Skip to main content

On the utility of the trail making test in migraine with and without aura: a meta-analysis

Abstract

This meta-analytical review assesses the utility of the Trail Making Test (TMT), versions A and B, in detecting migraine-related cognitive deficits. A comprehensive literature search was performed in two electronic databases and other sources to obtain relevant studies administering TMT to migraine patients. Search terms included “migraine” and “Trail Making”. Only studies in which the TMT-A, TMT-B or both were administered to adult patients suffering from migraine with and without aura were included. All pooled meta-analyses were based on random effects models. A total of 14 studies for TMT-A and 15 for TMT-B met inclusion criteria and were subjected to meta-analyses. Results showed that performance is worse in migraine patients than in controls for both the TMT-A (Hedges’ g = −.28) and TMT-B (g = −.37), with no difference between migraine with and without aura. This study demonstrates the sensitivity of the TMT in detecting cognitive alterations in migraine. This test should be considered for inclusion in cognitive batteries assessing patients with migraine.

Introduction

Migraine is a primary headache disorder associated with recurrent pain attacks involving throbbing or pulsing sensations, more frequently on one side of the head. Migraine attacks typically last from few hours to days, and the pain can be so incapacitating that it interferes with daily activities. These attacks could be preceded by sensory (primarily visual) disturbances called aura or not. While some authors have reported comparable cognitive abilities in migraineurs and healthy controls [1,2,3,4,5], the results of recent qualitative reviews [6, 7] suggest that, in contrast to other types of headache (e.g., tension type or cluster headache), cognitive dysfunctions are detectable in migraine sufferers even in the inter-ictal period [8], especially in clinic-based studies. These results are usually obtained above and beyond the side effects of preventive drugs and possible consequences of comorbidities, such as depression and anxiety [6]. Differences in cognitive abilities, when reported, are more often associated with migraine with aura (MwA), while whether also migraine without aura (MwoA) is related with cognitive impairment remains less clear [8].

Divergent results might also be partially due to heterogeneity of approaches used in assessing cognitive functions in individuals suffering from migraine. It would be therefore desirable to systematically assess the relevant literature. I will start by examining in this study whether migraine affects performance on the Trail Making Test (TMT), one of the most widely used neuropsychological tests to evaluate migraine-related cognitive dysfunction [9]. This test typically entails two forms: TMT-A requires patients to sequentially connect through lines 25 encircled numbers pseudo-randomly distributed on a sheet; In TMT-B patients must instead alternate between numbers and letters when connecting the different items in an ascending order (i.e., 1, A, 2, B etc.). The score of each part is calculated as the number of seconds required to complete the test. This test was incorporated into the US Army Individual Test Battery [10], and then later adapted for the Halstead-Reitan Test Battery [11,12,13] and other batteries [14]. The TMT-A is typically conceived as a measure of visual search and speed of processing, whereas the TMT-B is assumed to additionally measure mental flexibility and executive functions more generally [15,16,17,18]. The high popularity of the TMT in the neuropsychological assessment of cognitive and executive dysfunction in general, but also in migraine specifically, could be explained by its simplicity and short administration time.

However, to date there has not been any quantitative assessment of the sensitivity of the TMT in detecting cognitive deficits in the migraine literature. A meta-analytical approach is perfectly suited to formally test whether the TMT is sensitive and worth being used in the neuropsychological assessment of migraine, as it exhaustively reviews the literature, aggregates individual studies overcoming their limits (e.g., low power), and quantifies differences between groups.

The objective of this meta-analytical study is therefore to understand whether performance on the TMT-A and B (operationalized as the amount of time necessary to complete each form) differs between patients suffering from MwA and MwoA and matched healthy controls. The results of this quantitative review could be relevant to the clinical practitioners who want to assess cognitive disfunction in migraine and have to decide whether to include the TMT in their battery, and to generally inform the debate over whether migraine is associated with cognitive impairment or does not exert any impact on cognitive functioning [3, 5].

Methods

Protocol and registration

The protocol for this meta-analysis was submitted on PROSPERO (https://www.crd.york.ac.uk/PROSPERO/) with the registration ID #160041.

