Patients' preferences for systemic treatment of atopic dermatitis: safety and efficacy count the most

BACKGROUND

The advent of biologics and janus kinase inhibitors has revolutionized treatment of atopic dermatitis (AD).

OBJECTIVE

To investigate preferences of patients with AD for attributes of currently approved systemic treatments and assess influencing factors.

METHODS

An online discrete choice experiment was conducted in patients with AD throughout Germany to analyze preferences for outcome (probability of (almost) clear skin at week 16, probability of significant itch improvement, time to onset of itch relief and type of side effects) and process attributes (application method and frequency of laboratory tests).

RESULTS

Participants (n = 182, 75.3% female) considered side effects (Relative Importance Score (RIS): 31.2), (almost) clear skin (RIS: 24.2) and probability of itch improvement (RIS: 16.0) most important. Application method (RIS: 14.4), time to onset of itch relief (RIS: 7.4) and frequency of laboratory tests (RIS: 6.8) were less relevant. Preferences were significantly influenced by sex, age, psychiatric comorbidity, current therapy and health-related quality of life according to multivariate regression analysis.

CONCLUSIONS

Participants attached great importance to safety and symptom control. However, preferences were also dependent on individual characteristics, underscoring the importance of personal counseling. Conjoined with medical considerations, patients' preferences have fundamental impact on shared decisions for treatment of AD.

Multi-task global optimization-based method for vascular landmark detection

Vascular landmark detection plays an important role in medical analysis and clinical treatment. However, due to the complex topology and similar local appearance around landmarks, the popular heatmap regression based methods always suffer from the landmark confusion problem. Vascular landmarks are connected by vascular segments and have special spatial correlations, which can be utilized for performance improvement. In this paper, we propose a multi-task global optimization-based framework for accurate and automatic vascular landmark detection. A multi-task deep learning network is exploited to accomplish landmark heatmap regression, vascular semantic segmentation, and orientation field regression simultaneously. The two auxiliary objectives are highly correlated with the heatmap regression task and help the network incorporate the structural prior knowledge. During inference, instead of performing a max-voting strategy, we propose a global optimization-based post-processing method for final landmark decision. The spatial relationships between neighboring landmarks are utilized explicitly to tackle the landmark confusion problem. We evaluated our method on a cerebral MRA dataset with 564 volumes, a cerebral CTA dataset with 510 volumes, and an aorta CTA dataset with 50 volumes. The experiments demonstrate that the proposed method is effective for vascular landmark localization and achieves state-of-the-art performance.

Motivating Protective Behavior against COVID-19: Fear Versus Hope

OBJECTIVES

Based on protection motivation theory, we investigate how indicators of threat perception (perceived severity, perceived vulnerability, and fear arousal) and coping appraisal (hope) are associated with older people's motivation to engage in protective behavior after the outbreak of COVID-19.

METHODS

We use multivariate regression analyses with a sample of 40,282 individuals from 26 countries participating in the SHARE Corona Survey.

RESULTS

We find that 15% of all respondents stayed home completely-mainly the oldest and vulnerable people with prior health risk conditions. On average, older Europeans responded strongly to the recommended protective behavior measures (6 out of 7 measures adopted). Among the threat perception indicators, fear arousal is the main motivator for protective behavior, whereas the coping appraisal indicator hope shows an equally strong association.

DISCUSSION

Given the negative health effects of fear, our findings may help evaluate and revise governmental policy responses and communication strategies.

Time trends in liver cancer mortality rates in Montenegro from 1990 to 2018

OBJECTIVE

Liver cancer is the third most common cause of cancer-related deaths worldwide. Hepatitis B and C infections are the main factors affecting mortality. During recent years, Montenegro conducted activities on eradication of viral hepatitis according to the global strategy for the primary prevention of liver cancer mortality. The objective of this study was to assess the liver cancer mortality trend in Montenegro for the period of 1990-2018 using regression techniques.

METHODS

liver cancer mortality data in Montenegro from 1990 to 2018 were collected. Mortality rates were age standardized to the World Standard Population. The joinpoint, linear and Poisson regressions were used to assess liver cancer mortality trends both overall and gender specific.

RESULTS

The mortality trend was constant, with no significant increase or decrease in mortality rates both at the overall level and by gender. The number of cases, however, increases significantly at the overall level by an average of 1.4% per year [average annual percentage change (AAPC) (95% confidence interval, CI): 1.4 (0.5-2.3); P  = 0.004] and in women by 1.9% per year [AAPC (95% CI): 1.9 (0.8-3.1); P  = 0.002]. In men, there was no change in the number of cases. The three age groups most burdened by mortality from liver cancer were 65-74 (34.9%), 75-84 (26.6%) and 55-64 (25.8%).

CONCLUSION

The consistent implementation of prevention measures and hepatitis virus infection treatment has played a role in partially favorable liver cancer mortality trends in Montenegro. It is crucial to closely monitor guidelines for this cancer and give particular attention to the elderly population as the most affected.

The effects of psychological flexibility and resilience on psychopharmacological treatment response in patients with obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is a challenging psychiatric condition to treat. Previous research has explored various aspects of treatment response, but limited attention has been given to the significance of psychological flexibility and resilience. This study aimed to investigate the correlation between psychological flexibility, resilience, and different dimensions of OCD, as well as their role in treatment response specifically concerning OCD symptom sub-dimensions. The study involved 50 OCD patients and 42 healthy individuals as controls. Participants completed the Dimensional Obsessive-Compulsive Scale (DOCS), Acceptance and Action Questionnaire (AAQ-2), and Resilience Scale for Adults (RS). Initial scale scores were compared to post-treatment scores obtained after a 3-month follow-up using pharmacotherapy. The patient group exhibited significantly higher AAQ-2 scores and lower RS scores compared to the control group. During the post-treatment follow-up, a reduction in DOCS and AAQ-2 scores was observed, along with an increase in RS scores. The impact of differences in AAQ-2 and RS scores on the change in DOCS total scores was analyzed using mixed model linear regression analysis. The results showed a statistically significant effect of changes in AAQ-2 and RS sub-dimension scores on the change in DOCS total scores. The findings highlight the importance of flexibility and resilience in influencing treatment response among patients with OCD. When conventional pharmacotherapy and psychotherapy approaches prove insufficient, interventions focused on enhancing flexibility and resilience may contribute to improved treatment outcomes.

Relationship between Personality Traits and Subjective Well-Being in Emerging Adulthood: Moderating Role of Independent and Interdependent Self-Construal

During emerging adulthood, individuals' subjective well-being declines owing to challenges regarding identity, work, and romantic relationships. Although the relationships among personality traits, self-construal, and well-being have been examined, studies have focused on personal rather than relational subjective well-being. Furthermore, self-construal's moderating effect on the relationship between personality traits and subjective well-being remains unclear. Therefore, this study examined the relationships among the Big-five personality traits and subjective well-being (life satisfaction, happiness, and interdependent happiness) and the moderating effect of self-construal among 1548 Japanese emerging adults (Mage = 22.24, SD = 1.01). Regression analysis indicated that all aspects of subjective well-being were negatively associated with neuroticism and positively associated with extraversion, independent and interdependent self-construal. Further, agreeableness was positively associated with personal and relational well-being. Independent or interdependent self-construal can moderate the relationships between neuroticism, extraversion, and agreeableness and subjective well-being. Overall, these findings provide valuable insights for improving Japanese emerging adults' well-being.

Prediction of non-suicidal self-injury in adolescents at the family level using regression methods and machine learning

BACKGROUND

Adolescent non-suicidal self-injury (NSSI) is a major public health issue. Family factors are significantly associated with NSSI in adolescents, while studies on forecasting NSSI at the family level are still limited. In addition to regression methods, machine learning (ML) techniques have been recommended to improve the accuracy of family-level risk prediction for NSSI.

METHODS

Using a dataset of 7967 students and their primary caregivers from a cross-sectional study, logistic regression model and random forest model were used to test the forecasting accuracy of NSSI predictions at the family level. Cross-validation was used to assess model prediction performance, including the area under the receiver operator curve (AUC), precision, Brier score, accuracy, sensitivity, specificity, positive predictive value and negative predictive value.

RESULTS

The top three important family-related predictors within the random forest algorithm included family function (importance:42.66), family conflict (importance:42.18), and parental depression (importance:27.21). The most significant family-related risk predictors and protective predictors identified by the logistic regression model were family history of mental illness (OR:2.25) and help-seeking behaviors of mental distress from parents (OR:0.65), respectively. The AUCs of the two models, logistic regression and random forest, were 0.852 and 0.835, respectively.

