Home-Time as a Surrogate Measure for Functional Outcome After Stroke: A Validation Study

References

• Feigin VL, Norrving B, Mensah GA. Global burden of stroke. Circ Res. 2017;120(3):439–448. doi:10.1161/CIRCRESAHA.116.30841328154096
   PubMed Web of Science ®Google Scholar
• Hsieh CY, Su CC, Shao SC, et al. Taiwan’s National Health Insurance Research database: past and future. Clin Epidemiol. 2019;11:349–358. doi:10.2147/CLEP.S19629331118821
   PubMed Web of Science ®Google Scholar
• Ung D, Kim J, Thrift AG, et al. Promising use of big data to increase the efficiency and comprehensiveness of stroke outcomes research. Stroke. 2019;50(5):1302–1309. doi:10.1161/STROKEAHA.118.02037231009352
   PubMed Web of Science ®Google Scholar
• Hsieh CY, Wu DP, Sung SF. Registry-based stroke research in Taiwan: past and future. Epidemiol Health. 2018;40:e2018004. doi:10.4178/epih.e201800429421864
   PubMed Web of Science ®Google Scholar
• Hannah D, Lindholm B, Maisch L. Certain uncertainty: life after stroke from the patient’s perspective. Circ Cardiovasc Qual Outcomes. 2014;7(6):968–969. doi:10.1161/CIRCOUTCOMES.114.00131525387779
   PubMed Web of Science ®Google Scholar
• Shah S, Xian Y, Olson DM, et al. Home-time is a patient-centered outcome variable for stroke: an executive summary. J Neurosci Nurs. 2019;51(3):110–112. doi:10.1097/JNN.000000000000043730964840
   PubMed Web of Science ®Google Scholar
• Fonarow GC, Liang L, Thomas L, et al. Assessment of home-time after acute ischemic stroke in medicare beneficiaries. Stroke. 2016;47(3):836–842. doi:10.1161/STROKEAHA.115.01159926892279
   PubMed Web of Science ®Google Scholar
• Yu AYX, Rogers E, Wang M, et al. Population-based study of home-time by stroke type and correlation with modified Rankin score. Neurology. 2017;89(19):1970–1976. doi:10.1212/WNL.000000000000463129021355
   PubMed Web of Science ®Google Scholar
• McDermid I, Barber M, Dennis M, et al. Home-time is a feasible and valid stroke outcome measure in national datasets. Stroke. 2019;50(5):1282–1285. doi:10.1161/STROKEAHA.118.02391630896358
   PubMed Web of Science ®Google Scholar
• O’Brien EC, Xian Y, Xu H, et al. Hospital variation in home-time after acute ischemic stroke: insights from the PROSPER study (patient-centered research into outcomes stroke patients prefer and effectiveness research). Stroke. 2016;47(10):2627–2633. doi:10.1161/STROKEAHA.116.01356327625383
   PubMed Web of Science ®Google Scholar
• 中華民國衛生福利部. Health and welfare data science center, health and welfare data science center. 2017 Available from: https://dep.mohw.gov.tw/DOS/np-2497-113.html. Accessed 520, 2020.
   Google Scholar
• Hsieh FI, Lien LM, Chen ST, et al. Get with the guidelines-stroke performance indicators: surveillance of stroke care in the Taiwan stroke registry: get with the guidelines-stroke in Taiwan. Circulation. 2010;122(11):1116–1123. doi:10.1161/CIRCULATIONAHA.110.93652620805428
   PubMed Web of Science ®Google Scholar
• Lai EC, Man KK, Chaiyakunapruk N, et al. Brief report: databases in the Asia-Pacific region: the potential for a distributed network approach. Epidemiology. 2015;26(6):815–820. doi:10.1097/EDE.000000000000032526133022
   PubMed Web of Science ®Google Scholar
• Cheng CL, Kao YH, Lin SJ, Lee CH, Lai ML. Validation of the National Health Insurance Research Database with ischemic stroke cases in Taiwan. Pharmacoepidemiol Drug Saf. 2011;20(3):236–242. doi:10.1002/pds.208721351304
   PubMed Web of Science ®Google Scholar
• 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(5):604–607. doi:10.1161/01.STR.19.5.6043363593
   PubMed Web of Science ®Google Scholar
• Wardlaw JM, Murray V, Berge E, Del Zoppo GJ. Thrombolysis for acute ischaemic stroke. Cochrane Database Syst Rev. 2014;7:Cd000213.