Eligibility criteria

The following inclusion criteria were used to select articles for the meta-analyses: 1) Adult participants (age > 18 years) suffering from MwA or MwoA; whenever an alternative term was used in the retrieved article, that is “classic migraine” for MwA, and “common migraine” for MwoA, these were coded with the corresponding aura-related terms; 2) No comorbidity with other psychiatric/neurological conditions; 3) Testing during the inter-ictal period; 4) Inclusion of data on TMT-A, TMT-B or both; 5) Inclusion (or provision from corresponding author) of sample size for each sub-group and enough statistical information, such as means and standard deviations, and/or median and interquartile range, and/or t, F, X, so that effect sizes could be calculated or estimated; 6) Group studies (no single-cases) with a cross-sectional design; 7) Finally, given the variety of normative data available and their many limits (e.g., small sample size, restricted age and education ranges, lack of percentiles [19] cf. [18]), only articles in which TMT was also assessed in an ad-hoc matched control group were included. Studies with other types of headache, including inherited small-artery disease of the brain (CADASIL), familial hemiplegic migraine (FHM), cluster headache, and where the focus was on other pathologies were also excluded.

Information sources

A comprehensive literature search was carried out using Pubmed and PsychInfo. References in additional articles on the topic were also checked in order to identify other possibly relevant articles. Corresponding authors or co-authors were contacted by email when statistical information was insufficient in order to obtain missing information.

Search

The main literature search was carried out using the conjunction of the following search terms: “migraine” AND “trail making” with no restriction on publication date range. Studies should have been either published or in press to be included. All languages were considered, provided that there was an English version available. The last search was performed in the relevant databases on December first, 2019.

Study selection

Titles and abstracts of the retrieved studies were first screened by the author to assess adhesion to eligibility criteria. Then, full texts of retrieved articles were downloaded from sources when available; otherwise a request was made to the Network Inter Library Document Exchange system (NILDE, https://nilde.bo.cnr.it/) and/or to corresponding or other authors by email. Once a full text was obtained, a further eligibility check was performed by reading the whole article.

Selection choices for some studies also deserve mention. Since only two patients out of 40 (5%) had Familiar Hemiplegic Migraine (FHE) in El-Senousy et al. [20], that study was included. In another study [21], the standard deviation was estimated using the “range” method, whereby the difference between minimum and maximum values is divided by 4 [22]. For some studies ([21, 23, 24]; and two subgroups in [25]) it was not possible to know which type of migraine patients were tested. These works were retained assuming that the majority of the recruited patients would suffer from the most common types of migraine (MwA, MwoA). One study [26] also included adolescents (age range: 15–68 years); since visual inspection of their Fig. 1 showed that a very small minority of participants were < 18 years old, that study was included. Two studies [20, 27] were assumed to focus on adults, although exact age mean/range were missing.

Fig. 1
figure 1

PRISMA Flow Diagram of the studied screened, assessed for eligibility and included in the review

Age and education were well-matched between migraine patients and healthy controls in the vast majority of the included studies. However, a few exceptions need to be mentioned. In Martins and colleagues [24], the control sample was significantly older than the migraine group (66.8 ± 9 vs. 61.9 ± 7.6 years). Since the direction of this age difference should have acted against the hypothesis that TMT performance is affected in migraine, we decided to keep this study in our meta-analyses. In Tessitore and associates [28], the education level was significantly higher in controls than in migraine samples (MwoA: 13.2 ± 0.64; MwA: 14.85 ± 0.55; Healthy Controls: 17.25 ± 0.4 years). Since the samples were well-matched for other demographic characteristics (age, gender) and, more crucially, since the results of all the meta-analyses remained unaffected when this study was excluded, it was kept in the analyses reported here.

Data collection process

All statistical information necessary for performing the meta-analysis was extracted by the author from the retrieved articles, including sample size for each sub-group, and typically means and standard deviations of the number of seconds necessary to complete the TMT sub-tests or other information useful to calculate/estimate effect size. When statistical information was insufficient, the corresponding and/or another author were asked missing information by email. Data were reported, analyzed and plotted in Meta-Essentials 1.4 [29].