LIMITATIONS

The key limitation is that this cross-sectional survey only enabled the authors to examine predictors that were considered to be proximal rather than distal.

CONCLUSIONS

These findings highlight the significance of family-related factors in forecasting NSSI in adolescents. Combining both conventional statistical methods and ML methods to improve risk assessment of NSSI at the family level deserves attention.

United States-Based Colorectal Cancer Surgical Trials Lack Representation and Adequate Reporting of Racially and Ethnically Diverse Participants: Systematic Review and Regression Analysis

BACKGROUND

Despite the established National Institute of Health Revitalization Act, which aims to include ethnic and racial minority representation in surgical trials, racial and ethnic enrollment disparities persist.

OBJECTIVE

To assess the proportion of patients from minority races and ethnicities that are included in colorectal cancer surgical trials and reporting characteristics.

DATA SOURCES

Search was performed using MEDLINE (Ovid), Embase, Web of Science, and Cochrane Central.

STUDY SELECTION

Inclusion criteria included 1) trials performed in the United States between January 1, 2000, and May 30, 2022; 2) patients with colorectal cancer diagnosis; and 3) surgical intervention, technique, or postoperative outcome. Trials evaluating chemotherapy, radiotherapy, or other nonsurgical interventions were excluded.

INTERVENTIONS

Pooled proportion and regression analysis was performed to identify the proportion of patients by race and ethnicity included in surgical trials and the association of year of publication and funding source.

MAIN OUTCOME MEASURES

Proportion of trials reporting race and ethnicity and proportion of participants by race and ethnicity included in surgical trials.

RESULTS

We screened 10,673 unique publications, of which 80 were examined in full text. Fifteen studies met our inclusion criteria. Ten (66.7%) trials did not report race, 3 reported races as a proportion of White participants only, and 3 reported 3 or more races. There was no description of ethnicity in 11 (73.3%) trials, with 2 describing "non-Caucasian" as ethnicity and 2 describing only Hispanic ethnicity. Pooled proportion of White participants was 81.3%, of Black participants was 6.2%, of Asian participants was 3.6%, and of Hispanic participants was 3.5%.

LIMITATIONS

A small number of studies was identified that reported racial or ethnic characteristics of their participants.

CONCLUSIONS

Both race and ethnicity are severely underreported in colorectal cancer surgical trials. To improve outcomes and ensure the inclusion of vulnerable populations in innovative technologies and novel treatments, reporting must be closely monitored.

Neuropathic Pain After Burn Injury: A Severe and Common Problem in Recovery

OBJECTIVE

The aim of this study was to address the limited understanding of neuropathic pain (NP) among burn survivors by comprehensively examining its prevalence and related factors on a national scale using the Burn Model System (BMS) National Database.

BACKGROUND

NP is a common but underexplored complaint among burn survivors, greatly affecting their quality of life and functionality well beyond the initial injury. Existing data on NP and its consequences in burn survivors are limited to select single-institution studies, lacking a comprehensive national perspective.

METHODS

The BMS National Database was queried to identify burn patients responding to NP-related questions at enrollment, 6 months, 12 months, 2 years, and 5 years postinjury. Descriptive statistics and regression analyses were used to explore associations between demographic/clinical characteristics and self-reported NP at different time points.

RESULTS

There were 915 patients included for analysis. At discharge, 66.5% of patients experienced NP in their burn scars. Those with NP had significantly higher Patient-Reported Outcomes Measurement Information System 29 (PROMIS-29) pain inference, itch, anxiety, depression, and sleep disturbance scores and were less able to partake in social roles. Multiple logistic regression revealed male sex, % total body surface area, and moderate-to-severe pain as predictors of NP at 6 months. At 12 months, % total body surface area and moderate-to-severe pain remained significant predictors, while ethnicity and employment status emerged as significant predictors at 24 months.

CONCLUSIONS

This study highlights the significant prevalence of NP in burn patients and its adverse impacts on their physical, psychological, and social well-being. The findings underscore the necessity of a comprehensive approach to NP treatment, addressing both physical symptoms and psychosocial factors.

Engaging and following physical injury survivors at risk for developing posttraumatic stress disorder symptoms: A 25 site US national study

INTRODUCTION

Early intervention for patients at risk for Posttraumatic Stress Disorder (PTSD) relies upon the ability to engage and follow trauma-exposed patients. Recent requirements by the American College of Surgeons Committee on Trauma (College) have mandated screening and referral for patients with high levels of risk for the development of PTSD or depression. Investigations that assess factors associated with engaging and following physically injured patients may be essential in assessing outcomes related to screening, intervention, and referral.

METHODS

This investigation was a secondary analysis of data collected as part of a United States level I trauma center site randomized clinical trial. All 635 patients were ages ≥18 and had high PTSD symptom levels (i.e., DSM-IV PTSD Checklist score ≥35) at the time of the baseline trauma center admission. Baseline technology use, demographic, and injury characteristics were collected for patients who were followed up with over the course of the year after physical injury. Regression analyses were used to assess the associations between technology use, demographic and injury characteristics, and the attainment of follow-up outcome assessments.

RESULTS

Thirty-one percent of participants were missing one or more 3-, 6- or 12-month follow-up outcome assessments. Increased risk of missing one or more outcome assessments was associated with younger age (18-30 versus ≥55 Relative Risks [RR] = 1.78, 95 % Confidence Interval [CI] = 1.09, 2.91), lack of cell phone (RR = 1.32, 95 % CI = 1.01, 1.72), no internet access (RR = 1.47, 95 % CI = 1.01, 2.16), public versus private insurance (RR = 1.47, 95 % CI = 1.12, 1.92), having no chronic medical comorbidities (≥4 versus none, RR = 0.28, 95 % CI = 0.20, 0.39), and worse pre-injury mental health function (RR = 0.99, 95 % CI = 0.98, 0.99).

CONCLUSIONS

This multisite investigation suggests that younger and publicly insured and/or uninsured patients with barriers to cell phone and internet access may be particularly vulnerable to lapses in trauma center follow-up. Clinical research informing trauma center-based screening, intervention, and referral procedures could productively explore strategies for patients at risk for not engaging and adhering to follow-up care and outcome assessments.

Robust best linear weighted estimator with missing covariates in survival analysis

Missing data in covariates can result in biased estimates and loss of power to detect associations. We consider Cox regression in which some covariates are subject to missing. The inverse probability weighted approach is often applied to regression analysis with missing covariates. Inverse probability weighted estimators typically are less efficient than likelihood-based estimators, but in general are more robust against model misspecification. In this article, we propose a robust best linear weighted estimator for Cox regression with missing covariates. Our proposed estimator is the projection of the simple inverse probability weighted estimator onto the orthogonal complement of the score space based on a working regression model of the observed data. The efficiency gain is from the use of the association between the survival outcome variable and the available covariates, which is the working regression model. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via extensive simulation studies. The methods are applied to a colorectal cancer study to assess the association of the microsatellite instability status with colorectal cancer-specific mortality.

Effects of taxane-induced peripheral neuropathy on hand dexterity impairment: evaluation of quantitative and subjective assessments

PURPOSE

Chemotherapy-induced peripheral neuropathy (CIPN) commonly involves hand dexterity impairment. However, the factors affecting hand dexterity impairment are unknown and there is currently no established treatment. The purpose of the current study was to clarify factors influencing hand dexterity impairment in taxane-induced peripheral neuropathy using subjective and objective assessments.

METHODS

We assessed patient characteristics, treatment-related factors, subjective symptoms of CIPN (Patient Neurotoxicity Questionnaire [PNQ]), psychological symptoms, and upper limb dysfunction (Quick Disabilities of the Arm, Shoulder and Hand [Quick DASH]). Quantitative assessments were pinch strength, sensory threshold, hand dexterity impairment, and grip force control. Multiple regression analysis was performed using hand dexterity impairment as the dependent variable and age and PNQ, Quick DASH, and control of grip force as independent variables.

RESULTS

Forty-three breast cancer patients were included in the analysis. Hand dexterity impairment in taxane-induced peripheral neuropathy patients was significantly correlated with age, grip force control, and PNQ sensory scores (p < 0.008). Multiple regression analysis demonstrated that PNQ sensory scores and grip force control were significantly associated with hand dexterity impairment (p < 0.01).

CONCLUSION

Subjective symptoms (numbness and pain) and grip force control contributed to impaired hand dexterity in taxane-induced peripheral neuropathy.

