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M Van Baalen

Publications and source records attributed to M Van Baalen.

9 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Demystification of Processes that Effect Prioritization of Space Radiation Element Research

In an effort to demystify how research funding priorities are established , the Space Radiation Element will present an introduction to the Human Space Risk Board (HSRB) framework that is that used to inform Human System Risk and can be found at https://humanresearchroadmap.nasa.gov/Risks/. These risks are based on the consequences of hazards (space radiation, altered gravity, isolation & confinement, distance from earth and hostile/closed environment) a human body is exposed to during spaceflight. The HSRB regularly evaluates risks to humans in space which includes updating the knowledge base to reflect emerging research, the development of effective countermeasures, and evolving operational approaches toward addressing those risks. To increase understanding and clarity, this talk will step through how risks (with the focus on Risk of Radiation Carcinogenesis) are assigned a rating (and color code) based on design reference missions, likelihood, and consequence. Further, The Space Radiation Element will discuss how risks, including the magnitude/rating, required technical deliverables, and expected products from current research efforts affect our element strategy and prioritization of research. In addition, navigation of the publicly available www.nasa.gov/hrp, will be demonstrated to inform principal investigators where this information can be readily accessed. Our primary objectives for this presentation/demonstration are to demystify The Space Radiation Element’s internal processes and to educate researchers concerning publicly available documents that can be used to better align their proposed objectives with Element priorities.

J A Zawaski↗
NASA NTRSDate not supplied

High Value Risk Targets in Human System Risk

The Human System Risk Board (HSRB) has the overall responsibility for tracking the evolution of the top ~30 human system risks that it has identified to be associated with human spaceflight. The Board is also charged with maintaining a consistent, integrated process to mitigate those risks, and developing evidence-based risk posture recommendations. Each Risk Custodian Team (RCT) identifies High Value Risk Mitigation Targets (HVRMT) that have the highest likelihood or greatest impact in reducing their risk. These typically include areas where there are major gaps in knowledge or capability; or other targets that promise to yield returns worthy of investments in time, money and other resources by stakeholders interested in reducing Human System Risk. As part of the review of each risk the Board members consider and discuss the HVRMT statements, which are then approved by the Board Chair. High Value Risk Mitigation Targets can include research activities funded by the Human Research Program, but often involve recommending standards, monitoring, or other operational goals to reduce risk. This presentation will discuss common themes and highlights of the approved HVRTs to inform IWS attendees and the wider research community.

D M Buckland↗
NASA NTRSDate not supplied

Watching Without Seeing a Tool to Surveil Astronaut Health Outcomes While Maintaining Astronaut Medical Privacy

