Permutation Testing and Bootstrapping: NonParametric Approaches to Statistical Testing and Estimation

No abstract availabl

Food Acceptability, Menu Fatigue, and Aversion on ISS Missions

The acceptability of the spaceflight food system has been linked to caloric intake and associated nutritional benefits. The diets of the United States Operating Segment crewmembers during a mission are restricted to 200 processed and prepackaged standard menu items supplemented with personal preference foods. ISS crew members have noted in debriefs that they would prefer more food variety for the length of the missions and they tire of certain foods over six months. It is possible that menu fatigue leads to decreases in acceptability and increased aversion to available foods, potentially contributing to the body mass loss often experienced by ISS crew. However, the impact of repeat food consumption on acceptability within the current spaceflight food system has not yet been systematically investigated. Limited variety and crew preferences within food categories may have more severe physical and behavioral health and performance consequences as mission duration increases. Characterizing the relationship between food acceptability and mission duration will contribute to defining requirements for an acceptable food system that will support crew health and performance on long duration missions

Lifetime Surveillance of Astronaut Health (LSAH) / Life Sciences Data Archive (LSDA) Data Request Helpdesk

This session is intended to provide to HRP IWS attendees instant feedback on archived astronaut data, including such topics as content of archives, access, request processing, and data format. Members of the LSAH and LSDA teams will be available at a 'help desk' during the poster sessions to answer questions from researchers

NASA Astronaut Urinary Conditions Associated with Spaceflight

INTRODUCTION: Spaceflight is associated with many factors which may promote kidney stone formation, urinary retention, and/or Urinary Tract Infection (UTI). According to ISS mission predictions supplied by NASA's Integrated Medical Model, kidney stone is the second and sepsis (urosepsis as primary driver) the third most likely reason for emergent medical evacuation from the International Space Station (ISS). METHODS: Inflight and postflight medical records of NASA astronauts were reviewed for urinary retention, UTI and kidney stones during Mercury, Gemini, Apollo, Mir, Shuttle, and ISS expeditions 1-38. RESULTS: NASA astronauts have had 7 cases of kidney stones in the 12 months after flight. Three of these cases occurred within 90 to 180 days after landing and one of the seven cases occurred in the first 90 days after flight. There have been a total of 16 cases (0.018 events per person-flights) of urinary retention during flight. The event rates per mission are nearly identical between Shuttle and ISS flights (0.019 vs 0.021 events per person-flights). In 12 of the 16 cases, astronauts had taken at least one space motion sickness medication. Upon further analysis, it was determined that the odds of developing urinary retention in spaceflight is 3 times higher among astronauts who took promethazine. The female to male odds ratio for inflight urinary retention is 11:14. An astronaut with urinary retention is 25 times more likely to have a UTI with a 17% infection rate per mission. There have been 9 reported UTIs during spaceflight. DISCUSSION: It is unclear if spaceflight carries an increased post-flight risk of kidney stones. Regarding urinary retention, the female to male odds ratio is higher during flight compared to the general population where older males comprise almost all cases due to prostatic hypertrophy. This female prevalence in spaceflight is even more concerning given the fact that there have been many more males in space than females. Terrestrial medications with a known side effect of urinary retention are also associated with urinary retention during flight. However, not all cases of urinary retention surrounded medication use inflight. It is also known that UTI is a terrestrial cause of urinary retention. Furthermore, the treatment of urinary retention with a urinary catheter may be more likely to initiate a UTI in space than on the ground, as aseptic techniques can be particularly challenging with an inexperienced provider in a free-floating environment. Inflight urinary retention and UTI have proven to be highly associated and urinary risks should be considered collectively when planning for space flight

A Network-Based Algorithm for Clustering Multivariate Repeated Measures Data

The National Aeronautics and Space Administration (NASA) Astronaut Corps is a unique occupational cohort for which vast amounts of measures data have been collected repeatedly in research or operational studies pre-, in-, and post-flight, as well as during multiple clinical care visits. In exploratory analyses aimed at generating hypotheses regarding physiological changes associated with spaceflight exposure, such as impaired vision, it is of interest to identify anomalies and trends across these expansive datasets. Multivariate clustering algorithms for repeated measures data may help parse the data to identify homogeneous groups of astronauts that have higher risks for a particular physiological change. However, available clustering methods may not be able to accommodate the complex data structures found in NASA data, since the methods often rely on strict model assumptions, require equally-spaced and balanced assessment times, cannot accommodate missing data or differing time scales across variables, and cannot process continuous and discrete data simultaneously. To fill this gap, we propose a network-based, multivariate clustering algorithm for repeated measures data that can be tailored to fit various research settings. Using simulated data, we demonstrate how our method can be used to identify patterns in complex data structures found in practice

