- Journal List
- Sage Choice
- PMC6604401
As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsem*nt of, or agreement with, the contents by NLM or the National Institutes of Health.
Learn more: PMC Disclaimer | PMC Copyright Notice
Int J Stroke. 2019 Feb; 14(2): 115–124.
Published online 2018 Dec 3. doi:10.1177/1747493018816430
PMCID: PMC6604401
PMID: 30507363
Tess Fitzpatrick,1 Sophia Gocan,1 Chu Q Wang,2 Candyce Hamel,2 Aline Bourgoin,1 Dar Dowlatshahi,1,2 Grant Stotts,1,2 and Michel Shamy1,2
Author information Article notes Copyright and License information PMC Disclaimer
Associated Data
- Supplementary Materials
Abstract
Background
Identifying and treating patients with transient ischemic attack is aneffective means of preventing stroke. However, making this diagnosis can bechallenging, and over a third of patients referred to stroke preventionclinic are ultimately found to have alternate diagnoses.
Aims
We performed a systematic review to determine how neurologists diagnosetransient ischemic attack.
Summary of review
A systematic literature search was performed according to the PreferredReporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelinesusing MEDLINE, Embase, and the Cochrane Library databases. Publicationseligible for inclusion were those that included information on thedemographic or clinical features neurologists use to diagnose transientischemic attacks or transient ischemic attack–mimics. Of 1666 citations, 210abstracts were selected for full-text screening and 80 publications wereultimately deemed eligible for inclusion. Neurologists were more likely todiagnose transient ischemic attack based on clinical features includingnegative symptoms or speech deficits. Patients with positive symptoms,altered level of consciousness, or the presence of nonfocal symptoms such asconfusion or amnesia were more likely to be diagnosed with transientischemic attack–mimic. Neurologists commonly include mode of onset (i.e.sudden versus gradual), recurrence of attacks, and localizability ofsymptoms to a distinct vascular territory in the diagnostic decision-makingprocess. Transient ischemic attack diagnosis was more commonly associatedwith advanced age, preexisting hypertension, atrial fibrillation, and othervascular risk factors.
Conclusions
Neurologists rely on certain clinical and demographic features to distinguishtransient ischemic attacks from mimics, which are not currently reflected inwidely used risk scores. Clarifying how neurologists diagnose transientischemic attack may help frontline clinicians to better select patients forreferral to stroke prevention clinics.
Keywords: Transient ischemic attack, stroke, stroke mimic, stroke prevention, decision analysis
Introduction
In about 20% of cases, stroke is preceded by an episode of temporary symptoms calleda transient ischemic attack (TIA).1 Studies have shown that identifying and treating patients with TIA is aneffective means of preventing stroke.2,3 Since the highest risk forstroke is in the first 48 h following symptom onset,4–6 it is critical that diagnosisand assessment occur rapidly.
Unfortunately, diagnosing TIA can be difficult, as it depends on detailedhistory-taking; by definition, patients' symptoms have resolved at the time ofassessment, and there is no established biomarker for TIA. As a consequence,approximately 30–50% of patients referred to stroke prevention clinics (SPCs) with aprovisional diagnosis of TIA are ultimately found not to have had a TIA.7–9 This situation is problematic ashigh volumes of referrals of patients with TIA–mimics are directly related to delaysin the care of TIA patients.3
While a major focus of recent research has been on risk-stratifying patients with TIAin order to decrease wait times for the highest risk patients, the many proposedrisk scores10–13 suffer from an importantweakness: they are derived from, and applied to, an undifferentiated population ofpatients with transient neurological symptoms including both patients with TIAs andmimics (e.g. migraine or seizure).8,14 In other words, the riskscores themselves do not differentiate patients with TIA from other clinicalsyndromes.
