Category: Statistics

Geriatr Gerontol Int. 2021 Aug 28. doi: 10.1111/ggi.14269. Online ahead of print.

ABSTRACT

AIMS: Sarcopenia, one of the primary diseases of the older adult population, is a condition characterized by loss of skeletal muscle mass, strength and functionality. Due to its considerable economic impact, preventive interventions for sarcopenia play an important role in the older adult population. Urine includes many indicators of physiology and pathophysiology. Urine analysis is used to diagnose many different diseases. The goal of this cohort study was to examine the relationship between urine pH level and skeletal muscle mass.

METHODS: This community-based cross-sectional study was carried out among 9712 Taiwanese individuals (4992 men and 4720 women). We used urine pH as an independent variable and skeletal muscle mass as a dependent variable. Bioelectric impedance analysis was used to measure the percentage of skeletal muscle mass (PSMM). We collected first fasting morning urine samples after overnight fasting, and urine pH was measured with a dipstick. In the by-sex and by-obesity analyses, we stratified the sample into two subgroups and a linear regression model was used for covariate adjustment.

RESULTS: In the fully adjusted model, all-subject analysis showed a statistically significant association between urine pH and the PSMM with a β coefficient of 0.820 (95% CI 0.615-1.025; P < 0.001). Additionally, by-sex analysis showed that urine pH was related to the PSMM in both sexes, with β coefficients of 0.261 (95% CI 0.006-0.516; P = 0.045) in men and 0.179 (95% CI 0.029-0.328; P = 0.019) in women. By-obesity status analysis showed that urine pH was related to the PSMM in the body mass index <27 group with a β coefficient of 0.284 (95% CI 0.101-0.466; P = 0.002) after full adjustment. However, for the body mass index ≥27 group, there was no significant relationship between urine pH and the PSMM (P > 0.05).

CONCLUSION: The results showed the impacts of urine pH levels on skeletal muscle mass in both sexes and non-obese populations. Due to its easily accessible and economical characteristics, urine analysis is a convenient way to approach patients with low skeletal muscle mass and predict sarcopenia. Geriatr Gerontol Int 2021; ••: ••-••.

PMID:34453776 | DOI:10.1111/ggi.14269

Pediatr Diabetes. 2021 Aug 28. doi: 10.1111/pedi.13260. Online ahead of print.

ABSTRACT

INTRODUCTION: Patients with beta thalassemia major (TM) have a higher risk of diabetes and an abnormal oral glucose tolerance test (OGTT), but there is no single agree monitoring parameter that reflects glycemic status. The possible mechanisms include iron overload and blood transfusion, but they require further investigation.

PURPOSE: This study explored the role of glycated hemoglobin A1c (HbA1c), fructosamine, and glycated albumin (GA) in evaluating the glucose dysregulation and to determine the potential relationship between iron deposition and glucose metabolism disorder in beta TM.

METHODS: A cross-sectional study was performed on 118 patients with beta TM and the control group consisted of 33 healthy children with no statistical differences in age, sex, and body mass index (BMI). Fast plasma glucose (FPG), fast insulin (FINS), insulin resistance index (HOMA-IRI), and insulin sensitivity index (HOMA-ISI) were compared between the patient and control groups. HbA1c, GA, fructosamine, and serum ferritin (SF) were measured in the patient group. OGTT, as well as heart and liver magnetic resonance imaging (MRI) T2*, was performed. For all statistical analyses, SPSS 21.0 was used and P<0.05 was accepted as statistically significant RESULTS: FPG, FINS, and HOMA-IRI were significantly increased while HOMA-ISI decreased in the beta TM patients when compared with those in the control group. In patients with beta TM, 17 (14.41%) of patients had been diagnosed with diabetes, while 48 (40.68%) had both impaired fasting glucose (IFG) and glucose tolerance (IGT). HbA1c, GA, and fructosamine were increased according to the degree of abnormal glucose metabolism. Statistically significant differences were found in age, serum ferritin, and cardiac T2* between the abnormal and normal OGTT groups.

CONCLUSION: HbA1c may be used as a significant measure for monitoring glycemic levels in patients with beta TM. Furthermore, glycated albumin and fructosamine were alternative indicators of glucose status. Patients with heart iron deposition or an SF > 4000 μg/L were prone to abnormal glucose metabolism, so chelation therapy should be reinforced. This article is protected by copyright. All rights reserved.

PMID:34453777 | DOI:10.1111/pedi.13260

Acta Parasitol. 2021 Aug 28. doi: 10.1007/s11686-021-00464-7. Online ahead of print.

