Predictors Of Effects Research Articles

Outcomes and Predictors of Response to Pregabalin for the Treatment of Post-Traumatic Trigeminal Neuropathic Pain Following Neuroablative Procedures: A Retrospective Observational Study

BACKGROUND: Post-traumatic trigeminal neuropathic pain (PTNP) following trigeminal neuralgia (TN)-related neuroablative procedures is relatively rare. Due to the fear of debilitating complications, its treatment has been generally suboptimal. Pregabalin (PGB) has been reported to relieve neuropathic pain. However, the potential role of PGB and the predictors of response of PGB use as a strategy in the treatment of PTNP following TN-related neuroablative procedures have not been identified yet. OBJECTIVES: To report the efficacy and safety of PGB and the identification of predictors of PGB for PTNP following TN-related neuroablative procedures. STUDY DESIGN: Monocentric, retrospective, observational study. SETTING: This study consecutively enrolled patients with PTNP following TN-related neuroablative procedures who were prescribed PGB at Beijing Tiantan Hospital. METHODS: From January 2018 to June 2022, a total of 112 patients were included in this study, of whom 10 were excluded because of incomplete follow-up data and side effects immediately after taking PGB. Final analysis included 102 patients. Demographic data, pain-related baseline data, efficacy of patients with PTNP after one month of PGB evaluated by the Barrow Neurological Institute (BNI) scores for pain, and side effects of PGB were extracted and analyzed. The predictors of pain-relieving effects of PGB were identified by logistic regression analysis. RESULTS: Within one month after the use of PGB alone, 29 out of the 102 (28.4%) patients achieved pain relief with a significant reduction in the BNI scores (P < 0.01). All of the 73 patients who did not respond to PGB monotherapy either switched to other medications (n = 8) or combined additional oral medications to the existing PGB therapy (n = 65). The main side effect of PGB in our study was dizziness. Binary logistic regression analysis showed that longer disease durations (Adjusted odds ratio [OR] = 0.55, 95% confidence interval [CI] 0.43 to 0.72, P = 0.000) and higher Hospital Anxiety and Depression Scale (HADS) scores (Adjusted OR = 0.29, 95% CI 0.10 to 0.87, P = 0.022) were poor predictors of response to PGB. LIMITATIONS: This was a retrospective observational study. Long-term efficacy and safety of PGB in the treatment of PTNP patients were not evaluated. CONCLUSIONS: This study confirms that PGB monotherapy is not a very effective treatment for PTNP following TN-related neuroablative procedures. PGB was more beneficial in patients with shorter disease durations and lower HADS scores. KEY WORDS: Post-traumatic trigeminal neuropathic pain, efficacy, safety, predictor of response, pregabalin

Exploring Potential Predictors of Treadmill Training Effects in People With Parkinson Disease

ObjectiveTo explore the potential predictors of people with Parkinson disease (PD) who would benefit the most from treadmill training. DesignA cohort study. SettingMedical university rehabilitation settings. ParticipantsSeventy participants diagnosed of idiopathic PD. InterventionsTwelve sessions of treadmill training. Main Outcome MeasuresHierarchical logistic regression models were used to explore significant predictors of the treadmill training effect with respect to 3 health domains: Unified Parkinson's Disease Rating Scales part III (UPDRS III); gait speed; Parkinson's Disease Questionnaire-39 (PDQ-39). A receiver operating characteristic (ROC) curve analysis was conducted to identify proper cut-off points for clinical use. ResultsMale sex (adjusted odds ratio [OR]: 3.73, P=.036) significantly predicted the improvement of UPDRS III. Individuals with a slower baseline gait speed (cut-off: 0.92 m/s, adjusted OR: 14.06, P<.001) and higher baseline balance confidence measured by the Activity-specific Balance Confidence scale (cut-off: 84.5 points, adjusted OR: 4.66, P=.022) have greater potential to achieve clinically relevant improvements in gait speed. A poorer baseline PDQ-39 score (cut-off: 23.1, adjusted OR: 7.47, P<.001) predicted a greater quality of life improvement after treadmill training. ConclusionsThese findings provide a guideline for clinicians to easily identify suitable candidates for treadmill training. Generalization to more advanced patients with PD warrants further investigation.

