Tag: statistics

Curr Neuropharmacol. 2022 Oct 27. doi: 10.2174/1570159X21666221027143920. Online ahead of print.

ABSTRACT

BACKGROUND: Serum prolactin levels are influenced by sex, physical development and medications among other factors. Antipsychotics usually increase serum prolactin levels in both adults and younger patients, but no study had reviewed the potential association between sex and vulnerability for developing hyperprolactinemia among children and adolescents.

OBJECTIVE: Systematic review and meta-analysis of serum prolactin levels in children and adolescents on antipsychotic treatment for any psychiatric diagnosis to determine the effect of sex.

METHODS: A systematic search was performed in MEDLINE/PubMed/Web of Science and Cochrane databases for randomized controlled trials of antipsychotics in children and adolescents reporting serum prolactin levels by sex.

RESULTS: Of 1278 identified records, seven studies were included, comparing different single antipsychotics to placebo (risperidone N=4; lurasidone N=1; olanzapine N=1; queriapine N=1). Both male and female children and adolescents on antipsychotics presented a significant increase of prolactin levels relative to subjects receiving placebo. (Male: 16.53 with 95%CI: 6.15 – 26.92; Female: 26.97 with 95%CI: 9.18 – 44.75). The four studies using risperidone had similar findings (Male: 26.49 with 95%CI: 17.55 – 35.43; Female: 37.72 with 95%CI: 9.41 – 66.03). In the direct comparison between sexes, females showed somewhat greater increases of prolactin, but the differences were not statistically significant.

CONCLUSION: Serum prolactin levels are increased in children and adolescents of both sexes on antipsychotics; with females showing a slightly greater increase than males. Further research is needed to clarify the influence of sex and pubertal status on prolactin levels in children and adolescents taking antipsychotics.

PMID:36305138 | DOI:10.2174/1570159X21666221027143920

Curr Cancer Drug Targets. 2022 Oct 27. doi: 10.2174/1568009623666221027103845. Online ahead of print.

ABSTRACT

The objective of our research was to clarify the role of genetic polymorphisms in GST (T1 and M1) in the development of Ph-ve CML.

MATERIALS AND METHODS: We report on a case-control study, with 126 participants, divided into 26 patients with Ph-ve CML (57.7% male, 42.3% female) and 100 healthy volunteers (51% male, 49% female) with no medical history of cancer as a control population. All Ph-ve CML patients were diagnosed according to standard hematologic and cytogenetic criteria based on CBC, confirmed by Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) to determine the presence or absence of the BCR-ABL gene, followed by bone marrow (BM) examination.

RESULTS: Of the 26 studied cases, 50% had the GSTT1 null genotype against 21% of the control group, a statistically significant difference (CI= 1.519 – 9.317; p-value= 0.004). The GSTM1 null genotype was detected in 23.1% of cases and 35% of controls, a difference not statistically significant (OR= 0.557; CI= 0.205-1.515; p-value= 0.252). Distribution of GSTT1 and GSTM1 polymorphisms was also examined according to gender, age and ethnic grouping, these findings revealing no statistically significant differences.

CONCLUSION: Our study reveals a strong correlation between GSTT1 polymorphism and Ph-ve CML, whereas the data for GSTM1 polymorphisms indicates no role in the initial development of the disease. More studies are required to further clarify the roles that these and other genes may play in disease development.

PMID:36305131 | DOI:10.2174/1568009623666221027103845

Zhongguo Dang Dai Er Ke Za Zhi. 2022 Oct 15;24(10):1098-1103. doi: 10.7499/j.issn.1008-8830.2205074.

ABSTRACT

OBJECTIVES: To investigate the changes in the disease spectrum among hospitalized children in the pediatric intensive care units (PICU) within 2 years before and after the outbreak of coronavirus disease 2019 (COVID-19).

METHODS: The related data on disease diagnosis were collected from all children who were hospitalized in the PICU of Affiliated Hospital of Jining Medical College from January 2018 to December 2019 (pre-COVID-19 group) and from January 2020 to December 2021 (post-COVID-19 group). A statistical analysis was performed for the disease spectrum of the two groups.

RESULTS: There were 2 368 children in the pre-COVID-19 group and 1 653 children in the post-COVID-19 group. The number of children in the post-COVID-19 group was reduced by 30.19% compared with that in the pre-COVID-19 group. There was a significant difference in age composition between the two groups (P<0.05). The top 10 diseases in the pre-COVID-19 group by number of cases were respiratory diseases, neurological diseases, sepsis, critical illness, circulatory system diseases, severe neurosurgical diseases, digestive system diseases, unintentional injuries, endocrine system diseases, and tumors. The top 10 diseases in the post-COVID-19 group by number of cases were respiratory diseases, neurological diseases, sepsis, circulatory system diseases, unintentional injuries, endocrine system diseases, severe neurosurgical diseases, acute abdomen, trauma surgical diseases, and digestive system diseases. The proportions of respiratory diseases, critical illness and severe neurosurgical diseases in the post-COVID-19 group were lower than those in the pre-COVID-19 group (P<0.05), while the proportions of unintentional injuries, acute abdomen, endocrine system diseases, trauma surgical diseases and sepsis were higher than those in the pre-COVID-19 group (P<0.05).

