Category: Nevin Manimala

Res Synth Methods. 2023 Jul 10. doi: 10.1002/jrsm.1655. Online ahead of print.

ABSTRACT

Recent years have seen the development of many novel scoring tools for disease prognosis and prediction. To become accepted for use in clinical applications, these tools have to be validated on external data. In practice, validation is often hampered by logistical issues, resulting in multiple small-sized validation studies. It is therefore necessary to synthesize the results of these studies using techniques for meta-analysis. Here we consider strategies for meta analyzing the concordance probability for time-to-event data (“C-index”), which has become a popular tool to evaluate the discriminatory power of prediction models with a right-censored outcome. We show that standard meta-analysis of the C-index may lead to biased results, as the magnitude of the concordance probability depends on the length of the time interval used for evaluation (defined e.g., by the follow-up time, which might differ considerably between studies). To address this issue, we propose a set of methods for random-effects meta-regression that incorporate time directly as covariate in the model equation. In addition to analyzing nonlinear time trends via fractional polynomial, spline, and exponential decay models, we provide recommendations on suitable transformations of the C-index before meta-regression. Our results suggest that the C-index is best meta-analyzed using fractional polynomial meta-regression with logit-transformed C-index values. Classical random-effects meta-analysis (not considering time as covariate) is demonstrated to be a suitable alternative when follow-up times are small. Our findings have implications for the reporting of C-index values in future studies, which should include information on the length of the time interval underlying the calculations.

PMID:37429580 | DOI:10.1002/jrsm.1655

Bioresour Technol. 2023 Jul 8:129464. doi: 10.1016/j.biortech.2023.129464. Online ahead of print.

ABSTRACT

In this study, the effects of pumice, expanded perlite, and expanded vermiculite on nitrogen loss were examined for industrial sludge composting using the Box-Behnken experimental design. The independent factors and their levels were selected as amendment type, amendment ratio, and aeration rate, and codded as x₁, x₂, and x₃ at 3 levels (low, center, and high). The statistical significance of independent variables and their interactions were determined at 95% confidence limits by Analysis of Variance. The quadratic polynomial regression equation produced to predict the responses was solved and the optimum values of the variables were predicted by analyzing the three-dimensional response surfaces plots. The optimum conditions for minimum nitrogen loss by the regression model were as pumice of amendment type, 40% of amendment ratio, and 6 L/min of aeration rate. In this study, it was observed that time-consuming and laborious laboratory work can be minimized with the Box-Behnken experimental design.

PMID:37429554 | DOI:10.1016/j.biortech.2023.129464

Ann Thorac Surg. 2023 Jul 8:S0003-4975(23)00693-8. doi: 10.1016/j.athoracsur.2023.06.024. Online ahead of print.

ABSTRACT

BACKGROUND: We aim to longitudinally compare expanded-polytetrafluoroethylene (ePTFE) valved vs pulmonary homograft (PH) conduits after right ventricular outflow tract reconstruction in the Ross procedure.

METHODS: We identified patients undergoing a Ross procedure from June 2004 to December 2021. Echocardiographic data, catheter-based interventions or conduit replacement as well as time to first reintervention or replacement were comparatively assessed between handmade ePTFE-valved and PH conduits.

RESULTS: A total of 90 patients were identified. The median age, and weight were 13.8 years (IQR 8.08-17.80) and 48.3 kg (IQR 26.8-68.7). There were 66% (n=60) ePTFE-valved conduits and 33% (n=30) PH. The median size was 22 mm (IQR 18-24) for ePTFE-valved conduits and 25 mm (IQR 23-26) for PH conduits (p<0.001). Conduit type has no differential effect in the gradient evolution or the odds of presenting with severe regurgitation in the last follow-up echocardiogram. Out of the 26 first reinterventions, 81% were catheter-based interventions, without statistically significant differences between the groups (69% PH vs. 83% ePTFE). The overall surgical conduit replacement was 15% (n=14), being higher in the homograft group (30% vs 8%; p=0.008). However, conduit type was not associated with increased hazard for reintervention or reoperation after adjusting for covariates.

CONCLUSIONS: RVOT reconstruction using handmade ePTFE-valvedconduits after a Ross procedure provides encouraging midterm results, without a differential effect in hemodynamic performance or valve function compared to PH. These results reassure the utilization of handmade valved conduits in pediatric population and young adults. Longer follow-up of tricuspid conduits will complement valve competency assessment.