Data items

The number of seconds to complete each section (TMT-A and/or TMT-B) was chosen as the dependent variable, instead of more rarely reported measures of TMT performance, such as errors, ratio (TMT-B/TMT-A) or difference (TMT-B – TMT-A) scores. Separate effect sizes were calculated for each part (A/B) of the TMT, when both were available. The migraine type in the patient sample/s was also recorded (MwA, MwoA, mixed migraine). Whether a study adopted a blind neuropsychological evaluation on TMT performance or not was also reported (if nothing was specified, the study was considered non-blinded). It was also reported whether patients were tested during the inter-ictal period, during the attack (exclusion criterion) or this information was unspecified.

Risk of bias in individual studies

The author reported whether blinding was applied to the screened studies, to appreciate the risk of bias. To obtain more homogeneous results, studies focused on the adult age range only were included, while studies mainly recruiting children and adolescents were excluded. When reported, inclusion/exclusion criteria were noted. Since only few studies allowed patients with comorbidities or medication overuse (Table 1), their role could not be formally assessed.

Table 1 Summary of included studies assessing performance of patients with migraine on Trail Making Test (TMT)

Summary measures

The difference in mean number of seconds taken to complete each TMT section (TMT-A and TMT-B) between migraine patients and controls was used as the summary measure.

Synthesis of results

Data were synthesized if at least 5 studies were included. Two initial meta-analyses were performed for TMT-A and B, separately, by collapsing together patients suffering from MwA and MwoA. These two subgroups were either already combined in the original studies or combined means and standard deviations were calculated. Specifically, in those studies in which different subgroups of migraine patients were compared with the same group of healthy controls, data from the different experimental groups were combined by using formulas reported in [37], to avoid unit-of-analysis error due to unaddressed correlation between the estimated intervention effects from multiple comparisons. Inconsistency was calculated as the percentage of total variation across studies due to heterogeneity (named I2), as it does not depend on the number of studies [38]. Cochran’s Q statistic was used as an additional measure of consistency/heterogeneity across studies.

Risk of bias across studies

Risk of publication bias across studies was assessed through funnel plots [29]. In particular, if asymmetry was observed, the Trim-and-Fill method would impute potentially missing studies and adjust the combined effect size accordingly. The results of this approach should however be interpreted with caution, especially given that the included studies were few and not very homogeneous concerning several variables (age range, migraine duration, gender etc.).

Additional analyses

Since MwoA is typically associated with more frequent and disabling attacks than MwA, additional meta-analyses were performed to appreciate the performance difference for these two types of migraine on TMT-A and B performance, limited to studies reporting these data separately. Five studies satisfied this criterion.

Results

A PRISMA flowchart of the search and selection process is provided in Fig. 1.

Characteristics of included studies

Methods

All 15 studies finally selected for the review were published in English. All the studies involved an evaluation of migraine patients and controls with a neuropsychological battery that included the TMT but also other tests. Some also included structural and/or functional neuroimaging evaluation [21, 26, 28, 34, 35] and psychiatric assessment [20], while another evaluated the effect of drug (over) use [25].

Participants

The included articles for the TMT-A involved 545 patients with migraine and 727 healthy controls, whereas, for the TMT-B, they included 629 patients with migraine and 768 healthy controls for the TMT-B. Commonly used inclusion criteria (see Table 1) entailed age ranges not involving children or older adults (with variable ranges in the adult lifespan across studies), length of history of migraine (> 1–10 years), a minimum number of attacks in the last year/month, normal brain neuroimaging, absence of other types of headache or chronic pain conditions, absence of other comorbidities (e.g., psychiatric, neurological, vascular or systemic diseases), no psychotropic drugs at time of testing, normal general cognitive function (e.g., no dementia; Intelligence Quotient, IQ > 80).

