Generalized Linear Mixed Models Research Articles

Assessment of Repetitive Controlled Ovarian Stimulation (COS) Cycles on Oocyte Donors: Impact on Oocyte Quality and Viable Embryo Yield.

The utilization of donor eggs has broadened the options for Assisted Reproductive Technology (ART) among women facing challenges with egg quantity or quality. Given that donors are typically selected from young and fertile individuals, In Vitro Fertilization with egg donation (IVF-ED) tends to exhibit higher rates of implantation, pregnancy, and live births compared to IVF with the woman's own eggs, especially for females over 35years old. This has led to a projected increase in the demand for IVF-ED, surpassing the number of available donors. Consequently, many centers opt to use oocyte donors for multiple cycles. However, the correlation between repeated Controlled Ovarian Stimulation (COS) cycles and the performance of donors in terms of viable blastocyst stage embryo (VEC) or blastocyst embryo rate is not definitively established and remains of interest. This study aims to explore the preimplantation characteristics of embryo development and oocyte maturation status based on the number of donor COS cycles, employing a Generalized Linear Mixed Model (GLMM) framework. The study encompasses 1965 embryo transfer (ET) cycles involving 399 donors who underwent a minimum of two and a maximum of nine controlled ovarian hyperstimulation (COS) cycles. The findings indicate that, with the patient undergoing six or more cycles of ovarian stimulation, despite a 3.9% increase in both maturation and fertilization rates, there is a corresponding decrease of 4.5% in VEC rate and 4.7% in blastulation rates. In essence, an escalating number of donor COS cycles appears to be associated with a disadvantageous reduction in embryo quality.

Estimating software reliability using size-biased modelling

Software testing is an important step in software development where inputs are administered repeatedly to detect bugs present in the software. In this paper, we have considered the estimation of total number of bugs and software reliability as a size-biased sampling problem by introducing the concept of eventual bug size as a latent variable. We have developed a Bayesian generalised linear mixed model (GLMM) using software testing detection data to estimate software reliability and stopping phase. The model uses size-biased approach where the probability of detecting a bug is an increasing function of eventual size of the bug which is as an index for the potential number of inputs that may eventually pass through the bug. We have tested the sensitivity of the reliability estimates by varying the number of inputs and detection probability via a simulation study and have found that the key parameters could be accurately estimated. Further, we have applied our model to two empirical data sets – one from a commercial software and the other from ISRO launch mission software testing data set. The hierarchical modelling approach provides a unified modelling framework that may find applications in other fields (e.g. hydrocarbon explorations) apart from software management.

Assessment of biometrics and stress indicators of the adult Village Weaver birds (Ploceus cucullatus) during breeding and post-breeding seasons in Jos, Nigeria

In this era of climate change, some biological conservationists' concerns are based on seasonal studies that highlight how wild birds' physiological fitness are interconnected with the immediate environment to avoid population decline. We investigated how seasonal biometrics correlated to stress parameters of the adult Village Weavers (Ploceus cucullatus) during breeding and post-breeding seasons of the Weaver birds in Amurum Forest Reserve. Specifically, we explored the following objectives: (i) the seasonal number of birds captured; (ii) whether seasonal baseline corticosterone (CORT), packed cell volume (PCV), and heterophil to lymphocytes ratio (H:L) were sex-dependent; (iii) whether H:L ratio varied with baseline (CORT); (iv) whether phenotypic condition (post-breeding moult) and brood patch varied with baseline (CORT) and H:L ratio; and (v) how body biometrics co-varied birds’ seasonal baseline (CORT), (PCV) and (H:L) ratio. Trapping of birds (May–November) coincided with breeding and post-breeding seasons. The birds (n = 53 males, 39 females) were ringed, morphologically assessed (body mass, wing length, moult, brood patch) and blood collected from their brachial vein was used to assess CORT, PCV and H:L ratio. Although our results indicated more male birds trapped during breeding, the multiple analyses of variance (MANOVA) indicated that the seasonal temperature of the trapping sites correlated (P < 0.05) significantly to baseline (CORT). The general linear mixed model analyses (GLMMs) indicated that the baseline (CORT) also correlated significantly to H:L ratio of the male and female birds. However, PCV correlated significantly to body size of the birds (wing length) and not body mass. Haematological parameters such as the baseline CORT and the H:L ratio as indicators of stress in wild birds. Hence, there is the possibility that the Village Weaver birds suffered from seasonally induced stress under the constrained effect of environmental temperature. Hence, future studies should investigate whether the effect observed is also attributable to other passerine species.

