Innovations in Stroke
2016; Lippincott Williams & Wilkins; Volume: 47; Issue: 2 Linguagem: Inglês
10.1161/strokeaha.115.011377
ISSN1524-4628
AutoresIrene Katzan, Nicolas R. Thompson, Ken Uchino,
Tópico(s)Cerebrovascular and Carotid Artery Diseases
ResumoHomeStrokeVol. 47, No. 2Innovations in Stroke Free AccessResearch ArticlePDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessResearch ArticlePDF/EPUBInnovations in StrokeThe Use of PROMIS and NeuroQoL Scales in Clinical Stroke Trials Irene L. Katzan, MD, Nicolas Thompson, MS and Ken Uchino, MD Irene L. KatzanIrene L. Katzan From the Neurological Institute, Cleveland Clinic, OH. , Nicolas ThompsonNicolas Thompson From the Neurological Institute, Cleveland Clinic, OH. and Ken UchinoKen Uchino From the Neurological Institute, Cleveland Clinic, OH. Originally published5 Jan 2016https://doi.org/10.1161/STROKEAHA.115.011377Stroke. 2016;47:e27–e30Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: January 1, 2016: Previous Version 1 There are significant limitations with the use of modified Rankin Scale (mRS) score as the primary outcome in clinical stroke trials. We propose the exploration of the Patient-Reported Outcome Measure Information System (PROMIS) and Quality of Life in Neurological Disorders (NeuroQoL) tools as outcome measures in clinical trials and provide preliminary data on the distribution of these measures in a cohort of patients with ischemic stroke.The ChallengeThe mRS, a clinician-reported measure of global disability,1 is a commonly used primary outcome in clinical stroke trials. It is a 1-item measure ranging from grades 0 to 5 with 0 representing no symptoms and 5 representing severe disability. A score of 6 is often used to represent death. Although its beneficial attributes include simplicity and various modes of administration and demonstrated construct and convergent validity,2 there are also limitations when using mRS. There can be substantial interobserver variability in scoring, especially between scores 1 and 4,3 which is of key importance for stroke trials that dichotomize outcomes. In addition, the mRS is heavily weighted towards mobility4 and does not specifically delineate several other important domains of health that are frequently affected by stroke, such as cognition, fatigue, or ability to participate in social roles. The traditional approach to analyzing mRS in clinical trials is to dichotomize the score, which reduces the sensitivity to detect change. Shift analysis has the potential to increase power to detect differences compared with dichotomization. However, to allow adjustment for covariates and estimate an effect size, shift analyses must be done using ordinal regression, which requires that the data meet proportionality assumption.5 Importantly, because the mRS has only 6 levels, the ability to detect meaningful change and differences in outcomes among treatment groups is limited, even with the use of shift analysis. The use of continuous scales may provide more power to assess differences between treatment groups.5The importance of obtaining outcomes information directly from patients is gaining recognition. Patient and provider perceptions may differ and standard outcome measures do not often capture many aspects of outcomes relevant to patients.6 As such, the Food and Drug Administration has a renewed interest in the use of patient-reported outcome measures (PROMs) in clinical trials7 to include the patient's voice in the assessment of interventions.Potential SolutionIt would be a powerful advance for clinical stroke research to incorporate tools into outcomes measures that include multiple domains of health important to patients, can be efficiently and reliably captured through patient report, and could increase statistical power to detect differences between treatment groups. The use of the PROMIS or NeuroQoL system of tools may offer such a solution. PROMIS is a patient-reported system based on item response theory that uses a continuous scale to efficiently measure patient health status for different domains of health8 in individuals with a wide range of diseases and demographic characteristics. The mean of each scale is 50, reflecting