   PubMed Web of Science ®Google Scholar
• Quinn TJ, Dawson J, Walters MR, Lees KR. Functional outcome measures in contemporary stroke trials. Int J Stroke. 2009;4(3):200–205. doi:10.1111/j.1747-4949.2009.00271.x19659822
   PubMed Web of Science ®Google Scholar
• Taylor-Rowan M, Wilson A, Dawson J, Quinn TJ. Functional assessment for acute stroke trials: properties, analysis, and application. Front Neurol. 2018;9:191. doi:10.3389/fneur.2018.0019129632511
   PubMed Web of Science ®Google Scholar
• Broderick JP, Adeoye O, Elm J. Evolution of the modified rankin scale and its use in future stroke trials. Stroke. 2017;48(7):2007–2012. doi:10.1161/STROKEAHA.117.01786628626052
   PubMed Web of Science ®Google Scholar
• Hsieh CY, Huang HC, Wu DP, Li CY, Chiu MJ, Sung SF. Effect of rehabilitation intensity on mortality risk after stroke. Arch Phys Med Rehabil. 2018;99(6):1042–1048.e1046. doi:10.1016/j.apmr.2017.10.01129108967
   PubMed Web of Science ®Google Scholar
• Divani AA, Liu X, Di Napoli M, et al. Blood pressure variability predicts poor in-hospital outcome in spontaneous intracerebral hemorrhage. Stroke. 2019;50(8):2023–2029. doi:10.1161/STROKEAHA.119.02551431216966
   PubMed Web of Science ®Google Scholar
• Di Napoli M, Slevin M, Popa-Wagner A, Singh P, Lattanzi S, Divani AA. Monomeric C-reactive protein and cerebral hemorrhage: from bench to bedside. Front Immunol. 2018;9:1921. doi:10.3389/fimmu.2018.0192130254628
   PubMed Web of Science ®Google Scholar
• Lattanzi S, Pulcini A, Corradetti T, et al. Prediction of outcome in embolic strokes of undetermined source. J Stroke Cerebrovasc Dis. 2020;29(1):104486. doi:10.1016/j.jstrokecerebrovasdis.2019.10448631706753
   PubMed Web of Science ®Google Scholar
• Palmer WL, Bottle A, Davie C, Vincent CA, Aylin P. Meeting the ambition of measuring the quality of hospitals’ stroke care using routinely collected administrative data: a feasibility study. Int J Qual Health Care. 2013;25(4):429–436. doi:10.1093/intqhc/mzt03323584363
   PubMed Web of Science ®Google Scholar
• Balinskaite V, Bottle A, Shaw LJ, Majeed A, Aylin P. Reorganisation of stroke care and impact on mortality in patients admitted during weekends: a national descriptive study based on administrative data. BMJ Qual Saf. 2018;27(8):611–618. doi:10.1136/bmjqs-2017-006681
   Web of Science ®Google Scholar
• Hartley J, Li Y, Kunkel L, Crowcroft NS. The burden of infant group B streptococcal infections in Ontario: analysis of administrative data to estimate the potential benefits of new vaccines. Hum Vaccin Immunother. 2019;15(1):193–202. doi:10.1080/21645515.2018.151166630130440
   PubMed Web of Science ®Google Scholar
• Yu AY, Holodinsky JK, Zerna C, et al. Use and utility of administrative health data for stroke research and surveillance. Stroke. 2016;47(7):1946–1952. doi:10.1161/STROKEAHA.116.01239027174527
   PubMed Web of Science ®Google Scholar
• Sung SF, Hsieh CY, Kao Yang YH, et al. Developing a stroke severity index based on administrative data was feasible using data mining techniques. J Clin Epidemiol. 2015;68(11):1292–1300. doi:10.1016/j.jclinepi.2015.01.00925700940
   PubMed Web of Science ®Google Scholar
• Hsieh CY, Lin HJ, Chen CH, Li CY, Chiu MJ, Sung SF. “Weekend effect” on stroke mortality revisited: application of a claims-based stroke severity index in a population-based cohort study. Medicine. 2016;95(25):e4046. doi:10.1097/MD.000000000000404627336904
   PubMed Web of Science ®Google Scholar