METHODS: The warfarin maintenance doses for 140 patients were predicted using the dosing tool and compared with the observed maintenance dose. The impact of genotype was assessed by predicting maintenance doses with prior parameter values known to be altered by genetic variability (eg, EC50 for VKORC1 genotype). The prior population was evaluated by fitting the published kinetic-pharmacodynamic model, which underpins the Bayesian tool, to the observed data using NONMEM and comparing the model parameter estimates with published values.
RESULTS: The Bayesian tool produced positively biased dose predictions in the new cohort of patients (mean prediction error [95% confidence interval]; 0.32 mg/d [0.14-0.5]). The bias was only observed in patients requiring ≥7 mg/d. The direction and magnitude of the observed bias was not influenced by genotype. The prior model provided a good fit to our data, which suggests that the bias was not caused by different prior and posterior populations.
CONCLUSIONS: Maintenance doses for patients requiring ≥7 mg/d were overpredicted. The bias was not due to the influence of genotype nor was it related to differences between the prior and posterior populations. There is a need for a more mechanistic model that captures warfarin dose-response relationship at higher warfarin doses.
OBJECTIVE: The purpose of this study was to describe the natural history of acute elevated Micra vs traditional transvenous lead thresholds.
METHODS: Micra study VVI patients with threshold data (at 0.24 ms) at implant (n = 711) were compared with Capture study patients with de novo transvenous leads at 0.4 ms (n = 538). In both cohorts, high thresholds were defined as >1.0 V and very high as >1.5 V. Change in pacing threshold (0-6 months) with high (1.0 to ≤1.5 V) or very high (>1.5 V) thresholds were compared using the Wilcoxon signed-rank test.
RESULTS: Of the 711 Micra patients, 83 (11.7%) had an implant threshold of >1.0 V at 0.24 ms. Of the 538 Capture patients, 50 (9.3%) had an implant threshold of >1.0 V at 0.40 ms. There were no significant differences in patient characteristics between those with and without an implant threshold of >1.0 V, with the exception of left ventricular ejection fraction in the Capture cohort (high vs low thresholds, 53% vs 58%; P = .011). Patients with an implant threshold of >1.0 V decreased significantly (P < .001) in both cohorts. Micra patients with high and very high thresholds decreased significantly (P < .01) by 1 month, with 87% and 85% having 6-month thresholds lower than the implant value. However, when the capture threshold at implant was >2 V, only 18.2% had a threshold of ≤1 V at 6 months and 45.5% had a capture threshold of >2 V.
CONCLUSIONS: Pacing thresholds in most Micra patients with elevated thresholds decrease after implant. Micra device repositioning may not be necessary if the pacing threshold is ≤2 V.
METHODS AND RESULTS: The primary outcome (risk of cardiac failure, pacemaker syndrome, or syncope related to the Micra system or procedure) was compared between successfully implanted patients from the Micra IDE trial with a primary pacing indication associated with AF or history of AF (AF group) and those without (non-AF group). Among 720 patients successfully implanted with Micra, 228 (31.7%) were in the non-AF group. Reasons for selecting VVI pacing in non-AF patients included an expectation for infrequent pacing (66.2%) and advanced age (27.2%). More patients in the non-AF group had a condition that precluded the use of a transvenous pacemaker (9.6% vs. 4.7%, P = 0.013). Atrial fibrillation patients programmed to VVI received significantly more ventricular pacing compared to non-AF patients (median 67.8% vs. 12.6%; P
METHODS: Eleven case-control studies within the International Pancreatic Cancer Case-control Consortium took part in the present study, including in total 2838 case and 4748 control women. Pooled estimates of odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated using a 2-step logistic regression model and adjusting for relevant covariates.
RESULTS: An inverse OR was observed in women who reported having had hysterectomy (ORyesvs.no, 0.78; 95% CI, 0.67-0.91), remaining significant in postmenopausal women and never-smoking women, adjusted for potential PC confounders. A mutually adjusted model with the joint effect for hormone replacement therapy (HRT) and hysterectomy showed significant inverse associations with PC in women who reported having had hysterectomy with HRT use (OR, 0.64; 95% CI, 0.48-0.84).
CONCLUSIONS: Our large pooled analysis suggests that women who have had a hysterectomy may have reduced risk of PC. However, we cannot rule out that the reduced risk could be due to factors or indications for having had a hysterectomy. Further investigation of risk according to HRT use and reason for hysterectomy may be necessary.
METHODS: We assembled 1155 geographical records of yellow fever virus infection in people from 1970 to 2016. We used a Poisson point process boosted regression tree model that explicitly incorporated environmental and biological explanatory covariates, vaccination coverage, and spatial variability in disease reporting rates to predict the relative risk of apparent yellow fever virus infection at a 5 × 5 km resolution across all risk zones (47 countries across the Americas and Africa). We also used the fitted model to predict the receptivity of areas outside at-risk zones to the introduction or reintroduction of yellow fever transmission. By use of previously published estimates of annual national case numbers, we used the model to map subnational variation in incidence of yellow fever across at-risk countries and to estimate the number of cases averted by vaccination worldwide.
FINDINGS: Substantial international and subnational spatial variation exists in relative risk and incidence of yellow fever as well as varied success of vaccination in reducing incidence in several high-risk regions, including Brazil, Cameroon, and Togo. Areas with the highest predicted average annual case numbers include large parts of Nigeria, the Democratic Republic of the Congo, and South Sudan, where vaccination coverage in 2016 was estimated to be substantially less than the recommended threshold to prevent outbreaks. Overall, we estimated that vaccination coverage levels achieved by 2016 avert between 94 336 and 118 500 cases of yellow fever annually within risk zones, on the basis of conservative and optimistic vaccination scenarios. The areas outside at-risk regions with predicted high receptivity to yellow fever transmission (eg, parts of Malaysia, Indonesia, and Thailand) were less extensive than the distribution of the main urban vector, A aegypti, with low receptivity to yellow fever transmission in southern China, where A aegypti is known to occur.
INTERPRETATION: Our results provide the evidence base for targeting vaccination campaigns within risk zones, as well as emphasising their high effectiveness. Our study highlights areas where public health authorities should be most vigilant for potential spread or importation events.
FUNDING: Bill & Melinda Gates Foundation.