the mean of the general population, and the standard deviation (SD) is 10. Scores have a normal distribution allowing for simpler and more powerful parametric statistical models.9 Domains are assessed through patient questions from item banks, reducing ceiling and floor effects. The use of computer adaptive testing allows the system to query patients based on their previous responses until a prespecified level of precision is reached, typically within 3 to 4 questions, which significantly reduces patient burden. NeuroQoL is a sister suite of tools developed specifically for use in neurological populations10 with overlapping item banks with PROMIS. Stroke was one of the 5 neurological conditions used to perform item pool testing and score calibrations. NeuroQoL uses the same standardized scoring system as PROMIS, and the scales have been cocalibrated to the corresponding PROMIS scales, allowing measurement of both scales along a common metric (http://www.prosettastone.org/measures/Neuro-Qol).Extensive qualitative and quantitative evaluation of both PROMIS and NeuroQoL domains ensures that they capture a valid, reliable measure of the outcome of interest. Short forms are also available for PROMIS and NeuroQoL tools, consisting of static sets of questions, for situations where computer adaptive testing is unavailable or when providers prefer to deliver the same set of questions to all patients. The use of a continuous linear scale and normalized distribution may potentially increase sensitivity to change11 and improve statistical power to detect differences across treatment groups. As an added benefit, PROMIS and NeuroQoL tools can be used across conditions, making cross-population comparisons feasible. Electronic administration of PROMs is gaining popularity. Many PROMIS short forms are available in Epic's electronic health record (Epic Systems, Verona, WI), and they are considering incorporating PROMIS computer adaptive testing s in a future release (Richard Gershon, PhD, personal communication, August 27, 2015).Preliminary DataWe investigated the pattern and distribution of PROMIS scores in ischemic stroke patients seen in the Cleveland Clinic cerebrovascular ambulatory clinic through a cross-sectional analysis of data from several PROMIS domains. Patients in the cerebrovascular clinic routinely complete PROMs on electronic tablets at the time of the visit or through the patient portal to the electronic health record (Epic) before arriving for their visit with results immediately available within the electronic health record.12 The PROMIS Fatigue and PROMIS Physical Function (PROMIS PF) have been routinely collected as part of this system since September 2012. The PROMIS domains anxiety, satisfaction with social roles, sleep disturbance, and pain intensity were added in February 2015. Depression is assessed with the patient-reported Patient Health Questionnaire-9. These scores are then cocalibrated on the PROMIS metric,13 which provides an equivalent PROMIS depression score. The mRS is also completed by the provider at the visit.The patient cohort consisted of all patients with diagnosis of ischemic stroke who had a completed PROMIS score and mRS between September 14, 2012, and June 16, 2015. If data from >1 encounter was available, data from the first encounter was used.In this analysis, for all PROMIS scores, higher scales indicate better functioning. The frequency distribution of PROMIS PF was calculated overall and according to mRS level. mRS scores of 4 and 5 were combined because of low numbers within these levels. Spearman correlation coefficients were calculated between mRS and the PROMIS scales, and mean scores of the PROMIS scales stratified by mRS level were computed.There were 3762 visits by patients with ischemic stroke with a completed mRS and PROMIS PF scale, comprising 2431 unique patients (Table). Mean PROMIS PF score was 40.6 (SD=11.3), and median mRS score was 1 (interquartile range [IQR] 1–2). At the first visit during the study period, 541 (22.3%) patients had a normal mRS score (=0), demonstrating a significant ceiling effect. In contrast, 12 (0.5%) patients scored at ceiling of the PROMIS PF. It had a normal distribution