Fire regime attributes shape pre-fire vegetation characteristics controlling extreme fire behavior under different bioregions in Spain

BackgroundDesigning effective land management actions addressed to increase ecosystem resilience requires us to understand how shifting fire regimes are shaping landscapes. In this study, we aim to assess the link between fire regime and pre-fire vegetation biophysical characteristics (type, amount, and structure) in controlling extreme fire behavior across Atlantic-Transition-Mediterranean bioregions in Spain marked by different summer drought conditions and dominant plant regenerative traits. We used remote sensing metrics to estimate fire severity and pre-fire vegetation characteristics in eight study areas recently affected by large and highly severe wildfires under different environmental contexts. Furthermore, to account for fire regime attributes, we retrieved, for each target wildfire, the perimeter of the past wildfires that occurred between 1985 and 2022 and calculated fire recurrence, the time the since last fire (TSLF), and fire severity of previous wildfires (FSPW). The effect of fire regime attributes on pre-fire vegetation was examined using generalized linear mixed models (GLMMs).ResultsDuring the study period, fire recurrence decreased significantly in all bioregions analyzed. Fire severity increased under Atlantic conditions and decreased under Mediterranean environmental context, where the time since the last fire was the highest. Pre-fire fuel type and amount were identified as primary drivers of fire severity, being both strongly modulated by fire regime but following distinct mechanisms depending on the environmental context of each bioregion. In Atlantic sites, more frequent past wildfires of low to moderate fire severity were associated with a greater dominance of fire-prone shrublands with moderate fuel amounts, which increases the risk of severe wildfires. Similar trends occurred in Transition and Mediterranean sites but under the previous occurrence of highly severe wildfires. Specifically, long times after highly severe wildfires (> 30 years) increased fuel amount in conifer-dominated ecosystems in all bioregions analyzed, heightening susceptibility to extreme fire behavior.ConclusionsOur findings highlight that fire-prone ecosystems need adaptative management strategies to mitigate the effects of fire regime changes, but these actions should be specific to the climatic and ecological context.

Neighbors, Pros and Cons: Impact of Intergroup Interactions on the Welfare of Captive Chimpanzee Groups (Pan troglodytes)

Housing different animal groups in close-by facilities is common in wildlife centers. However, the impact on animal welfare is insufficiently studied in the literature. In this study, we analyzed the behavior of two adjacently housed chimpanzee groups to investigate how intergroup interactions may affect their behavior and, thus, their welfare. We recorded occurrences of abnormal and self-directed behaviors, two well-known indicators of stress in chimpanzees. Furthermore, we explored the social responses to said intergroup interactions by recording all inter- and intragroup affiliative and agonistic behaviors. Finally, we measured the number of vigilance occurrences that individuals directed towards other chimpanzees as an indicator of interest. Generalized Linear Mixed Models (GLMMs) were used to assess whether and how social interactions between neighboring groups might influence their behaviors, taking gender, age, group, and intergroup participation into account. Our results suggest that intergroup interactions promoted the occurrence of affiliative behaviors between group members. However, intergroup interactions caused the chimpanzees to exhibit a higher number of abnormal and self-directed behaviors and increased vigilance towards their group members when agonistic intergroup interactions occurred. Thus, adjacent housing does impact the chimpanzees’ behavior and welfare and should be continuously monitored and assessed to promote and maximize welfare.

An evaluation of computational methods for aggregate data meta-analyses of diagnostic test accuracy studies

