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Nevin Manimala Statistics

Ivabradine in the Prevention, and Reduction in Size, of Perioperative Myocardial Injury in Patients Undergoing Orthopedic Surgery for Acute Fracture

J Am Heart Assoc. 2023 Nov 20:e028760. doi: 10.1161/JAHA.122.028760. Online ahead of print.

ABSTRACT

BACKGROUND: Perioperative myocardial injury is common after major noncardiac surgery and is associated with adverse outcomes. This study investigated the use of ivabradine in patients undergoing urgent surgery for fracture.

METHODS AND RESULTS: This was a prospective, double-blind, placebo-controlled, randomized clinical trial. Participants were enrolled 1:1 into ivabradine or placebo arm, and study drug was commenced before operation and continued for 7 days or until discharge. High-sensitivity troponin I was measured daily using Abbott Alinity analyzer and assay, and heart rate data were obtained using continuous Holter monitoring. A total of 199 patients underwent acute orthopedic surgery, 98 in the ivabradine group and 101 in the placebo group. The mean age was 78.7 years (range, 77.5-79.9 years), with 68% women. The average heart rate was 5 to 11 beats per minute lower in the ivabradine group compared with the placebo group at all time points (P<0.001 for all). There was no statistically significant difference between the ivabradine and placebo groups in the number of patients who had perioperative myocardial injury: 28.6% versus 31.6% (P=0.71). In patients with perioperative myocardial injury, average peak troponin was 168.8 ng/L (±431.2 ng/L) in the ivabradine group and 2094.5 ng/L (±7201.9 ng/L) in the placebo group (P=0.16). There was no statistically significant difference between groups in 30-day mortality, blood pressure, stroke, or major adverse cardiovascular event.

CONCLUSIONS: Starting ivabradine preoperatively in elderly patients requiring acute surgery for fracture did not result in a statistically significant difference in the incidence of perioperative myocardial injury. There was no statistically significant difference in morbidity, mortality, or adverse events between treatment groups.

REGISTRATION: URL: https://www.anzctr.org.au/; Unique identifier: ACTRN12616001634460p.

PMID:37982213 | DOI:10.1161/JAHA.122.028760

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Nevin Manimala Statistics

Performance of Cardiovascular Risk Prediction Models in Korean Patients With New-Onset Rheumatoid Arthritis: National Cohort Study

J Am Heart Assoc. 2023 Nov 20:e030604. doi: 10.1161/JAHA.123.030604. Online ahead of print.

ABSTRACT

BACKGROUND: This study aimed to compare the performance of established cardiovascular risk algorithms in Korean patients with new-onset rheumatoid arthritis.

METHODS AND RESULTS: This retrospective cohort study identified patients newly diagnosed with rheumatoid arthritis without a history of cardiovascular diseases between 2013 and 2019 using the National Health Insurance Service database. The cohort was followed up until 2020 for the development of the first major adverse cardiovascular event. General cardiovascular risk prediction algorithms, such as the systematic coronary risk evaluation model, the Korean risk prediction model for atherosclerotic cardiovascular diseases, the American College of Cardiology/American Heart Association pooled equations, and the Framingham Risk Score, were used. The discrimination and calibration of cardiovascular risk prediction models were evaluated. Hazard ratios were estimated using Cox proportional hazards regression. A total of 611 patients among 24 889 patients experienced a major adverse cardiovascular event during follow-up. The median 10-year atherosclerotic cardiovascular diseases risk score was significantly higher in patients with major adverse cardiovascular events than those without. The C-statistics of risk algorithms ranged between 0.72 and 0.74. Compared with the low-risk group, the actual risk of developing major adverse cardiovascular events increased significantly in the intermediate- and high-risk groups for all algorithms. However, the risk predictions calculated from all algorithms overestimated the observed cardiovascular risk in the middle to high deciles, and only the systematic coronary risk evaluation algorithm showed comparable observed and predicted event rates in the low-intermediate deciles with the highest sensitivity.

CONCLUSIONS: The systematic coronary risk evaluation model algorithm and the general risk prediction models discriminated patients with rheumatoid arthritis appropriately. However, overestimation should be considered when applying the cardiovascular risk prediction model in Korean patients.

PMID:37982210 | DOI:10.1161/JAHA.123.030604

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Nevin Manimala Statistics

Electrogastrography in patients with gastric motility disorders

Proc Inst Mech Eng H. 2023 Nov 20:9544119231212269. doi: 10.1177/09544119231212269. Online ahead of print.

