Tag: statistics

Sci Rep. 2024 Mar 7;14(1):5680. doi: 10.1038/s41598-024-56399-2.

ABSTRACT

The world suffers from the acute respiratory syndrome COVID-19 pandemic, which will be scary if other co-existing illnesses exacerbate it. The co-occurrence of the COVID-19 virus with kidney disease has not been available in the literature. So, further research needs to be conducted to reveal the transmission dynamics of COVID-19 and kidney disease. This study aims to create mathematical models to understand how COVID-19 interacts with kidney diseases in specific populations. Therefore, the initial step was to formulate a deterministic Susceptible-Infected-Recovered (SIR) mathematical model to depict the co-infection dynamics of COVID-19 and kidney disease. A mathematical model with seven compartments has been developed using nonlinear ordinary differential equations. This model incorporates the invariant region, disease-free and endemic equilibrium, along with the positivity solution. The basic reproduction number, calculated via the next-generation matrix, allows us to assess the stability of the equilibrium. Sensitivity analysis is also utilised to understand the influence of each parameter on disease spread or containment. The results show that a surge in COVID-19 infection rates and the existence of kidney disease significantly enhances the co-infection risks. Numerical simulations further clarify the potential outcomes of treating COVID-19 alone, kidney disease alone, and co-infected cases. The study of the potential model can be utilised to maximise the benefits of simulation to minimise the global health complexity of COVID-19 and kidney disease.

PMID:38454115 | DOI:10.1038/s41598-024-56399-2

Sci Rep. 2024 Mar 7;14(1):5592. doi: 10.1038/s41598-024-56335-4.

ABSTRACT

To provide evidence for optimization of multi-kinase inhibitors (MKIs) use in the clinic, we use the public database to describe and evaluate electrolyte disorders (EDs) related to various MKIs treated for renal cell carcinoma. We analyzed spontaneous reports submitted to the Food and Drug Administration Adverse Events Reporting System (FAERS) in an observational and retrospective manner. Selecting electrolyte disorders’ adverse events to multikinase inhibitors (axitinib, cabozantinib, lenvatinib, pazopanib, sunitinib, and sorafenib). We used Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) algorithms to analyze suspected adverse reactions of electrolyte disorders induced by MKIs (which were treated for renal cell carcinoma) between January 2004 and December 2022. As of December 2022, 2772 MKIs (which were treated for renal cell carcinoma) ICSRs were related to electrolyte disorders AEs. In general, there were more AEs cases in males, except lenvatinib and 71.8% of the cases were submitted from North America. ICSRs in this study, the age group most frequently affected by electrolyte disorders AEs was individuals aged 45-64 years for axitinib, cabozantinib, pazopanib, and sunitinib, whereas electrolyte disorders AEs were more common in older patients (65-74 years) for sorafenib and lenvatinib. For all EDs documented in ICSRs (excluding missing data), the most common adverse outcome was hospitalization(1429/2674, 53.4%), and the most serious outcome was death/life-threat(281/2674, 10.5%). The prevalence of mortality was highest for sunitinib-related EDs (145/616, 23.5%), excluding missing data (n = 68), followed by cabozantinib-related EDs (20/237, 8.4%), excluding missing data (n = 1). The distribution of time-to-onset of Each drug-related ICSRs was not all the same, and the difference was statistically significant (P = 0.001). With the criteria of ROR, the six MKIs were all significantly associated with electrolyte disorders AEs, the strongest association was the association between cabozantinib and hypermagnesaemia. MKIs have been reported to have significant electrolyte disorders AEs. Patients and physicians need to recognize and monitor these potentially fatal adverse events.

PMID:38454105 | DOI:10.1038/s41598-024-56335-4

Sci Rep. 2024 Mar 7;14(1):5677. doi: 10.1038/s41598-024-56387-6.