BackgroundA Generalized Linear Mixed Model (GLMM) is recommended to meta-analyze diagnostic test accuracy studies (DTAs) based on aggregate or individual participant data. Since a GLMM does not have a closed-form likelihood function or parameter solutions, computational methods are conventionally used to approximate the likelihoods and obtain parameter estimates. The most commonly used computational methods are the Iteratively Reweighted Least Squares (IRLS), the Laplace approximation (LA), and the Adaptive Gauss-Hermite quadrature (AGHQ). Despite being widely used, it has not been clear how these computational methods compare and perform in the context of an aggregate data meta-analysis (ADMA) of DTAs.MethodsWe compared and evaluated the performance of three commonly used computational methods for GLMM - the IRLS, the LA, and the AGHQ, via a comprehensive simulation study and real-life data examples, in the context of an ADMA of DTAs. By varying several parameters in our simulations, we assessed the performance of the three methods in terms of bias, root mean squared error, confidence interval (CI) width, coverage of the 95% CI, convergence rate, and computational speed.ResultsFor most of the scenarios, especially when the meta-analytic data were not sparse (i.e., there were no or negligible studies with perfect diagnosis), the three computational methods were comparable for the estimation of sensitivity and specificity. However, the LA had the largest bias and root mean squared error for pooled sensitivity and specificity when the meta-analytic data were sparse. Moreover, the AGHQ took a longer computational time to converge relative to the other two methods, although it had the best convergence rate.ConclusionsWe recommend practitioners and researchers carefully choose an appropriate computational algorithm when fitting a GLMM to an ADMA of DTAs. We do not recommend the LA for sparse meta-analytic data sets. However, either the AGHQ or the IRLS can be used regardless of the characteristics of the meta-analytic data.

The global effects of digestive system cancers worldwide on the COVID-19 pandemic by negative binomial (mixed) regression models

In this study, the main goal is to determine statistically significant relationships between the biggest epidemic problem of last years as the COVID-19 pandemic and digestive system cancers belonging to 168 countries worldwide using generalized linear mixed model (GLMM) and its special case as generalized linear model (GLM) approaches, and to obtain global inferences that will shed light on this pandemic. For this goal, the response variable is “total cases of the COVID-19 pandemic per 100,000 people” until January 14, 2022. The explanatory variables are total number of people suffering from colon and rectum, stomach, lip and oral cavity, esophageal, and nasopharynx cancers belonging to 2019, respectively. In this study, the negative binomial (NB) regression model in GLM using iteratively reweighted least squares (IRLS) algorithm and the NB mixed regression model in GLMM with “countries” taken as “random effects” using Adaptive Gauss-Hermite Quadrature (AGHQ) approximation method at 1, 2, 10, and 20 quadrature points are used for modelling the COVID-19 pandemic and digestive systems cancer data. In this study, by using information criteria, the NB mixed regression model in GLMM under log-link function with 168 countries taken as random effects using AGHQ method at 20 quadrature point is detected as the most appropriate model for the global COVID-19 pandemic and digestive system cancers data.

76 Effect of 0.79% top-dressed arginine supplementation at different gestation periods and seasons on the colostrum composition and productive performance of sows and piglets

Abstract This study aimed to evaluate the effect of supplementation with 0.79% top-dressed arginine (Arg) at different gestation periods and seasons on the productive performance and colostrum composition of sows. A total of 320 sows were divided into 4 feeding groups (80 sows/group) under 2 different seasons (summer and winter): a control group (CO) fed a standard diet and 3 groups supplemented with 0.79% Arg either for the first 35 d of gestation (TRT35), the last 45 d of gestation (TRT45), or the entire gestation period (TRTCOM). Colostrum was collected at farrowing from 12 sows per group per season. Productive performance and individual piglet body weight (BW) were recorded at birth (d 0), d 6 of age, weaning (d 28) and 14 d post-weaning (d 14p). Data were analyzed using a general linear mixed model including diet, season, their interaction, and parity class as fixed factors. At the end of the gestation, sows from the TRTCOM group had a greater BW (P = 0.003) and average daily gain (ADG; P = 0.009) than the CO group. The diet did not influence the number of total born and total born alive piglets. The stillborn % was less in the TRT35 group than CO and TRTCOM groups (P &amp;lt; 0.001). The TRTCOM group had a greater crushed % and hypo-vital % than CO group (P &amp;lt; 0.001). Colostral IgG was reduced in the Arg groups compared with the CO group (P &amp;lt; 0.001) while no differences were found for IgA and IgM between the groups. The BW of pilets at d 0, d 6, d 28 and d 14p and ADGs were not affected by the diet; however, the TRT35 had a reduced % of low-birth BW piglets than CO (P = 0.02). The TRT45 tended to have greater % in low-birth BW piglets than CO (P = 0.051) and greater % in high-birth BW piglets than the other groups (P &amp;lt; 0.001). The sows having the gestation in summer had decreased BW at the beginning of gestation, a greater final BW and ADG (P &amp;lt; 0.001), a lower number of total born (P = 0.003), mummified % but a greater crushed % (P &amp;lt; 0.01). Piglets BW at birth, d 28 and d 14p was greater in winter. Lactose (P = 0.001) and IgG (P &amp;lt; 0.001) were greater in the winter. In conclusion, 0.79% of on top-dressed Arg had a negative effect on the productive performance of the sows during the entire gestation period. Conversely, supplementing Arg during the first 35 d of gestation led to a decrease in the percentage of stillborn and low-birth BW piglets.