ABSTRACT

Electrogastrography (EGG) is a novel diagnostic modality for assessing the gastrointestinal tract (GI) that generates spontaneous electrical activity and monitors gastric motility. The aim of this study was to compare patients with functional dyspepsia (FD) and diabetic gastroparesis (D-GP) with healthy controls (CT) to use established findings on abnormalities of gastric motility based on EGG characteristics. In this study, 50 patients with FD, 50 D-GP patients, and 50 CT subjects were studied to compare EGG with discrete wavelet transform models (DWT) to extract signal characteristics using a variety of different qualitative and quantitative metrics from pre-prandial and postprandial states. As a result, higher statistically significant (p < 0.05*) were found in the DWT models based on power spectral density (PSD) analysis in both states. We also present that the correlations between EGG metrics and the presence of FD, D-GP, and CT symptoms were inconsistent. This paper represents that EGG assessments of FD and D-GP patients differ from healthy controls in terms of abnormalities of gastric motility. Additionally, we demonstrate that diverse datasets showed adequate gastric motility responses to a meal. We anticipate that our method will provide a comprehensive understanding of gastric motility disorders for better treatment and monitoring in both clinical and research settings. In conclusion, we present potential future opportunities for precise gastrointestinal electrophysiological disorders.

PMID:37982194 | DOI:10.1177/09544119231212269

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Nevin Manimala Statistics

Literature review: Assessing heterogeneity on cardiovascular magnetic resonance imaging- a novel approach to diagnosis and risk stratification in cardiac diseases

Eur Heart J Cardiovasc Imaging. 2023 Nov 20:jead285. doi: 10.1093/ehjci/jead285. Online ahead of print.

ABSTRACT

Cardiac disease affects the heart non-uniformly. Examples include focal septal or apical hypertrophy with reduced strain in hypertrophic cardiomyopathy (HCM), replacement fibrosis with akinesia in an infarct-related coronary artery territory and pattern of scarring in dilated cardiomyopathy. The detail and versatility of cardiovascular magnetic resonance imaging (CMR) mean it contains a wealth of information imperceptible to the naked eye and not captured by standard global measures. CMR-derived heterogeneity biomarkers could facilitate earlier diagnosis, better risk stratification and more comprehensive prediction of treatment response. Small cohort and case-control studies demonstrate feasibility of proof-of-concept structural and functional heterogeneity measures. Detailed radiomic analyses of different CMR sequences using open source software delineate unique voxel patterns as hallmarks of histopathological changes. Meanwhile measures of dispersion applied to emerging CMR strain sequences describe variable longitudinal, circumferential and radial function across the myocardium. Two of the most promising heterogeneity measures are mean absolute deviation of regional standard deviations (madSD) on native T1 and T2 and the SD of time to maximum regional radial wall motion, termed tissue synchronisation index (TSI) in a 16-segment LV model. Real world limitations include the non-standardisation of CMR imaging protocols across different centres and the testing of large numbers of radiomic features in small inadequately powered patient samples. We therefore propose a 3-step roadmap to benchmark novel heterogeneity biomarkers, including defining normal reference ranges, statistical modelling against diagnosis and outcomes in large epidemiological studies and finally, comprehensive internal and external validation.

PMID:37982176 | DOI:10.1093/ehjci/jead285

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Nevin Manimala Statistics

Algorithms for Sparse Support Vector Machines

J Comput Graph Stat. 2023;32(3):1097-1108. doi: 10.1080/10618600.2022.2146697. Epub 2022 Dec 13.

ABSTRACT

Many problems in classification involve huge numbers of irrelevant features. Variable selection reveals the crucial features, reduces the dimensionality of feature space, and improves model interpretation. In the support vector machine literature, variable selection is achieved by 1 penalties. These convex relaxations seriously bias parameter estimates toward 0 and tend to admit too many irrelevant features. The current paper presents an alternative that replaces penalties by sparse-set constraints. Penalties still appear, but serve a different purpose. The proximal distance principle takes a loss function L(β) and adds the penalty ρ2dist(β,Sk)2 capturing the squared Euclidean distance of the parameter vector β to the sparsity set Sk where at most k components of β are nonzero. If βρ represents the minimum of the objective fρ(β)=L(β)+ρ2dist(β,Sk)2, then βρ tends to the constrained minimum of L(β) over Sk as ρ tends to . We derive two closely related algorithms to carry out this strategy. Our simulated and real examples vividly demonstrate how the algorithms achieve better sparsity without loss of classification power.

