Predictors of transition to schizophrenia and other long-lasting non-affective psychoses in first-episode patients with acute and transient psychotic disorders: A validation study

Background and objectives Almost half of the individuals with a first-episode of psychosis who initially meet criteria for acute and transient psychotic disorder (ATPD) will have had a diagnostic revision during their follow-up, mostly toward schizophrenia. This study aimed to determine the proportion of diagnostic transitions to schizophrenia and other long-lasting non-affective psychoses in patients with first-episode ATPD, and to examine the validity of the existing predictors for diagnostic shift in this population. Methods We designed a prospective two-year follow-up study for subjects with first-episode ATPD. A multivariate logistic regression analysis was performed to identify independent variables associated with diagnostic transition to persistent non-affective psychoses. This prediction model was built by selecting variables on the basis of clinical knowledge. Results Sixty-eight patients with a first-episode ATPD completed the study and a diagnostic revision was necessary in 30 subjects at the end of follow-up, of whom 46.7% transited to long-lasting non-affective psychotic disorders. Poor premorbid adjustment and the presence of schizophreniform symptoms at onset of psychosis were the only variables independently significantly associated with diagnostic transition to persistent non-affective psychoses. Conclusion Our findings would enable early identification of those inidividuals with ATPD at most risk for developing long-lasting non-affective psychotic disorders, and who therefore should be targeted for intensive preventive interventions. (AU)

Establishment and validation of a multivariate logistic model for risk factors of thyroid nodules using lasso regression screening.

Objective: This study aims to analyze the association between the occurrence of thyroid nodules and various factors and to establish a risk factor model for thyroid nodules. Methods: The study population was divided into two groups: a group with thyroid nodules and a group without thyroid nodules. Regression with the least absolute shrinkage and selection operator (Lasso) was applied to the complete dataset for variable selection. Binary logistic regression was used to analyze the relationship between various influencing factors and the prevalence of thyroid nodules. Results: Based on the screening results of Lasso regression and the subsequent establishment of the Binary Logistic Regression Model on the training dataset, it was found that advanced age (OR=1.046, 95% CI: 1.033-1.060), females (OR = 1.709, 95% CI: 1.342-2.181), overweight individuals (OR = 1.546, 95% CI: 1.165-2.058), individuals with impaired fasting glucose (OR = 1.590, 95% CI: 1.193-2.122), and those with dyslipidemia (OR = 1.588, 95% CI: 1.197-2.112) were potential risk factors for thyroid nodule disease (p<0.05). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve for the Binary Logistic Regression Model is 0.68 (95% CI: 0.64-0.72). Conclusions: advanced age, females, overweight individuals, those with impaired fasting glucose, and individuals with dyslipidemia are potential risk factors for thyroid nodule disease.

Frailty and spatialization of older adults in the city of Uberlândia with IVCF-20.

OBJECTIVE: To describe the functional clinical profile of elderly people linked to primary health care, using the Functional Clinical Vulnerability Index (IVCF-20) and to spatialize those with the greatest functional decline by primary health care units in the municipality of Uberlândia, in the state of Minas Gerais (MG), in the year 2022. METHODS: A cross-sectional study with secondary data from the Municipal Health Department of Uberlândia-MG. The variables were compared using Student's t-test, Mann Whitney test, Pearson's chi-square, and multinomial logistic regression to obtain the independent effect of each variable. The significance level adopted was 5% (p < 0.05). The georeferenced database in ArcGIS® was used. RESULTS: 47,182 older adults were evaluated with a mean age of 70.3 years (60 to 113 years), 27,138 of whom were women (57.52%), with a clear predominance of low-risk or robust older adults (69.40%). However, 11.09% are high-risk older adults and 19.52% are at risk of frailty. Older men had independently lower odds of moderate and high risk compared to older women (OR = 0.53; p < 0.001). A high prevalence of polypharmacy was observed, 21.40% of the older adult population, particularly in frail older adults, with a prevalence of 63.08%. There was a greater distribution of frail older adults around the central region of the municipality and in health units with a larger coverage area. The IVCF-20 made it possible to screen frailty in primary health care. CONCLUSION: The instrument is capable of stratifying the risk of older adults in health care networks through primary health care, enabling the application of individualized preventive, promotional, palliative, or rehabilitative interventions, according to the clinical functional stratum of the older adult and the compromised functional domains. Risk stratification and spatial distribution of the frailest older adults can be a good strategy for qualifying health professionals with the aim of maximizing the autonomy and independence of the older adults.

