Abstract P006: Multimorbidity In Patients With Atrial Fibrillation: A Community Study

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Alanna M Chamberlain ◽  
Alvaro Alonso ◽  
Peter A Noseworthy ◽  
Jill Killian ◽  
Susan Weston ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
False Discovery Rate ◽  
Chronic Conditions ◽  
Community Study ◽  
Perfect Agreement ◽  
Holter Monitor ◽  
False Discovery ◽  
Clinical Consequences ◽  
Community Controls

Background: Multimorbidity is common in patients with atrial fibrillation (AF), yet comorbidity patterns are not well documented. Methods: The prevalence of 18 chronic conditions was obtained in patients with AF from 2013-2017 from a 27-county region in the Midwest. All patients had AF documented on an electrocardiogram or Holter monitor. To compare comorbidity patterns between patients with and without AF, controls were matched 1:1 on age (± 5 years) and sex. For AF patients and controls separately, the Somers’ D statistic was used to quantify the non-random concordance of each pair of chronic conditions beyond chance (ranging from -1 [perfect disagreement] to 1 [perfect agreement]; 0 indicating coincidental agreement by chance alone). Significance of the Somers’ D statistic was evaluated using a permutation approach with the Benjamini-Hochberg procedure for controlling the false discovery rate at 0.1%. Results: Among the 16,543 patients with AF (median age 76 years, 57% men), the most common conditions were hypertension (70%), hyperlipidemia (61%), arthritis (41%), and diabetes (40%). Many pairs of chronic conditions co-occurred more frequently than expected. However, no material differences were observed in the co-occurrence of conditions in patients with AF compared to controls (data not shown). Among patients with AF, the co-occurrence of conditions differed by age (Figure). In those ≤65 years, the strongest co-occurrence of conditions was depression/anxiety, although several condition pairs had Somers’ D statistics of >0.4. In those aged 65-74 years, hypertension/hyperlipidemia and depression/anxiety had the strongest co-occurrence, whereas hypertension/hyperlipidemia was strongest for those aged ≥75 years. Conclusion: Although differences in the co-occurrence of conditions did not exist between AF and community controls, among the patients with AF, the patterns of co-existing conditions differed by age. A better understanding of the clinical consequences of multimorbidity in AF patients is needed.

Predictors of postoperative atrial fibrillation persisting beyond hospital discharge after coronary artery bypass grafting

Perfusion ◽  
2020 ◽  
pp. 026765912097864
Author(s):  
Aschraf El-Essawi ◽  
Ahmed Abdelhalim ◽  
Steffen Groeger ◽  
Ingo Breitenbach ◽  
Rene Brouwer ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Coronary Artery ◽  
Coronary Artery Bypass Grafting ◽  
Hospital Stay ◽  
Coronary Artery Bypass ◽  
Hospital Discharge ◽  
Artery Bypass ◽  
Bypass Grafting ◽  
Artery Bypass Grafting ◽  
Holter Monitor

Objective: Minimal invasive extracorporeal circuits (MiECC) have been associated with a significant reduction in the incidence of postoperative atrial fibrillation (AF). Nevertheless, AF remains one of the most common complications following elective primary coronary artery bypass grafting (CABG). The aim of this study was to identify the predictors of AF persisting beyond the hospital stay in elective primary CABG patients. Methods: We conducted a retrospective analysis for the predictors of AF that persisted beyond discharge between all patients who received an elective isolated CABG in our institution between 2009 and 2014. Patients with a positive history for intermittent or persistent AF were excluded from the analysis. Almost all patients were discharged to a rehabilitation facility where they stayed for 3 to 4 weeks postoperatively. At rehab approximately 91% of them received Holter monitoring at least once prior to their discharge. Results: A total of 770 patients were included in the analysis of which 763 patients survived the in-hospital stay. The incidence of AF at hospital discharge was 4.2% (32/763) while that on Holter monitor at Rehab was 1.5% (10/685). Age and the type of extracorporeal circuit (ECC) utilized were the only significant predictors for both AF at discharge ( p < 0.01 both) and on Holter monitor in rehab ( p < 0.01 and 0.02, respectively). This was also confirmed on multivariate analysis. Conclusion: Our findings show that the benefits of MiECC regarding the incidence of postoperative AF persist beyond hospital discharge. They may thus positively influence the outcomes of patients beyond the early postoperative period.