Genome wide association analysis reveals the genetic sites of heat resistance in largemouth bass (Micropterus salmoides)

Largemouth bass (Micropterus salmoides) is an important commercially cultured freshwater fish. High temperature is a common challenge encountered in the summer cultivation of largemouth bass. In this study, we conducted a genome-wide association study using general linear models and linear mixed models to identify significant single nucleotide polymorphisms (SNPs) and candidate genes associated with loss of equilibrium (LOE) and weight gain (WG) during high temperature challenge. We collected fin tissue from 353 individuals of largemouth bass exposed to high water temperature (37.5 °C) and performed whole-genome resequencing. Through association analysis, we successfully identified 10 SNPs and 38 candidate genes that were significantly associated with LOE, and four SNPs and 19 candidate genes that were significantly associated with WG. Using quantitative PCR and Western blot, we tested the expression of eight genes related to LOE in heat-sensitive and heat-tolerant individuals, and identified significant differences in the expression of the following five genes: Tmub2, Ngfr, Hgf, Hdac6, and Sypl. For WG, we assessed the expression of three candidate genes, among which Mrc2l displayed significant differences in expression between the high WG group and low WG group. We discuss the functions and potential biological processes of candidate genes for LOE and WG. Our results provide basic genetic information for breeding largemouth bass with high temperature tolerance.

Insecticides may compromise the benefits of tree-crop diversification on arthropod biodiversity in cocoa agroforestry smallholdings

ABSTRACT Arthropods play vital roles in ecosystem functions, yet their distribution is subjected to environmental factors. Hence, this study investigates the impact of habitat features on arthropod communities within cocoa smallholdings under different farming practices: agroforestry and monoculture systems. We conducted arthropod sampling using yellow sticky traps and assessed the habitat features at each plantation twice to capture temporal variations in arthropod populations. The study recorded 2945 individual arthropods belonging to eight different functional groups. The most abundant functional group was saprophagous, followed by phytophagous, parasitoid, predator, mycetophagous, frugivorous, palynivore, and nectarivorous group. Using Generalized Linear Mixed Models (GLMMs), we found that the abundance of phytophagous and predatory arthropods increases with leaf litter, while it decreases with saprophagous arthropods. Our findings suggest that tree-crop diversification within cocoa smallholdings can play a significant role in preserving higher arthropod biodiversity, particularly when these smallholdings remain free from chemical insecticide use. Canopy cover was also found to positively affect the variability of arthropods indicating that it is a crucial factor affecting arthropod biodiversity. This study underscores the significance of integrating agroforestry systems into cocoa production landscapes, particularly those utilizing agrochemicals, to support diverse arthropod communities and promote sustainable cocoa production.

Identifying Risk Indicators of Cardiovascular Disease in Fasa Cohort Study (FACS): An Application of Generalized Linear Mixed-Model Tree.