Can predictive factors determine the time to treatment initiation for oral and oropharyngeal cancer? A classification and regression tree analysis

This ecological study aimed to identify the factors with the greatest power to discriminate the proportion of oral and oropharyngeal cancer (OOC) records with time to treatment initiation (TTI) within 30 days of diagnosis in Brazilian municipalities. A descriptive analysis was performed on the variables grouped into five dimensions related to patient characteristics, access to health services, support for cancer diagnosis, human resources, and socioeconomic characteristics of 3,218 Brazilian municipalities that registered at least one case of OOC in 2019. The Classification and Regression Trees (CART) technique was adopted to identify the explanatory variables with greater discriminatory power for the TTI response variable. There was a higher median percentage of records in the age group of 60 years or older. The median percentage of records with stage III and IV of the disease was 46.97%, and of records with chemotherapy, radiation, or both as the first treatment was 50%. The median percentage of people with private dental and health insurance was low. Up to 75% had no cancer diagnostic support services, and up to 50% of the municipalities had no specialist dentists. Most municipalities (49.4%) started treatment after more than 30 days. In the CART analysis, treatment with chemotherapy, radiotherapy, or both explained the highest TTI in all municipalities, and it was the most relevant for predicting TTI. The final model also included anatomical sites in the oral cavity and oropharynx and the number of computed tomography services per 100,000. There is a need to expand the availability of oncology services and human resources specialized in diagnosing and treating OOC in Brazilian municipalities for a timely TTI of OOC.

HE4-based nomogram for predicting overall survival in patients with idiopathic pulmonary fibrosis: construction and validation

Idiopathic pulmonary fibrosis (IPF) is a life-threatening interstitial lung disease. Identifying biomarkers for early diagnosis is of great clinical importance. The epididymis protein 4 (HE4) is important in the process of inflammation and fibrosis in the epididymis. Its prognostic value in IPF, however, has not been studied. The mRNA and protein levels of HE4 were used to determine the prognostic value in different patient cohorts. In this study, prognostic nomograms were generated based on the results of the cox regression analysis. We identified the HE4 protein level increased in IPF patients, but not the HE4 gene expression. The increased expression of HE4 correlated positively with a poor prognosis for patients with IPF. The HR and 95% CI were 2.62 (1.61-4.24) (p < 0.001) in the training set. We constructed a model based on the risk-score = 0.16222182 * HE4 + 0/0.37580659/1.05003609 (for GAP index 0-3/4-5/6-8) + (- 1.1183375). In both training and validation sets, high-risk patients had poor prognoses (HR: 3.49, 95%CI 2.10-5.80, p = 0.001) and higher likelihood of dying (HR: 6.00, 95%CI 2.04-17.67, p = 0.001). Analyses of calibration curves and decision curves suggest that the method is effective in predicting outcomes. Furthermore, a similar formulation was used in a protein-based model based on HE4 that also showed prognostic value when applied to IPF patients. Accordingly, HE4 is an independent poor prognosis factor, and it has the potential to predict IPF patient survival.

Development and validation of the relational behavior interactions scale for couples

In this research, we developed and validated a measure of couple-based reported behavior interactions (RBI). Specifically, Study 1 was designed to describe the development of the scale and to examine its reliability; Study 2 (N = 222), was designed to examine factors that could differentiate men and women. Additionally, we tested if women's behaviors could predict their partner's behavior. Results from the exploratory factor analysis (EFA) revealed a three-factor structure for couples' RBI which were labelled: Social Companionship and Affective Behavior Interactions (SAI) (Factor 1), Fulfilling Obligations and Duties of the Partner (FOD) (Factor 2) and Openness in the Relationship (OR) (Factor 3). In linear regression analyses, there was a significant difference between men and women in the second factor, which represents behaviors associated with fulfilling the responsibilities of a partner. On the other hand, neither the SAI factor nor the OR factor showed any distinct gender differences. The SPSS PROCESS analysis revealed that women's Social Companionship and Affective Behavior Interactions (Factor 1), and Openness in the Relationship (Factor 3) significantly predicted their male partner's behaviors. The relationship duration significantly moderated the association between women's and men's behaviors for both factors. Results are discussed in light of the need for a broader understanding of romantic behavioral interactions.

Predictors of maternal health services uptake in West African region: a multilevel multinomial regression analysis of demographic health survey reports

BACKGROUND

Pursuant to studies, receiving the three key maternal health services (Antenatal Care, Skilled Delivery Service, and Postnatal Care) in a continuum could prevent 71% of global maternal deaths. Despite the Western African region being known for its high maternal death and poor access to maternal health services, there is a dearth of studies that delve into the spectrum of maternal health services uptake. Hence, this study aimed to assess the level and predictors of partial and adequate utilization of health services in a single analytical model using the most recent Demographic and Health Survey (DHS) data (2013-2021).

METHODS

This study was based on the appended women's (IR) file of twelve West African countries. STATA software version 16 was used to analyze a weighted sample of 89,504 women aged 15-49 years. A composite index of maternal health service utilization has been created by combining three key health services and categorizing them into 'no', 'partial', or 'adequate' use. A multilevel multivariable multinomial logistic regression analysis was carried out to examine the effects of each predictor on the level of service utilization. The degree of association was reported using the adjusted relative risk ratio (aRRR) with a corresponding 95% confidence interval, and statistical significance was declared at p < 0.05.

RESULTS

66.4% (95% CI: 64.9, 67.7) and 23.8% (95% CI: 23.3, 24.2) of women used maternal health services partially and adequately, respectively. Togo has the highest proportion of women getting adequate health care in the region, at 56.7%, while Nigeria has the lowest proportion, at 11%. Maternal education, residence, wealth index, parity, media exposure (to radio and television), enrolment in health insurance schemes, attitude towards wife beating, and autonomy in decision-making were identified as significant predictors of partial and adequate maternal health service uptake.

CONCLUSION

The uptake of adequate maternal health services in the region was found to be low. Stakeholders should plan for and implement interventions that increase women's autonomy. Program planners and healthcare providers should give due emphasis to those women with no formal education and from low-income families. The government and the private sectors need to collaborate to improve media access and increase public enrolment in health insurance schemes.

Improving the robustness of the Sequentially Optimized Reconstruction Strategy (SORS) for visual field testing

Perimetry, or visual field test, estimates differential light sensitivity thresholds across many locations in the visual field (e.g., 54 locations in the 24-2 grid). Recent developments have shown that an entire visual field may be relatively accurately reconstructed from measurements of a subset of these locations using a linear regression model. Here, we show that incorporating a dimensionality reduction layer can improve the robustness of this reconstruction. Specifically, we propose to use principal component analysis to transform the training dataset to a lower dimensional representation and then use this representation to reconstruct the visual field. We named our new reconstruction method the transformed-target principal component regression (TTPCR). When trained on a large dataset, our new method yielded results comparable with the original linear regression method, demonstrating that there is no underfitting associated with parameter reduction. However, when trained on a small dataset, our new method used on average 22% fewer trials to reach the same error. Our results suggest that dimensionality reduction techniques can improve the robustness of visual field testing reconstruction algorithms.

The influence of biological DMARDs on aseptic arthroplasty loosening: a retrospective cohort study

OBJECTIVE

To investigate whether biological DMARDs affect the risk of aseptic loosening after total hip/knee arthroplasty (THA/TKA) in patients with RA.

METHODS

We retrospectively identified all patients suffering from RA who underwent THA/TKA at our academic centre between 2002 and 2015 and linked them with an existing prospective observational RA database at our institution. The risk of aseptic loosening was estimated using radiological signs of component loosening (RCL). A time-dependent Cox regression analysis was used to compare the risk of implant loosening between patients treated with traditional DMARDS and biological DMARDs, or alternately both over time.

RESULTS

A total of 155 consecutive total joint arthroplasties (TJAs) (103 TKA vs 52 THA) was retrospectively included in the study. Mean age at implantation was 59 ± 13 years. Mean follow-up time was 69 ± 43 months. Overall, 48 (31%) TJAs showed signs of RCL, with 28 (27.2%) RCLs occurring after TKA compared with 20 after THA (38.5%). A significant difference regarding the incidence of RCL between the traditional DMARDs group (39 cases of RCL, 35%) and the biological DMARDs group (nine cases of RCL, 21%) (P = 0.026) was observed using the log-rank test. This was also true when using a time-dependent Cox regression with therapy as well as arthroplasty location (hip vs knee) as variables (P = 0.0447).

CONCLUSION

Biological DMARDs may reduce the incidence of aseptic loosening after TJA in patients with RA compared with traditional DMARDs. This effect seems to be more pronounced after TKA than THA.

Handgrip strength: Best practice for a rapid nutrition screening and risk stratification in male patients with alcoholic liver cirrhosis, a classification and regression tree analysis study

BACKGROUND

Rapid nutrition screening (NS) is vital for apt management in patients with alcoholic liver cirrhosis (ALC).