ABSTRACT

Hypertension is a disease closely related to inflammation, and the systemic immunity-inflammation index (SII) is a new and easily detectable inflammatory marker. We aimed to investigate the association between SII and hypertension risk in a adult population in the US. We utilized data from the National Health and Nutrition Examination Survey spanning from 1999 to 2018, incorporating comprehensive information from adults reporting hypertension. This included details on blood pressure monitoring, complete blood cell counts, and standard biochemical results. The SII was computed as the platelet count multiplied by the neutrophil count divided by the lymphocyte count. We employed a weighted multivariate logistic regression model to examine the correlation between SII and hypertension. Subgroup analyses were conducted to explore potential influencing factors. Furthermore, smooth curve fitting and two-piecewise logistic regression analysis were employed to describe non-linear relationships and identify inflection points. This population-based study involved 44,070 adults aged 20-85 years. Following Ln-transformation of the SII, multivariable logistic regression revealed that, in a fully adjusted model, participants in the highest quartile of Ln(SII) had a 12% increased risk of hypertension compared to those in the lowest quartile, which was statistically significant (OR:1.12; 95% CI 1.01, 1.24; P < 0.001), with a P for trend = 0.019. Subgroup analysis indicated no significant interactions between Ln(SII) and specific subgroups except for the body mass index subgroup (all P for interaction > 0.05). Additionally, the association between Ln(SII) and hypertension displayed a U-shaped curve, with an inflection point at 5.89 (1000 cells/μl). Based on this research result, we found a U-shaped correlation between elevated SII levels and hypertension risk in American adults, with a inflection point of 5.89 (1000 cells)/μl). To validate these findings, larger scale prospective surveys are needed to support the results of this study and investigate potential mechanisms.

PMID:38454104 | DOI:10.1038/s41598-024-56387-6

Eval Program Plann. 2024 Feb 24;103:102414. doi: 10.1016/j.evalprogplan.2024.102414. Online ahead of print.

ABSTRACT

Brazil ranked third in the number of Monkeypox infected worldwide in early September 2022 and eighth in multiple deaths. Brazilian Ministry of Health prepared a public policy to face the smallpox outbreak. This paper aims to analyze the governmental public policy’ impacts on Monkeypox using survival analysis. The information in the database was collected from epidemiological bulletins on the official websites of the Brazilian Ministry of Health and the World Health Organization (WHO). The survival analysis with parametric statistical analysis, semiparametric with Cox regression, and nonparametric analysis were used. The inference of causality was perceived by the impact caused by the national public policy with the proportional reduction in the number of cases in the treatment group (Chi-sq = 117.783, p < 0.001), contrary to what was perceived in the control group, as well as survival about the time of the states that elaborated their plans based on what was made available by the government. The need to evaluate government projects should be within the scope of project management in Brazilian states and provide for more assertive decision-making in the fight against smallpox.

PMID:38452410 | DOI:10.1016/j.evalprogplan.2024.102414

Gen Hosp Psychiatry. 2024 Feb 15;88:23-29. doi: 10.1016/j.genhosppsych.2024.02.006. Online ahead of print.

ABSTRACT

OBJECTIVE: A cluster randomized controlled trial (RCT) of two interventions for addressing perinatal depression treatment in obstetric settings was conducted. This secondary analysis compared treatment referral and participation among Minoritized perinatal individuals compared to their non-Hispanic white counterparts.

METHODS: Among perinatal individuals with depression symptoms, we examined rates of treatment 1) referral (i.e., offered medications or referred to mental health clinician), 2) initiation (i.e., attended ≥1 mental health visit or reported prescribed antidepressant medication), and 3) sustainment (i.e., attended >1 mental health visit per study month or prescribed antidepressant medication at time of study interviews). We compared non-Hispanic white (NHW) (n = 149) vs. Minoritized perinatal individuals (Black, Asian, Hispanic/Latina, Pacific Islander, Native American, Multiracial, and white Hispanic/Latina n = 157). We calculated adjusted odds ratios (aOR) for each outcome.

RESULTS: Minoritized perinatal individuals across both interventions had significantly lower odds of treatment referral (aOR = 0.48;95% CI = 0.27-0.88) than their NHW counterparts. There were no statistically significant differences in the odds of treatment initiation (aOR = 0.64 95% CI:0.36-1.2) or sustainment (aOR = 0.54;95% CI = 0.28-1.1) by race/ethnicity.