PMID:37429515 | DOI:10.1016/j.athoracsur.2023.06.024

J Biomed Inform. 2023 Jul 8:104440. doi: 10.1016/j.jbi.2023.104440. Online ahead of print.

ABSTRACT

The imputation of missing values in multivariate time series (MTS) data is a critical step in ensuring data quality and producing reliable data-driven predictive models. Apart from many statistical approaches, a few recent studies have proposed state-of-the-art deep learning methods to impute missing values in MTS data. However, the evaluation of these deep methods is limited to one or two data sets, low missing rates, and completely random missing value types. This survey performs six data-centric experiments to benchmark state-of-the-art deep imputation methods on five time series health data sets. Our extensive analysis reveals that no single imputation method outperforms the others on all five data sets. The imputation performance depends on data types, individual variable statistics, missing value rates, and types. Deep learning methods that jointly perform cross-sectional (across variables) and longitudinal (across time) imputations of missing values in time series data yield statistically better data quality compared to traditional imputation methods. Although computationally expensive, deep learning methods are practical given the current availability of high-performance computing resources, especially when data quality and sample size are highly important in healthcare informatics. Our findings highlight the importance of data-centric selection of imputation methods to optimize data-driven predictive models.

PMID:37429511 | DOI:10.1016/j.jbi.2023.104440

J Endod. 2023 Jul 8:S0099-2399(23)00391-6. doi: 10.1016/j.joen.2023.07.002. Online ahead of print.

ABSTRACT

INTRODUCTION: This study evaluated the effects of diabetes mellitus (DM) on the nanostructure of root canal dentin using high-resolution transmission electron microscopy (HRTEM) and inductively coupled plasma mass spectrometry (ICP-MS).

METHODS: Twenty extracted human premolars from diabetic and non-diabetic patients (n=10 in each group) were decoronated and sectioned horizontally into forty 2-mm-thick dentin discs, with each disc designated for a specific test. ICP-MS was used to determine the different elemental levels of Cu, Li, Zn, Se, Sr, Mn, and Mg in diabetic and non-diabetic specimens. HRTEM was used to analyze the shape and quantity of the apatite crystals in diabetic and non-diabetic dentin at the nanostructural level. Statistical analysis was performed using Kolmogorov-Smirnov and student’s t-test (p<0.05).

RESULTS: ICP-MS revealed significant differences in trace element concentrations between the diabetic and non-diabetic specimens (p<0.05), with lower levels of Mg, Zn, Sr, Li, Mn, and Se (p<0.05), and higher levels of Cu in diabetic specimens (p<0.05). HRTEM revealed that diabetic dentin exhibited a less compact structure with smaller crystallites and significantly more crystals in the 2500 nm² area (p<0.05).

CONCLUSION: Diabetic dentin exhibited smaller crystallites and altered elemental levels than non-diabetic dentin, which could explain the higher root canal treatment failure rate in diabetic patients.

PMID:37429496 | DOI:10.1016/j.joen.2023.07.002

Clin Biomech (Bristol, Avon). 2023 Jul 6;107:106040. doi: 10.1016/j.clinbiomech.2023.106040. Online ahead of print.

ABSTRACT

BACKGROUND: Rotator cuff muscles are responsible for humeral rotation. Moment arms of different regions of these muscles during humeral rotation were analyzed in neutral and abducted positions.

METHODS: In eight cadaveric shoulders, subregions of the rotator cuff muscles were identified and their excursion during humeral rotation was measured in neutral and abducted positions from an internal rotation of 30° to an external rotation of 45°, with 15° increments, using a 3-D digitizing system. Statistical tests were used to assess differences between subregions within a single muscle.

FINDINGS: The posterior-deep subregion of the supraspinatus muscle had greater moment arms compared to the anterior-superficial and anterior-middle subregions in both positions (p < 0.001). The middle and inferior subregions of the infraspinatus muscle and the teres minor muscle showed differences in moment arms compared to the superior region in an abducted position (p < 0.042). The superior subregion of the subscapularis muscle showed differences in moment arms compared to the middle and inferior subregions in an abducted position (p < 0.001).

INTERPRETATION: The posterior-deep subregion of the supraspinatus muscle behaved similar to the infraspinatus muscle, as an external rotator. The anterior-superficial and anterior-middle subregions of the supraspinatus muscle showed a biphasic behavior during rotation at a neutral position, but acted as pure external rotators during rotation at an abducted position. Inferior subregions of the infraspinatus and subscapularis muscles showed the largest moment arms compared to superior subregions. These findings support distinct functional roles of the rotator cuff muscle subregions.