Service Quality and Residents' Preferences for Facilitated Self-Service Fundus Disease Screening: Cross-Sectional Study.

BACKGROUND: Fundus photography is the most important examination in eye disease screening. A facilitated self-service eye screening pattern based on the fully automatic fundus camera was developed in 2022 in Shanghai, China; it may help solve the problem of insufficient human resources in primary health care institutions. However, the service quality and residents' preference for this new pattern are unclear. OBJECTIVE: This study aimed to compare the service quality and residents' preferences between facilitated self-service eye screening and traditional manual screening and to explore the relationships between the screening service's quality and residents' preferences. METHODS: We conducted a cross-sectional study in Shanghai, China. Residents who underwent facilitated self-service fundus disease screening at one of the screening sites were assigned to the exposure group; those who were screened with a traditional fundus camera operated by an optometrist at an adjacent site comprised the control group. The primary outcome was the screening service quality, including effectiveness (image quality and screening efficiency), physiological discomfort, safety, convenience, and trustworthiness. The secondary outcome was the participants' preferences. Differences in service quality and the participants' preferences between the 2 groups were compared using chi-square tests separately. Subgroup analyses for exploring the relationships between the screening service's quality and residents' preference were conducted using generalized logit models. RESULTS: A total of 358 residents enrolled; among them, 176 (49.16%) were included in the exposure group and the remaining 182 (50.84%) in the control group. Residents' basic characteristics were balanced between the 2 groups. There was no significant difference in service quality between the 2 groups (image quality pass rate: P=.79; average screening time: P=.57; no physiological discomfort rate: P=.92; safety rate: P=.78; convenience rate: P=.95; trustworthiness rate: P=.20). However, the proportion of participants who were willing to use the same technology for their next screening was significantly lower in the exposure group than in the control group (P<.001). Subgroup analyses suggest that distrust in the facilitated self-service eye screening might increase the probability of refusal to undergo screening (P=.02). CONCLUSIONS: This study confirms that the facilitated self-service fundus disease screening pattern could achieve good service quality. However, it was difficult to reverse residents' preferences for manual screening in a short period, especially when the original manual service was already excellent. Therefore, the digital transformation of health care must be cautious. We suggest that attention be paid to the residents' individual needs. More efficient man-machine collaboration and personalized health management solutions based on large language models are both needed.

Association of Waist Circumference and Body Mass Index Deciles Ratio with All-Cause Mortality: Findings from the National Health and Nutrition Examination Survey.

Given the importance and continued interest in finding a simple, accessible, and universal measure which reflects both general and abdominal adiposity, this study tested for an association of the ratio of WC decile to BMI decile (WC-d/BMI-d) with all-cause mortality. Individuals aged 18-79 years who had participated in the National Health and Nutrition Examination Survey (NHANES) during the years 2007 to 2018 were included in the analysis. WC and BMI deciles were defined separately for males and females, while WC-d/BMI-d was calculated for each individual. The association of WC-d/BMI-d with mortality was assessed using logistic models for the total study population, and then again after stratification by sex, ethnicity, morbidity level, and BMI categories. Positive associations between WC-d/BMI-d and mortality were demonstrated for the total study population (adjusted OR = 1.545, 95%CI: 1.369-1.722) and within different sub-groups, including the population with a normal BMI level (adjusted OR = 1.32, 95%CI: 1.13-1.50). WC-d/BMI-d increased with age, with ~40 years representing a critical time point when WC-d surpasses BMI-d, with a sharper incline for males as compared to females. WC-d/BMI-d was significantly associated with all-cause mortality amongst NHANES American adults; thus, measurements of WC and its integration with BMI in this metric should be considered in clinical practice.

Sick leave and disability pension following delivery in women with systemic lupus erythematosus.