overall and within most strata of mRS (Figure 1), suggesting the potential for PROMIS PF to more finely discriminate among patient groups.Table. Characteristics of Ischemic Stroke PopulationCharacteristicValueUnique patients2431Mean age (SD)62.9 (14.4)Female46.4%Race White77.1% Black18.6% Other race2.1%Days from last stroke event, median [IQR]79 [35–343]Modified Rankin score, median [IQR]1 [1–2]PROMIS physical function Mean (SD)40.6 (11.3) n2431PROMIS fatigue Mean (SD)53.2 (10.9) n2386PROMIS satisfaction with social roles Mean (SD)43.2 (11.6) n305PROMIS anxiety Mean (SD)52.5 (10.7) n323PROMIS sleep disturbance Mean (SD)49.6 (10.8) n316PROMIS pain intensity Mean (SD)53.4 (10.8) n308PHQ-9 on PROMIS metric Mean (SD)49.9 (10.7) n2266Scores from first visit that the scale was completed. PROMIS scores oriented so that higher scores indicate better functioning. IQR indicates interquartile range; PHQ-9, Patient Health Questionnaire-9; PROMIS, Patient-Reported Outcome Measure Information System; and SD, standard deviation.Download figureDownload PowerPointFigure 1. Distribution of PROMIS physical function T-scores across levels of the modified Rankin Scale (mRS). Scores are from the first visit during study period. Vertical red lines represent mean score of the US general population (T-score=50). PROMIS indicates Patient-Reported Outcome Measure Information System; and SD, standard deviation.Between February 17 and June 16, 2015, 323 patients completed the additional PROMIS scales (Table). Scores of the 7 PROMIS scales were lower with successively higher mRS levels, although difference in scores across mRS levels varied (Figure 2). The PROMIS PF had the highest overall correlation with mRS (ρ=−0.60), the PROMIS Sleep Disturbance had the lowest (ρ=−0.19). At higher levels of disability in functional activities as defined by mRS levels, patients reported worst physical function and social satisfaction, whereas sleep and pain were relatively less impacted. These findings show the potential of PROMIS tools to augment information on a patient's health status that is not captured by the mRS. Importantly, the domains of patient's perceived health do not decline to the same degree at increasing severities of mRS, further supporting the value of assessing individual health domains to allow detection of differential changes within different aspects of health.Download figureDownload PowerPointFigure 2. PROMIS T-scores across levels of the modified Rankin Scale (mRS). PROMIS scale scores oriented so that higher scores indicate better functioning. Scores are from the first visit the scale was completed. PROMIS indicates Patient-Reported Outcome Measure Information System; and SD, standard deviation. *Patient Health Questionnaire-9 on PROMIS metric.Limitations and Next StepsSeveral questions need to be addressed before PROMIS or NeuroQoL tools can be successfully used in clinical stroke trials. Evidence of acceptable psychometric properties is a prerequisite for inclusion of outcomes measures into clinical research, which includes content validity, test–retest reliability, and ability to detect change (responsiveness) and to discriminate between groups. Many of these items have already been addressed in stroke with the NeuroQoL tools.10 Determination of outcome domains that are relevant to patients, a form of content validity, is a requisite for the Food and Drug Administration to use PROMs for approval and labeling claims. Identification of the minimally important difference, which reflects a score difference large enough to have implications for a patient's care, is also critical. The minimally important difference of outcome measures typically estimated to be one-half the SD14 has been found to be accurate in an analysis of PROMIS scales designed for use in patients with cancer.15The use of PROMs will add a level of complexity when evaluating outcomes of care because they may be impacted by the patient's environment, social support, mental outlook, and their self-defined standards for health.16 Further exploration should be performed on the impact of various factors on patient report of health outcomes to determine whether and how to incorporate this information