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Development of a Telephone Interview Version of the Chedoke-McMaster Stroke Assessment Activity Inventory.

ABSTRACT: Purpose: To develop a telephone version of the Chedoke-McMaster Stroke Assessment Activity Inventory (CMSA-AI) and estimate the test-retest reliability, interrater reliability (between participant and proxy), and construct validity of the scores for individuals with stroke. Methods: Adults with stroke and their caregivers or proxies were included. Participants were assessed with the CMSA-AI at discharge from a stroke rehabilitation unit and interviewed using the telephone version (TCMSA-AI). Two months after discharge, participants were evaluated with the CMSA-AI and interviewed over the phone using the TCMSA-AI on two occasions 2-3 days apart. Proxies were interviewed with the TCMSA-AI within another 2-3 days. Results: The mean age of the 53 participants with stroke was 62 years; 59% were male; 43% had right-side hemiparesis; 42 completed follow-up interviews; and 18 had proxies who also participated. Test-retest reliability showed an intra-class correlation coefficient of 0.98 (95% CI: 0.96, 0.99) for the total score, 0.96 (95% CI: 0.91, 0.98) for the Gross Motor Function Index, and 0.96 (95% CI: 0.91, 0.98) for the Walking Index, and an interrater reliability (between participant and proxy) of 0.75 (95% CI: 0.28, 0.90) for total score. Spearman's rho correlation between CMSA-AI and TCMSA-AI total scores was 0.62 (lower-sided 95% CI: 0.42) at discharge and 0.90 (lower-sided 95% CI: 0.82) at 2 months after discharge. Correlations between the change scores of the CMSA-AI and TCMSA-AI were 0.50 or lower. Conclusion: There is potential for remote evaluation of the functional mobility of individuals with stroke in research and clinical settings.

SUBMITTER: Barclay R

PROVIDER: S-EPMC5125464 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundFor a trial of supportive self-management for people with chronic headache we needed to develop and validate a telephone classification interview that can be used by a non-headache specialist to classify common chronic headache types in primary care. We aimed to specifically: exclude secondary headaches other than medication overuse, exclude primary headache disorders other than migraine and tension type headache (TTH), distinguish between chronic migraine and chronic TTH, and identify medication overuse headache.MethodsWe held a headache classification consensus conference to draw on evidence and expertise to inform the content of a logic model underpinning the classification interview. Nurses trained to use the logic model did telephone classification interviews with participants recruited from primary care. Doctors specialising in headache did a second validation interview.ResultsTwenty-six delegates attended the headache classification conference including headache specialist doctors, nurses and lay representatives (with chronic headache). We trained six nurses to do the classification interviews and completed 107 paired interviews, median days between interviews was 32 days (interquartile range 21-48 days). We measured level of agreement between the nurse and doctor interviews using proportion of concordance, simple kappa and prevalence-adjusted bias-adjusted kappa (PABAK). Proportion of concordance of agreement between nurse and doctor interviews was 0.76, simple kappa coefficient κ 0.31 (95% CI, 0.09 to 0.52), and PABAK 0.51 (95% CI, 0.35 to 0.68), a moderate agreement. In a sensitivity test following review of headache characteristics recorded, concordance was 0.91, κ = 0.53 (95% CI, 0.28 to 0.79), and PABAK = 0.81 (95% CI, 0.70 to 0.92), a very good agreement.ConclusionWe developed and validated a new evidence-based telephone classification interview that can be used by a non-headache specialist to classify common chronic headache types in primary care.

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Project description:BackgroundTimely and appropriate hospital treatment of acute cerebrovascular diseases (stroke and Transient Ischemic Attacks - TIA) improves patient outcomes. Emergency Medical Service (EMS) dispatchers who can identify cerebrovascular disease symptoms during telephone requests for emergency service also contribute to these improved outcomes. The Italian Ministry of Health issued guidelines on the management of AC patients in pre-hospital emergency service, including Cincinnati Prehospital Stroke Scale (CPSS) use.We measured the sensitivity and Positive Predictive Value (PPV) of EMS dispatchers' ability to recognize stroke/TIA symptoms and evaluated whether the CPSS improves accuracy.MethodsA cross-sectional multicentre study was conducted to collect data from 38 Italian emergency operative centres on all cases identified with stroke/TIA symptoms at the time of dispatch and all cases with stroke/TIA symptoms identified on the scene by the ambulance personnel from November 2010 to May 2011.ResultsThe study included 21760 cases: 18231 with stroke/TIA symptoms at dispatch and 9791 with symptoms confirmed on the scene. The PPV of the dispatch stroke/TIA symptoms identification was 34.3% (95% CI 33.7-35.0; 6262/18231) and the sensitivity was 64.0% (95% CI 63.0-64.9; 6262/9791). Centres using CPSS more often (>10% of cases) had both higher PPV (56%; CI 95% 57-60 vs 18%; CI 95% 17-19) and higher sensitivity (71%; CI 95% 87-89 vs 52%; CI 95% 51-54).In the multivariate regression a centre's CPSS use was associated with PPV (beta 0.48 p = 0.014) and negatively associated with sensitivity (beta -0.36; p = 0.063); centre sensitivity was associated with CPSS (beta 0.32; p = 0.002), adjusting for PPV.ConclusionsCentres that use CPSS more frequently during phone dispatch showed greater agreement with on-the-scene prehospital assessments, both in correctly identifying more cases with stroke/TIA symptoms and in giving fewer false positives for non-stroke/TIA cases. Our study shows an extreme variability in the performance among OCs, highlighting that form many centres there is room for improvement in both sensitivity and positive predictive value of the dispatch. Our results should be used for benchmarking proposals in the effort to identify best practices across the country.

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Development of a Telephone Interview Version of the Chedoke-McMaster Stroke Assessment Activity Inventory.

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