Plant genus is a better predictor of plant effects on soil biotic and abiotic properties than plant invasion status

Plant genus is a better predictor of plant effects on soil biotic and abiotic properties than plant invasion status

Immunological Biomarkers as Predictors of Treatment Response in Psychotic Disorders.

Psychotic disorders, notably schizophrenia, impose a detrimental burden on both an individual and a societal level. The mechanisms leading to psychotic disorders are multifaceted, with genetics and environmental factors playing major roles. Increasing evidence additionally implicates neuro-inflammatory processes within at least a subgroup of patients with psychosis. While numerous studies have investigated anti-inflammatory add-on treatments to current antipsychotics, the exploration of immunological biomarkers as a predictor of treatment response remains limited. This review outlines the current evidence from trials exploring the potential of baseline inflammatory biomarkers as predictors of the treatment effect of anti-inflammatory drugs as add-ons to antipsychotics and of antipsychotics alone. Several of the studies have found correlations between baseline immunological biomarkers and treatment response; however, only a few studies incorporated baseline biomarkers as a primary endpoint, and the findings thus need to be interpreted with caution. Our review emphasizes the need for additional research on the potential of repurposing anti-inflammatory drugs while utilizing baseline inflammatory biomarkers as a predictor of treatment response and to identify subgroups of individuals with psychotic disorders where add-on treatment with immunomodulating agents would be warranted. Future studies investigating the correlation between baseline inflammatory markers and treatment responses can pave the way for personalized medicine approaches in psychiatry centred around biomarkers such as specific baseline inflammatory biomarkers in psychotic disorders.

Predictors of the response to phosphodiesterase-5 inhibitors in pulmonary arterial hypertension: an analysis of the Spanish registry

BackgroundAchieving and maintaining a low-risk profile is associated with favorable outcome in pulmonary arterial hypertension (PAH). The effects of treatment on risk profile are variable among patients.ObjectiveTo Identify variables that might predict the response to treatment with phosphodiesterase-5 inhibitors (PDE-5i) in PAH.MethodsWe carried out a cohort analysis of the Spanish PAH registry in 830 patients diagnosed with PAH that started PDE5i treatment and had > 1 year follow-up. 644 patients started PDE-5i either in mono- or add-on therapy and 186 started combined treatment with PDE-5i and endothelin receptor antagonist (ERA). Responders were considered when at 1 year they: (1) were alive; (2) did not present clinical worsening; and (3) improved European Society of Cardiology/European Respiratory Society (ESC/ERS) risk score or remained in low-risk. Univariate and multivariate logistic regression models were used to analyze variables associated with a favorable response.ResultsTwo hundred and ten patients (33%) starting PDE-5i alone were classified as responders, irrespective of whether it was mono- or add-on therapy. In addition to known predictors of PAH outcome (low-risk at baseline, younger age), male sex and diagnosis of portopulmonary hypertension (PoPH) or HIV-PAH were independent predictors of favorable response to PDE-5i. Diffusing capacity for carbon monoxide (DLco) ≤ 40% of predicted was associated with an unfavorable response. When PDE-5i were used in upfront combination, 58% of patients were responders. In this group, diagnosis of idiopathic PAH (IPAH) was an independent predictor of favorable response, whereas connective tissue disease-PAH was associated with an unfavorable response.ConclusionMale sex and diagnosis of PoPH or HIV-PAH are predictors of favorable effect of PDE-5i on risk profile when used as mono- or add-on therapy. Patients with IPAH respond more favorably to PDE-5i when used in upfront combination. These results identify patient profiles that may respond favorably to PDE-5i in monotherapy and those who might benefit from alternative treatment strategies.

