Tag: nevin manimala

BMJ Ment Health. 2023 Feb;26(1):e300677. doi: 10.1136/bmjment-2023-300677.

ABSTRACT

In recent years, network meta-analyses have been increasingly carried out to inform clinical guidelines and policy. This approach is under constant development, and a broad consensus on how to carry out several of its methodological and statistical steps is still lacking. Therefore, different working groups might often make different methodological choices based on their clinical and research experience, with possible advantages and shortcomings. In this contribution, we will critically assess two network meta-analyses on the topic of pharmacological prevention of relapse in schizophrenia, carried out by two different research groups. We will highlight the implications of different methodological choices on the analysis results and their clinical-epidemiological interpretation. Moreover, we will discuss some of the most relevant technical issues of network meta-analyses for which there is not a broad methodological agreement, including the assessment of transitivity.

PMID:37197798 | DOI:10.1136/bmjment-2023-300677

J Med Genet. 2023 May 16:jmg-2022-109132. doi: 10.1136/jmg-2022-109132. Online ahead of print.

ABSTRACT

BACKGROUND: Limb-girdle muscular dystrophies (LGMD) are a heterogeneous group of genetically determined muscle disorders. TRAPPC11-related LGMD is an autosomal-recessive condition characterised by muscle weakness and intellectual disability.

METHODS: A clinical and histopathological characterisation of 25 Roma individuals with LGMD R18 caused by the homozygous TRAPPC11 c.1287+5G>A variant is reported. Functional effects of the variant on mitochondrial function were investigated.

RESULTS: The c.1287+5G>A variant leads to a phenotype characterised by early onset muscle weakness, movement disorder, intellectual disability and elevated serum creatine kinase, which is similar to other series. As novel clinical findings, we found that microcephaly is almost universal and that infections in the first years of life seem to act as triggers for a psychomotor regression and onset of seizures in several individuals with TRAPPC11 variants, who showed pseudometabolic crises triggered by infections. Our functional studies expanded the role of TRAPPC11 deficiency in mitochondrial function, as a decreased mitochondrial ATP production capacity and alterations in the mitochondrial network architecture were detected.

CONCLUSION: We provide a comprehensive phenotypic characterisation of the pathogenic variant TRAPPC11 c.1287+5G>A, which is founder in the Roma population. Our observations indicate that some typical features of golgipathies, such as microcephaly and clinical decompensation associated with infections, are prevalent in individuals with LGMD R18.

PMID:37197784 | DOI:10.1136/jmg-2022-109132

J Appl Stat. 2022 Apr 24;50(7):1650-1663. doi: 10.1080/02664763.2022.2064439. eCollection 2023.

ABSTRACT

Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus has spread seriously throughout the world. Predicting the spread, or the number of cases, in the future can facilitate preparation for, and prevention of, a worst-case scenario. To achieve these purposes, statistical modeling using past data is one feasible approach. This paper describes spatio-temporal modeling of COVID-19 case counts in 47 prefectures of Japan using a nonlinear random effects model, where random effects are introduced to capture the heterogeneity of a number of model parameters associated with the prefectures. The negative binomial distribution is frequently used with the Paul-Held random effects model to account for overdispersion in count data; however, the negative binomial distribution is known to be incapable of accommodating extreme observations such as those found in the COVID-19 case count data. We therefore propose use of the beta-negative binomial distribution with the Paul-Held model. This distribution is a generalization of the negative binomial distribution that has attracted much attention in recent years because it can model extreme observations with analytical tractability. The proposed beta-negative binomial model was applied to multivariate count time series data of COVID-19 cases in the 47 prefectures of Japan. Evaluation by one-step-ahead prediction showed that the proposed model can accommodate extreme observations without sacrificing predictive performance.

PMID:37197760 | PMC:PMC10184601 | DOI:10.1080/02664763.2022.2064439

Biometrika. 2022 Aug 19;110(2):519-536. doi: 10.1093/biomet/asac050. eCollection 2023 Jun.

ABSTRACT

Zero-inflated nonnegative outcomes are common in many applications. In this work, motivated by freemium mobile game data, we propose a class of multiplicative structural nested mean models for zero-inflated nonnegative outcomes which flexibly describes the joint effect of a sequence of treatments in the presence of time-varying confounders. The proposed estimator solves a doubly robust estimating equation, where the nuisance functions, namely the propensity score and conditional outcome means given confounders, are estimated parametrically or nonparametrically. To improve the accuracy, we leverage the characteristic of zero-inflated outcomes by estimating the conditional means in two parts, that is, separately modelling the probability of having positive outcomes given confounders, and the mean outcome conditional on its being positive and given the confounders. We show that the proposed estimator is consistent and asymptotically normal as either the sample size or the follow-up time goes to infinity. Moreover, the typical sandwich formula can be used to estimate the variance of treatment effect estimators consistently, without accounting for the variation due to estimating nuisance functions. Simulation studies and an application to a freemium mobile game dataset are presented to demonstrate the empirical performance of the proposed method and support our theoretical findings.

