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Understanding patient outcomes after acute respiratory distress syndrome: identifying subtypes of physical, cognitive and mental health outcomes.

ABSTRACT: With improving short-term mortality in acute respiratory distress syndrome (ARDS), understanding survivors' posthospitalisation outcomes is increasingly important. However, little is known regarding associations among physical, cognitive and mental health outcomes. Identification of outcome subtypes may advance understanding of post-ARDS morbidities.We analysed baseline variables and 6-month health status for participants in the ARDS Network Long-Term Outcomes Study. After division into derivation and validation datasets, we used weighted network analysis to identify subtypes from predictors and outcomes in the derivation dataset. We then used recursive partitioning to develop a subtype classification rule and assessed adequacy of the classification rule using a kappa statistic with the validation dataset.Among 645 ARDS survivors, 430 were in the derivation and 215 in the validation datasets. Physical and mental health status, but not cognitive status, were closely associated. Four distinct subtypes were apparent (percentages in the derivation cohort): (1) mildly impaired physical and mental health (22% of patients), (2) moderately impaired physical and mental health (39%), (3) severely impaired physical health with moderately impaired mental health (15%) and (4) severely impaired physical and mental health (24%). The classification rule had high agreement (kappa=0.89 in validation dataset). Female Latino smokers had the poorest status, while male, non-Latino non-smokers had the best status.We identified four post-ARDS outcome subtypes that were predicted by sex, ethnicity, pre-ARDS smoking status and other baseline factors. These subtypes may help develop tailored rehabilitation strategies, including investigation of combined physical and mental health interventions, and distinct interventions to improve cognitive outcomes.

SUBMITTER: Brown SM

PROVIDER: S-EPMC5690818 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Understanding patient outcomes after acute respiratory distress syndrome: identifying subtypes of physical, cognitive and mental health outcomes.

Brown Samuel M SM Wilson Emily L EL Presson Angela P AP Dinglas Victor D VD Greene Tom T Hopkins Ramona O RO Needham Dale M DM

Thorax 20170804 12

<h4>Purpose</h4>With improving short-term mortality in acute respiratory distress syndrome (ARDS), understanding survivors' posthospitalisation outcomes is increasingly important. However, little is known regarding associations among physical, cognitive and mental health outcomes. Identification of outcome subtypes may advance understanding of post-ARDS morbidities.<h4>Methods</h4>We analysed baseline variables and 6-month health status for participants in the ARDS Network Long-Term Outcomes Stu ...[more]

PMID: 28778920

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Project description:Rationale: Increasingly, patients are surviving acute respiratory failure (ARF), prompting the need to better understand standardized outcome measures commonly used during ARF follow-up studies. Objectives: Investigate standardized outcome measures (patient-reported physical and mental health measures, and cognitive testing) compared with findings from semistructured, qualitative interviews. Methods: As part of two ARF multicenter follow-up studies, standardized outcome measures were obtained, followed by qualitative evaluation via an in-depth, semistructured interview conducted and coded by two independent researchers. Qualitative interviews revealed the following post-ARF survivorship themes: physical impairment; anxiety, depression, and post-traumatic stress disorder symptoms; and cognitive impairment. Scores from standardized measures related to these themes were compared for ARF survivors reporting versus not reporting these themes in their qualitative interviews. Results: Of 59 invited ARF survivors, 48 (81%) completed both standardized outcome measures and qualitative interviews. Participants' median (interquartile range) age was 53 (43-64) years; 54% were female, and 88% were living independently before hospitalization. The two independent reviewers classifying the presence or absence of themes from the qualitative interviews had excellent agreement (κ = 0.80). There were significantly worse scores on standardized outcome measures for survivors reporting (vs. not reporting) physical and mental health impairments in their qualitative interviews. However, standardized cognitive test scores did not differ between patients reporting versus not reporting cognitive impairments in their qualitative interviews. Conclusions: These findings support the use of recommended, commonly used standardized outcome measures for physical and mental health impairments in ARF survivorship research. However, caution is needed in interpreting self-reported cognitive function compared with standardized cognitive testing.