Today, cardiovascular disease (CVD) is the most important cause of death around the world. In this study, our main aim was to predict CVD using some of the most important indicators of this disease and present a tree-based statistical framework for detecting CVD patients according to these indicators. We used data from the baseline phase of the Fasa Cohort Study (FACS). The outcome variable was the presence of CVD. The ordinary Tree and generalized linear mixed models (GLMM) were fitted to the data and their predictive power for detecting CVD was compared with the obtained results from the GLMM tree. Statistical analysis was performed using the RStudio software. Data of 9499 participants aged 35‒70 years were analyzed. The results of the multivariable mixed-effects logistic regression model revealed that participants' age, total cholesterol, marital status, smoking status, glucose, history of cardiac disease or myocardial infarction (MI) in first- and second-degree relatives, and presence of other diseases (like hypertension, depression, chronic headaches, and thyroid disease) were significantly related to the presence of CVD (P<0.05). Fitting the ordinary tree, GLMM, and GLMM tree resulted in area under the curve (AUC) values of 0.58 (0.56, 0.61), 0.81 (0.77, 0.84), and 0.80 (0.76, 0.83), respectively, among the study population. In addition, the tree model had the best specificity at 81% but the lowest sensitivity at 65% compared to the other models. Given the superior performance of the GLMM tree compared with the standard tree and the lack of significant difference with the GLMM, using this model is suggested due to its simpler interpretation and fewer assumptions. Using updated statistical models for more accurate CVD prediction can result in more precise frameworks to aid in proactive patient detection planning.

Parent SMART: Effects of residential treatment and an adjunctive parenting intervention on behavioral health services utilization

IntroductionScant research has examined the impact of residential treatment on adolescent behavioral healthcare utilization post-discharge, even though behavioral healthcare utilization is major driver of healthcare costs. In the primary analyses of a pilot randomized trial, Parent SMART – a technology-assisted intervention for parents of adolescents in residential treatment – was found to improve parental monitoring and parent-adolescent communication, reduce adolescent drinking, and reduce adolescent school-related problems, relative to residential treatment as usual (TAU). The goal of this secondary analysis of the pilot randomized trial was to assess the effects of residential treatment and the adjunctive Parent SMART intervention on both the amount and type of subsequent behavioral healthcare utilization. MethodThe study randomized sixty-one parent-adolescent dyads to residential TAU (n = 31) or residential TAU plus Parent SMART (n = 30). Of the 61 dyads, 37 were recruited from a short-term residential facility and 24 were recruited from a long-term facility. Adolescents completed a structured clinical interview and self-reported their behavioral health-related visits to the emergency department, nights in residential/inpatient, and outpatient visits over the past 90 days, at baseline, 12-, and 24-weeks post-discharge. Generalized linear mixed models (GLMMs) examined both linear and non-linear (pre- to post- residential treatment) trends, pooled, and stratified by residential facility to examine behavioral health service utilization. ResultsBoth the linear and pre-post GLMMs revealed that behavioral health-related emergency department visits and residential/inpatient nights decreased across both residential facilities. GLMMs estimating change from the pre- to post period indicated that outpatient visits increased across both facilities. There were no significant effects of the Parent SMART adjunctive intervention in GLMMs, though bivariate tests and the direction of effects signaled that Parent SMART was associated with more nights of residential/inpatient utilization. ConclusionResidential substance use treatment may reduce adolescents' subsequent utilization of costly behavioral healthcare services such as emergency department visits and residential/inpatient nights, while increasing utilization of outpatient services. Parent SMART was not associated with significant changes in behavioral healthcare utilization, but the pattern of results was consistent with prior literature suggesting that stronger parenting skills are associated with greater utilization of non-emergency services.

Tacklers' shoulder abduction and flexion at contact alter when engaging in different front-on, one-on-one tackle instructions from an expert coach

ObjectivesTo ascertain how the three-dimensional shoulder kinematics of tacklers alter when performing four legal types of front-on, one-on-one, rugby-style torso tackles. DesignControlled laboratory study. MethodsThree-dimensional motion capture measured the movements of 15 male amateur-level rugby code players (24.3 ± 6.1 years) who were instructed by an expert coach to perform four sets of 10 front-on, one-on-one tackles. Four sets comprised two smother and two dominant tackles: two based on the Australian National Rugby League coaching manual (Dominant NRL, Smother NRL); and two modifications via increasing the contact height from the lower- to mid-torso (Dominant, Torso Stick) or from the upper- to mid-upper torso with a vertical ‘pop action’ that changes the way the tackler contacted the ball carrier's upper torso (Smother, Pop, Lock). Mixed general linear models were applied. ResultsGreater shoulder abduction, flexion and internal rotation were displayed by the Dominant NRL tackle technique than in any other technique (p < 0.001). At contact, the Smother NRL and Dominant NRL (p < 0.03) showed greater head–uptrunk contralateral rotation away from the tackle than the Smother, Pop, Lock. ConclusionsTacklers modified the way they positioned their shoulder joint when engaging in legal front-on, one-on-one tackles with different tackle instructions. More prominent positions of shoulder abduction and flexion, as well as head–uptrunk contralateral rotation were observed when executing the traditional tackle techniques (Smother NRL, Dominant NRL) as opposed to two variants of these (Smother, Pop, Lock and Dominant, Torso Stick). Inclusion of tackle specific coaching instructions provides emerging scientific evidence to support revised coaching tackling technique interventions that might enhance player safety.

