Category: Statistics

West Afr J Med. 2023 Jul 28;40(7):761-768.

ABSTRACT

BACKGROUND: Globally, female-perpetrated IPV has been well studied among various groups but little is known about IPV against heterosexual men living with HIV. This study sought to identify the prevalence and determinants of female-perpetrated IPV among heterosexual HIV-positive men in Birnin Kudu, Jigawa State, Nigeria.

MATERIALS AND METHODS: This was a descriptive crosssectional study carried out at one secondary and tertiary health facility respectively, both situated in Birnin Kudu. Using an intervieweradministered pre-tested questionnaire, the prevalence and determinants of female-perpetrated IPV was assessed among 322 heterosexual HIV-positive men attending the anti-retroviral therapy clinics at the two health facilities. Data was entered into and analyzed using statistical package for social sciences version 25.

RESULTS: The prevalence of IPV in the last year was 45% (145D 322). Out of the survivors of IPV, 143 (98.6%), 75 (51.7%), and 51 (35.2%) had experienced psychological aggression, physical assault and sexual coercion respectively. The number of children fathered, experience of childhood violence, and marital status were significantly associated with IPV (p< 0.05) However, they remained significant determinants of IPV after controlling for confounders (ethnicity, marital status, educational status ) {Adjusted Odds ratio (aOR) = 7.34 and 95% confidence interval (C.I.) = 1.49 – 35.4; aOR= 1.84 C.I. 1.33 – 2.80; aOR = O.51 (0.29 – 0.90) respectively}.

CONCLUSION: This study identified a high prevalence of femaleperpetrated IPV against heterosexual men living with HIV and emphasizes that exposure to childhood violence and being childless are determinants of IPV. Efforts should be made to screen for IPV among men living with HIV so as to optimize their health and wellbeing.

PMID:37516936

West Afr J Med. 2023 Jul 28;40(7):748-752.

ABSTRACT

BACKGROUND: Gallstones detected incidentally during imaging are termed ‘silent’ or asymptomatic gallstones and they account for 80% of all gallstones. About 1-2% of patients with silent gallstones develop symptoms yearly; however, determining those who will develop symptoms is a major challenge. Ultrasonography is the most sensitive and specific method of detecting gallstones with an accuracy greater than 95%. The study aims to determine the prevalence of ultrasound-diagnosed silent gallstones in a Nigerian population and to determine its association with age and gender.

METHODS: This was a retrospective analysis of abdominal ultrasound scans performed at the Radiology department of a tertiary institution between January 2013 and December 2015. Data retrieved included age, sex, and sonographic findings. Data analysis was done by simple proportions and percentages using the Statistical Package for Social Sciences version 20.0 software.

RESULTS: Two thousand, one hundred and thirty-eight patients had abdominal ultrasound scans for various reasons during the study period. These included 915 males and 1223 females. Incidental findings of gallstones were observed in 52 patients, giving a prevalence of 2.4%. The prevalence of gallstones increased with age (p=0.051) with the highest prevalence seen in the 5th decade. Gallstones prevalence was higher in females with a male-to-female ratio of 1:3.5.

CONCLUSION: The prevalence of silent gallstones is low in our environment, but given the complications that may arise, follow-up for early detection of complications in the patients is therefore strongly recommended.

PMID:37516927

West Afr J Med. 2023 Jul 28;40(7):742-747.

ABSTRACT

BACKGROUND: Covid-19 vaccination is recommended for the prevention of Covid-19 infection. However, there is paucity of studies assessing post-vaccination side effects, especially in Africa, and thus, the need for this study.

OBJECTIVES: To determine the prevalence of post-covid-19 vaccination side effects; the frequency of occurrence of each side effect and the willingness to receive the second dose of the vaccine.

METHODS: A descriptive cross-sectional study was conducted among Corp members undergoing the three-week compulsory orientation course in a National Youth Service Corps (NYSC) orientation camp in Keffi, North-Central Nigeria. A total of 552 Corp members received the Covid-19 vaccine (AstraZeneca), 268 consented and were enrolled in the study. Data were obtained through online Google forms and were analyzed using SPSS version 26.