Effects of microplastics exposure on soil inorganic nitrogen: A comprehensive synthesis

Microplastics, a growing environmental concern, impact soil inorganic nitrogen (N) transformation, specifically affecting water-extractable nitrate N (NO3−−N) and ammonium N (NH4+−N). However, inconsistencies among relevant findings necessitate a systematic analysis. Accordingly, the present meta-analysis addresses these discrepancies by evaluating the effects of microplastics on soil inorganic N and identifying key influencing factors. Our meta-analysis of 216 paired observations from 47 studies demonstrates microplastics exposure causes an overall significant reduction of 7.89% in soil NO3−−N concentration, but has no significant impact on NH4+−N concentration. Subgroup analysis further revealed effects of microplastics on soil inorganic N were modulated by microplastics characteristics, experimental conditions (exposure time, experimental temperature, plant effects), and soil properties (soil texture, initial soil pH, initial soil organic carbon, soil total N concentration). We found that microplastics exposure above 27 ℃ enhances soil NO3−−N concentration, a finding linked to specific soil properties and conditions, underscoring the impacts of global warming. Importantly, the microplastics polymer type was the most influential predictor of effects on soil NO3−−N concentration, while soil NH4+−N concentration was primarily affected by soil texture and microplastics type. These findings illuminate the complex effects of microplastics on soil inorganic N, informing soil management amid increasing microplastics pollution.

Multimodal learning of noncoding variant effects using genome sequence and chromatin structure.

A growing amount of noncoding genetic variants, including single-nucleotide polymorphisms, are found to be associated with complex human traits and diseases. Their mechanistic interpretation is relatively limited and can use the help from computational prediction of their effects on epigenetic profiles. However, current models often focus on local, 1D genome sequence determinants and disregard global, 3D chromatin structure that critically affects epigenetic events. We find that noncoding variants of unexpected high similarity in epigenetic profiles, with regards to their relatively low similarity in local sequences, can be largely attributed to their proximity in chromatin structure. Accordingly, we have developed a multimodal deep learning scheme that incorporates both data of 1D genome sequence and 3D chromatin structure for predicting noncoding variant effects. Specifically, we have integrated convolutional and recurrent neural networks for sequence embedding and graph neural networks for structure embedding despite the resolution gap between the two types of data, while utilizing recent DNA language models. Numerical results show that our models outperform competing sequence-only models in predicting epigenetic profiles and their use of long-range interactions complement sequence-only models in extracting regulatory motifs. They prove to be excellent predictors for noncoding variant effects in gene expression and pathogenicity, whether in unsupervised "zero-shot" learning or supervised "few-shot" learning. Codes and data can be accessed at https://github.com/Shen-Lab/ncVarPred-1D3D and https://zenodo.org/record/7975777.

Electrocardiographic Morphology-Voltage-P-Wave-Duration (MVP) Score to Select Patients for Continuous Atrial Fibrillation Screening to Prevent Stroke

Morphology-voltage-P-wave-duration (MVP) score combining P-wave duration (PWD), P-wave voltage in lead I (PWVI), and interatrial block (IAB) has been demonstrated to predict atrial fibrillation (AF). Therefore, this study aimed to examine MVP score and its P-wave components as potential predictors of AF screening effects on stroke prevention. This was a secondary analysis of the LOOP Study (Atrial Fibrillation detected by Continuous ECG Monitoring using Implantable Loop Recorder to prevent Stroke in High-risk Individuals) which randomized older persons (aged 70 to 90years) with additional stroke risk factors to either continuous monitoring with implantable loop recorder and anticoagulation upon detection of AF episodes ≥6minutes (the intervention group), or usual care. A total of 5,759 participants were included in the present analysis, where PWD, PWVI, and IAB were determined through a computerized analysis of 12-lead electrocardiogram and further employed to calculate baseline MVP score (0 to 6) for each participant. In total, 305 (5.3%) had stroke or systemic embolism during follow-up, with a higher risk in the group with MVP score 5 to 6 than those having score 0 to 2 (hazard ratio (HR) 1.54 [95% confidence interval (CI) 1.01 to 2.35]). This risk increase was mainly upheld by participants with IAB (HR 1.62 [95% CI 1.11 to 2.36] for IAB vs no IAB) and with longer PWD (HR 1.37 [95% CI 1.07 to 1.75] for >110 vs ≤110ms). Compared with usual care, implantable loop recorder screening did not significantly reduce the risk of stroke or systemic embolism in any MVP risk categories (HR 0.80 [95% CI 0.60 to 1.08] for MVP score 0 to 2, 0.54 [95% CI 0.16 to 1.85] for MVP score 3 to 4, and 0.89 [95% CI 0.35 to 2.25] for MVP score 5 to 6; pinteraction=0.78). In conclusion, a higher MVP score was associated with an increased stroke risk, but it did not demonstrate an association with effects of AF screening on stroke prevention. These findings should be considered hypothesis-generating and warrant further study.

