Search

Background The second-generation Carpentier-Edwards pericardial valve (Edwards Lifesciences LLC, Irvine, CA) is widely used for aortic valve replacement. However, knowledge on the long-term outcomes of patients after valve implantation is incomplete. We used microsimulation to calculate the long-term outcome of any given patient after aortic valve replacement with the Carpentier-Edwards pericardial valve. Methods A meta-analysis of 8 reports on aortic valve replacement with the Carpentier-Edwards pericardial valve (2,685 patients; 12,250 patient years) was used to estimate the hazards of valve-related events other than structural valvular deterioration. Structural valvular deterioration was described by age-dependent Weibull curves calculated from 18-year follow-up, premarket approval, Carpentier-Edwards pericardial primary data. These estimates provided the input data for the parameters of the microsimulation model, which was then used to calculate the outcomes of patients of different ages after valve implantation. The model estimates of survival were validated using two external data sets. Results The Weibull analysis estimated a median time to reoperation for structural valvular deterioration ranging from 18.1 years for a 55-year-old male to 23.2 years for a 75-year-old male. For a 65-year-old male, microsimulation calculated a life expectancy and event-free life expectancy of 10.8 and 9.1 years, respectively. The lifetime risk of at least one valve-related event was 38% and that of reoperation due to structural valvular deterioration 17%, respectively, for this patient. The model estimates of survival showed good agreement with external data. Conclusions Microsimulation provides detailed insight into the long-term prognosis of patients after aortic valve replacement. The Carpentier-Edwards pericardial valve performs satisfactorily and offers a low lifetime risk of reoperation due to structural valvular deterioration, especially for elderly patients requiring aortic valve replacement.

Background and Objectives: The performance of a prediction model is usually worse in external validation data compared to the development data. We aimed to determine at which effective sample sizes (i.e., number of events) relevant differences in model performance can be detected with adequate power. Methods: We used a logistic regression model to predict the probability that residual masses of patients treated for metastatic testicular cancer contained only benign tissue. We performed standard power calculations and Monte Carlo simulations to estimate the numbers of events that are required to detect several types of model invalidity with 80% power at the 5% significance level. Results: A validation sample with 111 events was required to detect that a model predicted too high probabilities, when predictions were on average 1.5 times too high on the odds scale. A decrease in discriminative ability of the model, indicated by a decrease in the c-statistic from 0.83 to 0.73, required 81 to 106 events, depending on the specific scenario. Conclusion: We suggest a minimum of 100 events and 100 nonevents for external validation samples. Specific hypotheses may, however, require substantially higher effective sample sizes to obtain adequate power.

Objective To study the value of a single antral follicle count and the additional value of repeated counts in different cycles for the prediction of poor ovarian response in IVF. Design Prospective. Setting Tertiary fertility center. Patient(s) One hundred twenty women undergoing their first IVF cycle. Intervention(s) Measurement of the number of antral follicles on cycle day 3 in two spontaneous cycles. Main outcome measure(s) Ovarian response. Result(s) A single antral follicle count is clearly predictive of poor ovarian response and there is good agreement between repeated measurements in subsequent cycles (area under the receiver operating characteristic curve [ROC AUC ]; cycle 1: 0.87, cycle 2: 0.85). In a logistic regression analysis, information obtained after the second cycle contributed significantly to the prediction of poor response by the antral follicle count of the first cycle. The predictive accuracy of the highest of two counts (ROC AUC 0.89) was slightly better than that of each single count. The predictive model with the highest count yielded slightly higher values of specificity and positive predictive value. Sensitivity, negative predictive value, and error rates were slightly lower. Conclusion(s) A single antral follicle count is a good predictor of poor ovarian response in IVF. Although the impact of a second antral follicle count on ovarian response predictions in IVF is statistically significant, clinical relevance is very limited. Repeating an antral follicle count in a subsequent cycle is not recommended.

Objective: To assess the predictive performance and clinical value of basal FSH as a test for ovarian reserve in in vitro fertilization (IVF) patients. Design: Meta-analysis. Setting: Tertiary fertility center. Patient(s): Patients undergoing IVF. Intervention(s): None. Main Outcome Measure(s): Poor ovarian response, nonpregnancy. Result(s): We located 21 studies that had reported on basal FSH and IVF outcome. No single study met high standards of methodological rigor; most studies are of moderate methodological quality only. The summary receiver operating characteristic curve indicated a moderate predictive performance for poor response, and a low predictive performance for nonpregnancy. Predictions with a substantial shift from pre-FSH-test probability to post-FSH test probability are only achieved at extreme cut-off levels for basal FSH. Sensitivity of such cut-off levels, for both the prediction of poor response and nonpregnancy, is limited. Conclusion(s): Clinical value of testing for basal FSH is restricted to a small minority of patients. Basal FSH should not be regarded as a useful routine test for the prediction of IVF outcome. The development of better tests to assess ovarian reserve remains of importance.

Background Aortic root replacement with cryopreserved allografts is associated with excellent hemodynamics, little endocarditis, low thromboembolic event rates, and no need for anticoagulation. There is, however, concern regarding the long-term durability of this valve substitute, especially in younger patients. Meta-analysis and microsimulation were used to calculate age-specific long-term prognosis after allograft aortic root replacement based on current evidence. Methods Our center's experience with cryopreserved allograft aortic root replacement in 165 adult patients was combined in a meta-analysis with reported and individual results from four other hospitals. Using this information, the microsimulation model predicted age- and gender-specific total and reoperation-free and event-free life expectancy. Results The pooled results comprised 629 patients with a total follow-up of 1860 patient-years (range 0 to 12.8 years). Annual risks were 0.6% for thromboembolism, 0.05% for bleeding, 0.5% for endocarditis, and 0.5% for nonstructural valve failure. Structural allograft failure requiring reoperation occurred in 15 patients, and a patient age–specific Weibull function was constructed accordingly. Calculated total life expectancy varied from 27 years in a 25-year-old to 12 years in a 65-year-old male; corresponding actual lifetime risk of reoperation was 89% and 35%, respectively. Conclusions Cryopreserved aortic allografts have an age-related limited durability. This results in a considerable lifetime risk of reoperation, especially in young patients. The combination of meta-analysis and microsimulation provides an appropriate tool for estimating individualized long-term outcome after aortic valve replacement and can be useful both for patient counseling and prognostic research purposes.

Objective: To establish whether initial screening characteristics of normogonadotropic anovulatory infertile women can aid in predicting live birth after induction of ovulation with clomiphene citrate (CC). Design: Prospective longitudinal single-center study. Setting: Specialist academic fertility unit. Patient(s): Two hundred fifty-nine couples with a history of infertility, oligoamenorrhea, and normal follicle-stimulating hormone (FSH) concentrations who have not been previously treated with any ovulation-induction medication. Intervention(s): 50, 100, or 150 mg of oral CC per day, for 5 subsequent days per cycle. Main Outcome Measure(s): Conception leading to live birth after CC administration. Result(s): After receiving CC, 98 (38%) women conceived, leading to live birth. The cumulative live birth rate within 12 months was 42% for the total study population and 56% for the ovulatory women who had received CC. Factors predicting the chances for live birth included free androgen index (testosterone/sex hormone–binding globulin ratio), body mass index, cycle history (oligomenorrhea versus amenorrhea), and the woman's age. Conclusion(s): It is possible to predict the individual chances of live birth after CC administration using two distinct prediction models combined in a nomogram. Applying this nomogram in the clinic may be a step forward in optimizing the decision-making process in the treatment of normogonadotropic anovulatory infertility. Alternative first line of treatment options could be considered for some women who have limited chances for success.