RESULTS: The mean age of the respondents was 25 years (SD = 2.5). The prevalence of post-covid-19 vaccination side effects was 90.7%, 95% CI (86.8 – 93.8). The most common side effects were weakness (53.5%), pain at the injection site (52.7%), and headache (52.7%). There was a weak association between the duration of symptoms and intake of medications (Cramer’s V = 0.148) which was not statistically significant. About a quarter, 62 (24.0%), of the respondents who received the first dose of the vaccine, were unwilling to accept the second dose, mainly due to their fear of the side effects – 53 (85.5%).

CONCLUSION: Our study population had a high prevalence of post-covid-19 vaccination side effects. Thus, the need to educate recipients on possible side effects and remedies.

PMID:37516926

Hum Brain Mapp. 2023 Jul 30. doi: 10.1002/hbm.26435. Online ahead of print.

ABSTRACT

The complexity of our actions and thinking is likely reflected in functional brain networks. Independent component analysis (ICA) is a popular data-driven method to compute group differences between such networks. A common way to investigate network differences is based on ICA maps which are generated from study-specific samples. However, this approach limits the generalizability and reproducibility of the results. Alternatively, network ICA templates can be used, but up to date, few such templates exist and are limited in terms of the functional systems they cover. Here, we propose a simple two-step procedure to obtain ICA-templates corresponding to functional brain systems of the researcher’s choice: In step 1, the functional system of interest needs to be defined by means of a statistical parameter map (input), which one can generate with open-source software such as NeuroSynth or BrainMap. In step 2, that map is correlated to group-ICA maps provided by the Human Connectome Project (HCP), which is based on a large sample size and uses high quality and standardized acquisition procedures. The HCP-provided ICA-map with the highest correlation to the input map is then used as an ICA template representing the functional system of interest, for example, for subsequent analyses such as dual regression. We provide a toolbox to complete step 2 of the suggested procedure and demonstrate the usage of our pipeline by producing an ICA templates that corresponds to “motor function” and nine additional brain functional systems resulting in an ICA maps with excellent alignment with the gray matter/white matter boundaries of the brain. Our toolbox generates data in two different file formats: volumetric-based (NIFTI) and combined surface/volumetric files (CIFTI). Compared to 10 existing templates, our procedure output component maps with systematically stronger contribution of gray matter to the ICA z-values compared to white matter voxels in 9/10 cases by at least a factor of 2. The toolbox allows users to investigate functional networks of interest, which will enhance interpretability, reproducibility, and standardization of research investigating functional brain networks.

PMID:37516917 | DOI:10.1002/hbm.26435

Hum Brain Mapp. 2023 Jul 30. doi: 10.1002/hbm.26408. Online ahead of print.

ABSTRACT

Overlapping clinical presentations in primary progressive aphasia (PPA) variants present challenges for diagnosis and understanding pathophysiology, particularly in the early stages of the disease when behavioral (speech) symptoms are not clearly evident. Divergent atrophy patterns (temporoparietal degeneration in logopenic variant lvPPA, frontal degeneration in nonfluent variant nfvPPA) can partially account for differential speech production errors in the two groups in the later stages of the disease. While the existing dogma states that neurodegeneration is the root cause of compromised behavior and cortical activity in PPA, the extent to which neurophysiological signatures of speech dysfunction manifest independent of their divergent atrophy patterns remain unknown. We test the hypothesis that nonword deficits in lvPPA and nfvPPA arise from distinct patterns of neural oscillations that are unrelated to atrophy. We use a novel structure-function imaging approach integrating magnetoencephalographic imaging of neural oscillations during a non-word repetition task with voxel-based morphometry-derived measures of gray matter volume to isolate neural oscillation abnormalities independent of atrophy. We find reduced beta band neural activity in left temporal regions associated with the late stages of auditory encoding unique to patients with lvPPA and reduced high-gamma neural activity over left frontal regions associated with the early stages of motor preparation in patients with nfvPPA. Neither of these patterns of reduced cortical oscillations was explained by cortical atrophy in our statistical model. These findings highlight the importance of structure-function imaging in revealing neurophysiological sequelae in early stages of dementia when neither structural atrophy nor behavioral deficits are clinically distinct.

PMID:37516916 | DOI:10.1002/hbm.26408

BMC Bioinformatics. 2023 Jul 29;24(1):303. doi: 10.1186/s12859-023-05420-y.