Income, aging, and the gendered patterns of wellness: Physical health and subjective well-being in China

This article investigates the impact of demographic and socioeconomic inequalities on wellness, composed of both physical health and subjective well-being. We examine how gender inequality moderates the joint effects of aging and income on wellness in China. Utilizing generalized linear mixed model (GLMM), we analyze data from the Chinese General Social Survey (CGSS) spanning from 2003 to 2021. Our results reveal that income inequality disproportionately affects physical health among older, underweight, lower-class females; males are more susceptible to negative impacts on subjective well-being, particularly among lower-class, middle-aged males. These gendered patterns are situated in the contemporary Chinese society and are explained in relation to intra-household distributional inequality and the gender role expectations in the Confucian culture. We also discussed the policy implications of how to reduce the gaps in wellness across social classes, age cohorts, and genders.

Effectiveness of the Integrated Dengue Education and Learning (iDEAL) module in improving the knowledge, attitude, practice, environmental cleanliness index, and dengue index among schoolchildren: A randomised controlled trial protocol.

Dengue is a mosquito-borne disease caused by four distinct, closely related dengue viruses (DENV). Global dengue incidence has markedly increased in the past decades. The World Health Organization reported that cases increased from 505,430 in 2000 to 5.2 million in 2019. Similarly, the total dengue cases in Malaysia increased from 7,103 in 2000 to a peak of 130,101 in 2019. Knowledge, attitude, and practice (KAP) remain the most effective dengue prevention and control tools. Furthermore, school-based health education is key to enhancing knowledge and raising awareness of the seriousness of dengue among schoolchildren and transferring knowledge and practice from classrooms to homes. Thus, it is necessary to plan an integrated module for the primary prevention of dengue infection, specifically among schoolchildren. The present study intends to develop, implement, and evaluate the effectiveness of a theory-based integrated dengue education and learning (iDEAL) module in improving the KAP, environmental cleanliness index, and dengue index among schoolchildren in Selangor and Kuala Lumpur. This study is a single-blinded, cluster randomised controlled trial to be conducted from 1 September 2023 to 31 August 2025. The study will involve 20 primary and 20 secondary schools in Selangor and Kuala Lumpur. The 1600 participants will be randomly allocated to intervention and control groups based on selected clusters to avoid contamination. A cluster is a comparable school that fulfils the inclusion and exclusion criteria. The intervention group will receive the iDEAL module, while the control group will receive standard education. The iDEAL module will be developed following a systematic procedure and delivered in-person by trained researchers to the participants. The outcome will be measured using validated, self-administered questionnaires at baseline (T0), immediately (T1), one month (T2), and three months (T3) post-intervention to measure the intervention module effectiveness. The data will be analysed using IBM Statistical Package for Social Science (SPSS) version 28 and descriptive and inferential statistics. Within-group changes over time will be compared using one-way repeated measure analysis of variance for continuous and normally distributed variables. Within-group analysis of categorical data will use Cochran's Q test. The main effect and interaction between and within the intervention and control groups at T0, T1, T2, and T3 will be tested using the generalised linear mixed model (GLMM). Hypothetically, the KAP, environmental cleanliness index, and dengue index among the intervention group will be significantly improved compared to the control group. The hypothesis will be tested using a significance level with a p-value of 0.05 and a confidence interval of 95%. The study protocol outlines developing and testing an iDEAL module for schoolchildren in Selangor and Kuala Lumpur, with no socio-demographic differences expected. The intervention aims to improve KAP, environmental cleanliness index, and dengue index, potentially reducing dengue risk. Results could inform public health policies, emphasizing school-based interventions' importance in combating diseases like dengue.

Early predictor for differentiation syndrome in newly diagnosed acute promyelocytic leukaemia patients treated with single-agent arsenic trioxide.

