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Group-Based Trajectory Modeling of Suppression Ratio After Cardiac Arrest.

ABSTRACT: Existing studies of quantitative electroencephalography (qEEG) as a prognostic tool after cardiac arrest (CA) use methods that ignore the longitudinal pattern of qEEG data, resulting in significant information loss and precluding analysis of clinically important temporal trends. We tested the utility of group-based trajectory modeling (GBTM) for qEEG classification, focusing on the specific example of suppression ratio (SR).We included comatose CA patients hospitalized from April 2010 to October 2014, excluding CA from trauma or neurological catastrophe. We used Persyst®v12 to generate SR trends and used semi-quantitative methods to choose appropriate sampling and averaging strategies. We used GBTM to partition SR data into different trajectories and regression associate trajectories with outcome. We derived a multivariate logistic model using clinical variables without qEEG to predict survival, then added trajectories and/or non-longitudinal SR estimates, and assessed changes in model performance.Overall, 289 CA patients had ?36 h of EEG yielding 10,404 h of data (mean age 57 years, 81 % arrested out-of-hospital, 33 % shockable rhythms, 31 % overall survival, 17 % discharged to home or acute rehabilitation). We identified 4 distinct SR trajectories associated with survival (62, 26, 12, and 0 %, P < 0.0001 across groups) and CPC (35, 10, 4, and 0 %, P < 0.0001 across groups). Adding trajectories significantly improved model performance compared to adding non-longitudinal data.Longitudinal analysis of continuous qEEG data using GBTM provides more predictive information than analysis of qEEG at single time-points after CA.

SUBMITTER: Elmer J

PROVIDER: S-EPMC5045751 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Group-Based Trajectory Modeling of Suppression Ratio After Cardiac Arrest.

Elmer Jonathan J Gianakas John J JJ Rittenberger Jon C JC Baldwin Maria E ME Faro John J Plummer Cheryl C Shutter Lori A LA Wassel Christina L CL Callaway Clifton W CW Fabio Anthony A

Neurocritical care 20161201 3

<h4>Background</h4>Existing studies of quantitative electroencephalography (qEEG) as a prognostic tool after cardiac arrest (CA) use methods that ignore the longitudinal pattern of qEEG data, resulting in significant information loss and precluding analysis of clinically important temporal trends. We tested the utility of group-based trajectory modeling (GBTM) for qEEG classification, focusing on the specific example of suppression ratio (SR).<h4>Methods</h4>We included comatose CA patients hosp ...[more]

PMID: 27033709

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Project description:BackgroundA hospital's risk-standardized survival rate (RSSR) for in-hospital cardiac arrest has emerged as an important metric to benchmark and incentivize hospital resuscitation quality. We examined whether hospital performance on the RSSR metric was stable or dynamic year-over-year and whether low-performing hospitals were able to improve survival outcomes over time.Methods and resultsWe used data from 84 089 adult patients with an in-hospital cardiac arrest from 166 hospitals with continuous participation in Get With The Guidelines-Resuscitation from 2012 to 2017. A 2-level hierarchical regression model was used to compute RSSRs during a baseline (2012-2013) and two follow-up periods (2014-2015 and 2016-2017). At baseline, hospitals were classified as top-, middle-, and bottom-performing if they ranked in the top 25%, middle 50%, and bottom 25%, respectively, on their RSSR metric during 2012 to 2013. We compared hospital performance on RSSR during follow-up between top, middle, and bottom-performing hospitals' at baseline. During 2012 to 2013, 42 hospitals were identified as top-performing (median RSSR, 31.7%), 82 as middle-performing (median RSSR, 24.6%), and 42 as bottom-performing (median RSSR, 18.7%). During both follow-up periods, >70% of top-performing hospitals ranked in the top 50%, a substantial proportion remained in the top 25% of RSSR during 2014 to 2015 (54.6%) and 2016 to 2017 (40.4%) follow-up periods. Likewise, nearly 75% of bottom-performing hospitals remained in the bottom 50% during both follow-up periods, with 50.0% in the bottom 25% of RSSR during 2014 to 2015 and 40.5% in the bottom 25% during 2016 to 2017. While percentile rankings were generally consistent over time at ≈45% of study hospitals, ≈1 in 5 (21.4%) bottom-performing hospitals showed large improvement in percentile rankings over time and a similar proportion (23.7%) of top-performing hospitals showed large decline in percentile rankings compared with baseline.ConclusionsHospital performance on RSSR during baseline period was generally consistent over 4 years of follow-up. However, 1 in 5 bottom-performing hospitals had large improvement in survival over time. Identifying care and quality improvement innovations at these sites may provide opportunities to improve in-hospital cardiac arrest care at other hospitals.

Project description:ObjectivesInflammatory bowel disease (IBD) is a heterogeneous group of chronic inflammatory gastrointestinal conditions with variable disease courses often requiring significant healthcare expenditures. We aimed to identify disease trajectory patterns based on longitudinal financial expenditures and to assess the association of classic disease activity parameters with financial charges.MethodsThis was an analysis of a consented, prospective, natural history IBD registry (2009-2013) from a tertiary IBD center of 2,203 patients and their associated medical charges excluding pharmacy expenses. We applied group-based trajectory modeling to longitudinal healthcare financial charges to determine patterns of charges. We assessed the association between charge patterns and disease activity, quality of life, healthcare utilization, and medication requirement.ResultsThe final model included 1,600 IBD patients with 5-year charges. We identified six distinct trajectories over the study period. Consistently High charges were associated with Crohn's disease (66.0% Consistently High patients, P<0.01), perianal involvement (22.6%, P<0.01), ulcerative colitis extent (89.7% extensive, P=0.01), prior IBD surgery (52.5%, P<0.01), and depression/anxiety (36.2%, P<0.01). Compared with other trajectories, Consistently High charges had higher 5-year disease activity indices (Harvey-Bradshaw P<0.01; ulcerative colitis activity index P<0.01), elevated C-reactive protein rates (72.3%, P<0.01), IBD surgery (64.5%, P<0.01), hospitalization (97.2%, P<0.01), corticosteroid (70.9%, P<0.01) and antitumor necrosis factor requirement (50.4%, P<0.01), and worse quality of life (P<0.01). Annual trends in parameters were reflected in temporal changes in financial charges. The majority of financial burden stemmed from inpatient care.ConclusionsHealthcare financial charges represent a novel phenotype in IBD that reflect trends in classic disease activity parameters and allow for subgroup identification of temporal disease trajectories.

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Dataset Information

Group-Based Trajectory Modeling of Suppression Ratio After Cardiac Arrest.

Publications

Group-Based Trajectory Modeling of Suppression Ratio After Cardiac Arrest.

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