PMID:37982129 | PMC:PMC10656054 | DOI:10.1080/10618600.2022.2146697

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Nevin Manimala Statistics

Second Primary Malignancy After Radioiodine Therapy in Thyroid Cancer Patient: A Nationwide Study

Nucl Med Mol Imaging. 2023 Dec;57(6):275-286. doi: 10.1007/s13139-023-00818-1. Epub 2023 Aug 18.

ABSTRACT

OBJECTIVE: This study aimed to investigate the risk of second primary malignancy after radioiodine (RAI) therapy in patients with thyroid cancer, using the National Health Insurance Service (NHIS) database.

METHODS: We extracted data from the NHIS database of South Korea, which covers the entire population of the nation. Risk of second primary malignancy in the thyroid cancer patients who received RAI therapy were compared with the thyroid cancer patients who received surgery only.

RESULTS: Between January 1, 2004, and December 31, 2018, we identified 363,155 patients who underwent thyroid surgery due to thyroid cancer for analysis. The surgery only cohort was 215,481, and the RAI cohort was 147,674 patients. A total of 19,385 patients developed second primary malignancy (solid cancer, 18,285; hematologic cancer, 1,100). There was no significant increase in the risk of second primary malignancy in patients who received a total cumulative dose of 100 mCi or less (hazard ratio [HR], 1.013; 95% confidence interval [CI], 0.979-1.049). However, a statistically significant increase in the risk of second primary malignancy was observed in patients who received 101-200 mCi (HR, 1.214; 95% CI, 1.167-1.264), 201-300 mCi (HR, 1.422; 95% CI, 1.258-1.607), and > 300 mCi (HR, 1.693; 95% CI, 1.545-1.854).

CONCLUSION: Total cumulative doses of 100 mCi or less of RAI can be safely administered without concerns about second primary malignancy. However, the risk of second primary malignancy increases in a dose-dependent manner, and the risk-benefit needs to be considered for doses over 100 mCi of RAI therapy.

PMID:37982105 | PMC:PMC10654320 | DOI:10.1007/s13139-023-00818-1

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Nevin Manimala Statistics

Comparison of Prognostic Value Between Stimulated and Nonstimulated Thyroglobulins in Differentiated Thyroid Cancer: A Retrospective Study

Nucl Med Mol Imaging. 2023 Dec;57(6):257-264. doi: 10.1007/s13139-023-00811-8. Epub 2023 Jul 3.

ABSTRACT

PURPOSE: The growing incidence of differentiated thyroid cancer (DTC) demands dependable prognostic factors to guide follow-up and treatment plans. This study investigated the prognostic value of response to therapy (RTT) assessment using TSH stimulated-thyroglobulin (sti-Tg) and nonstimulated-thyroglobulin (nonsti-Tg) and evaluates whether RTT using nonsti-Tg (nonstiRTT) can replace RTT using sti-Tg (stiRTT) in clinical practice to improve patients’ quality of life during assessment.

METHODS: We enrolled 419 DTC patients who underwent total thyroidectomy, radioactive iodine (RAI) therapy, and Tg assessment. Patients with structural incomplete responses were excluded. Initial RTT assessments based on the 2015 American Thyroid Association guidelines (excellent response; ER, indeterminate response, biochemical incomplete response) were performed 6-24 months after RAI therapy. The second RTT assessments were performed 6-24 months after the first assessment. Statistical analysis for recurrence-free survival (RFS) was done with the log-rank test for stiRTT and nonstiRTT.

RESULTS: Although initial stiRTT and nonstiRTT were significant predictors for RFS (p < 0.0001), stiRTT provided better RFS prediction than nonstiRTT. The RFS analysis of the second RTT assessment demonstrated statistical significance only for stiRTT (p < 0.0001). In 116 patients classified as ER on initial stiRTT, there was no RFS difference between patients classified as ER on either second stiRTT or nonstiRTT.

CONCLUSION: The prognostic power of stiRTT surpasses that of nonstiRTT in both the initial and second RTT assessment. Nevertheless, among patients classified as ER on initial stiRTT, a second stiRTT may not be required for those classified as ER on the second nonstiRTT.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13139-023-00811-8.

PMID:37982102 | PMC:PMC10654278 | DOI:10.1007/s13139-023-00811-8

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Nevin Manimala Statistics

Robust Alternatives to ANCOVA for Estimating the Treatment Effect via a Randomized Comparative Study

J Am Stat Assoc. 2019;114(528):1854-1864. doi: 10.1080/01621459.2018.1527226. Epub 2019 Mar 18.