PMID:37197742 | PMC:PMC10183836 | DOI:10.1093/biomet/asac050

Biometrika. 2022 Jul 25;110(2):485-498. doi: 10.1093/biomet/asac042. eCollection 2023 Jun.

ABSTRACT

Many partial identification problems can be characterized by the optimal value of a function over a set where both the function and set need to be estimated by empirical data. Despite some progress for convex problems, statistical inference in this general setting remains to be developed. To address this, we derive an asymptotically valid confidence interval for the optimal value through an appropriate relaxation of the estimated set. We then apply this general result to the problem of selection bias in population-based cohort studies. We show that existing sensitivity analyses, which are often conservative and difficult to implement, can be formulated in our framework and made significantly more informative via auxiliary information on the population. We conduct a simulation study to evaluate the finite sample performance of our inference procedure, and conclude with a substantive motivating example on the causal effect of education on income in the highly selected UK Biobank cohort. We demonstrate that our method can produce informative bounds using plausible population-level auxiliary constraints. We implement this method in the [Formula: see text] package [Formula: see text].

PMID:37197741 | PMC:PMC10183833 | DOI:10.1093/biomet/asac042

Biometrika. 2022 Jul 12;110(2):339-360. doi: 10.1093/biomet/asac041. eCollection 2023 Jun.

ABSTRACT

Sparse principal component analysis is an important technique for simultaneous dimensionality reduction and variable selection with high-dimensional data. In this work we combine the unique geometric structure of the sparse principal component analysis problem with recent advances in convex optimization to develop novel gradient-based sparse principal component analysis algorithms. These algorithms enjoy the same global convergence guarantee as the original alternating direction method of multipliers, and can be more efficiently implemented with the rich toolbox developed for gradient methods from the deep learning literature. Most notably, these gradient-based algorithms can be combined with stochastic gradient descent methods to produce efficient online sparse principal component analysis algorithms with provable numerical and statistical performance guarantees. The practical performance and usefulness of the new algorithms are demonstrated in various simulation studies. As an application, we show how the scalability and statistical accuracy of our method enable us to find interesting functional gene groups in high-dimensional RNA sequencing data.

PMID:37197740 | PMC:PMC10183835 | DOI:10.1093/biomet/asac041

Biometrika. 2022 Aug 13;110(2):395-410. doi: 10.1093/biomet/asac047. eCollection 2023 Jun.

ABSTRACT

We propose a reinforcement learning method for estimating an optimal dynamic treatment regime for survival outcomes with dependent censoring. The estimator allows the failure time to be conditionally independent of censoring and dependent on the treatment decision times, supports a flexible number of treatment arms and treatment stages, and can maximize either the mean survival time or the survival probability at a certain time-point. The estimator is constructed using generalized random survival forests and can have polynomial rates of convergence. Simulations and analysis of the Atherosclerosis Risk in Communities study data suggest that the new estimator brings higher expected outcomes than existing methods in various settings.

PMID:37197739 | PMC:PMC10183834 | DOI:10.1093/biomet/asac047

Ophthalmol Sci. 2023 Mar 11;3(3):100298. doi: 10.1016/j.xops.2023.100298. eCollection 2023 Sep.

ABSTRACT

PURPOSE: To assess the safety and efficacy of a ciliary neurotrophic factor (CNTF) intraocular implant on neuroprotection and neuroenhancement in glaucoma.

DESIGN: Open-label, prospective, phase I clinical trial.

PARTICIPANTS: A total of 11 participants were diagnosed with primary open-angle glaucoma (POAG). One eye of each patient was assigned as the study (implant) eye.

METHODS: The study eye was implanted with a high-dose CNTF-secreting NT-501 implant, whereas the other eye served as a control. All patients were followed up for 18 months. Analysis was limited to descriptive statistics.

MAIN OUTCOME MEASURES: Primary outcome was safety through 18 months after implantation assessed by serial eye examinations, structural and functional testing, and adverse events (AEs) recording. Parameters measured included visual acuity (VA), Humphrey visual field (HVF), pattern electroretinogram, scanning laser polarimetry with variable corneal compensation (GDx VCC), and OCT. These parameters were also used for secondary analysis of efficacy outcome.