into the interpretation of clinical stroke trial results.Stroke patients may have cognitive or other functional limitations preventing them from completing PROMs. Proxy assessment may substitute for patient self-assessment in these cases. Preliminary data with NeuroQoL scales in stroke patients suggest comparable performance between patient and proxy responses in group-level analyses for moderate-high functioning patients with stroke.17 Patients may also die or become too ill to complete patient-reported questions. A method to account for dropouts because of death or worsening health has been described.18An imbalance in prognostic variables between treatment groups, including premorbid health status, may result in incorrect results.5 In acute stroke trials that use mRS as the outcome, imbalance in premorbid functioning is reduced somewhat with the common enrollment requirement of a premorbid mRS score <2 or 3. Imbalance in premorbid status may have more consequence when using outcomes measures that allow finer discrimination in health status than the mRS. More research will be useful to determine the importance of accounting for differences in premorbid states of health in the various domains used in the assessment of outcome with the PROMIS or NeuroQoL tools, and if salient, how best to accomplish this.To explore the use of PROMIS or NeuroQoL domains in clinical research in stroke, prospective observational studies of a broad population of patients should be performed that entails completion of the selected PROMIS/NeuroQoL tools at specific time points after stroke. This will provide important information on the range and variability in scores and patterns of change over time across patients of different ages and severities of impairment, which will inform the use of these tools in clinical trials. Inclusion of PROMIS/NeuroQoL tools as outcomes in clinical stroke trials will provide direct information on their ability to detect differences in patient outcomes across treatment groups. Ideally, power and sample size calculations would account for the statistical analysis of one or more of these PROMs as key secondary outcomes.ConclusionsThe potential benefits of including PROMIS/NeuroQoL tools as outcomes in stroke clinical trials are compelling and include the ability to measure outcomes on a continuous scale potentially improving their power to detect change, the incorporation of patient viewpoints, and the ability to assess outcomes across multiple domains affected by stroke. Recent advances in the technical capabilities to electronically administer PROMs make this feasible. Further research is warranted to evaluate several unresolved questions related to the use of PROMIS/NeuroQoL tools in stroke clinical trials.AcknowledgmentsSrividya Ramachandran, PhD, provided editorial assistance for this manuscript.DisclosuresNone.FootnotesCorrespondence to Irene Katzan, MD, 9500 Euclid Ave, S80, Cleveland, OH 44195. E-mail [email protected]References1. van Swieten JC, Koudstaal PJ, Visser MC, Schouten HJ, van Gijn J.Interobserver agreement for the assessment of handicap in stroke patients.Stroke. 1988; 19:604–607.LinkGoogle Scholar2. Banks JL, Marotta CA.Outcomes validity and reliability of the modified Rankin scale: implications for stroke clinical trials: a literature review and synthesis.Stroke. 2007; 38:1091–1096. doi: 10.1161/01.STR.0000258355.23810.c6.Google Scholar3. Quinn TJ, Dawson J, Walters MR, Lees KR.Exploring the reliability of the modified Rankin scale.Stroke. 2009; 40:762–766. doi: 10.1161/STROKEAHA.108.522516.LinkGoogle Scholar4. Naidech AM, Beaumont JL, Berman M, Francis B, Liotta E, Maas MB, et al. Dichotomous "good outcome" indicates mobility more than cognitive or social quality of life.Crit Care Med. 2015; 43:1654–1659. doi: 10.1097/CCM.0000000000001082.CrossrefMedlineGoogle Scholar5. Bath PM, Lees KR, Schellinger PD, Altman H, Bland M, Hogg C, et al; European Stroke Organisation Outcomes Working Group. Statistical analysis of the primary outcome in acute stroke trials.Stroke. 2012; 43:1171–1178. doi: 10.1161/STROKEAHA.111.641456.LinkGoogle Scholar6. Ali M, Fulton R, Quinn T, Brady M; VISTA Collaboration. How well do standard stroke outcome measures reflect quality of life? A retrospective analysis of clinical trial data.Stroke. 