PMID:37429101 | DOI:10.1016/j.clinbiomech.2023.106040

Am J Cardiol. 2023 Jul 8;202:119-130. doi: 10.1016/j.amjcard.2023.06.066. Online ahead of print.

ABSTRACT

Iron deficiency is an independent risk factor for heart failure (HF) exacerbation. We aim to study the safety and efficacy of intravenous (IV) iron therapy in patients with HF with reduced ejection fraction (HFrEF). A literature search was conducted on MEDLINE (Embase and PubMed) using a systematic search strategy by PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) until October 2022. CRAN-R software (The R Foundation for Statistical Computing, Vienna, Austria) was used for statistical analysis. The quality assessment was performed using the Cochrane Risk of Bias and Newcastle-Ottawa Scale. We included 12 studies with a total of 4,376 patients (IV iron n = 1,985 [45.3%]; standard of care [SOC] n = 2,391 [54.6%]). The mean age was 70.37 ± 8.14 years and 71.75 ± 7.01 years in the IV iron and SOC groups, respectively. There was no significant difference in all-cause mortality and cardiovascular mortality (risk ratio [RR] 0.88, 95% confidence interval [CI] 0.74 to 1.04, p <0.15). However, HF readmissions were significantly lower in the IV iron group (RR 0.73, 95% CI 0.56 to 0.96, p = 0.026). Non-HF cardiac readmissions were not significantly different between the IV iron and SOC groups (RR 0.92, 95% CI 0.82 to 1.02, p = 0.12). In terms of safety, there was a similar rate of infection-related adverse events in both arms (RR 0.86, 95% CI 0.74 to 1, p = 0.05). IV iron therapy in patients with HFrEF is safe and shows a significant reduction in HF hospitalizations compared with SOC. There was no difference in the rate of infection-related adverse events. The changing landscape of HFrEF pharmacotherapy in the last decade may warrant a re-demonstration of the benefit of IV iron with current SOC. The cost-effectiveness of IV iron use also needs further study.

PMID:37429060 | DOI:10.1016/j.amjcard.2023.06.066

Poult Sci. 2023 Jul 1;102(9):102902. doi: 10.1016/j.psj.2023.102902. Online ahead of print.

ABSTRACT

Driven by a global trend of applying replace-reduce-refine or 3Rs’ guidance for experimental animals in life sciences, chick embryo and particularly allantois with its chorioallantoic membrane have been increasingly utilized to substitute laboratory animals, which call for more extensive and updated knowledge about this novel experimental setup. In this study, being noninvasive, nonionizing, and super-contrasting with high spatiotemporal resolutions, magnetic resonance imaging (MRI) was chosen as an imaging modality for in ovo monitoring morphologic evolution of the chick embryo, allantois, and chorioallantoic membrane longitudinally throughout embryonic day (ED) 1 until ED20. Cooled in 0°C ice bath for 60 min to reduce MRI motion artifacts, 3 chick embryos (n = 60 in total) on each ED were scanned by a clinical 3.0T MRI scanner to demonstrate 3D images of both T2- and T1-weighted imaging (T2WI, T1WI) sequences at axial, sagittal, and coronal slices. The volumes of both the entire chick embryo and allantois were semi-automatically segmented based on intensity-based thresholding and region-growing algorithms. The morphometries or quantified 3D structures were achieved by refined segmentation, and confirmed by histological analyses (one for each ED). After MRI, the rest of chick embryos (n = 40) continued for incubation. The images from ED2 to ED4 could demonstrate the structural changes of latebra, suggesting its transition into a nutrient supplying channel of yolk sac. The allantois could be recognized by MRI, and its relative volumes on each ED revealed an evolving profile peaked on ED12, with a statistically significant difference from those of earlier and later EDs (P < 0.01). The hypointensity of the yolk due to the susceptibility effect of its enriched iron content overshadowed the otherwise hyperintensity of its lipid components. The chick embryos survived prior cooling and MRI till hatching on ED21. The results could be further developed into a 3D MRI atlas of chick embryo. Clinical 3.0T MRI proved effective as a noninvasive approach to study in ovo 3D embryonic development across the full period (ED1-ED20), which can complement the present knowhow for poultry industry and biomedical science.