Intervention

Most of the works included in this review were focused on the assessment of neuropsychological deficits in migraine with TMT, versions A and/or B and other tests. Even those works which had other primary aims entailed some neuropsychological evaluation.

Outcome

The number of seconds to complete each section (TMT-A and B) was the chosen dependent variable. Other performance measures, such as errors, ratio (TMT-B/A) or difference (TMT B-A) scores, were excluded because they were very rarely reported. Separate effect sizes were calculated for each TMT part (A and B).

Results of individual studies

TMT-A: In the pooled TMT-A analysis (Fig. 2), migraine patients performed significantly more poorly than healthy controls (Hedges’ g = −.28, SE = .11, 95% confidence intervals, CI = -.51/−.05, prediction intervals = −.88/.32; Z-value = − 2.66, two-tailed p = .008). There was moderate evidence of heterogeneity (I2 = 52.25%; Q = 27.23, pq = .012).

Fig. 2
figure 2

Left: Summary results of meta-analysis regarding TMT-A performance differences between migraine patients and healthy controls, including Hedges’ g, Confidence Intervals (CI) and relative weight of each study. Right: Forest plot showing the effect size (with confidence interval) of individual studies and, below, the combined effect size with its confidence interval (in black) and its prediction interval (in green)

TMT-B: In the pooled TMT-B analysis (Fig. 3), migraine patients performed significantly worse than healthy controls (Hedges’ g = −.37, SE = .09, 95% CI = -.56/−.18, prediction intervals = −.85/.12; Z-value = − 4.12, two-tailed p = .00004). There was modest evidence of heterogeneity (I2 = 43.33%; Q = 24.71, pq = .038).

Fig. 3
figure 3

Left: Summary results of meta-analysis regarding TMT-B performance differences between migraine patients and healthy controls, including Hedges’ g, Confidence Intervals (CI) and relative weight of each study. Right: Forest plot showing the effect size (with confidence interval) of individual studies and, below, the combined effect size with its confidence interval (in black) and its prediction interval (in green)

Risk of bias across studies

Modest evidence of heterogeneity was observed for both TMT-A (I2 = 52.25%; Q = 27.23, pq = .012) and TMT-B (I2 = 43.33%; Q = 24.71, pq = .038). However, funnel plots (Fig. 4) did not show any risk of bias across studies for either TMT-A or TMT-B, as no evidence of asymmetry was found.

Fig. 4
figure 4

Funnel plots of the studies in the TMT-A (left) and TMT-B (right) meta-analyses (represented by blue dots), with effect size (on the x-axis above) and standard error (on the y-axis). The combined effect size (green dot) with its confidence interval (black) and prediction interval (green) is also shown. The plots also show a vertical line (in red) that runs through the (adjusted) combined effect size (CES) and the related lower and upper boundaries of the confidence interval (red diagonal lines). The absence of imputed data demonstrates no risk of bias

Additional analyses

In the meta-analyses contrasting migraine patients with and without aura (Fig. 5), there was no evidence of performance difference between these two groups either for TMT-A (Hedges’ g = 0, SE = .09, 95% CI = -.26/.26, prediction intervals = −.26/.26; Z-value = .01, two-tailed p = .992) or for TMT-B (Hedges’ g = 0, SE = .14, 95% CI = -.41/.40, prediction intervals = −.41/.40; Z-value = −.03, two-tailed p = .974). Moreover, there was no evidence of heterogeneity in the studies focusing on differences between MwA and MwoA either for TMT-A (I2 = 0%; Q = 1.60, pq = .809) or for TMT-B (I2 = 0%; Q = 3.89, pq = .421).

Fig. 5
figure 5

a: Summary results of meta-analysis regarding TMT-A performance differences between migraine with aura and migraine without aura, including Hedges’ g, Confidence Intervals (CI) and relative weight of each study. b: Forest plot showing the effect size (with CI) of individual studies and, below, the combined effect size with its CI (in black). c: Summary results of meta-analysis regarding TMT-B performance differences between migraine with aura and migraine without aura, including Hedges’ g, CI and relative weight of each study. d: Forest plot showing the effect size (with CI) of individual studies and, below, the combined effect size with its CI (in black)

Discussion

This meta-analytic study demonstrates that the TMT-A and B, which are used very frequently to assess cognitive abilities in migraine, are indeed useful neuropsychological tools to detect some of the cognitive deficits observed, even interictally, in patients suffering from MwA or MwoA. Specifically, the outcomes of the reported meta-analyses clearly showed migraine-related deficits in the amount of time necessary to complete both versions of the TMT.

