To assess temporal trends in the association between newly diagnosed atrial fibrillation and death.

Community based cohort study.

Framingham Heart Study cohort, in 1972-85, 1986-2000, and 2001-15 (periods 1-3, respectively), in Framingham, MA, USA.

Participants with no atrial fibrillation, aged 45-95 in each time period, and identified with newly diagnosed atrial fibrillation (or atrial flutter) during each time period.

The main outcome was all cause mortality. Hazard ratios for the association between time varying atrial fibrillation and all cause mortality were calculated with adjustment for time varying confounding factors. The difference in restricted mean survival times, adjusted for confounders, between participants with atrial fibrillation and matched referents at 10 years after a diagnosis of atrial fibrillation was estimated. Meta-regression was used to test for linear trends in hazard ratios and restricted mean survival times over the different time periods.

5671 participants were select ratios for the association between atrial fibrillation and all cause mortality was found. click here The mean number of life years lost to atrial fibrillation at 10 years had improved significantly, but a two year gap compared with individuals without atrial fibrillation still remained.This study was performed to determine the effect of ischemic postconditioning on cell apoptosis and angiotensin II receptor type 1 (AT1), connexin 43 (Cx43), and β-tubulin mRNA expression in non-culprit arteries. Non-culprit arterial tissues were isolated from a rabbit myocardial ischemia-reperfusion model and randomly divided into sham, ischemia-reperfusion, and ischemic postconditioning groups. Cell apoptosis was detected by terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) staining. Expression of angiotensin II, AT1, Cx43, and β-tubulin mRNA was evaluated by quantitative real-time polymerase chain reaction (qRT-PCR). TUNEL analysis indicated significantly higher ratios of apoptotic cells in the ischemia-reperfusion group than in the sham group. However, significantly fewer apoptotic cells were observed in the ischemic postconditioning group than in the ischemia-reperfusion group. The qRT-PCR results indicated significantly higher expression of AT1, Cx43, and β-tubulin mRNA in the ischemia-reperfusion group than in the sham group. However, expression of AT1, Cx43, and β-tubulin was lower in the ischemic postconditioning group than in the ischemia-reperfusion group. The ratios of apoptotic cells and mRNA expression of AT1, Cx43, and β-tubulin in non-culprit arteries were increased after ischemia-reperfusion. Ischemic postconditioning may decrease these features and inhibit the progression of non-culprit arteries.

Polycystic ovarian syndrome (PCOS) is a common endocrine disorder in women. Women with PCOS have androgen excess as a defining feature. They also have increased insulin resistance and obesity, which are also risk factors for non-alcoholic fatty liver disease (NAFLD). However, published data regarding PCOS as independent risk factor for NAFLD remain controversial. Therefore, we conducted this study to evaluate the association between PCOS and NAFLD using a large national database.

We identified adult female patients (≥18 years) with PCOS using the National Inpatient Sample database between 2002 and 2014. The control group included patients who did not have a diagnosis of PCOS. Multivariate logistic regression analysis was performed to study the association of NAFLD with PCOS.

Out of a total of 50 785 354 women, 77 415 (0.15%) had PCOS. These patients were younger (32.7 vs 54.8; p<0.001) and more likely to be obese (29.4% vs 8.6%; p<0.001) compared with non-PCOS patients. However, the PCOS group had less hypertension (23.2% vs 39.8%), dyslipidaemia (12% vs 17.8%) and diabetes mellitus (18.1% vs 18.3%) (p<0.001 for all). Using multivariate logistic regression, patients with PCOS had significantly higher rate of NAFLD (OR 4.30, 95% CI 4.11 to 4.50, p<0.001).

Our study showed that patients with PCOS have four times higher risk of developing NAFLD compared with women without PCOS. Further studies are needed to assess if specific PCOS treatments can affect NAFLD progression.

Our study showed that patients with PCOS have four times higher risk of developing NAFLD compared with women without PCOS. Further studies are needed to assess if specific PCOS treatments can affect NAFLD progression.

The International Cancer Benchmarking Partnership demonstrated international differences in ovarian cancer survival, particularly for women aged 65-74 with advanced disease. These findings suggest differences in treatment could be contributing to survival disparities.

To compare clinical practice guidelines and patterns of care across seven high-income countries.

A comparison of guidelines was performed and validated by a clinical working group. To explore clinical practice, a patterns of care survey was developed. A questionnaire regarding management and potential health system-related barriers to providing treatment was emailed to gynecological specialists. Guideline and survey results were crudely compared with 3-year survival by ‘distant’ stage using Spearman’s rho.

Twenty-seven guidelines were compared, and 119 clinicians completed the survey. Guideline-related measures varied between countries but did not correlate with survival internationally. Guidelines were consistent for surgical recommenda undertake extensive/ultra-radical procedures; greater access to high-cost drugs; and auditing.

Findings suggest international variations in ovarian cancer treatment. Characteristics relating to countries with higher stage-specific survival included higher reported rates of primary surgery; willingness to undertake extensive/ultra-radical procedures; greater access to high-cost drugs; and auditing.[This corrects the article DOI 10.2196/14923.].

The rapid spread of COVID-19 means that government and health services providers have little time to plan and design effective response policies. It is therefore important to quickly provide accurate predictions of how vulnerable geographic regions such as counties are to the spread of this virus.

The aim of this study is to develop county-level prediction around near future disease movement for COVID-19 occurrences using publicly available data.

We estimated county-level COVID-19 occurrences for the period March 14 to 31, 2020, based on data fused from multiple publicly available sources inclusive of health statistics, demographics, and geographical features. We developed a three-stage model using XGBoost, a machine learning algorithm, to quantify the probability of COVID-19 occurrence and estimate the number of potential occurrences for unaffected counties. Finally, these results were combined to predict the county-level risk. This risk was then used as an estimated after-five-day-vulnerability of the county.