CONCLUSIONS: COVID-19 epidemic has led to a significant reduction in the number of children admitted to the PICU, and there are significant changes in the disease spectrum within 2 years before and after the outbreak of COVID-19. Relevant prevention and control measures taken during the COVID-19 epidemic can reduce the incidence of respiratory diseases, neurological diseases, and other critical illness in children, but it is necessary to strengthen the prevention of unintentional injuries and chronic disease management during the epidemic.

PMID:36305109 | DOI:10.7499/j.issn.1008-8830.2205074

J Neuropsychol. 2022 Oct 28. doi: 10.1111/jnp.12298. Online ahead of print.

ABSTRACT

Cognitive impairment in schizophrenia and other psychiatric disorders is a challenge to be overcome in order to maintain patients’ quality of life and social function. The neurological pathogenesis of cognitive impairment requires further elucidation. In general, the hippocampus interacts between the cortical and subcortical areas for information processing and consolidation and has an important role in memory. We examined the relationship between structural connectivity of the hippocampus and cortical/subcortical areas and cognitive impairment in schizophrenia, major depressive disorder and bipolar disorder. Subjects comprised 21 healthy controls, 19 patients with schizophrenia, 20 patients with bipolar disorder and 18 patients with major depressive disorder. Diffusion-weighted tensor images data were processed using ProbtrackX2 to calculate the structural connectivity between the hippocampus and cortical/subcortical areas. Cognitive function was assessed using the Brief Assessment of Cognition in schizophrenia composite score. Hippocampal structural connectivity index was significantly correlated with composite score in the schizophrenia group but not in the healthy control, major depressive disorder or bipolar disorder groups. There were no statistically significant differences in hippocampal structural connectivity index between the four groups. Structural connectivity between the hippocampus and cortical/subcortical areas is suggested to be a pathophysiological mechanism of comprehensive cognitive impairment in schizophrenia.

PMID:36305099 | DOI:10.1111/jnp.12298

J Clin Lab Anal. 2022 Oct 28:e24750. doi: 10.1002/jcla.24750. Online ahead of print.

ABSTRACT

OBJECTIVE: Genetic variations can affect individual response to methadone maintenance treatment (MMT) for heroin addiction. The A118G variant (rs1799971) in the mu opioid receptor gene (OPRM1) is a potential candidate single nucleotide polymorphism (SNP) for personalized MMT. This study determined whether rs1799971 is related to MMT response or dose.

METHODS: We recruited 286 MMT patients from a Han Chinese population. The rs1799971 genotype was determined via TaqMan genotyping assay. The genetic effect of this SNP on MMT response or dose was evaluated using logistic regression. A meta-analysis was performed to merge all available data to evaluate the role of rs1799971 in MMT using RevMan 5.3 software.

RESULTS: No statistical significance was observed in the association between the OPRM1 rs1799971 and MMT response or dose in our Chinese cohort. Meta-analysis indicated that the OPRM1 A118G variation was not significantly associated with MMT response or dose requirement.

CONCLUSION: The results suggest that rs1799971 in OPRM1 might not play a critical role alone in influencing MMT response or dose.

PMID:36305091 | DOI:10.1002/jcla.24750

Behav Cogn Psychother. 2022 Oct 28:1-6. doi: 10.1017/S1352465822000467. Online ahead of print.

ABSTRACT

BACKGROUND: An earlier evaluation (Fox et al., ) highlighted reductions in risk behaviours and restrictive practices for women admitted to low secure dialectical behaviour therapy (DBT) unit. Since then, a value-based healthcare model has been adopted.

AIMS: To explore changes in health, social and psychological functioning, risk, quality of life, and in incidents of violence and restrictive practices, over the initial 12-month period of admission to a specialist DBT service.

METHOD: Data were extracted from electronic clinical records for 41 women with emotionally unstable personality disorder admitted to a specialist integrated practice unit (IPU) providing a comprehensive DBT programme. Secondary analysis was conducted on an anonymous dataset of routinely collected outcome measures at baseline admission, and 6 and 12 months post-admission. ANOVAs and pairwise post hoc comparisons, and non-parametric equivalents, were conducted to examine changes in outcomes.