Notably, the present analyses only focused on MwA and MwoA, and studies focusing on other types of migraine, and headache more generally, were not included. Thus, conclusions do not apply to othe important subsets of migraine patients. Additional meta-analyses evaluating potential performance differences between the specific subgroups of MwA and MwoA did not show any evidence of such differences either for the TMT-A or B. This is an important finding, as there is a debate in the literature concerning whether MwoA patients show a less severe cognitive impairment or even no disfunction when compared with MwA patients [8]. However, the interpretation of the latter ancillary analyses is limited by the fact that only few studies (N = 5) could be included.

It should also be noted that very few included studies adopted a blind design (N = 3). Moreover, some studies did not report important details, such as the migraine type, inclusion/exclusion criteria, gender composition or age range, which limits the generalizability of our findings and the possibility to carry out follow up meta-analyses regressing moderator variables on the effect size. Other studies were excluded because the reported information was not sufficient for the present purposes.

The TMT has reasonably high sensitivity, specificity and test-retest reliability from a clinical viewpoint [39, 40]; cf. [41]. However, the specificity of the cognitive constructs it measures is not high [42, 43]. Consequently, a derived score (e.g., TMT-B–TMT-A)/TMT-A), is recommended as a purer measure of executive functioning [17] which controls for general processing speed. However, derived TMT scores are rarely reported in studies on migraine. Moreover, while the results of this quantitative review clearly show that migraine is associated with cognitive deficits, only the performance on two tests (TMT-A and B) was taken into consideration. Some empirical studies failed to report cognitive deficits in migraine when other neuropsychological tests were used [3, 5]. Therefore, future work should also extend meta-analysis to other neuropsychological tests.

As a final remark, it would have been interesting to systematically evaluate the mediatory role of psychiatric comorbidities and treatment in the reported meta-analyses. There is indeed evidence that psychiatric comorbidities, such as depression and anxiety [44], and preventive medication [45, 46] may contribute to cognitive decline in migraineurs (see [47], for a review). However, the majority of studies comprised here either used these factors as exclusion criteria or did not mention them. Although it has been suggested that cognitive deficits in migraine are not fully explainable with prophylactic treatment and comorbidities [6], future meta-analyses should more carefully control for the impact of these factors when evaluating cognitive functioning in migraine patients.

Conclusions

The present work tested the utility of the TMT, in its two main forms A and B, in detecting cognitive alterations in patients suffering from MwA and MwoA during the inter-ictal period. By using a meta-analytical approach, it was shown that the time needed to complete the TMT is generally longer in patients with migraine as compared to healthy controls, with no difference between the two migraine subcategories considered here (MwA and MwoA). These findings fully justify the recommendation that the TMT should be included in neuropsychological batteries aimed at evaluating the long-term impact of migraine on cognition and at monitoring treatment-related effects in this disease.

Availability of data and materials

Data and material used for this meta-analytical review can be shared, until two years after publication, upon reasonable request to the corresponding author from qualified researchers for purposes of replicating procedures and results.