AIM

To identify a quick method of NS having high reliability and prognostic significance.

METHODS

NS of patients with ALC was assessed using mid-upper arm circumference (MUAC), handgrip strength (HGS), fat-free mass index (FFMI), and the Royal Free Hospital-Global Assessment (RFH-GA). Baseline clinical and biochemical information were recorded along with 90-day survival data. The classification and regression tree method was used to classify HGS, MUAC, and FFMI values as well nourished (WN), moderately malnourished (MM), and severely malnourished (SM), and their concordance with RFH-GA categories was assessed using Kendall tau-b coefficient. The prognostic proficiency of each method was tested by Cox regression analysis.

RESULTS

According to the RFH-GA, of 140 male patients with ALC, 13 of 140 (9.3%) were WN, 93 of 140 (66.4%) were MM, and 34 of 140 (26.8%) were SM. HGS has the strongest association with the RFH-GA (Kendall tau-b = 0.772; diagnostic accuracy -81.4%). HGS was found to be the independent predictor of 90-day mortality (26 of 140 [18.6%]; hazard ratio, 0.93; 95% CI, 0.88-0.98; P = 0.002) after adjusting for age, body mass index, and disease severity. The hazard of mortality was 8.5-times higher in patients with ALC with HGS < 22 kg as compared with those with HGS > 29.

CONCLUSION

HGS is a reliable tool for rapid NS. HGS < 22 kg suggests a high risk for severe malnutrition and is strongly associated with short-term mortality in male patients with ALC.

Acute kidney injury in infants with hypoxic-ischemic encephalopathy

BACKGROUND

This study aimed to investigate the prevalence of acute kidney injury (AKI) in infants with varying degrees of hypoxic-ischemic encephalopathy (HIE) and its associated outcomes, including mortality and length of stay (LOS).

METHODS

The study used the National Inpatient Sample (NIS) dataset from 2010 to 2018. Regression analysis was used to control confounding variables.

RESULTS

Of 31,220,784 infants included in the study, 30,130 (0.1%) had HIE. The prevalence of AKI was significantly higher in infants with HIE (9.0%) compared to those without (0.04%), with an adjusted odds ratio (aOR) of 77.6 (CI:70.1-85.7, p < 0.001), with the highest prevalence of AKI in infants with severe HIE (19.7%), aOR:130 (CI: 107-159), p < 0.001). Infants with AKI had a higher mortality rate compared to those without AKI in those diagnosed with any degree of HIE (28.9% vs. 8.8%), aOR 3.5 (CI: 3.2-3.9, p < 0.001), particularly among those with severe HIE, aOR:1.4 (1.2-1.6, p < 0.001).

CONCLUSIONS

HIE is associated with an increased prevalence of AKI. Infants with severe HIE had the highest prevalence of AKI and associated mortality. The study highlights the need for close monitoring and early detection of AKI in infants with HIE, particularly those with severe HIE, to ameliorate the associated adverse outcomes.

Association of adversities and mental health among first- and second-generation Arab American young adults

The prevalence of mental health problems among young adults is widely recognized. However, limited research has examined the mental health of Arab American young adults specifically. To address this gap in the literature, this study aimed to investigate the effects of multiple stressors including adverse childhood experiences (ACEs), discrimination, and bullying victimization on the mental health of first- and second-generation Arab American young adults. The participants (N = 162) were recruited from a Midwest university using online and in-person methods. They were screened and completed a demographic questionnaire and self-report measures of ACEs, discrimination, bullying victimization, and mental health. Hierarchical multiple regression analysis was conducted to examine the effect of psychosocial stressors on mental health and the moderating effect of generation (first vs. second) on that relationship. Female gender, increased perceived discrimination, and more ACEs were associated with lower mental health scores (β = -0.316, p < 0.001, β = -0.308, p < 0.001, and β = -0.230, p = 0.002, respectively). There was a significant negative relationship between victimization and mental health for first-generation Arab Americans (β = -0.356, p = 0.010). However, that association all but disappeared for second-generation participants (β = 0.006, p = 0.953). The results highlight the impact of multiple adversities on Arab American young adults' mental health and indicate important nuances related to their generation in the association between bullying victimization and mental health. Implications for practice and future research are discussed.

The Epidemiology of Posttraumatic Osteoarthritis of the Knee in the United States: An Analysis of 948,853 Patients From 2000 to 2022

INTRODUCTION

Posttraumatic osteoarthritis of the knee (PTOAK) is a known sequela of bony and soft-tissue articular knee injuries, although its historically reported prevalence is highly variable with no recent population-based studies.

METHODS

The TriNetX/US Collaborative Network database was queried to identify adult patients diagnosed with a history of knee trauma using ICD-10-CM coding. Primary outcomes measured were yearly incidence proportion (IP), incidence rate (IR), and prevalence of knee osteoarthritis in the United States from 2000 to 2022. Chi square analyses were conducted to compare outcomes across categorical data. Regression modeling was performed to project PTOAK epidemiology to 2030. Statistical significance was held at P < 0.05 for all analyses.

RESULTS

Nine hundred forty-eight thousand eight hundred fifty-three patients meeting criteria were identified. As of 2022, the IP of PTOAK was 5.93%, IR was 2.26 × 10 -4 cases/person-day, and prevalence was 21.1%. By strata in 2022, posttraumatic knee OA is most prevalent among the 54 to 59-year-old age group (50.9%), 60 to 64-year-old age group (50.3%), 50 to 54-year-old age group (49.7%), female patients (24.2%), and White patients (23.1%). Regression analyses revealed that the IP, IR, and prevalence of PTOAK have increased exponentially from 2000 to 2022. By 2030, the model predicts that the IP will further increase to 10.7% (95% PI = 9.79% to 11.7%), IR will be 3.79 × 10 -4 cases/person-day (95% PI = 3.28 × 10 -4 to 4.29 × 10 -4 ), and prevalence of PTOAK in the United States will be 40.6% (95% PI = 39.1% to 42.0%).

DISCUSSION

These findings echo earlier, smaller scale studies but reveal an alarming rise in PTOAK prevalence, potentially doubling by 2030. The financial burden of knee OA treatment in the United States is already substantial, costing between $5.7 and $15 billion USD annually. This projected increase in prevalence could further increase healthcare expenditures by $1 to 3 billion by 2030. These results emphasize the need for additional research into factors contributing to PTOAK, evidence-based preventive public health interventions, and the development of multidisciplinary system-based care delivery optimization pathways.

Out-of-Pocket Costs and Payments in Autologous and Implant-Based Breast Reconstruction: A Nationwide Analysis

BACKGROUND

Many factors influence a patient's decision to undergo autologous versus implant-based breast reconstruction, including medical, social, and financial considerations. This study aims to investigate differences in out-of-pocket and total spending for patients undergoing autologous and implant-based breast reconstruction.

METHODS

The IBM MarketScan Commercial Databases were queried to extract all patients who underwent inpatient autologous or implant-based breast reconstruction from 2017 to 2021. Financial variables included gross payments to the provider (facility and/or physician) and out-of-pocket costs (total of coinsurance, deductible, and copayments). Univariate regressions assessed differences between autologous and implant-based reconstruction procedures. Mixed-effects linear regression was used to analyze parametric contributions to total gross and out-of-pocket costs.

RESULTS

The sample identified 2079 autologous breast reconstruction and 1475 implant-based breast reconstruction episodes. Median out-of-pocket costs were significantly higher for autologous reconstruction than implant-based reconstruction ($597 vs $250, P < 0.001) as were total payments ($63,667 vs $31,472, P < 0.001). Type of insurance plan and region contributed to variable out-of-pocket costs (P < 0.001). Regression analysis revealed that autologous reconstruction contributes significantly to increasing out-of-pocket costs (B = $597, P = 0.025) and increasing total costs (B = $74,507, P = 0.006).

CONCLUSION

The US national data demonstrate that autologous breast reconstruction has higher out-of-pocket costs and higher gross payments than implant-based reconstruction. More study is needed to determine the extent to which these financial differences affect patient decision-making.

Association Between Days of the Week and Intraocular Pressure: Japan Ningen Dock Study

PRCIS

The analysis of intraocular pressure (IOP) by day of the week using the mega database showed a periodic weekly pattern with the highest value on Monday.

PURPOSE

To evaluate IOP by the day of the week.

PATIENTS AND METHODS

Annual health checkup examinees between April 2014 and March 2015 were cross-sectionally evaluated. As a result, 655,818 participants [51.5±10.5 (range: 20-96) years, 40.1% women] from 103 medical centers were included. IOP was measured using a noncontact tonometer. The mean IOPs of each day of the week were compared using multiple comparison test and multiple linear regression analysis. Wednesday was set as the reference. Moreover, weekly IOP variations stratified by sex and age were also evaluated.