Multiple small studies15–17 have looked atTIA diagnosis post hoc using expert panels for adjudication, though none has studieddecision-making in vivo and none has sought to describe the diagnostic process, i.e.why a certain diagnosis is made. As such, we performed a systematic review to assesshow and why neurologists call a particular clinical event a TIA or a mimic. We choseto study neurologists because they are considered stroke experts in most countriesand because expertise is currently the “gold standard” for TIA diagnosis. Ultimatelyour goal is to make the SPC referral process more efficient by developing a methodof selecting patients with TIA as accurately as possible from all those presentingto emergency departments and ambulatory clinics with transient neurological symptoms.18
Methods
A systematic review was performed to address the question: “How do neurologistsdiagnose TIA?” We adhered to the PRISMA 2009 statement and conformed to itschecklist (Supplementary Figure I).19
Search strategy and selection criteria
Keywords were selected and submitted to a librarian who created an initial searchstrategy. The search strategy was then revised to ensure that key studies werenot omitted. Databases searched included MEDLINE, Embase, and the CochraneLibrary. Supplementary Figure II details the search strategy that was used forMEDLINE. Similar strategies were utilized for the Embase and the CochraneLibrary. The searches were conducted from inception of each database until 23February 2017 with no language or date restrictions. The reference lists ofmanuscripts selected for inclusion were hand-searched for any additionalpotentially relevant citations that were not captured with the electronic searchstrategy alone.
Manuscripts were included if they explicitly addressed TIA diagnosis or if theirinclusion criteria directly informed our study. To reduce the risk ofpublication bias, both peer-reviewed publications and unpublished studies (e.g.conference abstracts without a subsequent publication) were included.
Both quantitative and qualitative studies were eligible for inclusion. Allobservational studies, including cohort, case–control, and cross-sectionaldesigns, and all interventional studies with primary or secondary outcomes aimedat answering our research question were included. Studies that did not directlyfocus on answering our question but indirectly revealed neurologists' diagnosticdecision-making by way of key statements or study inclusion criteria were alsoincluded. To ensure this systematic review was comprehensive and reflective ofexpert practice, textbooks and reviews, including nonsystematic approaches suchas opinion pieces, commentaries, and literature reviews, were eligible forinclusion if written by a neurologist. Because the diagnosis of TIA depends uponclinical judgment, we included manuscripts containing statements of expertopinion and experience-based reasoning, both of which are often best reflectedin nonsystematic reviews.
Manuscripts reflective of a nonneurologist only were excluded, as our goal was tofocus on neurologist diagnostic decision-making. These exclusions wereclassified as “wrong setting.” Unpublished studies were eligible for inclusionbut were excluded if there was not enough information in the abstract alone toanswer our research question and if a full publication did not follow.
Although the initial search strategy, as well as the title/abstract screeningstage did not have language restrictions, during full-text screening, studieswere excluded if the full text was in a language other than English astranslation services were unavailable. Language restrictions were not imposedearlier to allow us to keep track of the number of articles deemed ineligiblesimply due to language and therefore to allow us to assess the magnitude of anypotential language bias.
Studies of pediatric patients (under the age of 18) were similarly excludedduring the full-text screening stage as the objective of our systematic reviewwas to identify clinical features of TIA, and patients in this population mayexperience different symptoms, may be unable to recognize transient neurologicaldeficits, or may be unable to express their symptoms.
Screening
Search results were compiled using Covidence systematic review software.20 Duplicate references were automatically detected and removed. Tworeviewers independently screened each citation based on title and abstract.Pilot screening was performed for the first 25 records to ensure reviewers wereconsistent and to decrease conflicts. All disagreements were resolved throughconsensus discussion between the two reviewers with input from a thirdreviewer.
Two reviewers then independently reviewed the full text of each article includedfrom title and abstract screening, assessing eligibility for inclusion. Alldisagreements were again resolved through consensus discussion with input from athird reviewer.
Data extraction and synthesis
An abstraction datasheet was created using Microsoft Excel (2010) and tworeviewers independently extracted study-level characteristics (e.g. studydesign, country of conduct) and the relevant data from each publication. Thefocus was on the identification of factors associated with diagnosis of TIA orTIA–mimic, and the process utilized by neurologists in their diagnosticdecision-making. Where available, the rates of diagnosis of TIA and TIA–mimicwere also collected.