Abbreviations

FHE:

Familiar Hemiplegic Migraine

IQ:

Intelligence Quotient

MwA:

Migraine with aura

MwoA:

Migraine without aura

TMT:

Trail Making Test

References

  1. Gaist D, Pedersen L, Madsen C, Tsiropoulos I, Bak S, Sindrup S, McGue M, Rasmussen BK, Christensen K (2005) Long-term effects of migraine on cognitive function: a population-based study of Danish twins. Neurology 64:600–607

    Article  CAS  PubMed  Google Scholar 

  2. Jelicic M, van Boxtel MP, Houx PJ, Jolles J (2000) Does migraine headache affect cognitive function in the elderly? Report from the Maastricht aging study (MAAS). Headache 40:715–719

    Article  CAS  PubMed  Google Scholar 

  3. Leijdekkers ML, Passchier J, Goudswaard P, Menges LJ, Orlebeke JF (1990) Migraine patients cognitively impaired? Headache 30:352–358

    Article  CAS  PubMed  Google Scholar 

  4. Mulder EJ, Linssen WH, Passchier J, Orlebeke JF, de Geus EJ (1999) Interictal and postictal cognitive changes in migraine. Cephalalgia 19:557–565 discussion 541

    Article  CAS  PubMed  Google Scholar 

  5. Pearson AJ, Chronicle EP, Maylor EA, Bruce LA (2006) Cognitive function is not impaired in people with a long history of migraine: a blinded study. Cephalalgia 26:74–80

    Article  CAS  PubMed  Google Scholar 

  6. de Araújo CM, Barbosa IG, Lemos SMA, Domingues RB, Teixeira AL (2012) Cognitive impairment in migraine: a systematic review. Dement Neuropsychol 6:74–79

    Article  PubMed  PubMed Central  Google Scholar 

  7. Vuralli D, Ayata C, Bolay H Cognitive dysfunction and migraine. J Headache Pain; 19. Epub ahead of print 15 November 2018. https://doi.org/10.1186/s10194-018-0933-4

  8. O’Bryant SE, Marcus DA, Rains JC, Penzien DB (2005) Neuropsychology of migraine: present status and future directions. Expert Rev Neurother 5:363–370

    Article  PubMed  Google Scholar 

  9. Bowie CR, Harvey PD (2006) Administration and interpretation of the trail making test. Nat Protoc 1:2277–2281

    Article  CAS  PubMed  Google Scholar 

  10. U.S. Army Individual Test Battery (1944) Manual of directions and scoring. War Department, Adjunct General’s Office, Washington, DC

    Google Scholar 

  11. Reitan RM (1958) Validity of the Trail Making Test as an Indicator of Organic Brain Damage. Percept Mot Skills 8:271–276

    Article  Google Scholar 

  12. Reitan RM, Wolfson D (1985) The Halstead-Reitan neuropsychological test battery: theory and clinical interpretation. Neuropsychology Press, Tucson

    Google Scholar 

  13. Barth JT, Jarvis PE (1984) Halstead-Reitan Test Battery: An Interpretive Guide

    Google Scholar 

  14. Mondini S, Mapelli D, Vestri A, Arcara G, Bisiacchi P. Esame Neuropsicologico Breve 2. II. Milano: Raffaello Cortina Editore, http://www.raffaellocortina.it/scheda-libro/sara-mondini-daniela-mapelli-alec-vestri/esame-neuropsicologico-breve-2-9788860304193-870.html (2011, accessed 5 February 2020)

  15. Arbuthnott K, Frank J (2000) Trail making test, part B as a measure of executive control: validation using a set-switching paradigm. J Clin Exp Neuropsychol 22:518–528

    Article  CAS  PubMed  Google Scholar 

  16. Kortte KB, Horner MD, Windham WK (2002) The trail making test, part B: cognitive flexibility or ability to maintain set? Appl Neuropsychol 9:106–109

    Article  PubMed  Google Scholar 

  17. Sánchez-Cubillo I, Periáñez JA, Adrover-Roig D, Rodríguez-Sánchez JM, Ríos-Lago M, Tirapu J, Barceló F (2009) Construct validity of the trail making test: role of task-switching, working memory, inhibition/interference control, and visuomotor abilities. J Int Neuropsychol Soc 15:438–450

    Article  PubMed  Google Scholar 

  18. Tombaugh TN (2004) Trail making test a and B: normative data stratified by age and education. Arch Clin Neuropsychol 19:203–214

    Article  PubMed  Google Scholar 

  19. Mitrushina MN, Boone KB, Razani LJ, D'Elia LF (2005) Handbook of normative data for neuropsychological assessment, 2nd edn. Oxford University Press, Oxford