2013; 44:3161–3165. doi: 10.1161/STROKEAHA.113.001126.LinkGoogle Scholar7. US Food & Drug Administration. PDUFA V clinical outcomes assessment development and implementation: Opportunities and challenges public workshop.http://www.Fda.Gov/drugs/newsevents/ucm431040.Htm. April 1, 2015.Google Scholar8. PROMIS Network. PROMIS - dynamic tools to measure health outcomes from the patient perspective.http://www.nihpromis.org. Accessed June 29, 2013.Google Scholar9. Vickers AJ.Parametric versus non-parametric statistics in the analysis of randomized trials with non-normally distributed data.BMC Med Res Methodol. 2005; 5:35. doi: 10.1186/1471-2288-5-35.CrossrefMedlineGoogle Scholar10. Cella D, Lai JS, Nowinski CJ, Victorson D, Peterman A, Miller D, et al. Neuro-QOL: brief measures of health-related quality of life for clinical research in neurology.Neurology. 2012; 78:1860–1867. doi: 10.1212/WNL.0b013e318258f744.CrossrefMedlineGoogle Scholar11. Saver JL.Optimal end points for acute stroke therapy trials: best ways to measure treatment effects of drugs and devices.Stroke. 2011; 42:2356–2362. doi: 10.1161/STROKEAHA.111.619122.LinkGoogle Scholar12. Katzan I, Speck M, Dopler C, Urchek J, Bielawski K, Dunphy C, et al. The Knowledge Program: an innovative, comprehensive electronic data capture system and warehouse.AMIA Annu Symp Proc. 2011; 2011:683–692.MedlineGoogle Scholar13. Choi SW, Schalet B, Cook KF, Cella D.Establishing a common metric for depressive symptoms: linking the BDI-II, CES-D, and PHQ-9 to PROMIS depression.Psychol Assess. 2014; 26:513–527. doi: 10.1037/a0035768.CrossrefMedlineGoogle Scholar14. Norman GR, Sloan JA, Wyrwich KW.The truly remarkable universality of half a standard deviation: confirmation through another look.Expert Rev Pharmacoecon Outcomes Res. 2004; 4:581–585. doi: 10.1586/14737167.4.5.581.CrossrefMedlineGoogle Scholar15. Yost KJ, Eton DT, Garcia SF, Cella D.Minimally important differences were estimated for six Patient-Reported Outcomes Measurement Information System-Cancer scales in advanced-stage cancer patients.J Clin Epidemiol. 2011; 64:507–516. doi: 10.1016/j.jclinepi.2010.11.018.CrossrefMedlineGoogle Scholar16. Kaplan SH, Kravitz RL, Greenfield S.A critique of current uses of health status for the assessment of treatment effectiveness and quality of care.Med Care. 2000; 38(9 suppl):II184–II191.CrossrefMedlineGoogle Scholar17. Kozlowski AJ, Singh R, Victorson D, Miskovic A, Lai JS, Harvey RL, et al. Agreement between responses from community-dwelling persons with stroke and their proxies on the NIH Neurological Quality of Life (Neuro-QoL) short forms.Arch Phys Med Rehabil. 2015; 96:1986–1992.e14. doi: 10.1016/j.apmr.2015.07.005.CrossrefMedlineGoogle Scholar18. Cella D, Wang M, Wagner L, Miller K.Survival-adjusted health-related quality of life (HRQL) among patients with metastatic breast cancer receiving paclitaxel plus bevacizumab versus paclitaxel alone: results from Eastern Cooperative Oncology Group Study 2100 (E2100).Breast Cancer Res Treat. 2011; 130:855–861. doi: 10.1007/s10549-011-1725-6.CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetailsCited By Wolf S, Holm S, Ingwersen T, Bartling C, Bender G, Birke G, Meyer A, Nolte A, Ottes K, Pade O, Peller M, Steinmetz J, Gerloff C and Thomalla G (2022) Pre-stroke socioeconomic status predicts upper limb motor recovery after inpatient neurorehabilitation, Annals of Medicine, 10.1080/07853890.2022.2059557, 54:1, (1265-1276), Online publication date: 31-Dec-2022. de Graaf J, Volkers E, Schepers V, Visser-Meily J and Post M (2021) Validity of the Utrecht scale for evaluation of rehabilitation-participation restrictions scale in a hospital-based stroke population 3 months after stroke, Topics in Stroke Rehabilitation, 10.1080/10749357.2021.1956047, 29:7, (516-525), Online publication date: 3-Oct-2022. Morris R, Figueroa J, Pokrzywa C, Barber J, Temkin N, Bergner C, Karam B, Murphy P, Nelson L, Laud P, Cooper Z, de Moya M, Trevino C, Tignanelli C and deRoon-Cassini T (2022) Predicting outcomes after traumatic brain injury: A novel hospital prediction model for