The results from the two independent extractions were then compared to ensureaccuracy and completeness. Any discrepancies were resolved through discussionbetween the two reviewers. The data were then compiled using QSR's InternationalNVivo 11 qualitative data analysis software.21
We performed a multistep “thematic synthesis,” which began with coding of text inNVivo in a “line-by-line” fashion, ensuring all relevant information wascaptured by the two reviewers. From the codes that were created, common themesemerged and concepts were grouped into the following categories: (1) symptomssuggestive of TIA, (2) qualitative features suggestive of TIA, (3) symptomssuggestive of TIA–mimic, (4) qualitative features suggestive of TIA–mimic, (5)risk factors and demographic features more common in TIA, and (6) risk factorsand demographic features more common in TIA–mimic. Finally, analytical themeswere generated from these descriptive themes to answer our initial question—“Howdo neurologists diagnose TIA?”
The only quantitative information collected, TIA–mimic rate, was analyzed withdescriptive statistics.
Critical appraisal
For descriptive purposes, each article that was included was assessed for risk ofbias and strength/quality of evidence. Records were critically appraised basedon six criteria—clarity of statement of aims, appropriateness of methodology,reliability/validity of data collection tools, reliability/validity of methodsof data analysis, clarity of statement of results, and overall relevance to ourquestion. These criteria were adapted from various quality assessment toolsavailable for qualitative research and selected after discussion between threereviewers.22,23 Two reviewers performed the ratings independently andevaluations were compared. Disagreements were settled through consensus-baseddiscussion.
Results
Search results
The database search identified 1985 citations (Figure 1). An additional 44 were lateridentified by hand-searching citation lists. With duplicates removed, there werea total of 1666 references. After title and abstract screening, 1456 recordswere excluded and the remaining 210 articles were assessed for eligibility withfull-text review. Ultimately 80 records were included in this review (seeSupplementary References). Reasons for exclusion were categorized as: (1)outcome not of interest; (2) abstract only, without enough information provided;(3) language other than English; (4) wrong population; (5) wrong setting; and(6) previous publication with duplicate material. A reference list of theexcluded studies with reasons for exclusion is presented in the SupplementaryMethods.
Figure 1.
PRISMA flow diagram.
Study characteristics
Study characteristics are presented in Supplementary Table 1. A total of 21different countries were represented, with the United States (31 publications),and the United Kingdom (20 publications) being most common. Seven unpublishedcohort studies and one unpublished case–control study were included (conferenceabstracts without subsequent manuscript publications). Publications includedwere mostly cohort design (49%), followed by literature review (21%) (Table 1).
Table 1.
Comparison of included records by study design
| Study design | Number (%) |
|---|---|
| Cohort study | 39 (49%) |
| Literature review | 17 (21%) |
| Opinion | 8 (10%) |
| Case report | 5 (6%) |
| Case series | 4 (5%) |
| Cross-sectional study | 3 (4%) |
| Case–control | 1 (1%) |
| Systematic review | 1 (1%) |
| Survey | 1 (1%) |
| Textbook | 1 (1%) |
Open in a separate window
Critical appraisal
Critical appraisal assessments are summarized in Table 2. Critical appraisal of eachindividual study is presented in Supplementary Table 2. Statement of aims andstatement of results were clear in the vast majority of publications (94 and90%, respectively). Data collection was performed appropriately in 88% ofpublications. Appraisal questions related to methodology and data analysis werenot applicable to certain study designs including opinion pieces and literaturereviews. Where applicable, however, most studies performed well on this qualitymeasure. Many of the studies (60%) were ultimately found to be of low relevance,but were included in our analysis because they did contribute content to thedata collected.
Table 2.
Summary of the critical appraisal for included studies
| Appraisal question | Yes | No | Unclear | N/A |
|---|---|---|---|---|
| Is there a clear statement of aims or a clearly definedquestion? | 75 (94%) | 5 (6%) | 0 (0%) | 0 (0%) |
| Was the methodology employed appropriate to the researchquestion? | 47 (59%) | 0 (0%) | 4 (5%) | 29 (36%) |
| Was the data collection performed appropriately? | 70 (88%) | 9 (11%) | 1 (1%) | 0 (0%) |
| Was the data analysis rigorous? | 34 (42%) | 5 (6%) | 6 (8%) | 35 (44%) |
| Was there a clear statement of results? | 72 (90%) | 8 (10%) | 0 (0%) | 0 (0%) |
| Was the overall relevance to our research questionhigh? | 32 (40%) | 48 (60%) | 0 (0%) | 0 (0%) |
Open in a separate window
N/A: not applicable.