scholarly journals False Discovery Rate in Linkage and Association Genome Screens for Complex Disorders

Genetics ◽  
2003 ◽  
Vol 164 (2) ◽  
pp. 829-833
Author(s):  
Chiara Sabatti ◽  
Susan Service ◽  
Nelson Freimer
Keyword(s):  
Gene Mapping ◽  
False Discovery Rate ◽  
Disease Gene ◽  
Susceptibility Genes ◽  
Complex Disorders ◽  
Disease Gene Mapping ◽  
False Discovery ◽  
Simple Step ◽  
Multiple Comparison Procedure ◽  
Step Down

Abstract We explore the implications of the false discovery rate (FDR) controlling procedure in disease gene mapping. With the aid of simulations, we show how, under models commonly used, the simple step-down procedure introduced by Benjamini and Hochberg controls the FDR for the dependent tests on which linkage and association genome screens are based. This adaptive multiple comparison procedure may offer an important tool for mapping susceptibility genes for complex diseases.

scholarly journals P14.21 Tehila Kaisman-Elbaz MD/PhD

2019 ◽  
Vol 21 (Supplement_3) ◽  
pp. iii71-iii71
Author(s):  
T Kaisman-Elbaz ◽  
Y Elbaz ◽  
V Merkin ◽  
L Dym ◽  
A Noy ◽  
...  
Keyword(s):  
Overall Survival ◽  
Multivariate Analysis ◽  
False Discovery Rate ◽  
Medical Center ◽  
Tumor Resection ◽  
Multiple Hypothesis Testing ◽  
Hemoglobin Level ◽  
Distribution Width ◽  
False Discovery ◽  
Dismal Prognosis

Abstract BACKGROUND Glioblastoma is known for its dismal prognosis though its dependency on patients’ readily available RBCs parameters defining the patient’s anemic status such as hemoglobin level and Red blood cells distribution Width (RDW) is not fully established. Several works demonstrated a connection between low hemoglobin level or high RDW values to overall glioblastoma patient’s survival, but in other works, a clear connection was not found. This study addresses this unclarity. MATERIAL AND METHODS In this work, 170 glioblastoma patients, diagnosed and treated in Soroka University Medical Center (SUMC) in the last 12 years were retrospectively inspected for their survival dependency on pre-operative RBCs parameters using multivariate analysis followed by false discovery rate procedure due to the multiple hypothesis testing. A survival stratification tree and Kaplan-Meier survival curves that indicate the patient’s prognosis according to these parameters were prepared. RESULTS Beside KPS>70 and tumor resection supplemented by oncological treatment, age<70 (HR=0.4, 95% CI 0.24–0.65), low hemoglobin level (HR=1.79, 95% CI 1.06–2.99) and RDW<14% (HR=0.57, 95% CI 0.37–0.88) were found to be prognostic to patients’ overall survival in multivariate analysis, accounting for false discovery rate of less than 5%. CONCLUSION A survival stratification highlighted a non-anemic subgroup of nearly 30% of the cohort’s patients whose median overall survival was 21.1 months (95% CI 16.2–27.2) - higher than the average Stupp protocol overall median survival of about 15 months. A discussion on the beneficial or detrimental effect of RBCs parameters on glioblastoma prognosis and its possible causes is given.

scholarly journals Associations Between Genetically Predicted Protein Levels and COVID-19 Severity

2020 ◽  
Vol 223 (1) ◽  
pp. 19-22
Author(s):  
Jingjing Zhu ◽  
Chong Wu ◽  
Lang Wu
Keyword(s):  
False Discovery Rate ◽  
Drug Repurposing ◽  
Bonferroni Correction ◽  
Host Genetics ◽  
Protein Levels ◽  
False Discovery

Abstract It is critical to identify potential causal targets for SARS-CoV-2, which may guide drug repurposing options. We assessed the associations between genetically predicted protein levels and COVID-19 severity. Leveraging data from the COVID-19 Host Genetics Initiative comparing 6492 hospitalized COVID-19 patients and 1 012 809 controls, we identified 18 proteins with genetically predicted levels to be associated with COVID-19 severity at a false discovery rate of &lt;0.05, including 12 that showed an association even after Bonferroni correction. Of the 18 proteins, 6 showed positive associations and 12 showed inverse associations. In conclusion, we identified 18 candidate proteins for COVID-19 severity.

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