RESULTS: Findings showed statistically significant improvements in mental health scores on the ReQOL (p<.01), global, wellbeing, problems, functioning and risk scores on the COREOM (all p<.01), and severe disturbance, emotional wellbeing, socioeconomic status, risk and need scores on the HoNOS-Secure (all p<.05). Significant reductions in risk behaviours (p<.01) and restrictive practices (p<.01) were also apparent. The most substantiative improvements were largely demonstrated over a 12-month admission period.

CONCLUSIONS: Admission to the DBT IPU yielded significant improvements on outcomes pertaining to quality of life, psychological distress, and risk. Importantly, these are outcomes that aligned with patients’ perceptions of recovery.

PMID:36305087 | DOI:10.1017/S1352465822000467

Biometrics. 2022 Oct 27. doi: 10.1111/biom.13783. Online ahead of print.

ABSTRACT

Unmeasured confounding is a key threat to reliable causal inference based on observational studies. Motivated from two powerful natural experiment devices, the instrumental variables and difference-in-differences, we propose a new method called instrumented difference-in-differences that explicitly leverages exogenous randomness in an exposure trend to estimate the average and conditional average treatment effect in the presence of unmeasured confounding. We develop the identification assumptions using the potential outcomes framework. We propose a Wald estimator and a class of multiply robust and efficient semiparametric estimators, with provable consistency and asymptotic normality. In addition, we extend the instrumented difference-in-differences to a two-sample design to facilitate investigations of delayed treatment effect and provide a measure of weak identification. We demonstrate our results in simulated and real datasets. This article is protected by copyright. All rights reserved.

PMID:36305081 | DOI:10.1111/biom.13783

Biol Cybern. 2022 Oct 27. doi: 10.1007/s00422-022-00948-3. Online ahead of print.

ABSTRACT

The visual systems of insects are relatively simple compared to humans. However, they enable navigation through complex environments where insects perform exceptional levels of obstacle avoidance. Biology uses two separable modes of optic flow to achieve this: rapid gaze fixation (rotational motion known as saccades); and the inter-saccadic translational motion. While the fundamental process of insect optic flow has been known since the 1950’s, so too has its dependence on contrast. The surrounding visual pathways used to overcome environmental dependencies are less well known. Previous work has shown promise for low-speed rotational motion estimation, but a gap remained in the estimation of translational motion, in particular the estimation of the time to impact. To consistently estimate the time to impact during inter-saccadic translatory motion, the fundamental limitation of contrast dependence must be overcome. By adapting an elaborated rotational velocity estimator from literature to work for translational motion, this paper proposes a novel algorithm for overcoming the contrast dependence of time to impact estimation using nonlinear spatio-temporal feedforward filtering. By applying bioinspired processes, approximately 15 points per decade of statistical discrimination were achieved when estimating the time to impact to a target across 360 background, distance, and velocity combinations: a 17-fold increase over the fundamental process. These results show the contrast dependence of time to impact estimation can be overcome in a biologically plausible manner. This, combined with previous results for low-speed rotational motion estimation, allows for contrast invariant computational models designed on the principles found in the biological visual system, paving the way for future visually guided systems.

PMID:36303043 | DOI:10.1007/s00422-022-00948-3

Nat Struct Mol Biol. 2022 Oct 27. doi: 10.1038/s41594-022-00844-1. Online ahead of print.

ABSTRACT

It is estimated that 10%-30% of disease-associated genetic variants affect splicing. Splicing variants may generate deleteriously altered gene product and are potential therapeutic targets. However, systematic diagnosis or prediction of splicing variants is yet to be established, especially for the near-exon intronic splice region. The major challenge lies in the redundant and ill-defined branch sites and other splicing motifs therein. Here, we carried out unbiased massively parallel splicing assays on 5,307 disease-associated variants that overlapped with branch sites and collected 5,884 variants across the 5′ splice region. We found that strong splice sites and exonic features preserve splicing from intronic sequence variation. Whereas the splice-altering mechanism of the 3′ intronic variants is complex, that of the 5′ is mainly splice-site destruction. Statistical learning combined with these molecular features allows precise prediction of altered splicing from an intronic variant. This statistical model provides the identity and ranking of biological features that determine splicing, which serves as transferable knowledge and out-performs the benchmarking predictive tool. Moreover, we demonstrated that intronic splicing variants may associate with disease risks in the human population. Our study elucidates the mechanism of splicing response of intronic variants, which classify disease-associated splicing variants for the promise of precision medicine.

PMID:36303034 | DOI:10.1038/s41594-022-00844-1

Nat Methods. 2022 Oct 27. doi: 10.1038/s41592-022-01640-x. Online ahead of print.

ABSTRACT

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

PMID:36303018 | DOI:10.1038/s41592-022-01640-x