ABSTRACT

In comparing two treatments via a randomized clinical trial, the analysis of covariance (ANCOVA) technique is often utilized to estimate an overall treatment effect. The ANCOVA is generally perceived as a more efficient procedure than its simple two sample estimation counterpart. Unfortunately, when the ANCOVA model is nonlinear, the resulting estimator is generally not consistent. Recently, various nonparametric alternatives to the ANCOVA, such as the augmentation methods, have been proposed to estimate the treatment effect by adjusting the covariates. However, the properties of these alternatives have not been studied in the presence of treatment allocation imbalance. In this article, we take a different approach to explore how to improve the precision of the naive two-sample estimate even when the observed distributions of baseline covariates between two groups are dissimilar. Specifically, we derive a bias-adjusted estimation procedure constructed from a conditional inference principle via relevant ancillary statistics from the observed covariates. This estimator is shown to be asymptotically equivalent to an augmentation estimator under the unconditional setting. We utilize the data from a clinical trial for evaluating a combination treatment of cardiovascular diseases to illustrate our findings.

PMID:37982094 | PMC:PMC10655936 | DOI:10.1080/01621459.2018.1527226

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Nevin Manimala Statistics

What Do Confessions Reveal About Abusive Head Trauma? A Systematic Review

Child Abuse Rev. 2020 May-Jun;29(3):253-268. doi: 10.1002/car.2627. Epub 2020 Jun 23.

ABSTRACT

Although confessions related to abusive head trauma (AHT) are reported, no detailed analysis exists. Therefore, we systematically reviewed studies of AHT confessions and examined the details, including country of origin, mechanisms and perpetrators’ characteristics [PUBLISHER – THE PRECEDING UNDERLINED TEXT IS FOR THE MARGIN]. Employing 36 search terms across three search engines, we searched Medline and CINAHL from 1963 to 2018. All relevant studies underwent two independent reviews and data extraction. Descriptive statistics were used to characterise the sample; chi square and Fisher’s exact tests were used to assess differences in demographic and clinical characteristics. Of 6759 identified studies, 157 full texts were reviewed and 55 articles from 15 countries spanning four continents were included. Included articles contained 434 confessions. The mechanisms of abuse included shaking alone (64.1%), impact alone (17.1%), shaking plus impact (18.0%) and other (0.9%). There was no statistically significant difference in the percentage of confessions reporting shaking alone when comparing continents: North America (64.0%), Europe (64.2%) and Oceania (60.0%; P=.92), or when comparing circumstances in which the confession was obtained: medical evaluation (74.6%) vs police or judicial investigations (63.4%; P=.11). Of 119 cases with identified perpetrators, 67.2 per cent were cases with males alone. Confessions reveal striking similarities in the mechanism of AHT (predominantly shaking) and occur across the globe.

PMID:37982093 | PMC:PMC10655946 | DOI:10.1002/car.2627

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Nevin Manimala Statistics

REDACS: Regional emergency-driven adaptive cluster sampling for effective COVID-19 management

Stoch Anal Appl. 2023;41(3):474-508. doi: 10.1080/07362994.2022.2033126. Epub 2022 Feb 25.

ABSTRACT

As COVID-19 is spreading, national agencies need to monitor and track several metrics. Since we do not have perfect testing programs on the hand, one needs to develop an advanced sampling strategies for prevalence study, control and management. Here we introduce REDACS: Regional emergency-driven adaptive cluster sampling for effective COVID-19 management and control and justify its usage for COVID-19. We show its advantages over classical massive individual testing sampling plans. We also point out how regional and spatial heterogeneity underlines proper sampling. Fundamental importance of adaptive control parameters from emergency health stations and medical frontline is outlined. Since the Northern hemisphere entered Autumn and Winter season (this paper was originally submitted in November 2020), practical illustration from spatial heterogeneity of Chile (Southern hemisphere, which already experienced COVID-19 winter outbreak peak) is underlying the importance of proper regional heterogeneity of sampling plan. We explain the regional heterogeneity by microbiological backgrounds and link it to behavior of Lyapunov exponents. We also discuss screening by antigen tests from the perspective of “on the fly” biomarker validation, i.e., during the screening.

PMID:37982071 | PMC:PMC10655945 | DOI:10.1080/07362994.2022.2033126