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PurposeThe aim of this study was to evaluate the utility of adding quantitative assessments of cardiac function from echocardiography to clinical factors in predicting the outcome of patients with acute pulmonary embolism (PE).MethodsPatients with a diagnosis of acute PE, based on a positive ventilation perfusion scan or computed tomography (CT) chest angiogram, were identified using the Duke University Hospital Database. Of these, 69 had echocardiograms within 24–48 h of the diagnosis that were suitable for offline analysis. Clinical features that were analyzed included age, gender, body mass index, vital signs and comorbidities. Echocardiographic parameters that were analyzed included left ventricular (LV) ejection fraction (EF), regional, free wall and global RV speckle-tracking strain, RV fraction area change (RVFAC), Tricuspid Annular Plane Systolic Excursion (TAPSE), pulmonary artery acceleration time (PAAT) and RV myocardial performance (Tei) index. Univariable and multivariable regression statistical analysis models were used.ResultsOut of 69 patients with acute PE, the median age was 55 and 48 % were female. The median body mass index (BMI) was 27 kg/m2. Twenty-nine percent of the cohort had a history of cancer, with a significant increase in cancer prevalence in non-survivors (57 % vs 29 %, p = 0.02). Clinical parameters including heart rate, respiratory rate, troponin T level, active malignancy, hypertension and COPD were higher among non-survivors when compared to survivors (p ≤ 0.05). Using univariable analysis, NYHA class III symptoms, hypoxemia on presentation, tachycardia, tachypnea, elevation in Troponin T, absence of hypertension, active malignancy and chronic obstructive pulmonary disease (COPD) were increased in non-survivors compared to survivors (p ≤ 0.05). In multivariable models, RV Tei Index, global and free (lateral) wall RVLS were found to be negatively associated with survival probability after adjusting for age, gender and systolic blood pressure (p ≤ 0.05).ConclusionThe addition of echocardiographic assessment of RV function to clinical parameters improved the prediction of outcomes for patients with acute PE. Larger studies are needed to validate these findings.

In this African-American cohort, we found that aldosterone may modify the association between serum potassium and incident diabetes. In participants with normal aldosterone, high-normal serum potassium was associated with a lower risk of diabetes than was low-normal serum potassium. Additional studies are warranted to determine whether serum potassium is a modifiable risk factor that could be a target for diabetes prevention. This trial was registered at clinicaltrials.gov as NCT00415415.

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This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2018_01_03_CJASNPodcast_18_2_L.mp3.

Objectives Data suggest that poor sleep quality as measured by the Pittsburgh Sleep Quality Index (PSQI) contributes to suboptimal diabetes control. How the subscales comprising the PSQI individually relate to diabetes control is poorly understood. Methods In order to explore how PSQI subscales relate to diabetes control, we analyzed baseline data from a trial of a telemedicine intervention for diabetes. We used multivariable modeling to examine: (1) the relationship between the global PSQI and hemoglobin A1c (HbA1c); (2) the relationships between the 7 PSQI subscales and HbA1c; and (3) medication nonadherence as a possible mediating factor. Results Global PSQI was not associated with HbA1c ( n = 279). Only one PSQI subscale, sleep disturbances, was associated with HbA1c after covariate adjustment; HbA1c increased by 0.4 points for each additional sleep disturbances subscale point (95%CI 0.1 to 0.8). Although the sleep disturbances subscale was associated with medication nonadherence (OR 2.04, 95%CI 1.27 to 3.30), a mediation analysis indicated nonadherence does not mediate the sleep disturbances-HbA1c relationship. Discussion The sleep disturbances subscale may drive the previously observed relationship between PSQI and HbA1c. The mechanism for the relationship between sleep disturbances and HbA1c remains unclear, as does the impact on HbA1c of addressing sleep disturbances.

NCT01829256.

Assessed after a median of 8 years (range 6-11 years), baseline BMI and waist circumference were not associated with incident CKD. Higher visceral adipose volume was independently associated with incident CKD (P = 0.008) in a nonlinear fashion, but this effect was limited to those with lower dietary quality (P = 0.001; P-interaction = 0.04). In additional interaction models, higher waist circumference was associated with greater risk of incident CKD among those with the low-risk APOL1 genotype (P = 0.04) but not those with a high-risk genotype (P-interaction = 0.02). Other proposed factors did not modify obesity-CKD associations. Conclusions. Higher risks associated with metabolically active visceral adipose volume and interactions with dietary quality suggest that metabolic factors may be key determinants of obesity-associated CKD risk. Interactions between obesity and APOL1 genotype should be considered in studies of African Americans.