RESULTS

Mean IOPs from Monday to Sunday were 13.19±2.97, 13.06±2.92, 13.05±2.91, 13.05±2.92, 13.12±2.94, 13.10±2.96, and 13.16±2.78 mm Hg. IOP was significantly higher on Monday, Friday, and Saturday than those on Wednesday ( P <0.001, <0.001, 0.002). After adjusting for factors affecting IOP, the IOPs on Monday and Saturday were higher than those on Wednesday [β=0.097 (95% CI: 0.074-0.121), P <0.001; β=0.032 (95% CI: 0.005-0.059), P =0.019]. Men had significantly higher IOPs on Monday and Saturday than on Wednesday [β=0.142 (95% CI: 0.110-0.173), P <0.001; β=0.053 (95% CI: 0.017-0.089), P =0.004], whereas women did not have a significant trend. Participants aged below 65 years had higher IOPs on Monday ( P <0.001 in under 60 years; P =0.003 in 60-64 years), while those aged 65 years or older did not ( P =0.856).

CONCLUSION

IOP values may have a periodic weekly pattern. The high IOP on Monday was more pronounced in men aged less than 65 years.

Well-Being Inequality Among Adolescents and Young Adults

PURPOSE

This study aimed to examine patterns of well-being across developmental stages and patterns of inequality in well-being among young adults and adolescents. Well-being exists when adolescents and young adults thrive and can achieve their full potential.

METHODS

We used individual-level survey data from the Gallup World Poll from 164 countries between 2009 and 2017 (N = 446,934). Regression analyses were used to determine associations.

RESULTS

We documented substantial inequality in well-being across three developmental stages (adolescence, early adulthood, young adulthood). Health, education, income, and social relations are strongly associated with mean well-being and well-being inequality. We showed, for mean well-being, the relative importance of these factors varies over life-cycle stages. For inequality, most factors were consistent across developmental groups; however, we identified certain characteristics that were only relevant at certain developmental stages.

DISCUSSION

Given the policy importance of well-being at all stages of life and the significance of adolescence and early adulthood in developing positive health-related behaviors, policies and programs targeting the highlighted characteristics are likely to be effective but require a multisectoral approach.

Regression analysis of longitudinal data with random change point

A great deal of literature has been established for regression analysis of longitudinal data and in particular, many methods have been proposed for the situation where there exist some change points. However, most of these methods only apply to continuous response and focus on the situations where the change point only occurs on the response or the trend of the individual trajectory. In this article, we propose a new joint modeling approach that allows not only the change point to vary for different subjects or be subject-specific but also the effect heterogeneity of the covariates before and after the change point. The method combines a generalized linear mixed effect model with a random change point for the longitudinal response and a log-linear regression model for the random change point. For inference, a maximum likelihood estimation procedure is developed and the asymptotic properties of the resulting estimators, which differ from the standard asymptotic results, are established. A simulation study is conducted and suggests that the proposed method works well for practical situations. An application to a set of real data on COVID-19 is provided.

Predictors of age at diagnosis in autism spectrum disorders: the use of multiple regression analyses and a classification tree on a clinical sample

The increasing prevalence of autism spectrum disorders (ASD) has led to worldwide interest in factors influencing the age of ASD diagnosis. Parents or caregivers of 237 ASD children (193 boys, 44 girls) diagnosed using the Autism Diagnostic Observation Schedule (ADOS) completed a simple descriptive questionnaire. The data were analyzed using the variable-centered multiple regression analysis and the person-centered classification tree method. We believed that the concurrent use of these two methods could produce robust results. The mean age at diagnosis was 5.8 ± 2.2 years (median 5.3 years). Younger ages for ASD diagnosis were predicted (using multiple regression analysis) by higher scores in the ADOS social domain, higher scores in ADOS restrictive and repetitive behaviors and interest domain, higher maternal education, and the shared household of parents. Using the classification tree method, the subgroup with the lowest mean age at diagnosis were children, in whom the summation of ADOS communication and social domain scores was ≥ 17, and paternal age at the delivery was ≥ 29 years. In contrast, the subgroup with the oldest mean age at diagnosis included children with summed ADOS communication and social domain scores < 17 and maternal education at the elementary school level. The severity of autism and maternal education played a significant role in both types of data analysis focused on age at diagnosis.

The impact of myasthenia gravis severity on work and daily activities

INTRODUCTION/AIMS

People with myasthenia gravis (MG) experience impaired quality of life. However, the impact of MG symptoms on work productivity has not been well-studied. We aimed to evaluate this impact and to examine associations between disease severity and the degree of impairment.

METHODS

Data were drawn from the Adelphi MG Disease-Specific Programme™, a multinational (USA, France, Germany, Italy, Spain, UK) survey completed by physicians and their patients with MG in 2020. Patient-reported measures included the Work Productivity and Activity Impairment (WPAI): Specific Health Problem questionnaire.

RESULTS

The WPAI questionnaire was completed by 330 patients. Among those currently employed, the mean percentage of work time missed (absenteeism) was 13.3% (N = 116), percentage impairment of productivity at work (presenteeism) was 26.7% (N = 121), and overall work impairment was 30.0% (N = 110). Across all patients, impairment of non-work-related activities due to health problems (ADL impairment) was 39.2% (N = 330). Regression analysis indicated that impairment differed according to MG Foundation of America (MGFA) class (p = .0147, p < .0001, p < .0001 and p < .0001 for absenteeism, presenteeism, overall work impairment and ADL impairment, respectively). Being MGFA class III/IV was a predictor of presenteeism, overall work impairment and ADL impairment in a predictor model.

DISCUSSION

Patients with MG experience substantial work impairment particularly those with more severe symptoms, highlighting an important way in which patient quality of life is negatively affected. More effective treatment strategies would enable patients to lead more productive lives and could impact decisions relating to work and career.

Understanding the effects of sub-inhibitory antibiotic concentrations on the development of β-lactamase resistance based on quantile regression analysis

AIMS

Quantile regression is an alternate type of regression analysis that has been shown to have numerous advantages over standard linear regression. Unlike linear regression, which uses the mean to fit a linear model, quantile regression uses a data set's quantiles (or percentiles), which leads to a more comprehensive analysis of the data. However, while relatively common in other scientific fields such as economic and environmental modeling, it is infrequently used to understand biological and microbiological systems.

METHODS AND RESULTS

We analyzed a set of bacterial growth rates using quantile regression analysis to better understand the effects of antibiotics on bacterial fitness. Using a bacterial model system containing 16 variant genotypes of the TEM β-lactamase enzyme, we compared our quantile regression analysis to a previously published study that uses the Tukey's range test, or Tukey honestly significantly difference (HSD) test. We find that trends in the distribution of bacterial growth rate data, as viewed through the lens of quantile regression, can distinguish between novel genotypes and ones that have been clinically isolated from patients. Quantile regression also identified certain combinations of genotypes and antibiotics that resulted in bacterial populations growing faster as the antibiotic concentration increased-the opposite of what was expected. These analyses can provide new insights into the relationships between enzymatic efficacy and antibiotic concentration.

CONCLUSIONS

Quantile regression analysis enhances our understanding of the impacts of sublethal antibiotic concentrations on enzymatic (TEM β-lactamase) efficacy and bacterial fitness. We illustrate that quantile regression analysis can link patterns in growth rates with clinically relevant mutations and provides an understanding of how increasing sub-lethal antibiotic concentrations, like those found in our modern environment, can affect bacterial growth rates, and provide insight into the genetic basis for varied resistance.

An authentic leadership training programme to increase nurse empowerment and patient safety: A quasi-experimental study

BACKGROUND

Authentic leadership and empowered nurses are necessary if a healthy work environment is to be created and patient safety maintained; however, few studies have examined the impact of authentic leadership, on nurse empowerment and the patient safety climate.

PURPOSE

The aim of the study was to investigate the impact of an educational intervention delivered through a multi-faceted training programme on nurses' perceptions of authentic leadership, nurse empowerment (both structural and psychological) and the patient safety climate.

DESIGN

A quasi-experimental study using a one-group pretest-posttest design consistent with TREND guidelines.

METHODS

The study was conducted in a university hospital between December 2018 and January 2020. Participants were followed for 6 months. The programme involved 36 head nurses (leaders) and 153 nurses (followers). The effectiveness of the programme was evaluated using repeated measures of analysis of variance, dependent sample t-tests and hierarchical regression analysis.

