Greenwood’s formula is used to calculate the standard errors, and the log-log method is used to produce the 2-sided 95% confidence bounds. Confidence intervals are provided as a way to indicate the degree of certainty of the estimates. As performance experience accumulates, the accuracy of the estimation improves. The survival curves are statistical estimates. For example, a device survival probability of 90% indicates that through the stated follow-up time, the device had a 10% risk of incurring a product performance event since the time of implant. This survival estimate is a good representation of the probability a device will survive a period of time without a product performance event. These figures show the percentage of implanted devices that remain free from product performance-related events at various time points.
Throughout this report, cumulative device survival plots are presented. Thus, in some cases sample sizes may fluctuate from one time interval to the next interval.
Left truncation provides a statistical technique that uses data from existing devices while appropriately adjusting the device survival curves for the time the device was not actively followed in the registry. For the PPR analysis, a statistical method to incorporate data from these retrospectively enrolled devices was applied. 1 The survival probability of such a device is conditional on survival to the time when the device enters the registry. In some cases in the registry, active surveillance of a device starts after the device was implanted, which is called left truncation. 1 The estimates are intended to illustrate the probability that a device will survive for a given number of years without a product performance related event.Īctive surveillance normally begins at the time of implant and continues until a product performance or censoring event occurs. These survival probabilities are estimated using the Kaplan-Meier method. Device performance is expressed in terms of device survival estimates, where ”survival” refers to freedom from a product performance event, not the survival of the patient.
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