Descriptive themes
The main themes that emerged are presented in the following subsections:
1) Symptoms suggestive of TIA
The most common clinical features that neurologists noted were suggestive ofTIA rather than a non-TIA diagnosis are presented in Figure 2 including the frequency ofeach reference.
Figure 2.
Commonly identified clinical features suggestive of TIA. Symptomsare depicted in light gray bubbles and qualitative features aredepicted in dark gray bubbles. N = number of publications makingreference to each differentiating feature. The percentage ofincluded studies is shown in parentheses. TIA: transientischemic attack.
Overall, “negative symptoms”—characterized by loss of function—were the mostfrequently described (69% of included studies). This broad category includedmotor, sensory, and visual symptoms. Terms utilized to describe negativemotor symptoms included “hemiparesis,” “unilateral arm/face/leg weakness,”“loss of motor function,” and “loss of muscle power.” Negative sensorysymptoms were described with the terms “sensory loss” and “numbness.” Bothmonocular and binocular negative visual symptoms were encompassed by thenegative visual symptoms category. Terms grouped included “hom*onymoushemianopsia,” “visual field deficit,” “visual loss,” “cortical blindness,”“monocular blindness,” and “amaurosis fugax.”
The second-most frequently described symptom neurologists noted to be inkeeping with TIA was “speech disturbance” (55% of included studies).Although some authors used specific terms such as “aphasia” or “dysarthria,”others used more general terms such as “speech disturbance” or “impairedspeech.” These nonspecific terms were difficult to interpret separately andtherefore all references to speech and communication were grouped into onecategory.
Other symptoms commonly considered by neurologists to be supportive of adiagnosis of TIA included “ataxia,” “diplopia,” and “vertigo with otherposterior circulation symptoms.” These were described in 14–18% of records.“Dizziness” was not a helpful differentiating feature: while some authorsidentified it as a symptom suggestive of TIA, a similar number of articlesstated that it was a symptom more suggestive of TIA–mimic. When specified as“isolated vertigo” neurologists were also much more likely to diagnose aTIA–mimic.
2) Qualitative features suggestive of TIA
In addition to the clinical symptoms described above, the expert diagnosticprocess also identified pattern of onset, localizability, and duration asimportant elements considered in diagnostic decision-making. In almostone-third of the articles (n = 25), neurologists were more likely todiagnose TIA if the onset of symptoms was “sudden,” “maximal at onset,”“nonprogressive,” or “acute.” Another characteristic identified in onequarter of included articles (n = 20) was “localizability” of the symptoms;terms grouped together included “focal,” “corresponding to a vascularterritory,” and “consistent with a known stroke syndrome.” The lastcharacteristic that was commonly identified as a TIA feature was symptomswith a “duration less than 1 h.”
3) Symptoms suggestive of TIA–mimic
Figure 3 displays thefeatures of transient neurological disturbance that neurologists consider tobe indicative of a TIA–mimic diagnosis. The most commonly identifiedsymptoms were those that fell under the category of “positive symptoms,”including motor, sensory, or visual phenomena (48% of records). Positivemotor symptoms were described with the following terms: “jerking,”“shaking,” “seizure-like activity,” and “involuntary movement.” Terms usedto describe positive sensory symptoms included “tingling” and“paresthesias.” “Scintillating scotoma,” “flashing lights,” and “visualaura” were grouped under the positive visual phenomena subsection.
Figure 3.
Commonly identified clinical features suggestive of TIA–mimic.Symptoms are depicted in light gray bubbles and qualitativefeatures are depicted in dark gray bubbles. N = number ofpublications making reference to each differentiating feature.The percentage of included studies is shown in parentheses. TIA:transient ischemic attack.
The next category of TIA–mimic symptoms identified by neurologists was“altered level of consciousness (LOC)” (46% of included studies). Withinthis category we grouped any disturbance in consciousness including“presyncope,” “loss of consciousness,” “decreased level of consciousness,”and “impaired consciousness.”