BACKGROUND The Privacy Act of 1974 regulates the use a nd disclosure of personally identifiable information by US Federal agencies. The Act applies to biographical, financial, a nd other identity-linked information, a s well a s personal health information (PHI). As such, the use of astronaut PHI is limited to authorized personnel for preapproved uses, with data reporting often limited to aggregated information about groups. These limitations on the use a nd reporting of astronaut PHI complicates surveillance efforts, wherein epidemiologists a t the National Aeronautics and Space Administration (NASA)monitor the incidence of targeted health conditions in the astronaut population, or to discover emerging trends of aging and disease. Stratification on one or more covariates –particularly time-period, sex, a nd mission participation –can lead to extremely small datasets such that the reporting of results is potentially attributable to individuals. An additional challenge is the small size of the astronaut population, both in terms of numbers of individuals a s well a s in terms of density of exposure time. Such small datasets yield volatile rate estimates that are difficult to interpret. To a id the epidemiological surveillance efforts, a surveillance tool is required that can (a) satisfy the need for rapid computation of condition-specific incidence and mortality rates; (b) improve the statistical estimates of these estimated rates; and (c) maintain astronaut privacy. Here we describe a nd demonstrate such a tool. METHODS We devised a system that models incidence a nd mortality rates rather than calculating them directly. This ha s the advantage of using all the available data to derive the estimates, lea ding to rates that a re not attributable to any one individual, a nd a re a s numerically stable a s they can be given the extremely limited data. The system models disease endpoints using a Poisson regression model with exposure density (measured in person-years) a s a n offset term. By doing so the model is estimating event counts per person-year, equivalent to modeling the rates directly. It uses a standard (pre-specified)set of covariates; the system does not engage in “model-building” as model parsimony is not the goa l. Instead, it is explicitly recognized that if a covariate is not statistically significant a nd not a confounder then it will likely have very little effect on the estimate of the incidence a nd mortality rates. Users are able to specify the disease endpoint of interest and the covariates over which they would like to stratify. The system then uses the resulting model to compute the estimated rates for the user-chosen configuration of variables as visualizes those either over an age range within a specified time-period, or over time for astronauts with a specified age range. RESULTS The first iteration of the tool computes incidence a nd mortality rates for cardiovascular conditions and cancers. Code ha s been developed to retrieve the appropriate data from the IMPALA analysis platform, compute the models for incidence a nd mortality, a nd then use those models to generate the corresponding rate curves. A companion graphical user interface allows the user to specify the curves and visualize the results. CONCLUSIONS It is important to note that the rapid surveillance tool described here is neither meant to be a definitive assessment of the incidence or mortality of any particular disease or condition in the astronaut population, nor is it meant to be used for research purposes. Rather, it is meant as an early indicator that in-depth investigation may be warranted. By automating a repetitive process and leveraging carefully curated astronaut health outcomes, the tool makes possible a rapid “first look” into known areas of concern, and, if used judiciously, may surface new areas of concern for long-term astronaut health. This work is supported in part by the Translational Research Institute for Space Health (TRISH) through NASA Cooperative Agreement NNX16AO69A.

R J Reynolds↗
NASA NTRSDate not supplied

Spaceflight Associated Neuro-ocular Syndrome (SANS): Clinical Update

Spaceflight Associated Neuro-ocular Syndrome (SANS) is a condition unique to long-duration spaceflight, with an unclear pathogenesis and pathophysiology, and no perfect terrestrial analog. Approximately 69% of long duration astronauts present with the earliest indications of SANS, which is defined as development of one or more of the following new signs in at least one eye during or immediately after spaceflight: 1) optic disc edema (ODE; represented by an increase of ≥ 20 microns in peripapillary total retinal thickness [ΔTRT]); 2) chorioretinal folds; 3) globe flattening; and 4) excessive shift in refractive error (≥ +0.75D). Each of these signs presents potential risk to a crewmember’s vision and mission effectiveness, with ODE posing the highest risk overall. It is not yet known what severity and/or duration of signs represents the “pathological” threshold of SANS, or how this threshold will eventually influence the SANS case definition. Brain anatomical changes also occur during long-duration spaceflight and are being monitored in the astronaut population; however, these changes have not yet been associated with functional decrements or with SANS. An update will be provided on the latest SANS clinical analyses, diagnostic technologies, and program initiatives.