ABSTRACT

PURPOSE: Toxocara canis is a common intestinal nematode parasite of dogs with recognized zoonotic potential in tropical countries. The purpose of this study was to determine the seroprevalence of anti-T. canis antibodies in two target dog populations: household and community-owned, distributed over three distinct geographical regions of India.

METHODS: Two recombinant proteins of T. canis, cathepsin L-1 (CL-1) and Toxocara excretory-secretory-26 (TES-26), expressed in Escherichia coli, were used for studying the prevalence of anti-T. canis antibodies in dog populations in three distinct geographical regions of the country using an IgG-enzyme-linked immunosorbent assay. A total of 615 sera, 507 from household and 108 from community owned dogs were screened for IgG antibodies.

RESULTS: ELISA with recombinant (r) CL-1 showed 37.7% and 53.7% seroreactivity in household and community owned dogs, respectively. However, the rTES-26 antigen showed higher seroreactivity of 39.6% and 87.9% in the corresponding groups of household and community owned dogs, respectively. Chi-squared analysis of the data indicated that there was not any association in the prevalence of anti-T. canis antibodies between the samples analyzed from the three regions and the two cohorts of dog groups. However, the seroprevalence was higher in community owned dogs compared to household owned dogs.

CONCLUSION: The results of the serological evaluation suggest that both the groups of dogs show high seroreactivity rates and are likely to harbor T. canis infections of tissue dwelling dormant larvae.

PMID:34453704 | DOI:10.1007/s11686-021-00464-7

J Med Virol. 2021 Aug 28. doi: 10.1002/jmv.27304. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: The safety of human papillomavirus (HPV) vaccines, one of the major challenges to public vaccination, has been controversial. This study assessed the adverse reactions of various HPV vaccines, including bivalent HPV (2vHPV), quadrivalent HPV (4vHPV), and 9-valent HPV (9vHPV) vaccines.

METHODS: PubMed, Embase, and Central databases were searched for randomized controlled trials (RCTs) on the comparative safety of HPV vaccines. A network meta-analysis was performed based on the Bayesian framework random-effects model.

RESULTS: This study included 23 RCTs. Analysis across these reports indicated that the 2vHPV vaccine was associated with significantly more systemic adverse events than the 4vHPV vaccine (risk ratio [RR]: 1.28, 95% credible interval [CrI]: 1.14 to 1.44), 9vHPV vaccine (RR: 1.25, 95% CrI: 1.06 to 1.49), and placebo (RR: 1.31, 95% CrI: 1.18 to 1.46). However, there were no statistically significant differences in serious adverse events between the vaccinated and placebo groups. For injection site adverse events, there were substantial inconsistencies between the direct and indirect effects; therefore, the analysis results of the safety were presented only for systemic and serious adverse events.

CONCLUSIONS: The 2vHPV vaccine resulted in more systemic adverse events than other vaccines and placebo. No significant differences in serious adverse events were observed. Further studies are needed to obtain more information regarding the safety of HPV vaccines. This article is protected by copyright. All rights reserved.

PMID:34453758 | DOI:10.1002/jmv.27304

Clin Transl Oncol. 2021 Aug 28. doi: 10.1007/s12094-021-02700-y. Online ahead of print.

ABSTRACT

BACKGROUND: Patients with prostate-specific antigen (PSA) persistence are at the increased risk of disease progression. The aim of our study was to evaluate the impact of early salvage therapy on oncological outcomes in patients with persistent PSA after radical prostatectomy (RP).

METHODS: Within a single tertiary centre database, we identified men with persistent (≥ 0.1 ng/ml) versus undetectable (< 0.1 ng/ml) PSA 4-8 weeks after RP for high-risk prostate cancer (HRPCa). The cumulative incidence function was used to estimate cancer-specific survival (CSS) and clinical progression-free survival (CPFS). The Kaplan-Meier method was used to estimate overall survival (OS). The effects on oncological outcomes of salvage radiotherapy (SRT) ± androgen deprivation therapy (ADT) vs. ADT monotherapy were tested in the subgroup of patients with persistent PSA.

RESULTS: Of 414 consecutive patients who underwent RP for HRPC, 125 (30.2%) had persistent PSA. Estimated 10-year CPFS, CSS and OS for men with persistent vs. undetectable PSA were 63.8% vs. 93.5%, 78.5% vs. 98.3% and 54% vs. 83.2% (all p < 0.0001), respectively. In men with persistent PSA, ADT alone was associated with higher risk (hazard ratio (HR) for worse CSS (HR 3.9, p = 0.005) and OS (HR 4.7, p < 0.0001) but not for CP (HR 1.6, p = 0.2) when compared with SRT ± ADT.