    Google Scholar 

  20. El-Senousy M, Mubarak A (1995) A study on psychiatric aspects of migraine. Arab J Psychiatry 6:200–213

    Google Scholar 

  21. Gómez-Beldarrain M, Carrasco M, Bilbao A, García-Moncó JC (2011) Orbitofrontal dysfunction predicts poor prognosis in chronic migraine with medication overuse. J Headache Pain 12:459–466

    Article  PubMed  PubMed Central  Google Scholar 

  22. Mendenhall W, Ott L, Scheaffer R (1971) Elementary Survey Sampling. Wadsworth Pub. Co, Belmont

    Google Scholar 

  23. Martínez S, Cáceres C, Mataró M, Escudero D, Latorre P, Dávalos A (2010) Is there progressive cognitive dysfunction in Sjögren syndrome? A preliminary study. Acta Neurol Scand 122:182–188

    Article  PubMed  Google Scholar 

  24. Martins IP, Gil-Gouveia R, Silva C, Maruta C, Oliveira AG (2012) Migraine, headaches, and cognition. Headache 52:1471–1482

    Article  PubMed  Google Scholar 

  25. Cai X, Xu X, Zhang A, Lin J, Wang X, He W, Fang Y (2019) Cognitive decline in chronic migraine with nonsteroid anti-inflammation drug overuse: a cross-sectional study. Pain Res Manag 2019:7307198

    Article  PubMed  PubMed Central  Google Scholar 

  26. Calandre EP, Bembibre J, Arnedo ML, Becerra D (2002) Cognitive disturbances and regional cerebral blood flow abnormalities in migraine patients: their relationship with the clinical manifestations of the illness. Cephalalgia 22:291–302

    Article  CAS  PubMed  Google Scholar 

  27. Dresler T, Lürding R, Paelecke-Habermann Y, Gaul C, Henkel K, Lindwurm-Späth A, Leinisch E, Jürgens TP (2012) Cluster headache and neuropsychological functioning. Cephalalgia 32:813–821

    Article  PubMed  Google Scholar 

  28. Tessitore A, Russo A, Conte F, Giordano A, De Stefano M, Lavorgna L, Corbo D, Caiazzo G, Esposito F, Tedeschi G (2015) Abnormal connectivity within executive resting-state network in migraine with Aura. Headache 55:794–805

    Article  PubMed  Google Scholar 

  29. Suurmond R, van Rhee H, Hak T (2017) Introduction, comparison, and validation of meta-essentials: a free and simple tool for meta-analysis. Res Synth Methods 8:537–553

    Article  PubMed  PubMed Central  Google Scholar 

  30. Baschi R, Monastero R, Cosentino G, Costa V, Giglia G, Fierro B, Brighina F (2019) Visuospatial learning is fostered in migraine: evidence by a neuropsychological study. Neurol Sci 40:2343–2348

    Article  PubMed  Google Scholar 

  31. Burker E, Hannay HJ, Halsey JH (1989) Neuropsychological functioning and personality characteristics of migrainous and nonmigrainous female college students. Neuropsychology 3:61–73

    Article  Google Scholar 

  32. Camarda C, Monastero R, Pipia C, Recca D, Camarda R (2007) Interictal executive dysfunction in migraineurs without aura: relationship with duration and intensity of attacks. Cephalalgia 27:1094–1100

    Article  CAS  PubMed  Google Scholar 

  33. Hooker WD, Raskin NH (1986) Neuropsychologic alterations in classic and common migraine. Arch Neurol 43:709–712

    Article  CAS  PubMed  Google Scholar 

  34. Le Pira F, Reggio E, Quattrocchi G, Sanfilippo C, Maci T, Cavallaro T, Zappia M (2014) Executive dysfunctions in migraine with and without aura: what is the role of white matter lesions? Headache 54:125–130

