescribed 57% more antibiotics per provider (207 vs 132 antibiotics per provider), rural NPs prescribed 115% more (284 vs 132), and rural PAs prescribed 53% more (289 vs 189). Conclusions: The relative contribution of APPs to outpatient antibiotic prescriptions more than doubled over the past decade, accounting for 1 in 3 prescriptions in 2022. This contribution was especially prominent among NPs in rural counties. Further evaluation of antibiotic prescribing appropriateness among APPs and integration of APPs into antibiotic stewardship efforts in various settings.