“Confusion” was separated from “altered level of consciousness” and wasgrouped with “cognitive symptoms” and “amnesia.” The presence of any ofthese symptoms was frequently considered to be supportive of a TIA–mimicdiagnosis (31% of records). Other recurrent TIA–mimic themes were“headache,” “bowel or bladder symptoms,” and “generalized weakness.”
4) Qualitative features suggestive of TIA–mimic
Features of symptoms suggestive of TIA–mimic included the inverse of thoseseen with TIA, including “nonfocal” and “nonlateralizing.” “Slow onset” ofsymptoms typically swayed neurologists toward a non-TIA diagnosis, as did,“slow progression,” “slow spread,” or “march” of symptoms (n = 30). Thepresence of a “Jacksonian march” was specifically identified as a key mimicfeature. Lastly, many authors considered TIA–mimic more likely if thepatient had had “recurrent” or “stereotyped” episodes (n = 9).
5) Risk factors and demographic features more common in TIA
Risk factors and demographic features associated with the diagnosis of TIAincluded advanced age, atrial fibrillation, preexisting hypertension,previous stroke/TIA, or other vascular risk factors including dyslipidemiaand type II diabetes (Figure 4). These features were mentioned relatively infrequentlycompared to the clinical characteristics described above.
Figure 4.
Risk factors and demographic features commonly identified aspredictors of TIA diagnosis and TIA–mimic diagnosis. N = numberof publications making reference to each risk factor. Thepercentage of included studies is shown in parentheses. TIA:transient ischemic attack.
6) Risk factors and demographic features more common in TIA–mimic
The only demographic feature that was consistently associated with adiagnosis of TIA–mimic diagnosis was younger age (Figure 4).
7) TIA–mimic rate
Twenty-seven (34%) of the included articles provided a TIA–mimic rate. Themimic rates ranged between 6 and 73%,24,25 with a median mimicrate of 36% (25th, 75th percentiles range: 26%, 50%).
Discussion
Diseases are often defined in relation to blood tests, imaging findings, or somecombination thereof. In the absence of such markers, diseases are diagnosed througha process of decision-making by experts, and this is the state of TIA incontemporary medicine. Therefore, we sought to perform a systematic review of allrelevant qualitative, quantitative, and mixed methods studies that would inform ourunderstanding of the process by which neurologists diagnose TIA. While in someregions, nonneurologists (i.e. geriatricians) may provide stroke care, we chose tolimit the scope of our search to neurologists for the sake of consistency and as ageneral reflection of practice in most regions. To the best of our knowledge, thisis the first qualitative systematic review to assess how neurologists diagnoseTIA.
Our study has revealed that according to neurologists, the most consistent predictorsfor a diagnosis of TIA include negative symptoms (loss of motor, sensory, or visualfunction) and speech disturbance. The strongest predictors for TIA–mimic arepositive symptoms (such as motor jerking, sensory tingling, or visual scotomas) andany alteration of consciousness. Certain characteristics including pattern of onset,localizability of symptoms, and symptom recurrence were also importantdiscriminative diagnostic features. While these findings may appear obvious to thosewho are experts, that speaks to the accuracy of our results at capturing theirdecision-making process. Moreover, these findings are not obvious to nonexperts,suggesting the importance of work like this. We recognize that this study is apreliminary step to further characterizing the decision-making process surroundingTIA.
Diffusion-weighted (DWI) MRI is more sensitive than CT for detecting acute ischemia,and up to one-third of patients diagnosed with TIA are found to have an infarct onDWI MRI.26 Consequently, many organizations have moved away from the traditional“time-based” definition of TIA toward a new “tissue-based” definition.27 While MRI can be a very useful tool and certainly reduces the rate offalse-negative diagnoses, it still cannot replace expert assessment, especially forthose patients who are MRI-negative. Furthermore, MRI is not available in allhealthcare settings. For these reasons, we chose to focus our study entirely on theclinical diagnosis of TIA.
