Prehospital stroke scales as screening tools for early identification of stroke and transient ischemic attack.

BACKGROUND: Rapid and accurate detection of stroke by paramedics or other emergency clinicians at the time of first contact is crucial for timely initiation of appropriate treatment. Several stroke recognition scales have been developed to support the initial triage. However, their accuracy remains uncertain and there is no agreement which of the scales perform better. OBJECTIVES: To systematically identify and review the evidence pertaining to the test accuracy of validated stroke recognition scales, as used in a prehospital or emergency room (ER) setting to screen people suspected of having stroke. SEARCH METHODS: We searched CENTRAL, MEDLINE (Ovid), Embase (Ovid) and the Science Citation Index to 30 January 2018. We handsearched the reference lists of all included studies and other relevant publications and contacted experts in the field to identify additional studies or unpublished data. SELECTION CRITERIA: We included studies evaluating the accuracy of stroke recognition scales used in a prehospital or ER setting to identify stroke and transient Ischemic attack (TIA) in people suspected of stroke. The scales had to be applied to actual people and the results compared to a final diagnosis of stroke or TIA. We excluded studies that applied scales to patient records; enrolled only screen-positive participants and without complete 2 × 2 data. DATA COLLECTION AND ANALYSIS: Two review authors independently conducted a two-stage screening of all publications identified by the searches, extracted data and assessed the methodologic quality of the included studies using a tailored version of QUADAS-2. A third review author acted as an arbiter. We recalculated study-level sensitivity and specificity with 95% confidence intervals (CI), and presented them in forest plots and in the receiver operating characteristics (ROC) space. When a sufficient number of studies reported the accuracy of the test in the same setting (prehospital or ER) and the level of heterogeneity was relatively low, we pooled the results using the bivariate random-effects model. We plotted the results in the summary ROC (SROC) space presenting an estimate point (mean sensitivity and specificity) with 95% CI and prediction regions. Because of the small number of studies, we did not conduct meta-regression to investigate between-study heterogeneity and the relative accuracy of the scales. Instead, we summarized the results in tables and diagrams, and presented our findings narratively. MAIN RESULTS: We selected 23 studies for inclusion (22 journal articles and one conference abstract). We evaluated the following scales: Cincinnati Prehospital Stroke Scale (CPSS; 11 studies), Recognition of Stroke in the Emergency Room (ROSIER; eight studies), Face Arm Speech Time (FAST; five studies), Los Angeles Prehospital Stroke Scale (LAPSS; five studies), Melbourne Ambulance Stroke Scale (MASS; three studies), Ontario Prehospital Stroke Screening Tool (OPSST; one study), Medic Prehospital Assessment for Code Stroke (MedPACS; one study) and PreHospital Ambulance Stroke Test (PreHAST; one study). Nine studies compared the accuracy of two or more scales. We considered 12 studies at high risk of bias and one with applicability concerns in the patient selection domain; 14 at unclear risk of bias and one with applicability concerns in the reference standard domain; and the risk of bias in the flow and timing domain was high in one study and unclear in another 16.We pooled the results from five studies evaluating ROSIER in the ER and five studies evaluating LAPSS in a prehospital setting. The studies included in the meta-analysis of ROSIER were of relatively good methodologic quality and produced a summary sensitivity of 0.88 (95% CI 0.84 to 0.91), with the prediction interval ranging from approximately 0.75 to 0.95. This means that the test will miss on average 12% of people with stroke/TIA which, depending on the circumstances, could range from 5% to 25%. We could not obtain a reliable summary estimate of specificity due to extreme heterogeneity in study-level results. The summary sensitivity of LAPSS was 0.83 (95% CI 0.75 to 0.89) and summary specificity 0.93 (95% CI 0.88 to 0.96). However, we were uncertain in the validity of these results as four of the studies were at high and one at uncertain risk of bias. We did not report summary estimates for the rest of the scales, as the number of studies per test per setting was small, the risk of bias was high or uncertain, the results were highly heterogenous, or a combination of these.Studies comparing two or more scales in the same participants reported that ROSIER and FAST had similar accuracy when used in the ER. In the field, CPSS was more sensitive than MedPACS and LAPSS, but had similar sensitivity to that of MASS; and MASS was more sensitive than LAPSS. In contrast, MASS, ROSIER and MedPACS were more specific than CPSS; and the difference in the specificities of MASS and LAPSS was not statistically significant. AUTHORS' CONCLUSIONS: In the field, CPSS had consistently the highest sensitivity and, therefore, should be preferred to other scales. Further evidence is needed to determine its absolute accuracy and whether alternatives scales, such as MASS and ROSIER, which might have comparable sensitivity but higher specificity, should be used instead, to achieve better overall accuracy. In the ER, ROSIER should be the test of choice, as it was evaluated in more studies than FAST and showed consistently high sensitivity. In a cohort of 100 people of whom 62 have stroke/TIA, the test will miss on average seven people with stroke/TIA (ranging from three to 16). We were unable to obtain an estimate of its summary specificity. Because of the small number of studies per test per setting, high risk of bias, substantial differences in study characteristics and large between-study heterogeneity, these findings should be treated as provisional hypotheses that need further verification in better-designed studies.

A comparison of antiepileptic drug therapy in patients with severe intellectual disability and patients with normal intellect.

We describe and compare the antiepileptic drug (AED) management in patients with severe intellectual disability (ID) and those with normal intellect (NI) and focal epilepsy at a tertiary epilepsy center. Fifty patients with ID were compared to a control group of 50 patients with NI; the majority of the patients in both groups had medically refractory epilepsy. Patients with ID were currently taking and had been previously exposed to a greater number of different AEDs. Despite the fact that both groups of patients had beene qually exposed to both old and newer AEDs, patients with ID were more likely to be taking at least one old AED and were more commonly treated with benzodiazepines (clobazam was the most commonly used drug in this group). This difference is likely related to greater seizure frequency and co-morbid behavioral disturbance in the ID group as no bias was identified against utilization of the newer AEDs in patients with ID.

Trajectories of behavioral disturbance in dementia.

Predicting the progression of dementia is a challenge for clinicians yet this information is highly valued by patients' families. An informally observed 4-stage model of dementia can be helpful in educating caregivers and preparing them for what lies ahead. In the behavioral variant of frontotemporal dementia (bvFTD), this model describes the evolution of behavioral disturbances and is characterized by an inflection point between stage 2 (progressively severe behavioral aberration) and stage 3 (increasing apathy and remission of behavior problems). In this study, we sought evidence for this model using a database of serial Neuropsychiatric Inventory (NPI) scores for 45 patients with FTD and 47 patients with Alzheimer's disease (AD). We transformed the NPI scores into a single variable for each participant that represented the yearly rate of change in total NPI score and used this as the dependent variable in a multivariate linear regression. Age at onset of dementia, NPI score at initial visit, and duration of illness at first NPI all contributed significantly to the regression model in the bvFTD group. Participants with an initial NPI acquired before 6 years of disease duration tended to have a more positive rate of change in NPI total score (representing worsening behavioral disturbances) than those with an initial NPI performed after 6 years. None of the aforementioned variables were significantly associated with yearly change in NPI total score in the AD group. These results support a crescendo-decrescendo trajectory of behavioral symptoms in bvFTD but do not suggest that there is a similar pattern in AD, and further longitudinal data collection is necessary.