Nevin Manimala

Soc Sci Med. 2022 Jan 13;294:114722. doi: 10.1016/j.socscimed.2022.114722. Online ahead of print.

ABSTRACT

Relative income deprivation (RID) is a known risk factor for poor health. Previous research has proposed several measures to assess RID, e.g., Income Rank and the Yitzhaki Index. Hounkpatin et al. (2020) presented a new approach – the CR˜_i index – to account for the observation that individuals are more sensitive to the differences in incomes of others who are closer to them, rather than to comparisons with incomes of others far above them. Using a Japanese nationwide cohort of older adults (n = 62,438; mean [SD] age: 73.0 [5.6] years), this study compared the performance of alternative indices of RID in predicting health outcomes (depressive symptoms, functional capacity, and self-rated health), as well as the use of alternative CR˜_i index weights (α weight range: -0.9 to 0.9). When 0<α<1, higher income differences lead to a more significant increase in relative deprivation, while when -1< α <0, excessively high incomes contribute less to the relative deprivation of lower income individuals in the same reference group. Results showed that all measures of relative income deprivation were associated with deteriorating mental and physical health among older Japanese adults. However, while the CR˜_i index consistently outperformed the Yitzhaki Index, this did not hold true invariably when compared to the Income Rank – depending on the health outcome and the reference group. Also, while negative α parameters showed a good statistical fit in most models, the findings were not conclusive – the best-fitting CR˜_i weight parameters ranged from -0.9 to 0.9. Therefore, a clear direction for the contribution of higher incomes to relative deprivation could not be established based on the study population.

PMID:35065345 | DOI:10.1016/j.socscimed.2022.114722

Int J Pediatr Otorhinolaryngol. 2022 Jan 19;154:111050. doi: 10.1016/j.ijporl.2022.111050. Online ahead of print.

ABSTRACT

OBJECTIVE: turbinate surgery in pediatric patients is gradually increasing in popularity amongst pediatric otolaryngologists. However, despite this, there is scarce information regarding this surgical procedure in children. The present research is designed with the aim of assessing changes in nasal resistance, nasal airflow and quality of life in pediatric patients undergoing turbinate radiofrequency ablation.

METHODS: A prospective uncontrolled intervention clinical trial design was followed. Children between 4 and 15 years old undergoing turbinate radiodiofrequency ablation (TRA) were consecutively selected. Children were examined preoperatively and 1, 3, 6 and 12 months after turbinate surgery. Anterior active rhinomanometry with and without nasal decongestant and examination of the turbinates and adenoid size were carried out in each follow-up visit. The SN5 quality of live survey was answered by parents.

RESULTS: 81 children were included, 28 with associated adenoidectomy. A significant improvement in quality of life was demonstrated since the first month after TRA. Regarding nasal resistance, there was an improvement 1 month after surgery, but it only reached statistical significance for the whole sample (p < 0.001)) and for the cohort of isolated turbinate surgery (p < 0.001) at 3 months, while the values for the cohort of children who underwent adenoidectomy reached significance at 6 months after surgery (p = 0.04). The difference in nasal resistance before and after decongestant was compared to the change in nasal resistance after surgery. It demonstrated a strong correlation with the change in nasal resistance at 1 month (R = 0.985; p < 0.001), 3 months (R = 0.995; p < 0.001), 6 months (R = 0.98; p < 0.001) and 12 months (R = 0.98; p < 0.001) after surgery.

CONCLUSIONS: turbinate surgery in pediatric patients seems to be a safe procedure which objectively and subjectively improves the symptoms of children suffering from nasal obstruction.

PMID:35065329 | DOI:10.1016/j.ijporl.2022.111050

J Sport Health Sci. 2022 Jan 19:S2095-2546(22)00019-9. doi: 10.1016/j.jshs.2022.01.004. Online ahead of print.

ABSTRACT

BACKGROUND: The trade-off between the benefits of regular physical activity (PA) and the potentially detrimental effects of augmented exposure to air pollution in highly polluted regions remains unclear. This study aimed to examine whether ambient fine particulate matter (PM_2.5) exposure modified the impacts of PA volume and intensity on hypertension risk.

METHODS: We included 54,797 participants without hypertension at baseline in a nationwide cohort of the Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project. PA volume and intensity were assessed by questionnaire, and high-resolution (1×1 km) PM_2.5 estimates were generated using a satellite-based model.