    Article  PubMed  Google Scholar 

  35. Lo Buono V, Bonanno L, Corallo F, Pisani LR, Lo Presti R, Grugno R, Di Lorenzo G, Bramanti P, Marino S (2017) Functional connectivity and cognitive impairment in migraine with and without aura. J Headache Pain 18:72

    Article  PubMed  PubMed Central  Google Scholar 

  36. Zeitlin C, Oddy M (1984) Cognitive impairment in patients with severe migraine. Br J Clin Psychol 23(Pt 1):27–35

    Article  PubMed  Google Scholar 

  37. Higgins J, Green S. Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0. The Cochrane Collaboration, https://training.cochrane.org/handbook/archive/v5.1/ (2011, accessed 5 February 2020)

  38. Higgins JPT, Thompson SG (2002) Quantifying heterogeneity in a meta-analysis. Stat Med 21:1539–1558

    Article  PubMed  Google Scholar 

  39. Adjorlolo S (2018) Diagnostic accuracy, sensitivity, and specificity of executive function tests in moderate traumatic brain injury in Ghana. Assessment 25:498–512

    Article  PubMed  Google Scholar 

  40. Giovagnoli AR, Del Pesce M, Mascheroni S, Simoncelli M, Laiacona M, Capitani E (1996) Trail making test: normative values from 287 normal adult controls. Ital J Neurol Sci 17:305–309

    Article  CAS  PubMed  Google Scholar 

  41. Dobbs BM, Shergill SS (2013) How effective is the trail making test (parts a and B) in identifying cognitively impaired drivers? Age Ageing 42:577–581

    Article  PubMed  Google Scholar 

  42. MacPherson SE, Allerhand M, Cox SR, Deary IJ (2019) Individual differences in cognitive processes underlying trail making test-B performance in old age: the Lothian birth cohort 1936. Intelligence 75:23–32

    Article  PubMed  PubMed Central  Google Scholar 

  43. Periáñez JA, Ríos-Lago M, Rodríguez-Sánchez JM, Adrover-Roig D, Sánchez-Cubillo I, Crespo-Facorro B, Álvarez-Linera J, Adrover-Roig D, Rodriguez-Sanchez JM (2007) Trail making test in traumatic brain injury, schizophrenia, and normal ageing: sample comparisons and normative data. Arch Clin Neuropsychol 22:433–447

    Article  PubMed  Google Scholar 

  44. Radat F, Swendsen J (2005) Psychiatric comorbidity in migraine: a review. Cephalalgia 25:165–178

    Article  CAS  PubMed  Google Scholar 

  45. Láinez MJA, Freitag FG, Pfeil J, Ascher S, Olson WH, Schwalen S (2007) Time course of adverse events most commonly associated with topiramate for migraine prevention. Eur J Neurol 14:900–906

    Article  PubMed  Google Scholar 

  46. Romigi A, Cervellino A, Marciani MG, Izzi F, Massoud R, Corona M, Torelli F, Zannino S, Uasone E, Placidi F (2008) Cognitive and psychiatric effects of topiramate monotherapy in migraine treatment: an open study. Eur J Neurol 15:190–195

    Article  CAS  PubMed  Google Scholar 

  47. Suhr JA, Seng EK (2012) Neuropsychological functioning in migraine: clinical and research implications. Cephalalgia 32:39–54

    Article  PubMed  Google Scholar 

  48. Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group (2010) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg 8:336–341

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

No funding to declare.

Author information

Authors and Affiliations

Authors

Contributions

AV: Conceptualization, Methodology, Formal Analysis, Writing – Original Manuscript, Writing – Review and Editing. The author(s) read and approved the final manuscript.

Corresponding author

Correspondence to Antonino Vallesi.

Ethics declarations

Ethics approval and consent to participate

The present meta-analysis was conducted by adhering as much as possible to the recommendation of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA [48];). Ethical approval is not required as this is a literature-based study.

Consent for publication

Not applicable.

Competing interests

Not applicable.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vallesi, A. On the utility of the trail making test in migraine with and without aura: a meta-analysis. J Headache Pain 21, 63 (2020). https://doi.org/10.1186/s10194-020-01137-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s10194-020-01137-y

Keywords