RESUMEN
Pharmaceuticals selected for exploration space missions must remain stable and effective throughout mission timeframes. Although there have been six spaceflight drug stability studies, there has not been a comprehensive analytical analysis of these data. We sought to use these studies to quantify the rate of spaceflight drug degradation and the time-dependent probability of drug failure resulting from the loss of active pharmaceutical ingredient (API). Additionally, existing spaceflight drug stability studies were reviewed to identify research gaps to be addressed prior to exploration missions. Data were extracted from the six spaceflight studies to quantify API loss for 36 drug products with long-duration exposure to spaceflight. Medications stored for up to 2.4 years in low Earth orbit (LEO) exhibit a small increase in the rate of API loss with a corresponding increase in risk of product failure. Overall, the potency for all spaceflight-exposed medications remains within 10% of terrestrial lot-matched control with a ~1.5 increase in degradation rate. All existing studies of spaceflight drug stability have focused primarily on repackaged solid oral medications, which is important because non-protective repackaging is a well-established factor contributing to loss of drug potency. The factor most detrimental to drug stability appears to be nonprotective drug repackaging, based on premature failure of drug products in the terrestrial control group. The result of this study supports a critical need to evaluate the effects of current repackaging processes on drug shelf life, and to develop and validate suitable protective repackaging strategies that help assure the stability of medications throughout the full duration of exploration space missions.
RESUMEN
BACKGROUND: Use of the sequential probability cumulative sum (CUSUM) technique may be more sensitive than standard statistical analyses in detecting a cluster of surgical failures. We applied CUSUM methods to evaluate the learning curve after a policy change by a single surgeon from routine on-pump (cardiopulmonary bypass [CPB]) to off-pump coronary artery bypass grafting (OPCAB). METHODS: Fifty-five consecutive first-time coronary artery bypass patients (CPB group) were compared with the next 55 patients undergoing an attempt at routine OPCAB using the same coronary stabilizer. The goal in OPCAB patients was to obtain complete revascularization, albeit with a low threshold for conversion to CPB to maximize patient safety during the learning curve. Preoperative patient risk was calculated using previously validated models of the Cardiac Care Network of Ontario. The occurrence of operative mortality and nine predefined major complications (myocardial infarction, bleeding, stroke, renal failure, balloon pump use, mediastinitis, respiratory failure, life-threatening arrhythmia, and sepsis) was compared between the CPB and OPCAB groups using Wilcoxon, Fisher exact, and two-tailed t tests, as well as CUSUM methodology. An intention to treat analysis was performed. RESULTS: The CPB and OPCAB groups had similar predicted mortality and length of stays (2.2% +/- 2.5%, 8.1 +/- 2.5 days versus 2.4% +/- 3.5%, 8.1 +/- 2.4 days, respectively). The mean number of grafts per patient was 3.1 +/- 0.7 in the CPB group versus 3.0 +/- 0.7 in the OPCAB group (p = 0.45). Two of 55 (3.6%) CPB patients died, as opposed to 1 of 55 (1.8%) OPCAB patients (p = 0.99). Eight of 55 CPB patients (14.5%) incurred major complications, as opposed to 4 of 55 (7.3%) OPCAB patients (p = 0.36). Median hospital length of stay was 6.0 days in the CPB group versus 5.0 days in the OPCAB group (p = 0.28). On CUSUM analysis, the failure curve in CPB patients approached the upper 80% alert line after eight cases, whereas the curve in OPCAB patients reached below the lower 80% (reassurance) boundary 28 cases after the policy change, indicating superior results in the OPCAB group despite the learning curve. CONCLUSIONS: A policy change from coronary artery bypass on CPB to routinely attempting OPCAB can be accomplished safely despite the learning curve. CUSUM analysis was more sensitive than standard statistical methods in detecting a cluster of surgical failures and successes.