Project description:ObjectiveAdiponectin (APN) is an anti-inflammatory hormone derived from adipose tissue that attenuates acute lung injury in rodents. In this study, we investigated the association between circulating APN and outcomes among patients with acute respiratory distress syndrome (ARDS).MethodsWe performed a retrospective cohort study using data and plasma samples from participants in the multicenter ARDS Network Fluid and Catheter Treatment Trial.ResultsPlasma APN concentrations were measured in 816 (81.6%) trial participants at baseline and in 568 (56.8%) subjects at both baseline and day 7 after enrollment. Clinical factors associated with baseline APN levels in multivariable-adjusted models included sex, body mass index, past medical history of cirrhosis, and central venous pressure (model R2 = 9.7%). We did not observe an association between baseline APN and either severity of illness (APACHE III) or extent of lung injury (Lung Injury Score). Among patients who received right heart catheterization (n = 384), baseline APN was inversely related to mean pulmonary artery pressure (β = -0.015, R2 1.5%, p = 0.02); however, this association did not persist in multivariable models (β = -0.009, R2 0.5%, p = 0.20). Neither baseline APN levels [HR per quartile1.04 (95% CI 0.91-1.18), p = 0.61], nor change in APN level from baseline to day 7 [HR 1.04 (95% CI 0.89-1.23), p = 0.62)] were associated with 60 day mortality in Cox proportional hazards regression models. However, subgroup analysis identified an association between APN and mortality among patients who developed ARDS from extra-pulmonary etiologies [HR per quartile 1.31 (95% CI 1.08-1.57)]. APN levels did not correlate with mortality among patients developing ARDS in association with direct pulmonary injury [HR 0.96 (95% CI 0.83-1.13)], pinteraction = 0.016.ConclusionsPlasma APN levels did not correlate with disease severity or mortality in a large cohort of patients with ARDS. However, higher APN levels were associated with increased mortality among patients developing ARDS from extra-pulmonary etiologies.

Project description:PurposeTo analyze the long-term consequences of critical COVID-19, regarding physical, mental, cognitive and functional impairments, and to describe its evolution through time.MethodsProspective cohort study, with consecutive inclusion of patients admitted due to SARS-CoV-2 to intensive care units(ICU) of a tertiary-care center, between May/2020 and September/2021. All included patients were included in Physical and Rehabilitation Medicine(PRM) inpatient programs during ICU stay. Eligible patients were evaluated on PRM appointments 6 and 12 months after ICU discharge. In each visit, physical examination and a predefined set of scales were applied, aiming to comprehensively evaluate the three domains (physical, mental and cognitive) of post-intensive care syndrome and the patients' functionality. Statistical analysis encompassed descriptive and univariate analysis.ResultsA total of 42 patients were included: 66.7% males, mean age of 62 yo. In the physical domain, 6 months after ICU discharge, there was a significant reduction in quality of life (p-value = 0.034), muscle strength (p-value = 0.002), gait ability (p-value<0.001) and balance (p-values<0.001) and increased fatigue levels (p-value = 0.009), in comparison with reference values. Yet, a significative positive evolution was observed in all referred subdomains (p-values<0.05). Nevertheless, 12 months after discharge, muscle strength (p-value = 0.001), gait (p-value<0.001) and balance (p-value<0.001) were still significantly compromised. Regarding the mental domain, both at 6 and 12 months after discharge, the levels of anxiety and depression were significantly increased (p-values<0.001). Nonetheless, a positive evolution was also found (p-values<0.02). Cognitive performance was significantly impaired in comparison with reference values, both at 6 and 12 months (p-value<0.001). Yet, a global improvement was also depicted (p-value = 0.003). Six months after ICU discharge, 54.8% were autonomous in activities of daily living, a value that improved to 74.0% in the subsequent 6 months (p-value = 0.002).ConclusionCritical COVID-19 survivors present significant physical, mental and cognitive impairments 6 and 12 months after ICU discharge, despite their positive evolution through time.

Project description:Following in the footsteps of other large "population neuroscience" studies, the Adolescent Brain Cognitive Development? (ABCD) study is the largest in the U.S. assessing brain development. The study is examining approximately 11,875 youth from 21 sites from age 9 to 10 for approximately ten years into young adulthood. The ABCD Study® has completed recruitment for the baseline sample generally using a multi-stage probability sample including a stratified random sample of schools. The dataset has a wealth of measured attributes of youths and their environment, including neuroimaging, cognitive, biospecimen, behavioral, youth self-report and parent self-report metrics, and environmental measures. The initial goal of the ABCD Study was to examine risk and resiliency factors associated with the development of substance use, but the project has expanded far beyond this initial set of questions and will also greatly inform our understanding of the contributions of biospecimens (e.g., pubertal hormones), neural alterations, and environmental factors to the development of both healthy behavior and brain function as well as risk for poor mental and physical outcomes. This review outlines how the ABCD Study was designed to elucidate factors associated with the development of negative mental and physical health outcomes and will provide a selective overview of results emerging from the ABCD Study. Such emerging data includes initial validation of new instruments, important new information about the prevalence and correlates of mental health challenges in middle childhood, and promising data regarding neural correlates of both healthy and disordered behavior. In addition, we will discuss the challenges and opportunities to understanding both healthy development and the emergence of risk from ABCD Study data. Finally, we will overview the future directions of this large undertaking and the ways in which it will shape our understanding of the development of risk for poor mental and physical health outcomes.