a patient reported outcome, The American Journal of Surgery, 10.1016/j.amjsurg.2022.05.016, 224:4, (1150-1155), Online publication date: 1-Oct-2022. Gans S, Michaels E, Thaler D and Leung L (2021) Detection of symptoms of late complications after stroke in young survivors with active surveillance versus usual care, Disability and Rehabilitation, 10.1080/09638288.2021.1883749, 44:15, (4023-4028), Online publication date: 17-Jul-2022. Bui Q, Kaufman K, Pham V, Lenze E, Lee J, Mohr D, Fong M, Metts C, Tomazin S and Wong A (2022) Ecological Momentary Assessment of Real-World Functional Behaviors in Individuals With Stroke: A Longitudinal Observational Study, Archives of Physical Medicine and Rehabilitation, 10.1016/j.apmr.2022.02.011, 103:7, (1327-1337), Online publication date: 1-Jul-2022. Arwert H, Oosterveer D, Schoones J, Terwee C and Vliet Vlieland T (2022) Use of Patient-Reported Outcomes Measurement Information System Measures in Clinical Research in Patients With Stroke: A Systematic Literature Review, Archives of Rehabilitation Research and Clinical Translation, 10.1016/j.arrct.2022.100191, 4:2, (100191), Online publication date: 1-Jun-2022. Marshall I, McKevitt C, Wang Y, Wafa H, Skolarus L, Bhalla A, Muruet-Gutierrez W, Emmett E, Sommerville P, Birns J, Sackley C, Clarke S, Hamidi F, Stevens E, Rudd A, Rodgers H and Wolfe C (2022) Stroke pathway — An evidence base for commissioning — An evidence review for NHS England and NHS Improvement, NIHR Open Research, 10.3310/nihropenres.13257.1, 2, (43) Asaithambi G and Tipps M (2020) Quality of life among ischemic stroke patients eligible for endovascular treatment: analysis of the DEFUSE 3 trial, Journal of NeuroInterventional Surgery, 10.1136/neurintsurg-2020-016399, 13:8, (703-706), Online publication date: 1-Aug-2021. DE GRAAF J, VISSER-MEILY J, SCHEPERS V, BAARS A, KAPPELLE L, PASSIER P, WERMER M, DE WIT D and POST M Comparison between EQ-5D-5L and PROMIS-10 to evaluate health-related quality of life 3 months after stroke: a cross-sectional multicenter study, European Journal of Physical and Rehabilitation Medicine, 10.23736/S1973-9087.21.06335-8, 57:3 Lapin B, Thompson N, Schuster A, Honomichl R and Katzan I (2021) The validity of proxy responses on patient-reported outcome measures: Are proxies a reliable alternative to stroke patients' self-report?, Quality of Life Research, 10.1007/s11136-021-02758-9, 30:6, (1735-1745), Online publication date: 1-Jun-2021. Lapin B, Thompson N, Schuster A and Katzan I (2021) Magnitude and Variability of Stroke Patient-Proxy Disagreement Across Multiple Health Domains, Archives of Physical Medicine and Rehabilitation, 10.1016/j.apmr.2020.09.378, 102:3, (440-447), Online publication date: 1-Mar-2021. Lin C, Lee J, Hurt C, Lazar R, Arevalo Y, Prabhakaran S and Harvey R (2020) Gait Measures at Admission to Inpatient Rehabilitation after Ischemic Stroke Predict 3‐Month Quality of Life and Function, PM&R, 10.1002/pmrj.12402, 13:3, (258-264), Online publication date: 1-Mar-2021. Lens C, Demeestere J, Vanhaecht K and Lemmens R (2021) Patient Reported Outcomes Measurements Information System in Stroke Patients in Full and Shortened Format, Frontiers in Neurology, 10.3389/fneur.2020.630850, 11 MUTU C, CEREI Larisa-Georgiana and Munteanu C (2020) The effect of the thrombolytic therapy on the early rehabilitation of patients with acute ischemic stroke – study report, Balneo Research Journal, 10.12680/balneo.2020.386:Vol.11, no.4, (494-497), Online publication date: 5-Dec-2020. Gadson D, Marshall R and Franic D (2020) Psychometric evaluation of condition-specific instruments used to assess health-related quality of life and related constructs in aphasia, Aphasiology, 10.1080/02687038.2020.1787731, 34:12, (1506-1534), Online publication date: 1-Dec-2020. Mills K, Schneider R, Saint-Hilaire M, Ross G, Hauser R, Lang A, Halverson M, Oakes D, Eberly S, Litvan I, Blindauer K, Aquino C, Simuni T and Marras C (2020) Cognitive impairment in Parkinson's disease: Associations between subjective and objective cognitive decline in a large longitudinal study, Parkinsonism & Related Disorders, 10.1016/j.parkreldis.2020.09.028, 80, (127-132), Online publication date: 1-Nov-2020. Askew