RESULTS: During 413,516 person-years of follow-up, 12,100 incident hypertension cases were identified. PM_2.5 significantly modified the relationship between PA and hypertension incidence (P_interaction < 0.001). Increased PA volume was negatively associated with incident hypertension in the low PM_2.5 stratum (<59.8 μg/m³, P_trend < 0.001), with a hazard ratio (95% confidence interval (95%CI)) of 0.81 (0.74-0.88) when comparing the 4^th with the 1st quartile of PA volume. However, the health benefits were not observed in the high PM_2.5 stratum (≥59.8 μg/m³, P_trend = 0.370). Moreover, compared with light PA intensity, vigorous intensity was related to a 20% (95%CI: 9%-29%) decreased risk of hypertension for participants exposed to low PM_2.5, but a 17% (95%CI: 4%-33%) increased risk for those with high PM_2.5 levels.

CONCLUSION: PA was associated with a reduced risk of hypertension only among participants with low PM_2.5 exposure. Our findings recommended regular PA to prevent hypertension in less polluted regions and reinforced the importance of air quality improvement.

PMID:35065296 | DOI:10.1016/j.jshs.2022.01.004

Photodiagnosis Photodyn Ther. 2022 Jan 19:102730. doi: 10.1016/j.pdpdt.2022.102730. Online ahead of print.

ABSTRACT

AIM: To assess the tensile bond strength (TBS) of conventional glass ionomer cement (GIC) and resin cemented fiber post to radicular dentin when disinfected with different photosensitizers methylene blue photosensitizer (MBP), curcumin photosensitizer (CP), and laser therapy Er, Cr: YSGG laser (ECYL) MATERIAL AND METHODS: Sixty carefully extracted, non-traumatic, non-carious, closed apex human mandibular premolars were collected. Periodontal fibers, plaque, or calculi were detached. Decoration of samples was executed up till the cementoenamel junction. Samples were embedded perpendicularly in a heat cure acrylic resin. Canals of all specimens were shaped and cleaned with Protaper universal NiTi system dehydrated with paper points and obturated with gutta-percha. Post space was prepared after the removal of gutta-percha via peso reamers. Post space was disinfected with MBPv100mg/L in group 1; group 2 500mg/L and group 3 ECL. After sequential photo-irradiation therapies, fiber post was luted with resinous cement and GIC (n=10 each). After post-cementation, all specimens were subjected to tensile strength in the universal testing machine in Newton. Failure analysis was assessed at 30x magnification.TBS determination was statistically analyzed by one-way variance analysis (ANOVA), followed by the Tukey test (p = 0.05) by parallelizing different groups.

RESULTS: Fiber post cemented to radicular dentin with Rely X ARC resin cement and radicular canal disinfected with CP offered the highest TBS (289.25±3.27N). Similarly, canal space disinfected with MBP and post-luted via Rely X ARC showed the lowest TBS (281.54±4.46N). Intragroup comparison unveiled that there is no statistical difference between tensile strength sustained by two luting cement (p>0.05).

CONCLUSION: Rely X ARC resinous cement bared the highest tensile bond strength for a post-dentine-cement bond with different photo-activated canal disinfectants (MBP, CP) and Er, Cr: YSGG then Vidrion C (GIC).

PMID:35065279 | DOI:10.1016/j.pdpdt.2022.102730

Int J Infect Dis. 2022 Jan 19:S1201-9712(22)00016-9. doi: 10.1016/j.ijid.2022.01.016. Online ahead of print.

ABSTRACT

BACKGROUND: It is not clear whether previous thyroid diseases influence the course and outcomes of COVID-19.

METHODS: The study is a part of a multicentric cohort of patients with confirmed COVID-19 diagnosis from 37 hospitals. Matching for age, sex, number of comorbidities and hospital was performed for the paired analysis.

RESULTS: From 7,762 COVID-19 patients, 526 had previously diagnosed hypothyroidism and 526 were matched controls. The median age was 70 years-old and 68.3% were females. The prevalence of comorbidities was similar, except for coronary and chronic kidney diseases that were higher in the hypothyroidism group (p=0.015 and p=0.001). D-dimer levels were lower in hypothyroid patients (p=0.037). In-hospital management was similar, but hospital length-of-stay (p=0.029) and mechanical ventilation requirement (p=0.006) were lower for patients with hypothyroidism. There was a trend of lower in-hospital mortality in patients with hypothyroidism (22.1% vs. 27.0%; p=0.062).

CONCLUSION: Patients with hypothyroidism had a lower requirement of mechanical ventilation, and showed a trend of lower in-hospital mortality. Therefore, hypothyroidism does not seem to be associated with a worse prognosis.

PMID:35065257 | DOI:10.1016/j.ijid.2022.01.016

J Clin Epidemiol. 2022 Jan 19:S0895-4356(22)00011-7. doi: 10.1016/j.jclinepi.2022.01.005. Online ahead of print.

