Agreement between ambulance nurses and physicians in assessing stroke patients

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included studies and other relevant publications and contacted experts in the field to identify additional studies or unpublished data.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.

Acute stroke alert activation, emergency service use, and reperfusion therapy in Sweden

OBJECTIVES

Ambulance services and stroke alerts reduce the time from stroke onset to acute stroke diagnosis. We describe the use of stroke alerts and ambulance services in different hospitals and patient groups and their relationship with reperfusion therapy.

METHODS

This nationwide study included 49,907 patients admitted with acute stroke who were registered in The Swedish Stroke Register (Riksstroke) in 2011-2012.

RESULTS

The proportions of patients admitted as stroke alerts out of all acute stroke admissions varied from 12.2% to 45.7% in university hospitals (n = 9), 0.5% to 38.7% in specialized nonuniversity hospitals (n = 22), and 4.2% to 40.3% in community hospitals (n = 41). Younger age, atrial fibrillation (AF), living in an institution, reduced consciousness upon admission, and hemorrhagic stroke were factors associated with a higher probability of stroke alerts. Living alone, primary school education, non-European origin, previous stroke, diabetes, smoking, and dependency in activities of daily living (ADL) were associated with a lower probability of stroke alert. The proportion of patients arriving at the hospital by ambulance varied from 60.3% to 94.5%. Older age, living alone, primary school education, being born in a European country, previous stroke, AF, dependency in ADL, living in an institution, reduced consciousness upon admission, and hemorrhagic stroke were associated with ambulance services. Hospital stroke alert frequencies correlated strongly with reperfusion rates (r = .75).

CONCLUSION

Acute stroke alerts have a significant potential to improve stroke reperfusion rates. Prehospital stroke management varies conspicuously between hospitals and patient groups, and the elderly and patients living alone have a markedly reduced likelihood of stroke alerts.

Detecting Sepsis: Are Two Opinions Better Than One?

The diagnosis of sepsis requires that objective criteria be met with a corresponding subjective suspicion of infection. We conducted a study to characterize the agreement between different providers' suspicion of infection and the correlation with patient outcomes using prospective data from a general medicine ward. Registered nurse (RN) suspicion of infection was collected every 12 hours and compared with medical doctor or advanced practice professional (MD/APP) suspicion, defined as an existing order for antibiotics or a new order for blood or urine cultures within the 12 hours before nursing screen time. During the study period, 1386 patients yielded 11,489 screens, 3744 (32.6%) of which met at least 2 systemic inflammatory response syndrome (SIRS) criteria. Infection was suspected by RN and MD/APP in 5.8% of cases, by RN only in 22.2%, by MD/APP only in 7.2%, and by neither provider in 64.7%. Overall agreement rate was 80.7% for suspicion of infection (κ = 0.11, P < 0.001). Progression to severe sepsis or shock was highest when both providers suspected infection in a SIRS-positive patient (17.7%), was substantially reduced with single-provider suspicion (6.0%), and was lowest when neither provider suspected infection (1.5%) (P < 0.001). Provider disagreement regarding suspected infection is common, with RNs suspecting infection more often, suggesting that a collaborative model for sepsis detection may improve timing and accuracy. Journal of Hospital Medicine 2017;12:256-258.

Assessment of acute stroke cerebral CT examinations by anaesthesiologists

Background and purpose

It is essential to diagnose ischaemic stroke as soon as possible after symptom onset, so that thrombolytic treatment can be initiated as quickly as possible. This might be greatly facilitated if cerebral CT could be carried out in a pre‐hospital setting. The aim of this study was to evaluate if anaesthesiologists, who in Norway provide pre‐hospital medical care, could be trained to assess cerebral CT scans to exclude radiological contraindications for thrombolytic stroke treatment.

Methods

Thirteen anaesthesiologists attended an 8‐h course in acute stroke assessment, including a 2‐h introduction to the neuroradiology of acute stroke. Each participant then assessed 12 non‐contrast cerebral CT examinations of acute stroke patients with specific regard to radiological contraindications for thrombolytic therapy. Test results were compared with those of three experienced neuroradiologists. Inter‐rater agreement between anaesthesiologists and neuroradiologists was calculated using Cohen's Kappa statistics. Robustness of the results was assessed using the non‐parametric bootstrap.

Results

Among the neuroradiologists, Kappa was 1 for detecting radiological contraindications for thrombolytic therapy. Twelve of the 13 anaesthesiologists showed good or excellent agreement (Kappa > 0.60) with the neuroradiologists. The anaesthesiologists spent a median time of 2 min and 18 s on each CT scan.

Conclusions

This study suggests that anaesthesiologists who are experienced in pre‐hospital care may be quickly trained to assess cerebral CT examinations in acute stroke patients with regard to radiological contraindications for thrombolytic therapy.