ABSTRACT

BACKGROUND: The growing power and ever decreasing cost of RNA sequencing (RNA-Seq) technologies have resulted in an explosion of RNA-Seq data production. Comparing gene expression values within RNA-Seq datasets is relatively easy for many interdisciplinary biomedical researchers; however, user-friendly software applications increase the ability of biologists to efficiently explore available datasets.

RESULTS: Here, we describe ROGUE (RNA-Seq Ontology Graphic User Environment, https://marisshiny.

RESEARCH: chop.edu/ROGUE/ ), a user-friendly R Shiny application that allows a biologist to perform differentially expressed gene analysis, gene ontology and pathway enrichment analysis, potential biomarker identification, and advanced statistical analyses. We use ROGUE to identify potential biomarkers and show unique enriched pathways between various immune cells.

CONCLUSIONS: User-friendly tools for the analysis of next generation sequencing data, such as ROGUE, will allow biologists to efficiently explore their datasets, discover expression patterns, and advance their research by allowing them to develop and test hypotheses.

PMID:37516886 | DOI:10.1186/s12859-023-05420-y

Cardiovasc Diabetol. 2023 Jul 29;22(1):193. doi: 10.1186/s12933-023-01930-4.

ABSTRACT

BACKGROUND: We aimed to examine the association between smoking behavior change and risk of cardiovascular disease (CVD) incidence and mortality in patients with type 2 diabetes mellitus (T2DM).

METHODS: This study used nationwide data from the Korean National Health Insurance System and included 349,137 T2DM patients who smoked. Smoking behavior changes were defined with five groups: quitters, reducers I (≥ 50% reduction), reducers II (20-50% reduction), sustainers (± 20%), and increasers (≥ 20% increase) from the number of cigarettes/day at the baseline.

RESULTS: During a median follow-up of 5.1 years, 6,514 cases of myocardial infarction (MI) (1.9%), 7,837 cases of ischemic stroke (IS) (2.2%), and 14,932 deaths (4.3%) were identified. Quitters had a significantly decreased risk of MI (adjusted hazard ratio [aHR] 0.80, 95% CI 0.75-0.86) and IS (aHR 0.80, 95% CI 0.75-0.85) compared to sustainers, whereas reducers did not have a significant association with the risk of MI (aHR 1.03, 95% CI 0.94-1.13) and IS (aHR 1.00, 95% CI 0.92-1.08) in reducer I. Quitters also had a lower all-cause and CVD mortality than sustainers.

CONCLUSIONS: Smoking cessation was associated with decreased CVD incidence, and all-cause and CVD mortality among T2DM patients. However, smoking reduction was not associated with decreased risks for these.

PMID:37516874 | DOI:10.1186/s12933-023-01930-4

Clin Proteomics. 2023 Jul 29;20(1):29. doi: 10.1186/s12014-023-09420-1.

ABSTRACT

OBJECTIVE: Systemic lupus erythematosus (SLE) is a clinically and biologically heterogenous autoimmune disease. We aimed to investigate the plasma proteome of patients with active SLE to identify novel subgroups, or endotypes, of patients.

METHOD: Plasma was collected from patients with active SLE who were enrolled in the British Isles Lupus Assessment Group Biologics Registry (BILAG-BR). The plasma proteome was analysed using a data-independent acquisition method, Sequential Window Acquisition of All theoretical mass spectra mass spectrometry (SWATH-MS). Unsupervised, data-driven clustering algorithms were used to delineate groups of patients with a shared proteomic profile.

RESULTS: In 223 patients, six clusters were identified based on quantification of 581 proteins. Between the clusters, there were significant differences in age (p = 0.012) and ethnicity (p = 0.003). There was increased musculoskeletal disease activity in cluster 1 (C1), 19/27 (70.4%) (p = 0.002) and renal activity in cluster 6 (C6) 15/24 (62.5%) (p = 0.051). Anti-SSa/Ro was the only autoantibody that significantly differed between clusters (p = 0.017). C1 was associated with p21-activated kinases (PAK) and Phospholipase C (PLC) signalling. Within C1 there were two sub-clusters (C1A and C1B) defined by 49 proteins related to cytoskeletal protein binding. C2 and C6 demonstrated opposite Rho family GTPase and Rho GDI signalling. Three proteins (MZB1, SND1 and AGL) identified in C6 increased the classification of active renal disease although this did not reach statistical significance (p = 0.0617).