OBJECTIVE: To investigate sickness benefits following delivery in mothers with systemic lupus erythematosus (SLE) and mothers without SLE. METHOD: SLE and non-SLE mothers, matched by age and month of delivery, with a singleton liveborn (2004-2008), were identified from the Swedish Lupus Linkage cohort. Work loss (sum of sick leave and disability pension) was studied from 1 year prenatally to 3 years postpartum. Adjusted logistic regression models of covariates associated with > 30 days of work loss in the first and second years postpartum were estimated in SLE mothers. RESULTS: Among 130 SLE mothers and 440 non-SLE mothers, SLE mothers were more likely to have work loss from the prenatal year (42% vs 16%) to 3 years postpartum (49% vs 15%). In SLE mothers, work loss was on average 61 ± 112 days (mean ± sd) in the prenatal year and 38 ± 83 days in the first year postpartum, which increased to 71 ± 114 days in the third year postpartum. Having > 30 days of sick leave in the year of delivery [odds ratio (OR) 4.4, 95% confidence interval (CI) 1.5-12.9] and ≤ 12 years of education (OR 2.6, 95% CI 1.1-6.0) were associated with work loss in the first year postpartum. No covariates were associated with work loss in the second year postpartum. CONCLUSION: SLE mothers more often had work loss in the prenatal year to 3 years postpartum compared to non-SLE mothers. Lower education and sick leave in the year of delivery were associated with a higher odds of work loss in the first year postpartum in SLE.

Associations between Life's Essential 8 and post-stroke depression and all-cause mortality among US adults.

BACKGROUND: Depression is the common mental disease after stroke. Our objective was to investigate the correlation of Life's Essential 8 (LE8), the recently updated evaluation of cardiovascular health, with the occurrence of post-stroke depression (PSD) and all-cause mortality among United States (US) adults. METHODS: Participants with stroke were chosen from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018. The relationship between LE8 and the risk of PSD was assessed through weighted multiple logistic models. A restricted cubic spline was employed for the examination of correlations. To demonstrate the stability of the results, sensitivity analysis and subgroup analysis were carried out. Furthermore, Cox regression models were used for the correlation between LE8 and all-cause mortality. RESULTS: In this study, a total of 1071 participants were included for analysis. It was observed that LE8 score and PSD risk shared an inverse relationship in per 10 points increase [OR = 0.62 (0.52-0.74, P < 0.001)] in logistic regression models. The analysis of restricted cubic spline demonstrated approximately a noticeable inverse linear association between LE8 score and PSD risk. Sensitivity analysis verified the stability of the findings. Moreover, no statistically significant interactions were identified in subgroup analysis. A reverse association between LE8 score and all-cause mortality was also observed with a 10-point increase [HR = 0.85 (0.78-0.94, P < 0.001)] in cox regression models. CONCLUSIONS: A negative correlation was discovered between LE8 score and PSD and all-cause mortality risk among US adults. We need to conduct large-scale prospective studies to further validate our results.

An observational study to identify causative factors for not using hydroxychloroquine in systemic lupus erythematosus.

Hydroxychloroquine (HCQ) use is indicated for patients with systemic lupus erythematosus (SLE). Nevertheless, reports discussing the reasons for not prescribing HCQ are limited. We identified the factors that interfere with HCQ use in patients with SLE. This observational, single-center study included data from 265 patients with SLE in 2019. The patients were categorized into groups with and without a history of HCQ use. Between these groups, clinical characteristics were compared using univariate analysis and logistic regression models. Among the 265 patients, 133 (50.2%) had a history of HCQ use. Univariate analysis identified older age; longer disease duration; lower prednisolone dose, clinical SLE disease activity index 2000, and estimated glomerular filtration rate; higher C3 level; and lower anti-double-stranded DNA antibody concentration as HCQ non-use-related variables. Logistic regression models identified a positive association between HCQ non-use and longer disease duration (odds ratio [OR] 1.08), prednisolone dose ≤ 7.5 mg/day (OR 4.03), C3 level ≥ 73 mg/dL (OR 2.15), and attending physician having graduated > 10 years prior (OR 3.19). In conclusion, a longer disease duration, lower prednisolone dose, higher C3 level, and longer time since attending physicians' graduation correlated with HCQ non-use. Physicians and patients should be educated to facilitate HCQ use despite these factors.

Employment Preferences of Cardiologists in Türkiye: A Discrete Choice Experiment.

OBJECTIVE: The homogeneous distribution of physicians is important for ensuring patients' access to health services. To encourage physicians to work in underserved areas, policymakers create incentives. Understanding physicians' employment preferences is essential when developing these incentive packages. This study aims to quantitatively reveal the preferences of cardiologists in Türkiye using a discrete choice experiment (DCE). METHODS: A DCE questionnaire was distributed electronically to all cardiologists in Türkiye. It included 14 different pairs of hypothetical job offers based on seven parameters likely to influence their employment preferences. The data were analyzed using a conditional logit model. The coefficients (CEs) of conditional logistic regression and the willingness-to-accept (WTA) values were calculated. RESULTS: The analysis included 278 cardiologists. It revealed that the most influential parameter was location (CE: 2.86). To move to an undesirable location, the average participant would require an earnings increase of at least 123.3% relative to the average potential earnings of a cardiologist. Other parameters included availability of suitable facilities (CE: 1.07, WTA: 46.3%), harmony with co-workers (CE: 0.92, WTA: 39.61%), working conditions (CE: 0.68, WTA: 29.26%), and the number of night shifts (CE: 0.61, WTA: 26.34%). CONCLUSION: 'Location' emerged as the most important factor in the employment preferences of cardiologists in Türkiye. However, several other monetary and non-monetary factors were also influential, suggesting that policymakers should adopt a holistic approach when developing incentives for cardiologists.