R, Capo-Lugo C, Sangha R, Naidech A and Prabhakaran S (2020) Trade-Offs in Quality-of-Life Assessment Between the Modified Rankin Scale and Neuro-QoL Measures, Value in Health, 10.1016/j.jval.2020.06.011, 23:10, (1366-1372), Online publication date: 1-Oct-2020. Askew R, Capo-Lugo C, Naidech A and Prabhakaran S (2020) Differential Effects of Time to Initiation of Therapy on Disability and Quality of Life in Patients With Mild and Moderate to Severe Ischemic Stroke, Archives of Physical Medicine and Rehabilitation, 10.1016/j.apmr.2020.05.005, 101:9, (1515-1522.e1), Online publication date: 1-Sep-2020. Blum R, Tomlinson A, Jetté N, Kwon C, Easton A and Yeshokumar A (2020) Assessment of long-term psychosocial outcomes in anti-NMDA receptor encephalitis, Epilepsy & Behavior, 10.1016/j.yebeh.2020.107088, 108, (107088), Online publication date: 1-Jul-2020. Kumar S, Lanzino G and Flemming K (2019) Affected health domains in patients with brainstem cavernous malformations, Acta Neurochirurgica, 10.1007/s00701-019-04075-0, 161:12, (2521-2526), Online publication date: 1-Dec-2019. Lin C, Katkar M, Lee J, Roth E, Harvey R and Prabhakaran S (2019) Functional Measures Upon Admission to Acute Inpatient Rehabilitation Predict Quality of Life After Ischemic Stroke, Archives of Physical Medicine and Rehabilitation, 10.1016/j.apmr.2018.06.007, 100:3, (481-487.e2), Online publication date: 1-Mar-2019. Lapin B, Thompson N, Schuster A and Katzan I (2018) Clinical Utility of Patient-Reported Outcome Measurement Information System Domain Scales, Circulation: Cardiovascular Quality and Outcomes, 12:1, Online publication date: 1-Jan-2019. Yeoh Y, Koh G, Tan C, Lee K, Tu T, Singh R, Chang H, De Silva D, Ng Y, Ang Y, Yap P, Chew E, Merchant R, Yeo T, Chou N, Venketasubramanian N, Young S, Hoenig H, Matchar D and Luo N (2018) Can acute clinical outcomes predict health-related quality of life after stroke: a one-year prospective study of stroke survivors, Health and Quality of Life Outcomes, 10.1186/s12955-018-1043-3, 16:1, Online publication date: 1-Dec-2018. Oniszczenko W, Bitner-Szulc J, Szylberg A, Kuczko-Piekarska E, Zaborowska M and Wawrzyniak S (2018) Mental health and BIS/BAS dimensions in Parkinson's disease and multiple sclerosis patients and in stroke survivors, Personality and Individual Differences, 10.1016/j.paid.2018.05.016, 132, (1-5), Online publication date: 1-Oct-2018. Reeves M, Lisabeth L, Williams L, Katzan I, Kapral M, Deutsch A and Prvu-Bettger J (2018) Patient-Reported Outcome Measures (PROMs) for Acute Stroke: Rationale, Methods and Future Directions, Stroke, 49:6, (1549-1556), Online publication date: 1-Jun-2018.Katzan I and Lapin B (2018) PROMIS GH (Patient-Reported Outcomes Measurement Information System Global Health) Scale in Stroke, Stroke, 49:1, (147-154), Online publication date: 1-Jan-2018.Dobkin B and Dorsch A (2017) The Evolution of Personalized Behavioral Intervention Technology, Stroke, 48:8, (2329-2334), Online publication date: 1-Aug-2017.Lin C, Lee J, Chatterjee N, Corado C, Carroll T, Naidech A and Prabhakaran S (2017) Predicting Domain-Specific Health-Related Quality of Life Using Acute Infarct Volume, Stroke, 48:7, (1925-1931), Online publication date: 1-Jul-2017.Katzan I, Thompson N, Lapin B and Uchino K (2017) Added Value of Patient‐Reported Outcome Measures in Stroke Clinical Practice, Journal of the American Heart Association, 6:7, Online publication date: 1-Jul-2017.Knutson J, Gunzler D, Wilson R and Chae J (2016) Contralaterally Controlled Functional Electrical Stimulation Improves Hand Dexterity in Chronic Hemiparesis, Stroke, 47:10, (2596-2602), Online publication date: 1-Oct-2016. February 2016Vol 47, Issue 2 Advertisement Article InformationMetrics © 2016 American Heart Association, Inc.https://doi.org/10.1161/STROKEAHA.115.011377PMID: 26732572 Manuscript receivedSeptember 1, 2015Manuscript acceptedDecember 8, 2015Originally publishedJanuary 5, 2016Manuscript revisedNovember 20, 2015 Keywordsresearchpatient-reported outcomesstrokequality of lifePDF download Advertisement SubjectsCerebrovascular Disease/StrokeClinical StudiesIschemic StrokeQuality and Outcomes
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