Nasal Congestion on the International Space Station

No abstract availabl

NASA Astronaut Urinary Conditions Associated With Spaceflight

No abstract availabl

The Integrated Medical Model: A Probabilistic Simulation Model Predicting In-Flight Medical Risks

The Integrated Medical Model (IMM) is a probabilistic model that uses simulation to predict mission medical risk. Given a specific mission and crew scenario, medical events are simulated using Monte Carlo methodology to provide estimates of resource utilization, probability of evacuation, probability of loss of crew, and the amount of mission time lost due to illness. Mission and crew scenarios are defined by mission length, extravehicular activity (EVA) schedule, and crew characteristics including: sex, coronary artery calcium score, contacts, dental crowns, history of abdominal surgery, and EVA eligibility. The Integrated Medical Evidence Database (iMED) houses the model inputs for one hundred medical conditions using in-flight, analog, and terrestrial medical data. Inputs include incidence, event durations, resource utilization, and crew functional impairment. Severity of conditions is addressed by defining statistical distributions on the dichotomized best and worst-case scenarios for each condition. The outcome distributions for conditions are bounded by the treatment extremes of the fully treated scenario in which all required resources are available and the untreated scenario in which no required resources are available. Upon occurrence of a simulated medical event, treatment availability is assessed, and outcomes are generated depending on the status of the affected crewmember at the time of onset, including any pre-existing functional impairments or ongoing treatment of concurrent conditions. The main IMM outcomes, including probability of evacuation and loss of crew life, time lost due to medical events, and resource utilization, are useful in informing mission planning decisions. To date, the IMM has been used to assess mission-specific risks with and without certain crewmember characteristics, to determine the impact of eliminating certain resources from the mission medical kit, and to design medical kits that maximally benefit crew health while meeting mass and volume constraints

Changes in performance and bio-mathematical model performance predictions during 45 days of sleep restriction in a simulated space mission

Lunar habitation and exploration of space beyond low-Earth orbit will require small crews to live in isolation and confinement while maintaining a high level of performance with limited support from mission control. Astronauts only achieve approximately 6 h of sleep per night, but few studies have linked sleep deficiency in space to performance impairment. We studied crewmembers over 45 days during a simulated space mission that included 5 h of sleep opportunity on weekdays and 8 h of sleep on weekends to characterize changes in performance on the psychomotor vigilance task (PVT) and subjective fatigue ratings. We further evaluated how well bio-mathematical models designed to predict performance changes due to sleep loss compared to objective performance. We studied 20 individuals during five missions and found that objective performance, but not subjective fatigue, declined from the beginning to the end of the mission. We found that bio-mathematical models were able to predict average changes across the mission but were less sensitive at predicting individual-level performance. Our findings suggest that sleep should be prioritized in lunar crews to minimize the potential for performance errors. Bio-mathematical models may be useful for aiding crews in schedule design but not for individual-level fitness-for-duty decisions

Validation of the Nasa Integrated Medical Model: a Space Flight Medical Risk Prediction Tool

The Human Research Program funded the development of the Integrated Medical Model (IMM) to quantify the medical component of overall mission risk. The IMM uses Monte Carlo simulation methodology, incorporating space flight and ground medical data, to estimate the probability of mission medical outcomes and resource utilization. To determine the credibility of IMM output, the IMM project team completed two validation studies that compared IMM predicted output to observed medical events from a selection of Shuttle Transportation System (STS) and International Space Station (ISS) missions. The validation study results showed that the IMM underpredicted the occurrence of ~10% of the modeled medical conditions for the STS missions and overpredicted ~20% of the modeled medical conditions for the ISS missions. These findings imply that the strength of IMM predictions to inform decisions depends on simulated mission specifications including length. This discrepancy could result from medical recording differences between ISS and STS that possibly influence observed incidence rates, IMM combining all "mission type" data as constant occurrence rate or fixed proportion across both mission types, misspecification of symptoms to conditions, and gaps in the literature informing the model. Some of these issues will be alleviated by updating the IMM source data through incorporation of the observed validation data