Population under Stress: The Coping Mechanisms of Lebanese Adults in Times of Intermingling Crises and Their Relationship with Stress.

The Lebanese population has faced numerous stressors due to multiple crises in the past four years. This study aims to measure the perceived stress of the Lebanese population, identify the coping mechanisms being used, and determine whether they are associated with their stress levels. A cross-sectional study of 205 individuals randomly selected from Beirut was conducted. Frequency distribution, descriptive analysis, and multivariable cumulative logit models were used to determine the associations between coping mechanisms and perceived stress. Our results indicated that 95.4% of our population had moderate to high perceived stress levels. Problem-focused coping was the most adopted mechanism and was associated with a statistically significant lower stress level, whereas avoidant coping was associated with a statistically significant higher stress level. Our study can pave the way for raising awareness on the importance of managing stress with adaptive coping mechanisms.

Association of serum soluble α­klotho with risk of kidney stone disease: a population-based cross-sectional study.

BACKGROUND: The aim of the study was to explore the association of serum soluble klotho with kidney stone disease (KSD) in the general population over the age of 40 years in the United States. METHODS: We integrated the data in National Health and Nutrition Examination Survey from 2007 to 2016 years. The relationship between serum soluble α­klotho and prevalence of KSD was analyzed by constructing weighted multivariable logistic regression model, restricted cubic spline (RCS) curve, and subgroup analyses. RESULTS: In the study, a total of 13,722 individuals were included in our study. A U-shaped association between serum soluble klotho and the risk of KSD was shown by the RCS curve (P value for nonlinear < 0.05). In the full adjusted model, compared with the lowest quartile of serum soluble α­klotho, the adjusted odd ratios (95% confidence intervals) for KSD across the quartiles were (0.999 (0.859, 1.164), 1.005 (0.858, 1.176), and 1.061 (0.911, 1.235)). Subgroup analyses also showed that the U-shaped association of serum soluble α­klotho with KSD was found among subjects who were age < 60 years, female or male, with or without hypertension, and BMI ≥ 30 kg/m2. CONCLUSIONS: Our findings suggested that serum klotho levels had a U-shaped correlation with risk of KSD. When the Klotho level is at 818.66 pg/mL, prevalence of KSD is lowest. Therefore, maintaining a certain level of serum soluble α­klotho could prevent the occurrence of KSD.

Stage at diagnosis of colorectal cancer through diagnostic route: Who should be screened?

BACKGROUND: Colorectal cancer (CRC) is a global health concern, with advanced-stage diagnoses contributing to poor prognoses. The efficacy of CRC screening has been well-established; nevertheless, a significant proportion of patients remain unscreened, with > 70% of cases diagnosed outside screening. Although identifying specific subgroups for whom CRC screening should be particularly recommended is crucial owing to limited resources, the association between the diagnostic routes and identification of these subgroups has been less appreciated. In the Japanese cancer registry, the diagnostic routes for groups discovered outside of screening are primarily categorized into those with comorbidities found during hospital visits and those with CRC-related symptoms. AIM: To clarify the stage at CRC diagnosis based on diagnostic routes. METHODS: We conducted a retrospective observational study using a cancer registry of patients with CRC between January 2016 and December 2019 at two hospitals. The diagnostic routes were primarily classified into three groups: Cancer screening, follow-up, and symptomatic. The early-stage was defined as Stages 0 or I. Multivariate and univariate logistic regressions were exploited to determine the odds of early-stage diagnosis in the symptomatic and cancer screening groups, referencing the follow-up group. The adjusted covariates were age, sex, and tumor location. RESULTS: Of the 2083 patients, 715 (34.4%), 1064 (51.1%), and 304 (14.6%) belonged to the follow-up, symptomatic, and cancer screening groups, respectively. Among the 2083 patients, CRCs diagnosed at an early stage were 57.3% (410 of 715), 23.9% (254 of 1064), and 59.5% (181 of 304) in the follow-up, symptomatic, and cancer screening groups, respectively. The symptomatic group exhibited a lower likelihood of early-stage diagnosis than the follow-up group [P < 0.001, adjusted odds ratio (aOR), 0.23; 95% confidence interval (95%CI): 0.19-0.29]. The likelihood of diagnosis at an early stage was similar between the follow-up and cancer screening groups (P = 0.493, aOR for early-stage diagnosis in the cancer screening group vs follow-up group = 1.11; 95%CI = 0.82-1.49). CONCLUSION: CRCs detected during hospital visits for comorbidities were diagnosed earlier, similar to cancer screening. CRC screening should be recommended, particularly for patients without periodical hospital visits for comorbidities.