In the absence of a reliable tool for the diagnosis of TIA, frontline cliniciansfrequently apply risk-stratification instruments such as the ABCD2 scorefor diagnostic purposes.28 The ABCD and later ABCD2 scores were developed from populations ofpatients with a provisional diagnosis of TIA, many of whom where later given a finaldiagnosis of TIA–mimic by experts.2 When applied in a blanket fashion to any patient with transient neurologicalsymptoms, these instruments can result in a large number of inappropriate urgentreferrals to the SPC since TIA–mimics can very easily generate high ABCD2 scores.29 We believe that a more standardized decisional process should be establishedfor TIA so that the inappropriate use of risk-stratification tools can beavoided.
To address this deficiency, two diagnostic algorithms have previously been developedfor TIA—the Dawson Score and the Diagnosis of TIA Score (DOTS).30,31 The DawsonScore is a clinical scoring tool developed in a specialist setting that considersnine predictive variables and was found to be of limited utility in a primary care setting.32 It has been criticized for struggling with posterior circulation32 and retinal31 events. In contrast, the DOTS considers 17 variables, many of which reflectedthe factors we identified in our systematic review. It had a sensitivity of 89% (CI:84–93%) and a specificity of 76% (70–81%)31 in an internal cohort, but has not yet been externally validated. Ultimately,these scores are seeking to approximate a diagnostic process that, until now, hadnot yet been described empirically.
Most of the variables in the DOTS were identified by our systematic review; however,our systematic review has also identified several novel concepts, which are notreflected in any previously developed TIA diagnostic algorithms, including thepattern of onset/spread of symptoms and recurrence/stereotyped nature of episodes.We recognize that in the right clinical context, recurrent or stereotyped symptomsdo not exclude vascular etiology altogether (e.g. capsular warning syndrome). Thishighlights the importance of considering the whole clinical picture rather thanmaking decisions based on isolated features. Another important lesson from our studyis that neurologists clearly rely on focal/lateralizable symptoms for the diagnosisof TIA. While we acknowledge that some populations, especially elderly women, maypresent with “nontraditional” stroke symptoms,33 evidence is conflicting and more research is needed on this subject.
We intend to use the results of our systematic review to inform further in vivostudies on the expert diagnosis of TIA. Our goal is to identify reliable factorsthat will help frontline clinicians make a provisional diagnosis of TIA with moreaccuracy. Rather than creating a new TIA score, we hope to focus our efforts oneducation around the key elements used in the process of TIA diagnosis. Thedissemination of knowledge to primary care and emergency room physicians could havea substantial impact on patient care, as it would decrease the number of patientsfalsely labeled with a TIA event. As such, the quality and volumes of referrals toSPCs could be improved, contributing to enhanced efficiency of stroke preventioninterventions. High rates of TIA–mimics referred for assessment contributes todelays in care through bottlenecking. If we are able to improve wait times,particularly for high-risk TIA patients, this could ultimately reduce stroke rates.The implications on health services are also significant, as better referrals wouldlead to marked cost savings by decreasing the number of unnecessary tests orderedfor referred patients, and ultimately reducing the costs associated with preventablestrokes.
This systematic review is not without limitations. Given the nature of TIA diagnosis,a variety of qualitative research studies have informed our analysis. Furthermore,we chose to include literature reviews and opinion pieces since expert opinion isoften best reflected using these approaches. Since there is no confirmatory test forTIA, we are relying on the assumption that neurologist opinion is the “goldstandard.” This naturally introduces potential bias as there will always be anelement of subjectivity when it comes to making a diagnosis based on a patient'shistory alone. Unfortunately, we do not see any way to avoid this since at thepresent time there are no blood biomarkers or imaging tests available to reliablydistinguish TIAs from TIA–mimics. Finally, another limitation of our study is thatour literature search was performed as of February 2017.
In conclusion, our systematic review has identified the key clinical characteristicsthat neurologists consider when differentiating between TIAs and TIA–mimics. Weintend to explore this distinction further by studying real-world decision-makingfor patients referred to our SPC. Educating frontline clinicians on the featuresidentified could have a significant impact on patient care and our healthcaresystem.