ABSTRACT

OBJECTIVE: To compare estimates of effect and variability resulting from standard linear regression analysis and hierarchical multilevel analysis with cross-classified multilevel analysis under various scenarios.

STUDY DESIGN AND SETTING: We performed a simulation study based on a data structure from an observational study in clinical mental health care. We used a Markov chain Monte Carlo (MCMC) approach to simulate 18 scenarios, varying sample sizes, cluster sizes, effect sizes and between group variances. For each scenario, we performed standard linear regression, multilevel regression with random intercept on patient level, multilevel regression with random intercept on nursing team level and cross-classified multilevel analysis.

RESULTS: Applying cross-classified multilevel analyses had negligible influence on the effect estimates. However, ignoring cross-classification led to underestimation of the standard errors of the covariates at the two cross-classified levels and to invalidly narrow confidence intervals. This may lead to incorrect statistical inference. Varying sample size, cluster size, effect size and variance had no meaningful influence on these findings.

CONCLUSION: In case of cross-classified data structures, the use of a cross-classified multilevel model helps estimating valid precision of effects, and thereby, support correct inferences.

PMID:35065230 | DOI:10.1016/j.jclinepi.2022.01.005

Pharmacol Res. 2022 Jan 19:106089. doi: 10.1016/j.phrs.2022.106089. Online ahead of print.

ABSTRACT

BACKGROUND: Our study sought to investigate the efficacy and safety of bivalirudin versus those of unfractionated heparin (UFH) in patients undergoing extracorporeal membrane oxygenation (ECMO).

METHODS: PubMed, EMBASE and Cochrane Library were searched for studies enrolling ECMO patients on bivalirudin and UFH (from inception till July 2021). Meta-analysis was conducted. The I² statistic and p value were used in measuring heterogeneity, and random effects or fixed-effect model was adopted. The Newcastle-Ottawa Scale was used for the risk of bias assessment. Sensitivity and subgroup analyses were undertaken. We performed Egger’s test to evaluate publication bias.

RESULTS: Fourteen eligible retrospective observational studies with 1501 subjects were identified. Compared with UFH, bivalirudin significantly reduced the risk of in-circuit thrombosis (OR = 0.44, 95% CI [0.31-0.61], p = 0.000), thrombosis (OR = 0.61, 95% CI [0.45-0.83], p = 0.002) and hospital mortality (OR = 0.78, 95% CI [0.61-0.99], p = 0.04) and had a positive impact on survival ECMO (OR = 1.50, 95% CI [1.04-2.16], p = 0.032). Decrease in risk of bleeding (OR = 0.36, 95% CI [0.14-0.91], p = 0.031) associated with bivalirudin was observed. Sources of heterogeneity were identified, and sensitivity analysis revealed similar results.

CONCLUSION: Our meta-analysis suggested that bivalirudin was associated with the decreased risk of in-circuit thrombosis, thrombosis, hospital mortality and bleeding in patients on ECMO and improved survival ECMO, indicating the superiority of bivalirudin to UFH in terms of efficacy and safety.

PMID:35065202 | DOI:10.1016/j.phrs.2022.106089

J Appl Microbiol. 2022 Jan 22. doi: 10.1111/jam.15461. Online ahead of print.

ABSTRACT

AIMS: Worldwide, studies regarding antimicrobial resistance in rabbits are scarce. In addition, it seems that rearing conditions have important impact on emergence and spread of antimicrobial resistant bacteria. Thus, the authors sought to 1.) assess the role of rabbits residing across diverse ecosystems as potential reservoirs of antimicrobial-resistant enterococci and 2.) investigate the genetic background of detected resistances.

METHODS AND RESULTS: Faecal samples from 60 healthy farmed rabbits (one farm), 35 laboratory rabbits, and 31 wild rabbits were analyzed. Overall, 97 enterococci isolates were accumulated, as follows: 44 E. faecium, 37 E. faecalis, 7 E. gallinarum, 5 E. durans, and 4 E. avium. E. faecalis isolates were statistically associated with farm rabbits and wild rabbits (P < 0.05). High rates of resistance were observed for tetracycline [60.8%; tetM (n = 48; 81.3%), tetO (n = 7; 11.8%), and tetL (n = 1; 1.7%)], erythromycin [43.3%; msr(A) (n = 14; 33.3%) and ermB (n = 13; 31%)], ampicillin [29.9%], streptomycin [26.8%; ant(6)-Ia (n = 3, 11.5%)] , and vancomycin [21.6%; vanA (one E. faecium + one E. faecalis; 9.5%)]. Low frequencies of resistance were observed for teicoplanin [9.2%], linezolid [8.2%], ciprofloxacin [7.2%], and gentamicin [1%; aac(6′)-Ie-aph(2″)-Ia]. Resistance to ampicillin, and vancomycin was associated with laboratory rabbits (P < 0.05). Int-Tn (Tn916/1545) was detected in 27 (27.8%) isolates, of which ten isolates co-harbored tetM and ermB genes, while 16 comprised tetM.