Developing a risk prediction model for death at first suicide attempt-Identifying risk factors from Thailand's national suicide surveillance system data.

More than 60% of suicides globally are estimated to take place in low- and middle-income nations. Prior research on suicide has indicated that over 50% of those who die by suicide do so on their first attempt. Nevertheless, there is a dearth of knowledge on the attributes of individuals who die on their first attempt and the factors that can predict mortality on the first attempt in these regions. The objective of this study was to create an individual-level risk-prediction model for mortality on the first suicide attempt. We analyzed records of individuals' first suicide attempts that occurred between May 1, 2017, and April 30, 2018, from the national suicide surveillance system, which includes all of the provinces of Thailand. Subsequently, a risk-prediction model for mortality on the first suicide attempt was constructed utilizing multivariable logistic regression and presented through a web-based application. The model's performance was assessed by calculating the area under the receiver operating curve (AUC), as well as measuring its sensitivity, specificity, and accuracy. Out of the 3,324 individuals who made their first suicide attempt, 50.5% of them died as a result of that effort. Nine out of the 21 potential predictors demonstrated the greatest predictive capability. These included male sex, age over 50 years old, unemployment, having a depressive disorder, having a psychotic illness, experiencing interpersonal problems such as being aggressively criticized or desiring plentiful attention, having suicidal intent, and displaying suicidal warning signals. The model demonstrated a good predictive capability, with an AUC of 0.902, a sensitivity of 84.65%, a specificity of 82.66%, and an accuracy of 83.63%. The implementation of this predictive model can assist physicians in conducting comprehensive evaluations of suicide risk in clinical settings and devising treatment plans for preventive intervention.

SLESIS-R: an improved score for prediction of serious infection in patients with systemic lupus erythematosus based on the RELESSER prospective cohort.

OBJECTIVE: To develop an improved score for prediction of severe infection in patients with systemic lupus erythematosus (SLE), namely, the SLE Severe Infection Score-Revised (SLESIS-R) and to validate it in a large multicentre lupus cohort. METHODS: We used data from the prospective phase of RELESSER (RELESSER-PROS), the SLE register of the Spanish Society of Rheumatology. A multivariable logistic model was constructed taking into account the variables already forming the SLESIS score, plus all other potential predictors identified in a literature review. Performance was analysed using the C-statistic and the area under the receiver operating characteristic curve (AUROC). Internal validation was carried out using a 100-sample bootstrapping procedure. ORs were transformed into score items, and the AUROC was used to determine performance. RESULTS: A total of 1459 patients who had completed 1 year of follow-up were included in the development cohort (mean age, 49±13 years; 90% women). Twenty-five (1.7%) had experienced ≥1 severe infection. According to the adjusted multivariate model, severe infection could be predicted from four variables: age (years) ≥60, previous SLE-related hospitalisation, previous serious infection and glucocorticoid dose. A score was built from the best model, taking values from 0 to 17. The AUROC was 0.861 (0.777-0.946). The cut-off chosen was ≥6, which exhibited an accuracy of 85.9% and a positive likelihood ratio of 5.48. CONCLUSIONS: SLESIS-R is an accurate and feasible instrument for predicting infections in patients with SLE. SLESIS-R could help to make informed decisions on the use of immunosuppressants and the implementation of preventive measures.

Association between leucocyte telomere length and erectile dysfunction in US adults: a secondary study based on 2001-2002 NHANES data.