RESULTS: All NT-501 implants were well tolerated with no serious AEs associated with the implant. The majority of AEs were related to the implant placement procedure and were resolved by 12 weeks after surgery. Foreign-body sensation was the most commonly reported AE and was self-limited to the postoperative period. The most common implant-related AE was pupil miosis; no patients underwent explant. Visual acuity and contrast sensitivity decreased more in fellow eyes than in study eyes (VA, -5.82 vs. -0.82 letters; and contrast sensitivity, -1.82 vs. -0.37 letters, for fellow vs. study eyes, respectively). The median HVF visual field index and mean deviation measurements worsened (decreased) in fellow eyes (-13.0%, -3.9 dB) and improved (increased) in study eyes (2.7%, 1.2 dB). Implanted eyes showed an increase in retinal nerve fiber layer thickness measured by OCT and by GDx VCC (OCT, 2.66 μm vs. 10.16 μm; and GDx VCC, 1.58 μm vs. 8.36 μm in fellow vs. study eyes, respectively).

CONCLUSIONS: The NT-501 CNTF implant was safe and well tolerated in eyes with POAG. Eyes with the implant demonstrated both structural and functional improvements suggesting biological activity, supporting the premise for a randomized phase II clinical trial of single and dual NT-501 CNTF implants in patients with POAG, which is now underway.

FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found after the references.

PMID:37197702 | PMC:PMC10183667 | DOI:10.1016/j.xops.2023.100298

Evid Based Complement Alternat Med. 2023 May 8;2023:7486220. doi: 10.1155/2023/7486220. eCollection 2023.

ABSTRACT

AIM: To investigate the adverse pregnancy outcomes associated with endometriosis and its influencing factors.

METHODS: A total of 188 endometriosis patients who gave birth at our hospital between June 2018 and January 2021 were screened for eligibility and included in the research group, while a control group of 188 nonendometriosis women who delivered at our hospital during the same period were also included as healthy controls. Pregnancy outcomes were the key outcome measure, and the relationship between endometriosis and unfavorable pregnancy outcomes, as well as the influencing factors, were explored.

RESULTS: There was no significant difference in the risk of adverse pregnancy events such as miscarriage, ectopic pregnancy, termination of pregnancy, and fetal death between the two groups (P > 0.05). The differences in hypertensive disorder in pregnancy, gestational diabetes, placental abruption, fetal growth restriction, and luteal support between the two groups also failed to reach the statistical standard (P > 0.05). The two groups significantly differed in terms of cesarean delivery, preterm delivery, and placenta previa (1.92 (95% CI 1.33-2.85), 2.43 (95% CI 1.05-5.58), and 4.51 (95% CI 1.23-16.50)) (P < 0.05).

CONCLUSION: Endometriosis is an influential factor in adverse pregnancy outcomes and results in a high risk of preterm delivery, placenta previa, and cesarean delivery in patients. Mutual interactions exist among adverse pregnancy outcomes and thus require appropriate management.

PMID:37197694 | PMC:PMC10185417 | DOI:10.1155/2023/7486220

Orthop Rev (Pavia). 2023 May 13;15:74883. eCollection 2023.

ABSTRACT

BACKGROUND: For soccer athletes, injuries are frequent and pose a considerable health and financial burden for individuals and families. While studies have previously assessed the incidence of soccer injuries and preventive strategies male athletes use to reduce these occurrences, few have included women and players of varying skill levels.

OBJECTIVE: To report the frequency of injuries in a cohort of male and female soccer athletes and describe the training habits that have helped prevent injury.

METHODS: Two hundred (n=200) United States participants completed a questionnaire on soccer practicing frequency, habits, injuries, and treatments. A screening question ensured all respondents had played soccer for at least one year and determined eligibility for the study. Participant information related to age, sex, education, income, and race was also collected. JMP statistical software was used to analyze collected data and build multivariate regressions, mosaic plots, and histograms.

RESULTS: The mean number of practice sessions per week was 3.60 +/- 1.64, and the median experience playing soccer was 2-4 years. Older participants were more likely to practice once (p = 0.0001) or twice (p= 0.0008) per week. Women were less likely to include warmups before playing soccer (p = 0.022). This was problematic as participants who did not include a proper warmup routine were more likely to have been absent from play for longer amounts of time following injury (p = 0.032). The four most common injury sites were knees (n = 35, 17.5%), ankles (n = 31, 15.5%), shoulders (n = 25, 12.5%), and head/neck (n = 24, 12%). 140 (47.62%) patients used pain medication as their main remedy, 128 (43.54%) went to physical therapy, and 26 (10.78%) underwent surgery.

CONCLUSION: In any sample of soccer athletes involving variations in sex, race, and competitive play, injuries are highly common. Few studies before this one have included female athletes, and our findings highlight an important discrepancy in training habits between sexes. Women are less likely to follow a warmup regimen and are thus injured for longer. Incorporating dynamic stretching and plyometrics are particularly helpful to stay healthy.

PMID:37197671 | PMC:PMC10184884