CONCLUSION: Findings indicate that clinically relevant enterococci species isolated from rabbits are frequently resistant to antimicrobials and harbor a range of genes associated with the Tn916/1545 family.

SIGNIFICANCE AND IMPACT OF THE STUDY: This study highlights high rates of antimicrobial-resistant enterococci from rabbits and the occurrence of both vancomycin- and linezolid- resistant isolates, potentially representing a very serious threat to human and animal health.

PMID:35064986 | DOI:10.1111/jam.15461

CPT Pharmacometrics Syst Pharmacol. 2022 Jan 22. doi: 10.1002/psp4.12763. Online ahead of print.

ABSTRACT

Clinical trials investigate treatment endpoints that usually include measurements of pharmacodynamic and efficacy biomarkers in early phase studies and patient-reported outcomes, as well as event risks or rates in late phase studies. In recent years, a systematic trend in clinical trial data analytics and modeling has been observed, where retrospective data are integrated into a quantitative framework, to prospectively support analyses of interim data and design of ongoing and future studies of novel therapeutics. Joint modeling is an advanced statistical methodology that allows for the investigation of clinical trial outcomes by quantifying the association between baseline and/or longitudinal biomarkers and event risk. Using an exemplar dataset from NSCLC studies, we propose and test a workflow for joint modeling. It allows a modeling scientist to comprehensively explore the data, build survival models, investigate goodness-of-fit, and subsequently perform outcome predictions using interim biomarker data from an ongoing study. The workflow illustrates a full process, from data exploration to predictive simulations, for selected multivariate linear and nonlinear mixed-effects models and software tools in an integrative and exhaustive manner.

PMID:35064957 | DOI:10.1002/psp4.12763

J Magn Reson Imaging. 2022 Jan 22. doi: 10.1002/jmri.28074. Online ahead of print.

ABSTRACT

BACKGROUND: Dynamic-exponential intravoxel incoherent motion (IVIM) imaging is a potential technique for prediction, monitoring, and differential diagnosis of hepatic diseases, especially liver tumors. However, the use of such technique at voxel level is still limited.

PURPOSE: To develop an unsupervised deep learning approach for voxel-wise dynamic-exponential IVIM modeling and parameter estimation in the liver.

STUDY TYPE: Prospective.

POPULATION: Ten healthy subjects (4 males; age 28 ± 6 years).

FIELD STRENGTH/SEQUENCE: Single-shot spin-echo echo planar imaging (SE-EPI) sequence with monopolar diffusion-encoding gradients (12 b-values, 0-800 seconds/mm² ) at 3.0 T.

ASSESSMENT: The proposed deep neural network (DNN) was separately trained on simulated and in vivo hepatic IVIM datasets. The trained networks were compared to the approach combining least squares with Akaike information criterion (LSQ-AIC) in terms of dynamic-exponential modeling accuracy, inter-subject coefficients of variation (CVs), and fitting residuals on the simulated subsets and regions of interest (ROIs) in the left and right liver lobes. The ROIs were delineated by a radiologist (H.-X.Z.) with 7 years of experience in MRI reading.

STATISTICAL TESTS: Comparisons between approaches were performed with a paired t-test (normality) or a Wilcoxon rank-sum test (nonnormality). P < 0.05 was considered statistically significant.

RESULTS: In simulations, DNN gave significantly higher accuracy (91.6%-95.5%) for identification of bi-exponential decays with respect to LSQ-AIC (79.7%-86.8%). For tri-exponential identification, DNN was also superior to LSQ-AIC despite not reaching a significant level (P = 0.08). Additionally, DNN always yielded comparatively low root-mean-square error for estimated parameters. For the in vivo IVIM measurements, inter-subject CVs (0.011-0.150) of DNN were significantly smaller than those (0.049-0.573) of LSQ-AIC. Concerning fitting residuals, there was no significant difference between the two approaches (P = 0.56 and 0.76) in both the simulated and in vivo studies.

DATA CONCLUSION: The proposed DNN is recommended for accurate and robust dynamic-exponential modeling and parameter estimation in hepatic IVIM imaging.

LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

PMID:35064945 | DOI:10.1002/jmri.28074