CONCLUSIONS: Perinatal mental healthcare inequities are associated with disparities in treatment referrals. Interventions focusing on referral disparities across race and ethnicity are needed.

PMID:38452405 | DOI:10.1016/j.genhosppsych.2024.02.006

Biomed Tech (Berl). 2024 Mar 8. doi: 10.1515/bmt-2024-0060. Online ahead of print.

ABSTRACT

OBJECTIVES: Diagnosing the sleep apnea can be critical in preventing the person having sleep disorder from unhealthy results. The aim of this study is to obtain a sleep apnea scoring approach by comparing parametric and non-parametric power spectral density (PSD) estimation methods from EEG signals recorded from different brain regions (C4-M1 and O2-M1) for transient signal analysis of sleep apnea patients.

METHODS: Power Spectral Density (PSD) methods (Burg, Yule-Walker, periodogram, Welch and multi-taper) are examined for the detection of apnea transition states including pre-apnea, intra-apnea and post-apnea together with statistical methods.

RESULTS: In the experimental studies, EEG recordings available in the database were analyzed with PSD methods. Results showed that there are statistically significant differences between parametric and non-parametric methods applied for PSD analysis of apnea transition states in delta, theta, alpha and beta bands. Moreover, it was also revealed that PSD of EEG signals obtained from C4-M1 and O2-M1 channels were also found statistically different as proved by classification using the K-nearest neighbour (KNN) method.

CONCLUSIONS: It was concluded that not only applying different PSD methods, but also EEG signals from different brain regions provided different statistical results in terms of apnea transition states as obtained from KNN classification.

PMID:38452359 | DOI:10.1515/bmt-2024-0060

Bioinformatics. 2024 Mar 7:btae142. doi: 10.1093/bioinformatics/btae142. Online ahead of print.

ABSTRACT

MOTIVATION: Anticancer peptides (ACPs) have natural cationic properties and can act on the anionic cell membrane of cancer cells to kill cancer cells. Therefore, ACPs have become a potential anticancer drug with good research value and prospect.

RESULTS: In this paper, we propose AACFlow, an end-to-end model for identification of ACPs based on deep learning. End-to-end models have more room to automatically adjust according to the data, making the overall fit better and reducing error propagation. The combination of attention augmented convolutional neural network (AAConv) and multi-layer convolutional neural network (CNN) forms a deep representation learning module, which is used to obtain global and local information on the sequence. Based on the concept of flow network, multi-head flow-attention mechanism is introduced to mine the deep features of the sequence to improve the efficiency of the model. On the independent test dataset, the ACC, Sn, Sp, and AUC values of AACFlow are 83.9%, 83.0%, 84.8%, and 0.892, respectively, which are 4.9%, 1.5%, 8.0%, and 0.016 higher than those of the baseline model. The MCC value is 67.85%. In addition, we visualize the features extracted by each module to enhance the interpretability of the model. Various experiments show that our model is more competitive in predicting ACPs.

AVAILABILITY: The codes and datasets are accessible at https://github.com/z11code/AACFlow.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:38452348 | DOI:10.1093/bioinformatics/btae142

Anal Chem. 2024 Mar 7. doi: 10.1021/acs.analchem.3c02958. Online ahead of print.

ABSTRACT

Microorganisms are important sources of bioactive natural products. However, the complexity of microbial metabolites and the low abundance of active compounds render the isolation and purification process laborious and inefficient. During our search for active substances capable of inhibiting the newly discovered highly lethal Vibrio strain vp-HL, we found that the fermentation broth of multiple Bacillus strains exhibited antibacterial activity. However, the substances responsible for the activity remained unclear. Metabolomics, molecular networking (MN), and the Structural similarity Network Annotation Platform for Mass Spectrometry (SNAP-MS) were employed in conjunction with bioactivity screening to predict the antibacterial compounds from Bacillus strains. The analysis of fractions, and their isolation, NMR-based annotation, and bioactivity evaluation of an amicoumacin compound partially confirmed the prediction from these statistical analyses. This work presents the potential of marine Bacillus in producing active substances against Vibrio species. Additionally, it highlighted the significance and feasibility of metabolomics and MN in the dereplication of compounds and the determination of isolation targets.