RESULTS

Following the intervention, safety climate and authentic leadership scores increased among both leaders and followers. Structural and psychological empowerment scores also increased among followers. We found that authentic leadership and structural empowerment were predictors of safety climate.

CONCLUSION

The implementation of the education programme resulted in positive changes in participants' perceptions of authentic leadership and empowerment, which can enhance patient safety.

IMPLICATIONS

Healthcare organizations can implement similar multi-faceted training programmes focused on authentic leadership, and nurse empowerment to increase patient safety. Achieving effective results in such programmes can be facilitated by motivating participants with the support of the top management.

PATIENT OR PUBLIC CONTRIBUTION

The study included nurses in the intervention and the data collection processes.

IMPACT

Patient safety is a global concern, and improving patient safety culture/climate is a key strategy in preventing harm. Authentic leadership and nurse empowerment are essential in creating healthy work environments and delivering safe, high-quality care. Training programmes addressing these issues can help bring about improvements in healthcare organizations.

Pseudo-value regression trees

This paper presents a semi-parametric modeling technique for estimating the survival function from a set of right-censored time-to-event data. Our method, named pseudo-value regression trees (PRT), is based on the pseudo-value regression framework, modeling individual-specific survival probabilities by computing pseudo-values and relating them to a set of covariates. The standard approach to pseudo-value regression is to fit a main-effects model using generalized estimating equations (GEE). PRT extend this approach by building a multivariate regression tree with pseudo-value outcome and by successively fitting a set of regularized additive models to the data in the nodes of the tree. Due to the combination of tree learning and additive modeling, PRT are able to perform variable selection and to identify relevant interactions between the covariates, thereby addressing several limitations of the standard GEE approach. In addition, PRT include time-dependent effects in the node-wise models. Interpretability of the PRT fits is ensured by controlling the tree depth. Based on the results of two simulation studies, we investigate the properties of the PRT method and compare it to several alternative modeling techniques. Furthermore, we illustrate PRT by analyzing survival in 3,652 patients enrolled for a randomized study on primary invasive breast cancer.

High concordance of blood glucose measurement in cats between a beta prototype glucometer device and a reference laboratory standard in a clinical setting

OBJECTIVE

The objective of this study was to evaluate the accuracy of a beta prototype version of a new portable blood glucose meter in feline patients.

ANIMALS

60 client-owned cats.

METHODS

In this prospective study, 3-mL blood samples were collected from each cat and analyzed in triplicate using a beta prototype device (AlphaTRAK 3 [AT3]) and by a reference lab standard immediately after collection. Accuracy of the AT3 device was determined in accordance with the International Organization of Standardization (ISO) 15197:2013 criteria, including Bland-Altman plotting and consensus error grid analysis. A Passing-Bablok regression analysis was also performed.

RESULTS

96% of feline measurements fell within the ISO accuracy threshold, and 100% of measurements fell within zones A and B of the consensus error grid, meeting the ISO accuracy requirements. There was no significant bias in the data according to the Bland-Altman analysis. Within the full range of glucose concentrations (20 to 750 mg/dL) the correlation coefficient between the AT3 and the reference lab standard was 0.99. There was no significant constant or proportional bias present in the data.

CLINICAL RELEVANCE

The AT3 device met the ISO requirements and is accurate for measurement of blood glucose concentrations in cats.

Cooking at Home: Correlates of Frequency and Intention in Fifth Graders

Cooking at home is associated with health benefits, and 10- and 11-year-old children are capable of participating in meal preparation. However, opportunities for children to cook at home have declined. This study aimed to identify determinants of the frequency and the intention to cook at home in fifth graders using the Theory of Planned Behavior as a framework with quantitative methodology. A total of 241 participants across five elementary schools of the Chaudière-Appalaches region (Quebec, Canada) took part in this correlational study. Data were collected via a self-administered questionnaire based on the Theory of Planned Behavior. Regression analyses led to the identification of determinants of frequency and intention to cook at home. More than two-thirds of participants (69%) declared having cooked at home in the past 7 days. Intention was the only significant variable explaining 18% of the variance for frequency. Intention was determined by perceived behavioral control, attitude, descriptive norms, subjective norms, perceived barriers, being a girl, and normative beliefs, which explain 74% of the variance. Whereas other studies aiming at better understanding children's involvement in meal preparation at home focused on self-efficacy for cooking, this study highlights other behavioral determinants. For example, support from parents appears to be crucial to promote this behavior in this age group. Future research and interventions should be oriented toward determinants such as subjective norms and normative beliefs, and focus on children's autonomy.

[Experience with orthopaedic insoles-a cross-sectional study]

BACKGROUND

Orthopaedic insoles (OI) are used to treat a variety of foot problems.

OBJECTIVES

The aim of this cross-sectional study was to investigate the perceptions of the treatment with OI among the manufacturers of the OIs, the orthopaedic technicians (OT).

METHODS

OT from the federal states of Schleswig-Holstein and Lower Saxony in Germany were invited to take part in a survey. The questions included, among others, the number of prescriptions for the production of an OI per month and the materials used. Descriptive statistics, subgroup analyses and a linear regression analysis were performed.

RESULTS

Of the 312 questionnaires distributed, 159 were completed (response rate 51%). Most of the respondents were male (80%). The average age of the participants was 50. On average, OT produced 290 OI per month, with plastic being the most commonly used material (73%). OT with less than 20 years of professional experience are more likely to follow the doctor's instructions when producing OI than OT with more than 20 years of professional experience. The latter are more likely to base their decisions regarding the manufacture and issuing of OI on their own experience.

CONCLUSIONS

The production and issuing process of OI differs among OT. The different professional perspectives of the OT could play a role here, as does the lack of a standardized procedure. The factors listed in this study represent potential starting points for future research projects that could contribute to the development of evidence-based standards.

Trend and Seasonality of Hip Fractures in Catalonia, Spain: Exploring the Influence of Climate

To describe the secular trend and seasonality of the incidence of hip fracture (HF) and its relationship with climatic variables during the period 2010-2019 in Catalonia in people aged ≥ 65 years. The results were analyzed by sex, age groups (65-74, 75-84, and ≥ 85), and types of fracture (extracapsular and intracapsular). Data on sex, age, type of fracture, year, and month of hospitalization of patients admitted with a diagnosis of HF between January 1, 2010 and December 31, 2019 were collected. Crude and standardized HF incidence (HFi) rates were obtained. Data on the monthly mean of climatological variables (temperature, insolation, icy days, rain, relative humidity, atmospheric pressure, and wind force) were obtained from the network of meteorological stations in Catalonia. Time series analytical statistics were used to identify trends and seasonality. Linear regression and a seasonal autoregressive integrated moving average (ARIMA) were used to analyze the relationship of each climatic parameter with fracture rates. In addition, generalized additive models were used to ascertain the best predictive model. The total number of HF episodes was 90,149 (74.1% in women and 25.9% in men). The total number of HFs increased by 6.4% between 2010 and 2019. The median age (SD) was 84.5 (7.14) and 54% of patients were ≥ 85 years of age. Extracapsular fractures were the most common (55%). The standardized incidence rates decreased from 728.1/100,000 (95% CI 738.6-769.3) to 624.5/100,000 (95% CI 648.7-677.0), which represents a decrease of 14.2% (p < 0.05). The decline was greater at older ages. There were seasonal variations, with higher incidences in autumn (27.2%) and winter (25.7%) and lower rates in summer (23.5%) and spring (23.6%). Seasonality was more pronounced in elderly people and men. In the bivariate regression analysis, high temperatures and greater insolation were negatively associated with the HF rate, while the number of icy days, rainy days, and high relative humidity were associated with a higher incidence of fractures in all age groups and sexes. In the regression analysis using the seasonal ARIMA model, only insolation had a consistently significant association with overall HFi, after adjusting by trend and other climatic parameters. While the global number of HFs grew in Catalonia due to increases in the elderly population, the standardized HF rate decreased during the years 2010-2019. There was a seasonal trend, with predominance in the cold months and correlations with climatic parameters, especially with insolation.

Effects of physical and psychological symptoms on cancer-related fatigue among esophageal cancer patients

BACKGROUND

Cancer-related fatigue (CRF) is considered one of the most prevalent and distressing symptoms among cancer patients and may vary among patients with different cancer types. However, few studies have explored the influence of physical and psychological symptoms on CRF among esophageal cancer (EC) patients without esophagectomy. Therefore, this study aimed to examine the effects of physical and psychological symptoms on CRF among EC patients without esophagectomy.