Supplemental Material
Supplemental material for How do neurologists diagnose transient ischemicattack: A systematic review:
Click here for additional data file.(462K, pdf)
Supplemental Material for How do neurologists diagnose transient ischemic attack:A systematic review by Tess Fitzpatrick, Sophia Gocan, Chu Q Wang, CandyceHamel, Aline Bourgoin, Dar Dowlatshahi, Grant Stotts and Michel Shamy inInternational Journal of Stroke
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to theresearch, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research,authorship, and/or publication of this article: Funding provided by the StrokeResearch Consortium, University of Ottawa Brain and Mind Research Institute.
References
1. Johnston SC, Gress DR, Browner WS, Sidney S.Short-term prognosis after emergency departmentdiagnosis of TIA. JAMA2000; 284: 2901. [PubMed] [Google Scholar]
2. Rothwell PM, Giles MF, Chandratheva A, et al.Effect of urgent treatment of transient ischaemic attack andminor stroke on early recurrent stroke (EXPRESS study): a prospectivepopulation-based sequential comparison.Lancet2007; 370:1432–1442. [PubMed] [Google Scholar]
3. Hall R, Khan F, O'Callaghan C, et al.Ontario stroke evaluation report 2013: spotlight on secondary strokeprevention and care, Toronto:Institute for Clinical Evaluative Sciences,2013. [Google Scholar]
4. Coutts SB, Modi J, Patel SK, Demchuk AM, Goyal M, Hill MD.CT/CT angiography and MRI findings predictrecurrent stroke after transient ischemic attack and minor stroke: resultsof the prospective CATCH study. Stroke2012; 43:1013–1017. [PubMed] [Google Scholar]
5. Gladstone DJ, Kapral MK, Fang J, Laupacis A, Tu JV.Management and outcomes of transient ischemicattacks in Ontario. Can Med Assoc2004; 170:1099–1104. [PMC free article] [PubMed] [Google Scholar]
6. Giles MF, Rothwell PM.Risk of stroke early after transient ischaemicattack: a systematic review and meta-analysis.Lancet Neurol2007; 6:1063–1072. [PubMed] [Google Scholar]
7. Bradley D, Cronin S, Kinsella JA, et al.Frequent inaccuracies in ABCD2 scoring in non-stroke specialists'referrals to a daily Rapid Access Stroke Prevention service.J Neurol Sci2013; 332:30–34. [PubMed] [Google Scholar]
8. Sheehan OC, Merwick A, Kelly LA, et al.Diagnostic usefulness of the ABCD2 score to distinguish transientischemic attack and minor ischemic stroke from noncerebrovascular events:the North Dublin TIA Study. Stroke2009; 40:3449–3454. [PubMed] [Google Scholar]
9. Martin PJ, Young G, Enevoldson TP, Humphrey PR.Overdiagnosis of TIA and minor stroke:experience at a regional neurovascular clinic.QJM1997; 90:759–763. [PubMed] [Google Scholar]
10. Rothwell PM, Giles MF, Flossmann E, et al.A simple score (ABCD) to identify individuals at high early riskof stroke after transient ischaemic attack.Lancet2005; 366:29–36. [PubMed] [Google Scholar]
11. Johnston SC, Rothwell PM, Nguyen-Huynh MN, et al.Validation and refinement of scores to predict very early strokerisk after transient ischaemic attack.Lancet2007; 369:283–292. [PubMed] [Google Scholar]
12. Merwick Á, Albers GW, Amarenco P, et al.Addition of brain and carotid imaging to the ABCD2 score toidentify patients at early risk of stroke after transient ischaemic attack:a multicentre observational study. LancetNeurol2010; 9:1060–1069. [PubMed] [Google Scholar]
13. Perry JJ, Sharma M, Sivilotti MLA, et al.A prospective cohort study of patients with transient ischemicattack to identify high-risk clinical characteristics.Stroke2014; 45:92–100. [PubMed] [Google Scholar]
14. Josephson SA, Sidney S, Pham TN, Bernstein AL, Johnston SC.Higher ABCD2 score predicts patients most likelyto have true transient ischemic attack.Stroke2008; 39:3096–3098. [PubMed] [Google Scholar]
15. Hand PJ, Kwan J, Lindley RI, Dennis MS, Wardlaw JM.Distinguishing between stroke and mimic at thebedside: the brain attack study. Stroke2006; 37:769–775. [PubMed] [Google Scholar]
16. Castle J, Mlynash M, Lee K, et al.Agreement regarding diagnosis of transient ischemic attack fairlylow among stroke-trained neurologists.Stroke2010; 41:1367–1370. [PubMed] [Google Scholar]
17. Prabhakaran S, Silver AJ, Warrior L, McClenathan B, Lee VH.Misdiagnosis of transient ischemic attacks inthe emergency room. Cerebrovasc Dis2008; 26:630–635. [PubMed] [Google Scholar]
18. Coutts SB, Barrett KM.TIA risk stratification: what an event was andwhy it happened are more important than a score.Neurology2015; 85:304–305. [PubMed] [Google Scholar]
19. Moher D, Liberati A, Tetzlaff J, Altman DG.Preferred reporting items for systematic reviewsand meta-analyses. Ann Intern Med2014; 151:264–269. [PubMed] [Google Scholar]