OBJECTIVE: We aimed to explore the association between the leucocyte telomere length (LTL) and erectile dysfunction (ED) among a nationally representative sample of US adults. DESIGN: Secondary population-based study. SETTING: The National Health and Nutrition Examination Survey (NHANES) (2001-2002). PARTICIPANTS: A total of 1694 male participants were extracted from the NHANES database for 2001-2002. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary focus of the study was to determine the association between the LTL and ED, using multivariate logistic regression and restricted cubic spline models for examination. The secondary outcome measures involved conducting stratified subgroup analyses to exclude interactions of different variables with the LTL. RESULTS: Participants with ED had shorter LTLs than those without ED (p<0.05). After adjusting for confounding factors, compared with the reference lowest LTL quartile, the ORs and 95% CIs for the second, third and fourth LTL quartiles were (OR 1.51; 95% CI 1.01 to 2.26), (OR 1.79; 95% CI 1.24 to 2.58) and (OR 1.25; 95% CI 0.74 to 2.11), respectively. In addition, restricted cubic splines showed an inverted J-curve relationship between the LTL and ED. At an LTL of 1.037, the curve showed an inflection point. The ORs (95% CI) of ED on the left and right sides of the inflection point were (OR 1.99; 95% CI 0.39 to 10.20; p=0.385) and (OR 0.17; 95% CI 0.03 to 0.90; p=0.039). CONCLUSION: Our results demonstrated an inverted J-curve relationship between the LTL and ED. When the LTL was ≥1.037, the incidence of ED decreased with increasing LTL.

Relationship between lipid metabolism, coagulation and other blood indices and etiology and staging of non-traumatic femoral head necrosis: a multivariate logistic regression-based analysis.

BACKGROUND: To analyze the relationship between lipid metabolism, coagulation function, and bone metabolism and the contributing factor and staging of non-traumatic femoral head necrosis, and to further investigate the factors influencing the blood indicators related to the staging of non-traumatic femoral head necrosis. METHODS: The medical records of patients with femoral head necrosis were retrieved from the inpatient medical record management system, and the lipid metabolism, bone metabolism, and coagulation indices of non-traumatic femoral head necrosis (including alcoholic, hormonal, and idiopathic group) were obtained according to the inclusion and exclusion criteria, including Low-Density Lipoprotein Cholesterol, Triglycerides, Non-High-Density Lipoprotein Cholesterol, Apolipoprotein A1, Apolipoprotein (B), Apolipoprotein (E), Uric Acid, Alkaline Phosphatase, Bone-specific Alkaline Phosphatase, Activated Partial Thromboplastin Time, Prothrombin Time, D-dimer, Platelet count. The relationship between these blood indices and the different stages under different causative factors was compared, and the factors influencing the stages of non-traumatic femoral head necrosis were analyzed using multivariate logistic regression. RESULTS: (i) Gender, Age and BMI stratification, Low-density Lipoprotein Cholesterol, Triglycerides, Non-High-density Lipoprotein Cholesterol, Apolipoprotein (B), Apolipoprotein (E), Uric Acid, Bone-specific Alkaline Phosphatase, Activated Partial Thromboplastin Time, Plasminogen Time, D-dimer, and Platelet count of the alcohol group were statistically different when compared among the different ARCO staging groups; (ii) The differences in Age and BMI stratification, Triglycerides, Non-High-density Lipoprotein Cholesterol, Apolipoprotein A1, Apolipoprotein B, Apolipoprotein E, Uric Acid, Bone-specific Alkaline Phosphatase, Activated Partial Thromboplastin Time, Plasminogen Time, D-dimer, and Platelet count were statistically significant when compared among the different phases in the hormone group (P < 0.05); (iii) The differences in Age and BMI stratification, Non-High-Density Lipoprotein Cholesterol, Apolipoprotein A1, Apolipoprotein (B), Apolipoprotein (E), Uric Acid, Activated Partial Thromboplastin Time, D-dimer, and Platelet count were statistically significant when compared among the different stages in the idiopathic group (P < 0.05); (v) Statistically significant indicators were included in the multivariate logistic regression analysis, excluding the highly correlated bone-specific alkaline phosphatase, and the results showed that Low-density lipoprotein was negatively correlated with changes in the course of ARCO, and Non-High-Density Lipoprotein cholesterol, Apo B, Activated Partial Thromboplastin Time, and Platelet count were significantly and positively correlated with disease progression. CONCLUSION: An abnormal hypercoagulable state as well as an abnormal hyperlipidemic state are risk factors for the progression of non-traumatic femoral head necrosis under various exposure factors, as indicated by Non-High-Density Lipoprotein Cholesterol, Apolipoprotein B, Activated Fractional Thromboplastin Time, and Platelet Counts.