METHODS

In the present study, a cross-sectional study was conducted from February 2021 to March 2022 in Liaoning Province, China. Among the 112 included participants, 97 completed our investigation. The questionnaires used consisted of the Brief Fatigue Inventory (BFI), the MD Anderson Symptom Inventory Gastrointestinal Cancer Module (MDASI-GI), the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), and demographic and clinical information. Multivariate linear regression was conducted to test the relationships between physical and psychological symptoms and CRF.

RESULTS

Of the 97 EC patients, 60.8% reported CRF (BFI ≥ 4). The mean age of the participants was 64.92 years (SD = 8.67). According to the regression model, all the variables explained 74.5% of the variance in CRF. Regression analysis indicated that physical symptoms, including constipation, diarrhoea, and difficulty swallowing, contributed to CRF. On the other hand, depressive symptoms increased the level of CRF among EC patients without esophagectomy.

CONCLUSIONS

Given the high prevalence of CRF among EC patients without esophagectomy, it is urgent to emphasize the importance of fatigue management interventions based on physical and psychological symptoms to alleviate CRF in EC patients.

Effect of metformin on anti-mullerian hormone levels in women with polycystic ovarian syndrome: a systematic review and meta-regression analysis of randomized controlled trials with

BACKGROUND

Several interventional studies have evaluated the potential anti-Mullerian hormone (AMH)-reduction effect of metformin. However, the results are still contradictory. In order to obtain a better viewpoint from them, this study aimed to comprehensively investigate the effects of metformin on AMH in the women with with polycystic ovarian syndrome (PCOS).

METHODS

Scopus, PubMed/Medline, Web of Science, Cochrane, and Embase databases were searched using standard keywords to identify all controlled trials investigating the AMH levels following metformin administration. Pooled weighted mean difference and 95% confidence intervals were achieved by random-effects model analysis for the best estimation of outcomes.

RESULTS

Sixteen studies with 484 participants' were included in this article. The pooled findings showed that AMH levels in the single arm clinical trials were significantly reduced (pooled WMD of -3.06 ng/ml; 95% confidence interval [CI] -4.03 to -2.10; P < 0.001) after use of metformin. Furthermore, compared to the control group, in randomized clinical trials, a reduced significant effect on AMH levels was observed following use of metformin (pooled WMD of -3.47 ng/ml; 95% CI -7.14 to -0.19; P = 0.047). Furthermore, higher reduction in the AMH levels with a metformin dosage ≤ 1500 mg/day and duration of treatment ≤ 12 weeks when compared to higher dosages and duration of intervention, observed in this meta-analysis.

CONCLUSIONS

In conclusion, results this meta-analysis of clinical trials confirms the beneficial effect of the treatment with metformin in the reduction of the AMH levels in women.

Will coronal alignment postoperatively be deteriorating in adult spinal deformity after long-fusion surgery?

BACKGROUND

To investigate whether the coronal alignment (CA) will deteriorate, and identify the risk factors for coronal malalignment (CM) developing in adult spinal deformity (ASD) after long-fusion surgery.

METHODS

A multi-center retrospective study was performed, which included a total of 161 ASD patients who had undergone the surgical procedure of long-fusion (≥ 5 vertebras) with instrumentations in three medical centers. All of the participants were retrospectively reviewed, and subsequently assigned into the consistency group (C7 plumb line (C7PL) shifting towards the convex side of the main curve), and the opposition group (C7PL shifting towards the concave side). CM was considered if the coronal balance distance (CBD) being over 30 mm. A Kaplan-Meier curve and log-rank test were used to analyze the differences in CM-free survival during follow-up. Multivariate analysis via a Cox proportional hazards test was used to analyze the risk factors.

RESULTS

Patients showing CM equaled 35 (21.7%) at the pre-operation, and that increased significantly up to 51 (31.7%) at the final follow-up (P = 0.04). In the consistency group, the incidence of CM at the final follow-up was much higher than that preoperatively (35:16, P = 0.002). CM-free survival time decreased significantly in patients with larger CBD correction, pelvic fixation and more instrumented segments, respectively, during follow-up (P < 0.05, log-rank test). Age ≥ 60 years, the consistency CA, pelvic fixation, CBD-correction ≥ 30 mm and fixed-vertebra ≥ 8 were risk factors for CM happening after surgery using multivariate regression analysis (P < 0.05).

CONCLUSIONS

The coronal alignments in ASD patients underwent long-fusion surgeries may deteriorate during follow-up, for which the risk factors include the consistency CA, age ≥ 60, fixed-vertebra ≥ 8, CBD-correction ≥ 30 mm and pelvic fixation.

Statistical estimation of noise induced hearing loss among the drivers in one of the most polluted cities of India

In the present study, an attempt has been made to assess the impact of vehicular noise upon the 3-wheeler tempo drivers and to know whether there is any relationship between hearing loss and cumulative noise exposure. For this purpose, 3-wheeler tempo drivers (Exposed group) and non-commercial light motor vehicle car drivers (Unexposed group) were chosen as study subjects. Three traffic routes were selected to assess the noise level during waiting and running time in the exposed and unexposed groups. Among all three routes, the highest mean noise level (Leq) was observed on the Chowk to Dubagga route for waiting and en-route noise measurement. It was measured as 84.13 dB(A) and 86.36 dB(A) for waiting and en-route periods of 7.68 ± 3.46 and 31.05 ± 6.6 min, respectively. Cumulative noise exposure was found to be significantly different (p < 0.001) in all age groups of exposed and unexposed drivers. Audiometric tests have been performed over both exposed and unexposed groups. The regression analysis has been done keeping hearing loss among tempo drivers as the dependent variable and age (years) and Energy (Pa2 Hrs) as the independent variable using three different criteria of hearing loss definitions, i.e., World Health Organization, National Institute for Occupational Safety and Health (NIOSH), Occupational Safety and Health Administration criteria. Among these three criteria, the NIOSH criterion of hearing loss best explained the independent variables. It could explain the total variation in dependent variable by independent variable quite well, i.e., 68.1%. The finding showed a linear relationship between cumulative noise exposures (Pa2 Hrs) and the exposed group's hearing loss (dB), i.e., hearing loss increases with increasing noise dose. Based on the findings, two model equations were developed to identify the safe and unsafe noise levels with exposure time.

Regional variation in body size and estimated secular change among adult Indian males born in the 1890s-1950s

Regional variation in the body size of Indian men 18-84 years of age (birth years 1891-1957) was considered. Heights, weights, and BMIs of Indian males from four regions of the country - North, East-Northeast, Central, and West were compared. Heights of men 35+ years of age were adjusted for estimated height loss with age; the estimate was added to observed height to provide an estimate of maximum height. Linear regressions of measured height and estimated maximum height on year of birth were used to evaluate secular change by region. Differences in measured and estimated maximum heights and weight among regions were significant in all age groups, while differences in the BMI were significant in all age groups except 55+ years. Men from the North region were tallest and those from the East-Northeast region were shortest, while body weight and the BMI varied among regions. Regression analyses of year of birth on measured and estimated maximum heights indicated small differences in estimates of secular change among regions but suggested a decline in estimated maximum heights with age among men in the four regions born in 1891 through the 1930s, and small but variable estimates of secular change in heights among men born in the 1930s through 1957. The variation likely reflected socio-economic disparities and ecological differences among regions, and by inference nutritional status though data are limited.

COVID-19 vaccine intercountry distribution inequality and its underlying factors: a combined concentration index analysis and multiple linear regression analysis

Introduction

Inequitable access to COVID-19 vaccines among countries is a pressing global health issue. Factors such as economic power, political power, political stability, and health system strength contribute to disparities in vaccine distribution. This study aims to assess the inequality in vaccine distribution among countries based on these factors and identify their relationship with COVID-19 vaccine distribution.

Methods

A Concentration Index (CI) analysis was conducted to evaluate inequalities in the distribution of COVID-19 vaccines among countries based on four separate variables: GDP per capita, political stability (PS), World Power Index (WPI), and Universal Health Coverage (UHC). Additionally, Multiple Linear Regression (MLR) analysis was employed to explore the relationship between vaccine distribution and these independent variables. Two vaccine distribution variables were utilized for result reliability.

Results

The analysis revealed significant inequalities in COVID-19 vaccine distribution according to the countries' GDP/capita, PS, WPI, and UHC. However, the multiple linear regression analysis showed that there is no significant relationship between COVID-19 vaccine distribution and the countries' GDP/capita and that UHC is the most influential factor impacting COVID-19 vaccine distribution and accessibility.

Discussion

The findings underscore the complex interplay between economic, political, and health system factors in shaping vaccine distribution patterns. To improve the accessibility to vaccines in future pandemics, Global Health Governance (GHG) and countries should consider working on three areas; enhance political stabilities in countries, separate the political power from decision-making at the global level and most importantly support countries to achieve UHC.

Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements

Based on the data of the State of Global Air (2020), air quality deterioration in Thailand has caused ~32,000 premature deaths, while the World Health Organization evaluated that air pollutants can decrease the life expectancy in the country by two years. PM2.5 was collected at three air quality observatory sites in Chiang-Mai, Bangkok, and Phuket, Thailand, from July 2020 to June 2021. The concentrations of 25 elements (Na, Mg, Al, Si, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Se, Br, Sr, Ba, and Pb) were quantitatively characterised using energy-dispersive X-ray fluorescence spectrometry. Potential adverse health impacts of some element exposures from inhaling PM2.5 were estimated by employing the hazard quotient and excess lifetime cancer risk. Higher cancer risks were detected in PM2.5 samples collected at the sampling site in Bangkok, indicating that vehicle exhaust adversely impacts human health. Principal component analysis suggests that traffic emissions, crustal inputs coupled with maritime aerosols, and construction dust were the three main potential sources of PM2.5. Artificial neural networks underlined agricultural waste burning and relative humidity as two major factors controlling the air quality of Thailand.

Can routine assessment of older people's mental health lead to improved outcomes: A regression discontinuity analysis

OBJECTIVE

To assess whether case finding for depression among people aged 65 and above improves mental health.

DESIGN

Opportunistic evaluation using a regression discontinuity analysis with data from a randomised controlled trial.

SETTING

The REFORM trial, a falls prevention study that recruited patients from NHS podiatry clinics.

PARTICIPANTS

1010 community-dwelling adults over the age of 65 with at least one risk factor for falling (recent previous fall or fear of falling).

INTERVENTION

Letter sent to patient's General Practitioner if they scored 10 points or above on the 15-item Geriatric Depression Scale (GDS-15) informing them of the patient's risk of depression.

MAIN OUTCOME MEASURE

GDS-15 score six months after initial completion of GDS-15.

RESULTS

895 (88.6%) of the 1010 participants randomised into REFORM had a valid baseline and six-month GDS-15 score and were included in this study. The mean GDS-15 baseline score was 3.5 (SD 3.0, median 3.0, range 0-15); 639 (71.4%) scored 0-4, 204 (22.8%) scored 5-9 indicating mild depression, and 52 (5.8%) scored 10 or higher indicating severe depression. At six months follow-up, those scoring 10 points or higher at baseline had, on average, a reduction of 1.08 points on the GDS-15 scale (95% confidence interval -1.83 to -0.33, p = 0.005) compared to those scoring less than 10, using the simplest linear regression model.

CONCLUSION

Case finding of depression in podiatry patients based on a GDS-15 score of 10 or more followed by a letter to their General Practitioner significantly reduced depression severity. Whether this applies to all older patients in primary care is unknown. Further research is required to confirm these findings. Regression discontinuity analyses could be prespecified and embedded within other existing research studies.

The association between quality of life and diabetes: the Bushehr Elderly Health Program

BACKGROUND AND OBJECTIVE

Considering the importance of diabetes and its increased prevalence with aging, this study aimed to evaluate the association between diabetes status and quality of life (QOL) and the determining factors in individuals over 60.

METHODS

Two thousand three hundred seventy-five individuals including 819 (34.5%) with diabetes, aged 69.4 ± 6.4, from Bushehr Elderly Health Program (BEHP) were enrolled. We categorized the participants as non-diabetic, controlled diabetic, and poorly controlled diabetic. The QOL was assessed using the SF-12 questionnaire. The physical (PCS) and mental (MCS) component summaries of QOL were estimated. We compared the SF-12 domains and components between the categories using ANOVA. Further, the association of diabetes status with PCS and MCS was assessed after adjustment for possible confounders including age, sex, depression, cognitive impairment, physical activity, and other relevant factors using linear regression analysis.

RESULTS

Individuals with diabetes had lower PCS (40.9 ± 8.8 vs. 42.7 ± 8.6, p-value < 0.001), and MCS scores (45.0 ± 10.2 vs. 46.4 ± 9.4, p-value < 0.001) compared to participants without diabetes. No significant differences were observed in PCS or MCS scores between controlled or poorly controlled individuals with diabetes. Diabetes status was associated with PCS and MCS scores in univariable analysis. Regarding physical component of QOL, after adjusting for other confounders, poorly controlled diabetes was significantly associated with PCS [beta: -1.27 (-2.02, -0.52)]; some other determinants include depression [-7.66 (-8.51, -6.80)], male sex [3.90 (3.24,4.57)], and good physical activity [1.87 (1.17,2.57)]. As for the mental component, controlled diabetes was significantly associated with MCS [-1.17 (-2.13, -0.22)]; other contributing factors include depression [-14.35 (-15.34, -13.37)], male sex [1.97 (1.20,2.73)], good physical activity [-1.55 (-2.35, -0.75)], and smoking [-1.42 (-2.24, -0.59)]. BMI had an inverse association with PCS [-0.19 (-0.26, -0.13)] and a direct association with MCS [0.14 (0.07,0.21)].

CONCLUSION

Individuals with diabetes exhibited reduced QOL scores. Upon adjusting for other variables, it was found that uncontrolled diabetes correlated with decreased PCS scores, whereas controlled diabetes was linked to lower MCS scores. Factors such as depression and being female were identified as contributors to diminished QOL in both physical and mental aspects. These results have the potential to guide healthcare decision-making, facilitating the creation of tailored interventions aimed at improving the QOL for individuals with diabetes, with a specific focus on women and depression.

Stem moisture content prediction model for Larix olgensis based on beta regression

To investigate the longitudinal variation patterns of sapwood, heartwood, bark and stem moisture content along the trunk of artificial Larix olgensis, we constructed mixed effect models of moisture content based on beta regression by combining the effects of sampling plot and sample trees. We used two sampling schemes to calibrate the model, without limiting the relative height (Scheme Ⅰ) and with a limiting height of less than 2 m (Scheme II). The results showed that sapwood and stem moisture content increased gradually along the trunk, heartwood moisture content decreased slightly and then increased along the trunk, and bark moisture content increased along the trunk and then levelled off before increasing. Relative height, height to crown base, stand area at breast height per hectare, age, and stand dominant height were main factors driving moisture content of L. olgensis. Scheme Ⅰ showed the stable prediction accuracy when randomly sampling moisture content measurements from 2-3 discs to calibrate the model, with the mean absolute percentage error (MAPE) of up to 7.2% for stem moisture content (randomly selected 2 discs), and the MAPE of up to 7.4%, 10.5% and 10.5% for sapwood, heartwood and bark moisture content (randomly selected 3 discs), respectively. Scheme Ⅱ was appropriate when sampling moisture content measurements from discs of 1.3 and 2 m height and the MAPE of sapwood, heartwood, bark and stem moisture content reached 7.8%, 11.0%, 10.4% and 7.1%, respectively. The prediction accuracies of all mixed effect beta regression models were better than the base model. The two-level mixed effect beta regression models, considering both plot effect and tree effect, would be suitable for predicting moisture content of each part of L. olgensis well.

Creation of a machine learning-based prognostic prediction model for various subtypes of laryngeal cancer

Depending on the source of the blastophore, there are various subtypes of laryngeal cancer, each with a unique metastatic risk and prognosis. The forecasting of their prognosis is a pressing issue that needs to be resolved. This study comprised 5953 patients with glottic carcinoma and 4465 individuals with non-glottic type (supraglottic and subglottic). Five clinicopathological characteristics of glottic and non-glottic carcinoma were screened using univariate and multivariate regression for CoxPH (Cox proportional hazards); for other models, 10 (glottic) and 11 (non-glottic) clinicopathological characteristics were selected using least absolute shrinkage and selection operator (LASSO) regression analysis, respectively; the corresponding survival models were established; and the best model was evaluated. We discovered that RSF (Random survival forest) was a superior model for both glottic and non-glottic carcinoma, with a projected concordance index (C-index) of 0.687 for glottic and 0.657 for non-glottic, respectively. The integrated Brier score (IBS) of their 1-year, 3-year, and 5-year time points is, respectively, 0.116, 0.182, 0.195 (glottic), and 0.130, 0.215, 0.220 (non-glottic), demonstrating the model's effective correction. We represented significant variables in a Shapley Additive Explanations (SHAP) plot. The two models are then combined to predict the prognosis for two distinct individuals, which has some effectiveness in predicting prognosis. For our investigation, we established separate models for glottic carcinoma and non-glottic carcinoma that were most effective at predicting survival. RSF is used to evaluate both glottic and non-glottic cancer, and it has a considerable impact on patient prognosis and risk factor prediction.