CONCLUSION: In patients who underwent RP for HRPCa, persistent PSA was associated with poor oncological outcomes. Early SRT ± ADT resulted in significantly improved CSS and OS in men with persistent PSA comparing with early androgen deprivation monotherapy.

PMID:34453699 | DOI:10.1007/s12094-021-02700-y

Diabetes Ther. 2021 Aug 28. doi: 10.1007/s13300-021-01139-2. Online ahead of print.

ABSTRACT

INTRODUCTION: In the randomized, open-label, parallel-arm, active-controlled phase III AWARD-CHN2 trial, once-weekly dulaglutide plus concomitant oral antihyperglycemic medications (OAMs) improved HbA1c over 26 weeks compared with once-daily insulin glargine in patients with type 2 diabetes mellitus (T2DM). This post-hoc subgroup analysis of AWARD-CHN2 investigated the pancreatic safety of dulaglutide in Chinese patients with T2DM, stratified by potential influencing factors.

METHODS: Changes in pancreatic enzyme (pancreatic amylase, total amylase, and lipase) levels over 26 weeks were assessed and stratified by patient age (< 60, ≥ 60 years), sex (female, male), duration of diabetes (< 10, ≥ 10 years), baseline weight (< 70, ≥ 70 kg), BMI (< 25, ≥ 25 kg/m²), HbA1c (< 8.5, ≥ 8.5%), triglycerides (< 2.3, ≥ 2.3 mmol/L), and concomitant OAMs (metformin, sulfonylurea, metformin plus sulfonylurea).

RESULTS: A total of 203 Chinese patients with T2DM were included in this post-hoc analysis. Pancreatic enzyme levels increased within the normal range from baseline to Week 26, and no pancreatitis events were confirmed by independent adjudication. Least-squares mean increase in pancreatic amylase (U/L) from baseline to Week 26 was comparable across all subgroups with no statistically (all P-values > 0.05) or clinically significant between-group differences for age (< 60 years: 5.34; ≥ 60 years: 6.71), sex (female: 5.85; male: 5.66), duration of diabetes (< 10 years: 6.15; ≥ 10 years: 4.85), weight (< 70 kg: 6.19; ≥ 70 kg: 5.39), BMI (< 25 kg/m²: 5.92; ≥ 25 kg/m²: 5.61), HbA1c (< 8.5%: 6.82; ≥ 8.5%: 4.08), triglycerides (< 2.3 mmol/L: 4.94; ≥ 2.3 mmol/L: 8.04), and concomitant OAMs (metformin: 5.68; sulfonylurea: 5.44; metformin plus sulfonylurea: 5.87). Similar results were observed for total amylase and lipase.

CONCLUSION: In Chinese patients with T2DM receiving dulaglutide 1.5 mg in AWARD-CHN2, elevations of pancreatic enzymes over 26 weeks were within the normal range and were neither associated with pancreatitis nor baseline factors, which suggests the clinical use of dulaglutide in Chinese patients with T2DM is not associated with pancreatic safety issues.

CLINICAL TRIAL REGISTRATION: NCT01648582.

PMID:34453682 | DOI:10.1007/s13300-021-01139-2

J Thromb Thrombolysis. 2021 Aug 28. doi: 10.1007/s11239-021-02463-x. Online ahead of print.

ABSTRACT

RE-COVERY DVT/PE is a two-phase, international, observational study of anticoagulant therapy in patients with deep vein thrombosis and/or pulmonary embolism (DVT/PE). The objective of the second phase was to compare the safety and effectiveness of dabigatran versus a vitamin K antagonist (VKA) over 1 year of follow-up. Primary safety and effectiveness outcomes were major or clinically relevant nonmajor bleeding events (MBE/CRNMBEs) and symptomatic recurrent venous thromboembolism (VTE) (including deaths related to recurrent VTE). To minimize bias due to unbalanced patient characteristics, only patients in an overlapping range of estimated propensity scores were included (analytic set), and propensity score weighting was applied to compare outcomes. Outcome analysis used an as-treated approach, censoring patients after they stopped or switched their initial anticoagulant. Overall, 3009 patients enrolled from 2016 to 2018 were eligible: 60% were diagnosed with DVT alone, 21% with PE alone, and 19% with DVT plus PE. The analytic set consisted of 2969 patients. The incidence rate in %/year (95% confidence interval [CI]) of MBE/CRNMBEs was 2.63 (1.79-3.74) with dabigatran versus 4.48 (3.23-6.06) with warfarin; hazard ratio 0.63 (95% CI 0.32-1.25). For symptomatic recurrent nonfatal or fatal VTE the incidence rate was 1.53 (0.91-2.42) with dabigatran versus 2.01 (1.21-3.14) with VKAs; hazard ratio 0.78 (95% CI 0.30-2.02). In conclusion, we found lower annualized rates of MBE/CRNMBEs with dabigatran than VKA, although the difference was not statistically significant. Annualized rates of symptomatic VTE or related mortality were similar with dabigatran and VKA. These observational results with 1 year of follow-up reflect those of the randomized clinical trials. Trial registration: ClinicalTrials.gov identifier NCT02596230, first registered November 4, 2015.