Under What Conditions Can People With Severe Dementia in Nursing Homes Benefit From a Multicomponent Psychosocial Intervention?

The majority of psychosocial interventions are considered effective in the treatment of dementia symptoms. However, there are hardly any evaluated concepts for people with severe dementia. An RCT study of patients with severe dementia in nursing homes during the Covid-19 pandemic found no effect of the newly developed multi-component intervention MAKS-s (motor, activities of daily living, cognitive, social version for persons with severe dementia) on patients' quality of life, behavioural and psychological symptoms. At the end of the controlled phase, 6 months after beginning of the study, the nursing staff of the control groups were also trained in MAKS-s. They were then free to decide whether and how often they wanted to use MAKS-s (open phase). By means of a written follow-up survey, conducted with trained therapists, after another 6 months, predictors for positive effects of the intervention on people with severe dementia were to be identified. The survey also aimed to identify predictors of therapy fidelity. Data acquisition based on a self-developed questionnaire, assessing the therapists' subjective ratings of the three areas of structure, process and outcome quality of the MAKS-s intervention. Apart from descriptive evaluations, the predictors of benefit for people with severe dementia were analysed using a linear regression model and the predictors of therapy fidelity by using a binary logistic regression model. The more pronounced the normative restrictions due to the Covid-19 pandemic were, the more frequently manual deviations were observed. Fewer deviations from the manual were significantly associated with positive effects on people with severe dementia. The results indicate the importance of therapy fidelity for the success of MAKS-s intervention. Therapy fidelity is decisive for the extent of the positive effects of MAKS-s, experienced by the therapists. Furthermore, the survey results show that activity-restricting pandemic policies in nursing homes negatively influenced the perceived effectiveness.

Explaining Trust Divergence: Bifurcations in a Dynamic System

When people experience the same automation, their trust in automation can diverge. Prior research has used individual differences—trust propensity and complacency—to explain this divergence. We argue that bifurcation as an outcome of a dynamic system better explains trust divergence. Linear mixed-effect models were used to identify features to predict trust (i.e., individual differences, automation reliability, and exposure). Individual differences associated with trust propensity and complacency increases the R2 of the baseline model by 0.01, from R2 = 0.40 to 0.41. Furthermore, the Best Linear Unbiased Predictors (BLUPS) for random effect of participants were uncorrelated with trust propensity and complacency. In contrast, modeling trust divergence from a dynamic perspective, which considers the interaction between reliability and exposure along with the individual by-reliability variability fit the data well ( R2 = 0.84). These results suggest dynamic interaction with automation produce trust divergence and design should focus on state dependence and responsivity.

First-pass effect of mechanical thrombectomy for anterior circulation large vessel occlusion: incidence, predictors, and clinical impact. Insight from the ANGEL-ACT registry.