Project description:BackgroundElectronic patient-reported outcome (PROs) provides a fast and reliable assessment of a patient's health-related quality of life. Nevertheless, using PRO in the traditional paper format is not practical for clinical practice due to the limitations associated with data analysis and management. A questionnaire app was developed to address the need for a practical way to group and use distress and physical activity assessment tools.ObjectiveThe purpose of this study was to assess the level of agreement between electronic (mobile) and paper-and-pencil questionnaire responses.MethodsWe validated the app version of the distress thermometer (DT), International Physical Activity Questionnaire (IPAQ), and Patient Health Questionnaire-9 (PHQ-9). A total of 102 participants answered the paper and app versions of the DT and IPAQ, and 96 people completed the PHQ-9. The study outcomes were the correlation of the data between the paper-and-pencil and app versions.ResultsA total of 106 consecutive breast cancer patients were enrolled and analyzed for validation of paper and electronic (app) versions. The Spearman correlation values of paper and app surveys for patients who responded to the DT questionnaire within 7 days, within 3 days, and on the same day were .415 (P<.001), .437 (P<.001), and .603 (P<.001), respectively. Similarly, the paper and app survey correlation values of the IPAQ total physical activity metabolic equivalent of task (MET; Q2-6) were .291 (P=.003), .324 (P=.005), and .427 (P=.01), respectively. The correlation of the sum of the Patient Health Questionnaire-9 (Q1-9) according to the time interval between the paper-based questionnaire and the app-based questionnaire was .469 for 14 days (P<.001), .574 for 7 days (P<.001), .593 for 3 days (P<.001), and .512 for the same day (P=.03). These were all statistically significant. Similarly, the correlation of the PHQ (Q10) value according to the time interval between the paper-based questionnaire and the app-based questionnaire was .283 for 14 days (P=.005), .409 for 7 days (P=.001), .415 for 3 days (P=.009), and .736 for the same day (P=.001). These were all statistically significant. In the overall trend, the shorter the interval between the paper-and-pencil questionnaire and the app-based questionnaire, the higher the correlation value.ConclusionsThe app version of the distress and physical activity questionnaires has shown validity and a high level of association with the paper-based DT, IPAQ (Q2-6), and PHQ-9. The app-based questionnaires were not inferior to their respective paper versions and confirm the feasibility for their use in clinical practice. The high correlation between paper and mobile app data allows the use of new mobile apps to benefit the overall health care system.Trial registrationClinicalTrials.gov NCT03072966; https://clinicaltrials.gov/ct2/show/NCT03072966.

Project description:BackgroundMetrics based on self-reports of health status have been proposed for tracking population health and making comparisons among different populations. While these metrics have been used in the US to explore disparities by sex, race/ethnicity, and socioeconomic position, less is known about how self-reported health varies geographically. This study aimed to describe county-level trends in the prevalence of poor self-reported health and to assess the face validity of these estimates.MethodsWe applied validated small area estimation methods to Behavioral Risk Factor Surveillance System data to estimate annual county-level prevalence of four measures of poor self-reported health (low general health, frequent physical distress, frequent mental distress, and frequent activity limitation) from 1995 and 2012. We compared these measures of poor self-reported health to other population health indicators, including risk factor prevalence (smoking, physical inactivity, and obesity), chronic condition prevalence (hypertension and diabetes), and life expectancy.ResultsWe found substantial geographic disparities in poor self-reported health. Counties in parts of South Dakota, eastern Kentucky and western West Virginia, along the Texas-Mexico border, along the southern half of the Mississippi river, and in southern Alabama generally experienced the highest levels of poor self-reported health. At the county level, there was a strong positive correlation among the four measures of poor self-reported health and between the prevalence of poor self-reported health and the prevalence of risk factors and chronic conditions. There was a strong negative correlation between prevalence of poor self-reported health and life expectancy. Nonetheless, counties with similar levels of poor self-reported health experienced life expectancies that varied by several years. Changes over time in life expectancy were only weakly correlated with changes in the prevalence of poor self-reported health.ConclusionsThis analysis adds to the growing body of literature documenting large geographic disparities in health outcomes in the United States. Health metrics based on self-reports of health status can and should be used to complement other measures of population health, such as life expectancy, to identify high need areas, efficiently allocate resources, and monitor geographic disparities.

Dataset Information

Understanding patient outcomes after acute respiratory distress syndrome: identifying subtypes of physical, cognitive and mental health outcomes.

Publications

Understanding patient outcomes after acute respiratory distress syndrome: identifying subtypes of physical, cognitive and mental health outcomes.

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