Differentiation syndrome (DS) is the second leading cause of death in acute promyelocytic leukaemia (APL) patients. Few studies have tested predictors of DS events. This study aimed to identify optimized predictorsofDS events related to APL. The data of 298 consecutive patients who were newly diagnosed with APL between December 2012 and June 2023 were retrospectively investigated. A systematic review of computer-based patient medical records was conducted to obtain clinical data, including baseline characteristics, routine blood examination findings, biochemical indices and clinical manifestations of DS. Among the 298 patients, 158 were classified into the no-DS group, while 140 had DS. Compared with those of patients without DS, the peripheral blast count, age, and WBC count at each time point were significantly different in patients with DS (P < 0.05 for all time points). Generalized linear mixed models (GLMMs) revealed that WBC Double (Coeff. 0.442, P = 0.000) and WBCPeak (Coeff. 0.879, P = 0.000) were independent risk factors for DS. The frequencies of clinical manifestations of unexplained fever (P = 0.003), dyspnoea (P = 0.002), weight gain of more than 5kg (P = 0.006), pleural effusion (P = 0.001), pulmonary infiltrates (P < 0.001), pericardial effusion (P = 0.002) and renal failure (P = 0.006) were considerably lower in moderate DS patients than in severe DS patients. The WBCDouble occurs earlier than the WBCpeak occurrence, so WBCDouble might be a new indicator of DS.

A Chinese patent medicine's long-term efficacy on non-dialysis patients with CKD stages 3-5: a retrospective cohort study.

Chinese patent medicine is commonly used in China as an important treatment mechanism to thwart the progression of chronic kidney disease (CKD) stages 3-5, among which Niaoduqing granules are a representative Chinese patent medicine; however, its long-term efficacy on CKD prognosis remains unclear. Patients were grouped according to Niaoduqing granule prescription duration (non-Niaoduqing granule (non-NDQ) group vs Niaoduqing granule (NDQ) group). Serum creatinine (SCr) variation was compared using a generalized linear mixed model (GLMM). Multivariate Cox regression models were constructed, adjusting for confounding factors, to explore the risk of composite outcomes (receiving renal replacement therapy (RRT) or having an estimated glomerular filtration rate (eGFR)<5mL/min/1.73 m2, ≥50% decline in the eGFR from the baseline, and doubling of SCr) in individuals consuming Niaoduqing granules. A total of 1,271 patients were included, with a median follow-up duration of 29.71 (12.10, 56.07) months. The mean SCr Z-scores for the non-NDQ group and NDQ group were -0.175 and 0.153, respectively, at baseline (p = 0.015). The coefficients of the NDQ group from visit 1 to visit 5 were -0.207 (95% CI: -0.346, -0.068, p = 0.004), -0.214 (95% CI: 0.389, -0.039, p = 0.017), -0.324 (95% CI: 0.538, -0.109, p = 0.003), -0.502 (95% CI: 0.761, -0.243, p = 0.000), and -0.252 (95% CI: 0.569, 0.065, p = 0.119), respectively. The survival probability was significantly higher in the NDQ group (p = 0.0039). Taking Niaoduqing granules was a significant protective factor for thwarting disease progression (model 1: HR 0.654 (95% CI 0.489-0.875, p = 0.004); model 2: HR 0.646 (95% CI 0.476, 0.877, p = 0.005); and model 3: HR 0.602 (95% CI 0.442, 0.820, p = 0.001)). The long-term use of Niaoduqing granules improved SCr variation and lowered the risk of CKD progression by 39.8%.

Trends and determinants of mental illness in humanitarian migrants resettled in Australia: Analysis of longitudinal data.