PMID:38452345 | DOI:10.1021/acs.analchem.3c02958

Telemed J E Health. 2024 Mar 7. doi: 10.1089/tmj.2023.0554. Online ahead of print.

ABSTRACT

Background: The COVID-19 pandemic significantly increased telehealth adoption. Rural communities experience challenges relating to telehealth, including a shortage of clinicians, low health literacy, mistrust of medicine, and limited technology access, yet rural perceptions have not been a subject of robust study. The setting of this study was a rural Midwestern family medicine clinic within an academic health system. Methods: Surveys were given to all patients of age 18 or older visiting the clinic over a one-week period. Those who expressed interest were contacted for a semistructured interview. Descriptive statistics and chi-square testing were used to analyze survey results for significant relationships, while interview transcripts were analyzed for themes. Results: Of respondents, 27% indicated prior telehealth use and were more likely to prefer telehealth visits (p = 0.03). Perceptions of telehealth were sorted into themes, including scope of care, convenience, and technology. Telehealth was preferred for discussing test results or mental health. Barriers such as travel time and transportation access favored telehealth. Although more convenient, telehealth was found to be less effective for relationship building. The absence of physical examination during phone visits was a concern. Phone visits were more prevalent due to failure of video-based technology. Conclusions: Despite the potential to address these unique challenges in rural communities, telehealth acceptance is poor. Barriers such as accessibility of technology can be improved through governmental and health systemwide measures. Future work can help develop interventions that counter negative perceptions of telehealth while increasing interest and uptake in rural communities.

PMID:38452338 | DOI:10.1089/tmj.2023.0554

J Clin Oncol. 2024 Mar 7:JCO2302182. doi: 10.1200/JCO.23.02182. Online ahead of print.

ABSTRACT

PURPOSE: The US Food and Drug Administration (FDA) approved talazoparib with enzalutamide for first-line treatment of patients with homologous recombination repair (HRR) gene-mutated metastatic castration-resistant prostate cancer (mCRPC).

PATIENTS AND METHODS: The approval was based on the HRR gene-mutated (HRRm) population of TALAPRO-2, a randomized, double-blind trial that randomly assigned 1,035 patients with mCRPC to receive enzalutamide with either talazoparib or placebo. Two cohorts enrolled sequentially: an all-comer population (Cohort 1), followed by an HRRm-only population (Cohort 2). The independent primary end points were radiographic progression-free survival (rPFS) per blinded independent central review (BICR) in Cohort 1 (all-comers) and in the combined HRRm population (all HRRm patients from Cohorts 1 and 2). Overall survival (OS) was a key secondary end point.

RESULTS: A statistically significant improvement in rPFS by BICR was demonstrated in both the all-comers cohort and the combined HRRm population, with hazard ratio (HR) of 0.63 (95% CI, 0.51 to 0.78; P < .0001) and 0.45 (95% CI, 0.33 to 0.61; P < .0001), respectively. In an exploratory analysis of the 155 patients with BRCA-mutated (BRCAm) mCRPC, rPFS HR was 0.20 (95% CI, 0.11 to 0.36). In the non-HRRm/unknown stratum of Cohort 1 (n = 636), the rPFS HR was 0.70 (95% CI, 0.54 to 0.89). OS was immature.

CONCLUSION: Despite a statistically significant rPFS improvement in the all-comer cohort, FDA did not consider the magnitude of rPFS clinically meaningful in the context of the broad indication, combination treatment, and safety profile. Approval was therefore limited to patients with HRRm mCRPC, for whom there was a statistically significant and clinically meaningful improvement in rPFS and favorable OS results. This represents the first approval for the first-line treatment of patients with HRRm mCRPC.

PMID:38452327 | DOI:10.1200/JCO.23.02182