The objective of this study was to investigate the incidence and predictors of first-pass effect (FPE) and to compare the clinical outcomes among FPE, multiple-pass effect, and incomplete reperfusion (ICR) in acute anterior circulation large vessel occlusion. Patients from the ANGEL-ACT (Endovascular Treatment Key Technique and Emergency Workflow Improvement of Acute Ischemic Stroke) registry were included. FPE was defined as complete reperfusion after a single pass of the thrombectomy device without rescue treatment. MPE was defined as complete reperfusion after ≥ 2 passes of the thrombectomy device. ICR was defined as a modified Thrombolysis in Cerebral Infarction score of 2b independent of the number of passes. Multivariable analyses were used to determine predictors of FPE and to compare the following outcomes: functional independence, mortality within 90 days, intraprocedural complications, and intracranial hemorrhage (ICH) among FPE, MPE, and ICR. There were 1139 patients, of whom 307 (27.0%) achieved FPE. FPE was related to occlusion location (M1 vs internal carotid artery [ICA], adjusted OR [aOR] 1.57, 95% CI 1.15-2.15, p = 0.004; M2/anterior cerebral artery vs ICA, aOR 2.06, 95% CI 1.32-3.22, p = 0.002) and negatively associated with underlying intracranial atherosclerosis disease (ICAD) (aOR 0.33, 95% CI 0.23-0.49, p < 0.001). Patients with FPE had a higher rate of functional independence (52.7% of FPE patients vs 45.6% of MPE patients and 37.1% of ICR patients, p = 0.002; MPE vs FPE, aOR 0.69, 95% CI 0.51-0.95, p = 0.023; ICR vs FPE, aOR 0.45, 95% CI 0.31-0.66, p < 0.001), lower rate of intraprocedural complications (4.2% vs 18.1% and 21.2%, p < 0.001; MPE vs FPE, aOR 6.23, 95% CI 3.36-11.54, p < 0.001; ICR vs FPE, aOR 7.70, 95% CI 3.97-14.94, p < 0.001), and lower rate of ICH within 24 hours (18.3% vs 27.9% and 26.9%, p = 0.009; MPE vs FPE, aOR 1.97, 95% CI 1.35-2.86, p < 0.001; ICR vs FPE, aOR 2.03, 95% CI 1.30-3.16, p = 0.002) than those with MPE and ICR. FPE was achieved at a rate of 27.0% and associated with functional independence, decreased intraprocedural complications, and ICH. Non-ICA occlusion and underlying ICAD were predictors of FPE.

Assessing the utility of magnetic resonance imaging-based "SuStaIn" disease subtyping for precision medicine in relapsing-remitting and secondary progressive multiple sclerosis.

Patient stratification and individualized treatment decisions based on multiple sclerosis (MS) clinical phenotypes are arbitrary. Subtype and Staging Inference (SuStaIn), a published machine learning algorithm, was developed to identify data-driven disease subtypes with distinct temporal progression patterns using brain magnetic resonance imaging; its clinical utility has not been assessed. The objective of this study was to explore the prognostic capability of SuStaIn subtyping and whether it is a useful personalized predictor of treatment effects of natalizumab and dimethyl fumarate. Subtypes were available from the trained SuStaIn model for 3 phase 3 clinical trials in relapsing-remitting and secondary progressive MS. Regression models were used to determine whether baseline SuStaIn subtypes could predict on-study clinical and radiological disease activity and progression. Differences in treatment responses relative to placebo between subtypes were determined using interaction terms between treatment and subtype. Natalizumab and dimethyl fumarate reduced inflammatory disease activity in all SuStaIn subtypes (all p < 0.001). SuStaIn MS subtyping alone did not discriminate responder heterogeneity based on new lesion formation and disease progression (p > 0.05 across subtypes). SuStaIn subtypes correlated with disease severity and functional impairment at baseline but were not predictive of disability progression and could not discriminate treatment response heterogeneity.

Study protocol: effects of treatment expectation toward repetitive transcranial magnetic stimulation (rTMS) in major depressive disorder—a randomized controlled clinical trial

BackgroundPatients’ expectations toward any given treatment are highly important for the effectiveness of such treatment, as has been demonstrated for several disorders. In particular, in major depressive disorder (MDD), one of the most frequent and most serious mental disorders with severe consequences for the affected, the augmentation of available treatment options could mean a ground-breaking success. Repetitive transcranial magnetic stimulation (rTMS), a new, non-invasive, and well-tolerated intervention with proven effects in the treatment of MDD, appears particularly suitable in this context as it is assumed to exert its effect via structures implicated in networks relevant for both expectation and depression.MethodsAll patients will receive rTMS according to its approval. Half of the patients will be randomized to a psychological intervention, which is a comprehensive medical consultation aiming to improve positive treatment expectations; the control group will receive a conventional informed consent discussion (in the sense of a treatment-as-usual condition). As outcome parameters, instruments for both self-assessment and external assessment of depression symptoms will be applied. Furthermore, psycho-immunological parameters such as inflammation markers and the cortisol awakening response in saliva will be investigated. Resting-state functional magnetic resonance imaging (rs fMRI) will be performed to analyze functional connectivity, including the cerebellum, and to identify neuronal predictors of expectation effects. In addition, possible cerebellar involvement will be assessed based on a cerebellar-dependent motor learning paradigm (i.e., eyeblink conditioning).DiscussionIn this study, the effects of treatment expectations towards rTMS are investigated in patients with MDD. The aim of this study is to identify the mechanisms underlying the expectation effects and, beyond that, to expand the potential of non-invasive and well-tolerated treatments of MDD.Trial registrationGerman Registry of Clinical Studies (DRKS DRKS00028017. Registered on 2022/03/07. URL: https://www.drks.de/drks_web/.