TJ Brunstetter↗
NASA NTRSDate not supplied

SPACEFLIGHT ASSOCIATED NEURO-OCULAR SYNDROME (SANS): 2023 CLINICAL UPDATE

INTRODUCTION Spaceflight Associated Neuro-ocular Syndrome (SANS) is a condition unique to long-duration spaceflight, with an unclear pathogenesis and pathophysiology, and no perfect terrestrial analog. Approximately 66% of long duration spaceflight (LDSF) astronauts present with the earliest indication of SANS, which is defined as development of any of the following signs in at least one eye during or immediately following spaceflight: 1) optic disc edema (ODE; represented by an increase of ≥ 20 microns in peripapillary total retinal thickness [ΔTRT]); 2) chorioretinal folds; 3) globe flattening; and 4) excessive shift in refractive error (≥ +0.75D). Each of these signs presents potential risk to a crewmember’s vision and mission effectiveness, with ODE posing the highest risk overall. It is not yet known what severity and/or duration of these signs might lead to acute or permanent impacts to ocular anatomy or visual performance. Brain anatomical changes also occur during long-duration spaceflight and are being monitored in the astronaut population; however, these changes have not yet been associated with functional decrements or with SANS. An update will be provided on the latest SANS clinical analyses, diagnostics, and program initiatives. METHODS Data were obtained from clinical records and SANS subject matter experts (SMEs) to compile a SANS clinical update. Areas of interest include: 1) prevalence of SANS signs, 2) defining clinical thresholds for SANS, and 3) an overview of current and planned SANS clinical efforts. DISCUSSION SANS Sign Prevalence: Analysis at the time of this abstract submission indicates that the approximate prevalence of primary SANS findings in USOS LDSF crewmembers is: 64% for ODE (≥ 20-micron ΔTRT), 15% for chorioretinal folds, 26% for globe flattening, and 14% for hyperopic shifts in refractive error (≥ +0.75D). Clinical Thresholds:  The Earliest Indication of SANS was presented publicly for the first time at the 2020 NASA Human Research Program Investigators’ Workshop. See definition in Introduction section (above).  Clinically Concerning SANS – Development of any of the following signs during or immediately following spaceflight: 1) ODE (≥ 55-micron ΔTRT* and/or Frisèn grade ≥1*), 2) sharp chorioretinal folds in the vicinity of the macula, or 3) moderate globe flattening.  Pathological SANS with an Acute Functional Impact – Development of any of the following signs/symptoms during or immediately following spaceflight: 1) visual field loss (e.g., enlarged blindspot), 2) distorted centralvision, or 3) shift in refractive error beyond power of available correction (e.g., “space anticipation glasses”).  Pathological SANS affecting Long-Term Health – Development of any of the following signs/symptoms during or following spaceflight: 1) permanent visual field loss, 2) reduced retinal nerve fiber layer (RNFL) thickness, 3) permanently distorted central vision, 4) atrophy of retinal pigment epithelium (RPE) or photoreceptors, or 5) choroidal neovascularization. Current & Planned Clinical Efforts (accurate at time of abstract submission): All SANS diagnostic hardware are performing nominally onboard the International Space Station: vision screening, fundoscope, optical coherence tomography (OCT) device, ultrasound, and tonometer. The Goggle-Based Visual Field (GBVF) device is nearing completion of its clinical validation study at Ohio State University and is planned for parabolic flight testing in fiscal year 2023 (FY23); pending positive results, this sequence may pave the way towards an ISS technology demonstration in FY24.

T J Brunstetter↗
NASA NTRSDate not supplied

Using A Guided Interview to Create an Individual Exposure Profile for The Lifetime Surveillance of Astronaut Health (LSAH)

BACKGROUND To support NASA’s Lifetime Surveillance of Astronaut Health (LSAH) project, Individual Exposure Profiles (IEPs) were developed to record an astronaut’s pre-, in-, and post-NASA exposures. NASA astronauts were invited to participate in a one-time guided interview to review known hazard exposures and medical history documented in NASA records and to add new information not otherwise reported. The purpose of the IEP project was to determine if any significant information was gained from these interviews and identify potential trends in long-term health. METHODOLOGY The pre-filled exposure profile data was extracted from several sources including medical records, biographies, and LSAH records. The information that was pre-filled before the interview included occupational exposures prior to selection to the Astronaut Corps, during active astronaut career (e.g., EVA and ground-based training, on-orbit exposures), and after active career. The IEPs also contained relevant medical history (e.g., audiometry, illnesses, injuries) and significant non-occupational exposures. 189 interviews were conducted from 2012-2014. A Microsoft Access database was created to store the information collected in the IEPs before and after the interviews. The database houses the information from the IEPs to track the updates made to the original data. By analyzing which astronauts supplied additional information and which kinds of data were consistently added, potential gaps and trends in missing data may be identified. In designing the database, an efficient structure was implemented for ease of inputting data and to create variables that would generate quantifiable data. Creating standardized variables within the structure helped ease the process of inputting, organizing data, and analyzing data. Additional updates/data were denoted and were categorized by type of update. The categories identified were “Confirmed”, “Confirmed & Supplemented”, “Supplemented”, “Denied”, “Denied & Supplemented”, and “Other”. STATISTICAL ANALYSIS AND RESULTS To assess frequency of exposure updates, descriptive statistics will be generated and stratified by relevant factors such as astronaut selection decade, age at selection, and program/era. Hypothesis testing will be performed to understand the associations between updates to exposure information and population characteristics.

Astronaut health↗