Given the frequent exposure of humanitarian migrants to traumatic or stressful circumstances, there exists a potential predisposition to mental illness. Our objective was to pinpoint the trends and determinants of mental illness among humanitarian migrants resettled in Australia. This study considered five waves of longitudinal data involving humanitarian migrants resettled in Australia. Post-traumatic stress disorder (PTSD) and psychological distress were assessed using PTSD-8 and Kessler-6 screening tools. Through a Generalised Linear Mixed model (GLMM), variables displaying a 95% CI that excluded the value of 1.0 for the odds ratio were identified as associated factors for both PTSD and elevated psychological distress. The selection of multivariable covariates was guided by causal loop diagrams and least absolute shrinkage and selection operators methods. At baseline, there were 2399 humanitarian migrants with 1881 retained and at the fifth yearly wave; the response rate was 78.4%. PTSD prevalence decreased from 33.3% (95% CI: 31.4-35.3) at baseline to 28.3% (95% CI: 26.2-30.5) at year 5. Elevated psychological distress persisted across all waves: 17.1% (95% CI: 15.5-18.6) at baseline and 17.1% (95% CI: 15.3-18.9) at year 5. Across the five waves, 34.0% of humanitarian migrants met screening criteria for mental illness, either PTSD or elevated psychological distress. In the multivariate model, factors associated with PTSD were loneliness (AOR 1.5, 95% CI: 1.3-1.8), discrimination (AOR 1.6: 1.2-2.1), temporary housing contract (AOR 3.7: 2.1-6.7), financial hardship (AOR 2.2:1.4-3.6) and chronic health conditions (AOR 1.3: 1.1-1.5), whereas the associated factors for elevated psychological distress were loneliness (AOR 1.8: 1.5-2.2), discrimination (AOR 1.7: 1.3-2.2) and short-term lease housing (AOR 1.6: 1.0-1.7). The prevalence, persistence and consequential burden of mental illness within this demographic underscore the urgent need for targeted social and healthcare policies. These policies should aim to mitigate modifiable risk factors, thereby alleviating the significant impact of mental health challenges on this population.

Maladaptive defense mechanisms moderate treatment outcome in 6 months versus 12 months dialectical-behavior therapy for borderline personality disorder

Objective We investigated whether defense mechanisms in patients with borderline personality disorder (BPD) predict treatment response of dialectical behavior therapy (DBT) and whether they moderate outcome in different treatment lengths. Method We analyzed a subsample of 60 outpatients with BPD, randomized into either 6 (n = 30) or 12 (n = 30) months of DBT. The average level of defensive adaptiveness, assessed with observer-rated overall defensive functioning (ODF) and “immature” (i.e., maladaptive) defenses were used as predictors and moderators of self-reported frequency of self-harm. We conducted a Generalized Linear Mixed Model (GLMM). Results A lower ODF at treatment onset predicted smaller reductions in self-harm, irrespective of treatment length (IRR = 0.92, 95% CI = [0.86, 0.99], p = .020). Lower order “immature” (“major image distorting”) defenses showed significantly smaller (IRR = 1.13, 95% CI = [1.06, 1.21], p < .001) and higher order “immature” (“minor image distorting”) defenses showed significantly larger (IRR = .91, 95% CI = [.85, .97], p = .006) reductions in self harm in the 6-month but not in the 12-month treatment. Conclusion Even though the results have to be regarded as preliminary due to the small sample size, findings might indicate that patients with BPD and lower average defensive adaptiveness may benefit from individualized treatment plans including specific interventions targeting defense function.

Self-Rated Confidence in Vocal Emotion Recognition Ability: The Role of Gender.

We studied the role of gender in metacognition of voice emotion recognition ability (ERA), reflected by self-rated confidence (SRC). To this end, we guided our study in two approaches: first, by examining the role of gender in voice ERA and SRC independently and second, by looking for gender effects on the ERA association with SRC. We asked 100 participants (50 men, 50 women) to interpret a set of vocal expressions portrayed by 30 actors (16 men, 14 women) as defined by their emotional meaning. Targets were 180 repetitive lexical sentences articulated in congruent emotional voices (anger, sadness, surprise, happiness, fear) and neutral expressions. Trial by trial, the participants were assigned retrospective SRC based on their emotional recognition performance. A binomial generalized linear mixed model (GLMM) estimating ERA accuracy revealed a significant gender effect, with women encoders (speakers) yielding higher accuracy levels than men. There was no significant effect of the decoder's (listener's) gender. A second GLMM estimating SRC found a significant effect of encoder and decoder genders, with women outperforming men. Gamma correlations were significantly greater than zero for women and men decoders. In spite of varying interpretations of gender in each independent rating (ERA and SRC), our results suggest that both men and women decoders were accurate in their metacognition regarding voice emotion recognition. Further research is needed to study how individuals of both genders use metacognitive knowledge in their emotional recognition and whether and how such knowledge contributes to effective social communication.