Investigation of the efficacy of the change ratio of brain natriuretic peptide for predicting the cardiac effects of chemoradiotherapy on esophageal cancer.

The aim of this study was to investigate the effectiveness of brain natriuretic peptide (BNP) as a predictor of radiological effects on the heart. A total of 41 patients with esophageal cancer who underwent chemoradiotherapy (CRT) were retrospectively investigated. The BNP levels were measured on the first day of CRT (pre-CRT) and the last day of CRT (post-CRT), and the median concentration of BNP and dosimetric parameters of the heart were calculated. The change ratio of BNP was calculated as follows: [(BNP post-CRT) - (BNP pre-CRT)]/(BNP pre-CRT). The comparison of BNP pre-CRT with post-CRT was performed using a Wilcoxon signed-rank test. The relationship between dosimetric parameters and change ratio was analyzed using Spearman's correlation coefficient. The median levels of BNP of pre-CRT and post-CRT were 10 and 22 pg/ml, respectively, and the difference was statistically significant (P<0.0001). Significant correlations (all P<0.05) were observed between the change ratio and mean dose, V5, V10, V20, and V30. Of the cohort, 14 patients developed acute-to-subacute cardiac events, such as pericardial effusion, cardiomegaly, acute exacerbation of chronic heart failure, and a decreased ejection fraction. The change ratios of BNP, V5, V10, V20, and V30 were significantly higher in patients who experienced cardiac events compared with those who did not. The results of this study showed that BNP measurement, particularly the change ratio of BNP pre- and post-CRT, may be a useful cardiac event predictor in addition to dosimetric parameters.

Growth differentiation factor-15 and circulating biomarkers as predictors of periodontal treatment effects in patients with periodontitis: a randomized-controlled clinical trial

BackgroundDuring the last decades, in patients with periodontitis, periodontal treatment has been shown to reduce the potential release of local and systemic biomarkers linked to an early risk of systemic inflammatory disorders. This study evaluated the efficacy of non-surgical-periodontal treatment (NSPT) on growth differentiation factor 15 (GDF-15) and related circulating biomarkers such as glutathione peroxidase 1 (GPx-1), c-reactive protein (hs-CRP), and surfactant protein D (SP-D) in periodontal patients and explored whether subjects who had high GDF-15 levels at baseline showed increased clinical benefits following NSPT at 6-months follow-up.MethodsFor this two-arm, parallel randomized clinical trial, patients with periodontitis were randomly allocated to receive quadrant scaling and root-planing (Q-SRP, n = 23, median age 51 years old) or full-mouth disinfection (FMD, n = 23, median age 50 years old) treatment. Clinical and periodontal parameters were recorded in all enrolled patients. The primary outcome was to analyse serum concentrations changes of GDF-15 and of GPx-1, hs-CRP, and SP-D at baseline and at 30, 90, and 180-days follow-up after NSPT through enzyme-linked immunosorbent assay (ELISA) and nephelometric assay techniques.ResultsIn comparison with FMD, patients of the Q-SRP group showed a significant improvement in clinical periodontal parameters (p < 0.05) and a reduction in the mean levels of GDF-15 (p = 0.005), hs-CRP (p < 0.001), and SP-D (p = 0.042) and an increase of GPx-1 (p = 0.025) concentrations after 6 months of treatment. At 6 months of treatment, there was a significant association between several periodontal parameters and the mean concentrations of GDF-15, GPx-1, hs-CRP, and SP-D (p < 0.05 for all parameters). Finally, the ANOVA analysis revealed that, at 6 months after treatment, the Q-SRP treatment significantly impacted the reduction of GDF-15 (p = 0.015), SP-D (p = 0.026) and the upregulation of GPx-1 (p = 0.045).ConclusionThe results evidenced that, after 6 months of treatment, both NSPT protocols improved the periodontal parameters and analyzed biomarkers, but Q-SRP was more efficacious than the FMD approach. Moreover, patients who presented high baseline GDF-15 and SP-D levels benefited more from NSPT at 6-month follow-up.Trial registrationNCT05720481.

