Clinical Factors and Outcomes When Real-World Heart Teams Overruled STS Risk Scores in TAVR Cases.

Objectives: This study was conducted to determine why heart teams recommended transcatheter aortic valve replacement (TAVR) versus surgical AVR (SAVR) for patients at low predicted risk of mortality (PROM) and describe outcomes of these cases. Background: Historically, referral to TAVR was based predominately on the Society of Thoracic Surgeons (STS) risk model's PROM >3%. In selected cases, heart teams had latitude to overrule these scores. The clinical reasons and outcomes for these cases are unclear. Methods: Retrospective data were gathered for all TAVR and SAVR cases conducted by 9 hospitals between 2013 and 2017. Results: Cases included TAVR patients with STS PROM >3% (n = 2,711) and ≤3% (n = 415) and SAVR with STS PROM ≤3% (n = 1,438). Leading reasons for recommending TAVR in the PROM ≤3% group were frailty (57%), hostile chest (22%), severe lung disease (16%), and morbid obesity (13%), and 44% of cases had multiple reasons. Most postoperative and 30-day outcomes were similar between TAVR groups, but the STS PROM ≤3% group had a one-day shorter length of stay (2.5 ± 3.4 vs. 3.5 ± 4.7 days; p ≤ 0.001) and higher one-year survival (91.6% vs. 86.0%, p=0.002). In patients with STS PROM ≤3%, 30-day mortality was higher for TAVR versus SAVR (2.0% vs. 0.6%; p < 0.001). Conclusions: Heart teams recommended TAVR in patients with STS PROM ≤3% primarily due to frailty, hostile chest, severe lung disease, and/or morbid obesity. Similar postoperative outcomes between these patients and those with STS PROM >3% suggest that decisions to overrule STS PROM ≤3% were merited and may have reduced SAVR 30-day mortality rate.

Severe epistaxis after posterior nasal nerve ablation requiring surgical intervention: A multi-center case series.

KEY POINTS: Severe epistaxis occurs in 2% of PNN ablation cases, independent of method or device type. Major epistaxis requiring intervention after PNN ablation can occur on average 20 days post-procedure.

Temporal trends in first-line outpatient anticoagulation treatment for cancer-associated venous thromboembolism.

BACKGROUND: First-line treatment and secondary prevention of venous thromboembolism (VTE) in patients with cancer consisted, historically, of unfractionated heparin or low-molecular weight heparin (LMWH). With recent clinical trials of direct oral anticoagulants (DOAC) showing similar efficacy as LMWH, little is known about anticoagulant prescribing patterns in patients with cancer and a VTE. This study characterized the temporal trends in first-line outpatient anticoagulation therapy for cancer-associated VTE. MATERIALS AND METHODS: This retrospective cohort study of patients who were hospitalized for a cancer-associated venous thromboembolism (VTE) between 01/01/2000 and 10/31/2017 identified patients from the cancer registries at two regions of an integrated healthcare delivery system. The primary outcome was the trend in age- and sex-adjusted rates of first-line anticoagulant therapy during the 30 days post-hospital discharge. Therapies were categorized as 1) injectable LMWH monotherapy, 2) warfarin ± injectable, 3) injectable fondaparinux monotherapy, or 4) DOAC ± injectable. RESULTS: Overall, 9816 patients were included with a mean age of 66 ± 13 years and 54% were female. From 2000 to 2003, warfarin ± injectable was used in ≈90% of cases. After 2003, there was a steady decline in warfarin use (25% in 2017) corresponding with increased LMWH use: 11% in 2003 to 55% in 2017. The DOAC ± injectable use has rapidly increased from <1% in 2014 to 20% in 2017. CONCLUSIONS: From 2000 to 2017, first-line anticoagulant therapy for cancer-associated VTE has experienced a substantial increase in LMWH and DOAC use with a resultant decline in warfarin use.

Predictive power of statistical significance.

A statistically significant research finding should not be defined as a P-value of 0.05 or less, because this definition does not take into account study power. Statistical significance was originally defined by Fisher RA as a P-value of 0.05 or less. According to Fisher, any finding that is likely to occur by random variation no more than 1 in 20 times is considered significant. Neyman J and Pearson ES subsequently argued that Fisher's definition was incomplete. They proposed that statistical significance could only be determined by analyzing the chance of incorrectly considering a study finding was significant (a Type I error) or incorrectly considering a study finding was insignificant (a Type II error). Their definition of statistical significance is also incomplete because the error rates are considered separately, not together. A better definition of statistical significance is the positive predictive value of a P-value, which is equal to the power divided by the sum of power and the P-value. This definition is more complete and relevant than Fisher's or Neyman-Peason's definitions, because it takes into account both concepts of statistical significance. Using this definition, a statistically significant finding requires a P-value of 0.05 or less when the power is at least 95%, and a P-value of 0.032 or less when the power is 60%. To achieve statistical significance, P-values must be adjusted downward as the study power decreases.