20. Covidence systematic reviewsoftware. Melbourne: Veritas Health Innovation, www.covidence.org.
21. NVivo qualitative data analysissoftware. QSR International Pty Ltd. Version 11,2017.
22. Critical Appraisal SkillsProgramme (CASP). CASP (systematic review) checklist, www.casp-uk.net/ (2017, accessed 10 August2017).
23. Thomas J, Harden A.Methods for the thematic synthesis ofqualitative research in systematic reviews. BMC MedRes Methodol2008; 8: 45. [PMC free article] [PubMed] [Google Scholar]
24. Díaz-Guzmán J, Sierra Hidalgo F, Calleja Castaño P, Martínez Salio A, Sánchez Sánchez C, Delgado Babiano A, et al.Identification of disorders mimicking acute stroke in a strokeunit: a case–control study. Cerebrovasc Dis2014; 37(suppl 1):693. [Google Scholar]
25. Lee W, Frayne J.Transient ischaemic attack clinic: an evaluationof diagnoses and clinical decision making. J ClinNeurosci2015; 22:645–648. [PubMed] [Google Scholar]
26. Wardlaw J, Brazzelli M, Miranda H, et al.An assessment of the cost-effectiveness of magnetic resonance,including diffusion-weighted imaging, in patients with transient ischaemicattack and minor stroke: a systematic review, meta-analysis and economicevaluation. Health Technol Assess2014; 18:1–368. [PMC free article] [PubMed] [Google Scholar]
27. Kernan WN, Ovbiagele B, Black HR, et al.Guidelines for the prevention of stroke in patients with strokeand transient ischemic attack: a guideline for healthcare professionals fromthe American Heart Association/American Stroke Association.Stroke2014; 45:2160–2236. [PubMed] [Google Scholar]
28. Edwards D, Cohn SR, Mavaddat N, et al.Varying uses of the ABCD2 scoring system in primary and secondarycare: a qualitative study. BMJ Open2012; 2:1–7. [PMC free article] [PubMed] [Google Scholar]
29. Bose P, Wilson A, Mistri A.Diagnosis and management of transient ischemicattacks in primary care: a systematic review. J PrimHealth Care2017; 9:114–130. [PubMed] [Google Scholar]
30. Dawson J, Lamb KE, Quinn TJ, et al.A recognition tool for transient ischaemicattack. QJM2009; 102:43–49. [PubMed] [Google Scholar]
31. Dutta D.Diagnosis of TIA (DOT) score – design andvalidation of a new clinical diagnostic tool for transient ischaemicattack. BMC Neurol2016; 16: 20. [PMC free article] [PubMed] [Google Scholar]
32. Lasserson DS, Mant D, Hobbs FDR, Rothwell PM.Validation of a TIA recognition tool in primaryand secondary care: implications for generalizability.Int J Stroke2015; 10:692–696. [PubMed] [Google Scholar]
33. Girijala RL, Sohrabji F, Bush RL.Sex differences in stroke: review of currentknowledge and evidence. Vasc Med2017; 22:135–145. [PubMed] [Google Scholar]
Articles from International Journal of Stroke are provided here courtesy of SAGE Publications