Confirming the statistically significant superiority of tree-based machine learning algorithms over their counterparts for tabular data.

Many individual studies in the literature observed the superiority of tree-based machine learning (ML) algorithms. However, the current body of literature lacks statistical validation of this superiority. This study addresses this gap by employing five ML algorithms on 200 open-access datasets from a wide range of research contexts to statistically confirm the superiority of tree-based ML algorithms over their counterparts. Specifically, it examines two tree-based ML (Decision tree and Random forest) and three non-tree-based ML (Support vector machine, Logistic regression and k-nearest neighbour) algorithms. Results from paired-sample t-tests show that both tree-based ML algorithms reveal better performance than each non-tree-based ML algorithm for the four ML performance measures (accuracy, precision, recall and F1 score) considered in this study, each at p<0.001 significance level. This performance superiority is consistent across both the model development and test phases. This study also used paired-sample t-tests for the subsets of the research datasets from disease prediction (66) and university-ranking (50) research contexts for further validation. The observed superiority of the tree-based ML algorithms remains valid for these subsets. Tree-based ML algorithms significantly outperformed non-tree-based algorithms for these two research contexts for all four performance measures. We discuss the research implications of these findings in detail in this article.

Partial label learning for automated classification of single-cell transcriptomic profiles.

Single-cell RNA sequencing (scRNASeq) data plays a major role in advancing our understanding of developmental biology. An important current question is how to classify transcriptomic profiles obtained from scRNASeq experiments into the various cell types and identify the lineage relationship for individual cells. Because of the fast accumulation of datasets and the high dimensionality of the data, it has become challenging to explore and annotate single-cell transcriptomic profiles by hand. To overcome this challenge, automated classification methods are needed. Classical approaches rely on supervised training datasets. However, due to the difficulty of obtaining data annotated at single-cell resolution, we propose instead to take advantage of partial annotations. The partial label learning framework assumes that we can obtain a set of candidate labels containing the correct one for each data point, a simpler setting than requiring a fully supervised training dataset. We study and extend when needed state-of-the-art multi-class classification methods, such as SVM, kNN, prototype-based, logistic regression and ensemble methods, to the partial label learning framework. Moreover, we study the effect of incorporating the structure of the label set into the methods. We focus particularly on the hierarchical structure of the labels, as commonly observed in developmental processes. We show, on simulated and real datasets, that these extensions enable to learn from partially labeled data, and perform predictions with high accuracy, particularly with a nonlinear prototype-based method. We demonstrate that the performances of our methods trained with partially annotated data reach the same performance as fully supervised data. Finally, we study the level of uncertainty present in the partially annotated data, and derive some prescriptive results on the effect of this uncertainty on the accuracy of the partial label learning methods. Overall our findings show how hierarchical and non-hierarchical partial label learning strategies can help solve the problem of automated classification of single-cell transcriptomic profiles, interestingly these methods rely on a much less stringent type of annotated datasets compared to fully supervised learning methods.

Multivariate logistic regression analysis of risk factors for birth defects: a study from population-based surveillance data.