PMID:37429051 | DOI:10.1016/j.psj.2023.102902

Ann Intern Med. 2023 Jul 11. doi: 10.7326/M22-2504. Online ahead of print.

ABSTRACT

BACKGROUND: Medical groups, health systems, and professional associations are concerned about potential increases in physician turnover, which may affect patient access and quality of care.

OBJECTIVE: To examine whether turnover has changed over time and whether it is higher for certain types of physicians or practice settings.

DESIGN: The authors developed a novel method using 100% of traditional Medicare billing to create national estimates of turnover. Standardized turnover rates were compared by physician, practice, and patient characteristics.

SETTING: Traditional Medicare, 2010 to 2020.

PARTICIPANTS: Physicians billing traditional Medicare.

MEASUREMENTS: Indicators of physician turnover-physicians who stopped practicing and those who moved from one practice to another-and their sum.

RESULTS: The annual rate of turnover increased from 5.3% to 7.2% between 2010 and 2014, was stable through 2017, and increased modestly in 2018 to 7.6%. Most of the increase from 2010 to 2014 came from physicians who stopped practicing increasing from 1.6% to 3.1%; physicians moving increased modestly from 3.7% to 4.2%. Modest but statistically significant (P < 0.001) differences existed across rurality, physician sex, specialty, and patient characteristics. In the second and third quarters of 2020, quarterly turnover was slightly lower than in the corresponding quarters of 2019.

LIMITATION: Measurement was based on traditional Medicare claims.

CONCLUSION: Over the past decade, physician turnover rates have had periods of increase and stability. These early data, covering the first 3 quarters of 2020, give no indication yet of the COVID-19 pandemic increasing turnover, although continued tracking of turnover is warranted. This novel method will enable future monitoring and further investigations into turnover.

PRIMARY FUNDING SOURCE: The Physicians Foundation Center for the Study of Physician Practice and Leadership.

PMID:37429029 | DOI:10.7326/M22-2504

JAMA Otolaryngol Head Neck Surg. 2023 Jul 10. doi: 10.1001/jamaoto.2023.1975. Online ahead of print.

ABSTRACT

IMPORTANCE: Standard cancer prognosis models typically do not include much specificity in characterizing competing illnesses or general health status when providing prognosis estimates, limiting their utility for individuals, who must consider their cancer in the context of their overall health. This is especially true for patients with oral cancer, who frequently have competing illnesses.

OBJECTIVE: To describe a statistical framework and accompanying new publicly available calculator that provides personalized estimates of the probability of a patient surviving or dying from cancer or other causes, using oral cancer as the first data set.

DESIGN, SETTING, AND PARTICIPANTS: The models used data from the Surveillance, Epidemiology, and End Results (SEER) 18 registry (2000 to 2011), SEER-Medicare linked files, and the National Health Interview Survey (NHIS) (1986 to 2009). Statistical methods developed to calculate natural life expectancy in the absence of the cancer, cancer-specific survival, and other-cause survival were applied to oral cancer data and internally validated with 10-fold cross-validation. Eligible participants were aged between 20 and 94 years with oral squamous cell carcinoma.

EXPOSURES: Histologically confirmed oral cancer, general health status, smoking, and selected serious comorbid conditions.

MAIN OUTCOMES AND MEASURES: Probabilities of surviving or dying from the cancer or from other causes, and life expectancy in the absence of the cancer.

RESULTS: A total of 22 392 patients with oral squamous cell carcinoma (13 544 male [60.5%]; 1476 Asian and Pacific Islander [6.7%]; 1792 Black [8.0%], 1589 Hispanic [7.2%], 17 300 White [78.1%]) and 402 626 NHIS interviewees were included in this calculator designed for public use for patients ages 20 to 86 years with newly diagnosed oral cancer to obtain estimates of health status-adjusted age, life expectancy in the absence of the cancer, and the probability of surviving, dying from the cancer, or dying from other causes within 1 to 10 years after diagnosis. The models in the calculator estimated that patients with oral cancer have a higher risk of death from other causes than their matched US population, and that this risk increases by stage.

CONCLUSIONS AND RELEVANCE: The models developed for the calculator demonstrate that survival estimates that exclude the effects of coexisting conditions can lead to underestimates or overestimates of survival. This new calculator approach will be broadly applicable for developing future prognostic models of cancer and noncancer aspects of a person’s health in other cancers; as registries develop more linkages, available covariates will become broader, strengthening future tools.

PMID:37429022 | DOI:10.1001/jamaoto.2023.1975