Testing fear of COVID-19, difficulties in emotion regulation, state anxiety as predictors of withdrawal effects in individuals with problematic exercise behaviour: a serial mediation model

ABSTRACT The issue of the worldwide COVID-19 pandemic led to raising concerns about mental health issues. Research showed that changes in daily routines and life circumstances have brought negative feelings like stress and anxiety. Many individuals had to adapt their workout routines to lockdowns and restrictions. Evidence suggests during abstinence periods individuals with exercise addiction may experience withdrawal effects. The present study aimed to explore the serial mediating roles of difficulties in emotion regulation and state anxiety on the relationship between fear of COVID-19 and withdrawal effects in individuals with problematic exercise behaviour. The data (N = 160) was obtained using validated self-report measurements including the Fear of COVID-19 Scale, Difficulties in Emotion Regulation Scale-16, State-Trait Inventory for Cognitive and Somatic Anxiety, and Exercise Dependence Scale-21. To test the proposed model, a number of mediation analyses were performed via PROCESS Macro by Hayes for SPSS 27.0. The findings showed that when individuals with problematic exercise behaviour had increased levels of fear of COVID-19, they were likely to have difficulties in emotion regulation and that difficulties led to state anxiety, turning into withdrawal effects s. However, the mediating effect disappeared when controlling for age. The limitations, implications, and recommendations for further studies were discussed.

The effectiveness of hyperbaric oxygen therapy for managing radiation-induced proctitis - results of a 10-year retrospective cohort study.

Despite modern radiotherapy (RT) techniques, radiation-induced proctitis (RIP) remains a significant complication of RT for pelvic organ malignancies. Over the last decades, an enormous therapeutic armamentarium has been considered in RIP, including hyperbaric oxygen therapy (HBOT). However, the evidence regarding the impact of HBOT on RIP is conflicting. This study aims to evaluate the effectiveness and safety of HBOT in the treatment of RIP. Ten-year (2013-2023) retrospective analysis of all consecutive patients with RIP treated with HBOT at Centro de Medicina Subaquática e Hiperbárica (CMSH) (Armed Forces Hospital - Lisbon, Portugal). Patients were exposed to 100% oxygen at 2.5 ATA, in a multiplace first-class hyperbaric chamber, for 70-min periods, once daily, five times per week. Fisher's exact test was performed using SPSS (version 23.0); p<0.05 was accepted as statistically significant. Of a total of 151 patients with RIP, 88 were included in the final analysis, of whom 38.6% evidenced other concurrent radiation-induced soft tissue lesions. The most reported primary pelvic tumor treated with RT was prostate cancer (77.3%), followed by cervical cancer (10.2%). Hematochezia was the most observed clinical manifestation (86.4%). After a median of 60 HBOT sessions (interquartile range [IQR]: 40-87.5), 62.5% and 31.8% of patients achieved a clinical complete and partial response, respectively, with a hematochezia resolution rate of 93.7% (complete or partial). While partial and complete responses require fewer than 70 sessions of HBOT in terms of overall RIP symptoms (p=0.069), isolated hematochezia tends to require at least 70 sessions (p=0.075). Individuals with at least two concurrent late radiation tissue injuries were associated with a complete response to HBOT (p=0.029). Only about 5.7% of patients did not respond to the treatment. Eighteen patients (20.5%) developed reversible ear barotrauma. The number of HBOT sessions was a predictor of HBOT side effects (odds ratio: 1.010; 95% confidence interval, 1.000-1.020; p=0.047). The HBOT proved to be an effective and safe treatment for RIP refractory to medical and/or endoscopic treatments. This real-world evidence study adds value to published data on the management of RIP with HBOT.