PMID:34453675 | DOI:10.1007/s11239-021-02463-x

J Cardiovasc Transl Res. 2021 Aug 28. doi: 10.1007/s12265-021-10151-7. Online ahead of print.

ABSTRACT

Inadequate at-home management and self-awareness of heart failure (HF) exacerbations are known to be leading causes of the greater than 1 million estimated HF-related hospitalizations in the USA alone. Most current at-home HF management protocols include paper guidelines or exploratory health applications that lack rigor and validation at the level of the individual patient. We report on a novel triage methodology that uses machine learning predictions for real-time detection and assessment of exacerbations. Medical specialist opinions on statistically and clinically comprehensive, simulated patient cases were used to train and validate prediction algorithms. Model performance was assessed by comparison to physician panel consensus in a representative, out-of-sample validation set of 100 vignettes. Algorithm prediction accuracy and safety indicators surpassed all individual specialists in identifying consensus opinion on existence/severity of exacerbations and appropriate treatment response. The algorithms also scored the highest sensitivity, specificity, and PPV when assessing the need for emergency care. Here we develop a machine-learning approach for providing real-time decision support to adults diagnosed with congestive heart failure. The algorithm achieves higher exacerbation and triage classification performance than any individual physician when compared to physician consensus opinion.

PMID:34453676 | DOI:10.1007/s12265-021-10151-7

Environ Sci Pollut Res Int. 2021 Aug 28. doi: 10.1007/s11356-021-16089-2. Online ahead of print.

ABSTRACT

Precise carbon price forecasting matters a lot for both regulators and investors. The improvement of carbon price forecasting can not only provide investors with rational advice but also make for energy conservation and emission reduction. But traditional methods do not perform well in prediction because of the nonlinearity and non-stationarity of carbon price. In this study, an innovative multiscale nonlinear integration model is proposed to improve the accuracy of carbon price forecasting, which combines optimal feature reconstruction and biphasic deep learning. For one thing, the optimal feature reconstruction, including variational mode decomposition (VMD) and sample entropy (SE), is used to extract different features from the original carbon price effectively. For another thing, biphasic deep learning based on deep recurrent neural network (DRNN) and gate recurrent unit (GRU) is applied to predict carbon price. DRNN, a novel framework of deep learning, is applied to predict each component. Meanwhile, GRU is used for nonlinear integration, and the final prediction of carbon price can be acquired through this procedure. For illustration and comparison, this study takes carbon price from Beijing, Hubei, and Shanghai in China as sample data to examine the capability of the proposed model. The empirical result proves that the new hybrid model can improve the carbon price predictive accuracy in consideration of statistical measurement. Hence, the novel hybrid model can be considered as an efficient way of predicting carbon prices.

PMID:34453680 | DOI:10.1007/s11356-021-16089-2

Biometrics. 2021 Aug 27. doi: 10.1111/biom.13555. Online ahead of print.

ABSTRACT

Censored survival data are common in clinical trial studies. We propose a unified framework for sensitivity analysis to censoring at random in survival data using multiple imputation and martingale, called SMIM. The proposed framework adopts the δ-adjusted and control-based models, indexed by the sensitivity parameter, entailing censoring at random and a wide collection of censoring not at random assumptions. Also, it targets a broad class of treatment effect estimands defined as functionals of treatment-specific survival functions, taking into account missing data due to censoring. Multiple imputation facilitates the use of simple full-sample estimation; however, the standard Rubin’s combining rule may overestimate the variance for inference in the sensitivity analysis framework. We decompose the multiple imputation estimator into a martingale series based on the sequential construction of the estimator and propose the wild bootstrap inference by resampling the martingale series. The new bootstrap inference has a theoretical guarantee for consistency and is computationally efficient compared to the non-parametric bootstrap counterpart. We evaluate the finite-sample performance of the proposed SMIM through simulation and an application on an HIV clinical trial. This article is protected by copyright. All rights reserved.

PMID:34453313 | DOI:10.1111/biom.13555