OBJECTIVE: To explore risk factors for birth defects (including a broad range of specific defects). METHODS: Data were derived from the Population-based Birth Defects Surveillance System in Hunan Province, China, 2014-2020. The surveillance population included all live births, stillbirths, infant deaths, and legal termination of pregnancy between 28 weeks gestation and 42 days postpartum. The prevalence of birth defects (number of birth defects per 1000 infants) and its 95% confidence interval (CI) were calculated. Multivariate logistic regression analysis (method: Forward, Wald, α = 0.05) and adjusted odds ratios (ORs) were used to identify risk factors for birth defects. We used the presence or absence of birth defects (or specific defects) as the dependent variable, and eight variables (sex, residence, number of births, paternal age, maternal age, number of pregnancies, parity, and maternal household registration) were entered as independent variables in multivariate logistic regression analysis. RESULTS: Our study included 143,118 infants, and 2984 birth defects were identified, with a prevalence of 20.85% (95%CI: 20.10-21.60). Multivariate logistic regression analyses showed that seven variables (except for parity) were associated with birth defects (or specific defects). There were five factors associated with the overall birth defects. The risk factors included males (OR = 1.49, 95%CI: 1.39-1.61), multiple births (OR = 1.44, 95%CI: 1.18-1.76), paternal age < 20 (OR = 2.20, 95%CI: 1.19-4.09) or 20-24 (OR = 1.66, 95%CI: 1.42-1.94), maternal age 30-34 (OR = 1.16, 95%CI: 1.04-1.29) or > = 35 (OR = 1.56, 95%CI: 1.33-1.81), and maternal non-local household registration (OR = 2.96, 95%CI: 2.39-3.67). Some factors were associated with the specific defects. Males were risk factors for congenital metabolic disorders (OR = 3.86, 95%CI: 3.15-4.72), congenital limb defects (OR = 1.34, 95%CI: 1.14-1.58), and congenital kidney and urinary defects (OR = 2.35, 95%CI: 1.65-3.34). Rural areas were risk factors for congenital metabolic disorders (OR = 1.21, 95%CI: 1.01-1.44). Multiple births were risk factors for congenital heart defects (OR = 2.09, 95%CI: 1.55-2.82), congenital kidney and urinary defects (OR = 2.14, 95%CI: 1.05-4.37), and cleft lip and/or palate (OR = 2.85, 95%CI: 1.32-6.15). Paternal age < 20 was the risk factor for congenital limb defects (OR = 3.27, 95%CI: 1.10-9.71), 20-24 was the risk factor for congenital heart defects (OR = 1.64, 95%CI: 1.24-2.17), congenital metabolic disorders (OR = 1.56, 95%CI: 1.11-2.21), congenital limb defects (OR = 1.61, 95%CI: 1.14-2.29), and congenital ear defects (OR = 2.13, 95%CI: 1.17-3.89). Maternal age < 20 was the risk factor for cleft lip and/or palate (OR = 3.14, 95%CI: 1.24-7.95), 30-34 was the risk factor for congenital limb defects (OR = 1.37, 95%CI: 1.09-1.73), >=35 was the risk factor for congenital heart defects (OR = 1.51, 95%CI: 1.14-1.99), congenital limb defects (OR = 1.98, 95%CI: 1.41-2.78), and congenital ear defects (OR = 1.82, 95%CI: 1.06-3.10). Number of pregnancies = 2 was the risk factor for congenital nervous system defects (OR = 2.27, 95%CI: 1.19-4.32), >=4 was the risk factor for chromosomal abnormalities (OR = 2.03, 95%CI: 1.06-3.88) and congenital nervous system defects (OR = 3.03, 95%CI: 1.23-7.47). Maternal non-local household registration was the risk factor for congenital heart defects (OR = 3.57, 95%CI: 2.54-5.03), congenital metabolic disorders (OR = 1.89, 95%CI: 1.06-3.37), congenital limb defects (OR = 2.94, 95%CI: 1.86-4.66), and congenital ear defects (OR = 3.26, 95%CI: 1.60-6.65). CONCLUSION: In summary, several risk factors were associated with birth defects (including a broad range of specific defects). One risk factor may be associated with several defects, and one defect may be associated with several risk factors. Future studies should examine the mechanisms. Our findings have significant public health implications as some factors are modifiable or avoidable, such as promoting childbirths at the appropriate age, improving the medical and socio-economic conditions of non-local household registration residents, and devoting more resources to some specific defects in high-risk groups, which may help reducing birth defects in China.

Bayesian estimation of the measurement of interactions in epidemiological studies.

Background: Interaction identification is important in epidemiological studies and can be detected by including a product term in the model. However, as Rothman noted, a product term in exponential models may be regarded as multiplicative rather than additive to better reflect biological interactions. Currently, the additive interaction is largely measured by the relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), and the synergy index (S), and confidence intervals are developed via frequentist approaches. However, few studies have focused on the same issue from a Bayesian perspective. The present study aims to provide a Bayesian view of the estimation and credible intervals of the additive interaction measures. Methods: Bayesian logistic regression was employed, and estimates and credible intervals were calculated from posterior samples of the RERI, AP and S. Since Bayesian inference depends only on posterior samples, it is very easy to apply this method to preventive factors. The validity of the proposed method was verified by comparing the Bayesian method with the delta and bootstrap approaches in simulation studies with example data. Results: In all the simulation studies, the Bayesian estimates were very close to the corresponding true values. Due to the skewness of the interaction measures, compared with the confidence intervals of the delta method, the credible intervals of the Bayesian approach were more balanced and matched the nominal 95% level. Compared with the bootstrap method, the Bayesian method appeared to be a competitive alternative and fared better when small sample sizes were used. Conclusions: The proposed Bayesian method is a competitive alternative to other methods. This approach can assist epidemiologists in detecting additive-scale interactions.