Predictors of adverse effects to antiseizure drugs in adult patients with epilepsy from Colombia: A case–control study

IntroductionAdverse drug reactions (ADRs) to antiseizure therapy can worsen the quality of life, reduce adherence, and potentially lead to treatment discontinuation and uncontrolled seizures. ObjectivesThe aim of the study was to develop a prognostic model for ADRs to antiseizure therapy in adult patients with epilepsy from Colombia. MethodsThis case–control study included adult patients with epilepsy, who were separated into two groups: one group with ADRs to antiseizure therapy (cases), as determined by a complete evaluation conducted by an epileptologist, and another group without ADRs (controls). Variables were analyzed to identify statistical differences between the two groups and were then selected to construct a prognostic model using logistic regression. The Bonferroni method was applied for multiple comparisons. ResultsThree hundred fifty-four patients with epilepsy were studied. One hundred and fifty (42%) patients had ADRs and 204 (57%) patients did not have ADs. A total of 362 ADRs were reported, with a third of them being general symptoms and most frequently occurring with older-generation antiseizure drugs (58%). Female sex, drug-resistant epilepsy, LEV, and CZP were risk factors, whereras the presence of tumoral etiology, absence of seizure triggers, and VPA were identified as protective factors. A prognostic model was constructed using previously reported risk factors for ADRs to antiseizure therapy and other variables available in this population study. In the multivariable analysis, the number of previously used antiseizure drugs (1, 2, or ≥3), TPM, CZP, LEV, PHT, and female sex were predictors of ADRs. The corrected p-values were estimated by the Bonferroni method; however, not all the variables achieved statistical significance with this adjustment. ConclusionsIn adult patients with epilepsy from Colombia, we found that the number of previously used antiseizure drugs, TPM, CZP, LEV, PHT, and female sex were predictive factors for ADRs to antiseizure therapy.

Lipid profiles and production performance responses of laying hens to dietary Moringa oleifera leaf meal: systematic review and meta-analysis.

The inclusion of Moringa oleifera leaf meal (MLM) in chicken diets especially in developing countries is on the increase due to scarcity of traditional feedstuffs. Therefore, this investigation aimed to explore the effects of MLM on lipid profiles and production characteristics of laying hens. Twenty-three publications retrieved from Web of Science, PubMed, Scopus and Google Scholar search engines were used for the analysis. Data from the 23 studies were analysed using random-effects model in OpenMEE software. Results were presented as standardised mean difference (SMD) at a 95% confidence interval. The results show significant improvement in feed conversion ratio (SMD = - 0.49; p < .001), egg mass (SMD = 0.35; p = .003), Haugh unit (SMD = 0.39; p < .001), eggshell thickness (SMD = 0.63; p < .001) and eggshell weight (SMD = 0.45; p < .001) at a reduced feed intake. On the other hand, egg weight, hen-day egg production and blood high-density lipoprotein cholesterol were not statistically different from controls. Results reveal that dietary MLM enhanced blood cholesterol, low-density lipoprotein (LDL) cholesterol, triglycerides and yolk cholesterol concentrations in laying hens. There is presence of significant heterogeneity and meta-regression revealed that study country, number of hen, housing system, hen age, inclusion level and layer strains were predictors of the treatment effect. In conclusion, the results of this meta-analysis suggest that inclusion of MLM in the diet of laying hens improved feed conversion ratio, aspects of egg quality and blood/yolk cholesterol concentrations in laying hens at a reduced feed intake.

Modeling clustered binary data with nonparametric unobserved heterogeneity: An application to stock crash analysis

AbstractVarious random effects models have been developed for clustered binary data; however, traditional approaches to these models generally rely heavily on the specification of a continuous random effect distribution such as Gaussian or beta distribution. In this article, we introduce a new model that incorporates nonparametric unobserved random effects on unit interval (0,1) into logistic regression multiplicatively with fixed effects. This new multiplicative model setup facilitates prediction of our nonparametric random effects and corresponding model interpretations. A distinctive feature of our approach is that a closed‐form expression has been derived for the predictor of nonparametric random effects on unit interval (0,1) in terms of known covariates and responses. A quasi‐likelihood approach has been developed in the estimation of our model. Our results are robust against random effects distributions from very discrete binary to continuous beta distributions. We illustrate our method by analyzing recent large stock crash data in China. The performance of our method is also evaluated through simulation studies.