CONCLUSIONS: Unsupervised proteomic analysis identifies clusters of patients with active SLE, that are associated with clinical and serological features, which may facilitate biomarker discovery. The observed proteomic heterogeneity further supports the need for a personalised approach to treatment in SLE.

PMID:37516862 | DOI:10.1186/s12014-023-09420-1

Trials. 2023 Jul 29;24(1):484. doi: 10.1186/s13063-023-07528-1.

ABSTRACT

BACKGROUND: With the increase in age, the probability of cognitive impairment in the older people is increasing. More and more evidence shows that participating in leisure activities, especially chess and cards, is beneficial to the cognition and mental state of the older people. But the evidence for causal inference is limited. There is a need to conduct a fully powered randomized controlled trial (RCT) and long-term follow-up to test the effectiveness of intervention measures in improving cognitive function and mental state. This paper describes the methodology of a cluster RCT designed to determine the effect of chess and cards leisure activities on the cognitive function of the older people over 60 years old.

METHODS/DESIGN: A cluster RCT consisting of 8 clusters will be conducted in four regions of Ningxia, China (Helan, Litong, Qingtongxia, and Shapotou). Clusters will be randomly assigned to the advocacy intervention group, which is also delivered with free leisure activities tools (chess and cards), or the control group. A baseline survey will be conducted before the intervention. A mid-term and final survey will be carried out twelve and twenty-four months after the intervention, respectively. The primary outcome is a change in cognitive function, and the secondary outcomes are changes in anxiety, depression, and loneliness.

DISCUSSION: The results of this RCT will be helpful to (1) confirm the effectiveness of chess and cards leisure activities in improving the cognitive function of the older people over 60 years old; (2) determine the relationship between the frequency and duration of chess and cards leisure activities and cognitive function; (3) provide evidence of promoting participation in leisure activities through education campaigns and free provision of chess and cards tools; and (4) provide valuable information for successful aging.

TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR2200066817. Registered on 19 December 2022.

PMID:37516846 | DOI:10.1186/s13063-023-07528-1

BMC Med Res Methodol. 2023 Jul 29;23(1):174. doi: 10.1186/s12874-023-01993-7.

ABSTRACT

BACKGROUND: Care pathways are increasingly being used to enhance the quality of care and optimize the use of resources for health care. Nevertheless, recommendations regarding the sequence of care are mostly based on consensus-based decisions as there is a lack of evidence on effective treatment sequences. In a real-world setting, classical statistical tools were insufficient to consider a phenomenon with such high variability adequately and have to be integrated with novel data mining techniques suitable for identifying patterns in complex data structures. Data-driven techniques can potentially support empirically identifying effective care sequences by extracting them from data collected routinely. The purpose of this study is to perform a state sequence analysis (SSA) to identify different patterns of treatment and to asses whether sequence analysis may be a useful tool for profiling patients according to the treatment pattern.

METHODS: The clinical application that motivated the study of this method concerns the mental health field. In fact, the care pathways of patients affected by severe mental disorders often do not correspond to the standards required by the guidelines in this field. In particular, we analyzed patients with schizophrenic disorders (i.e., schizophrenia, schizotypal or delusional disorders) using administrative data from 2015 to 2018 from Lombardy Region. This methodology considers the patient’s therapeutic path as a conceptual unit, composed of a succession of different states, and we show how SSA can be used to describe longitudinal patient status.

RESULTS: We define the states to be the weekly coverage of different treatments (psychiatric visits, psychosocial interventions, and anti-psychotic drugs), and we use the longest common subsequences (dis)similarity measure to compare and cluster the sequences. We obtained three different clusters with very different patterns of treatments.

CONCLUSIONS: This kind of information, such as common patterns of care that allowed us to risk profile patients, can provide health policymakers an opportunity to plan optimum and individualized patient care by allocating appropriate resources, analyzing trends in the health status of a population, and finding the risk factors that can be leveraged to prevent the decline of mental health status at the population level.

PMID:37516839 | DOI:10.1186/s12874-023-01993-7