Introduction and aims: Post-stroke cognitive impairment is found as a common result of stroke in many patients (Hochstenbach et al., 2003). This literature is mainly based on individuals aged >50 years. Importantly, the incidence of individuals who had a first-ever stroke at a relatively young age (<50 years, young-stroke henceforth) has been rising over the past decade (George, 2020; Kissela et al., 2012), accounting for approximately 10% of all strokes (Ekker et al., 2019; Putaala, 2016). Studies on cognition and language in young-stroke are scarce. Given that ageing can also affect the brain and cognitive functioning (Yankner et al., 2008), it is an open question whether patterns from the general literature on stroke generalize to young-stroke. The present study aimed to obtain a comprehensive overview of the literature on post-stroke cognitive functioning in young adults through a systematic review and meta-analysis. One of our goals was to describe what measurement tools are used to evaluate cognitive and language functioning in the young-stroke population. Furthermore, we investigated the proportion of reported cognitive and language impairment in this population. Methods: Four electronic databases (MEDLINE, Embase, PsycINFO, and Web of Science) were systematically searched according to the PRISMA guidelines (Page et al., 2021) on 23 December 2021. Two independent reviewers screened a total of 458 articles and assessed 154 for eligibility, 26 of which met all inclusion criteria: young to middle-aged adults (18-55 years) with a clinical diagnosis of a stroke; cognitive functioning evaluated as an outcome measure; an empirical study design. Seventeen of the 26 studies did not use aphasia as an exclusion criterion in their selection of participants. Descriptive analyses were used to evaluate the measurement tools employed to assess cognitive and language functioning. The pooled prevalence rate for impairment, based on the eligible studies, was assessed with random-effects meta-analysis for binominal distributions. We quantified and evaluated the heterogeneity by the I2 statistics and by visually checking the forest plots with the overlap of the confidence intervals. Results: All 26 studies could be used to describe what measurement tools are used to evaluate cognitive and language functioning after stroke in young adults. Fourteen studies used a cognitive screening test (e.g., MMSE). Ten studies used a more extensive neuropsychological test battery (including language tests) to evaluate cognitive functioning. Seven studies used both a cognitive screening test and a more extensive neuropsychological test battery (including language tests). Four studies used a questionnaire with self-report on cognitive and/or language functioning. In five studies cognitive and/or language functioning was not based on a reported test. Ten of the 26 studies were eligible for determining the prevalence of global cognitive impairment after stroke in young adults (total N across studies = 1,495). Seven of these 10 studies quantified cognitive impairment as their outcome measure by providing a cut-off score on a test. The pooled prevalence was 44% (95% CI: 34-54%). However, heterogeneity was very high (I2 = 92%, p < 0.01). Twelve of the 26 studies were eligible for determining the prevalence of language impairment after stroke in young adults (total N across studies = 3,018). Five of these 12 studies quantified language impairment as their outcome measure by providing a cut-off score on a language test. The pooled prevalence was 26% (95% CI: 17-37%). However, heterogeneity was very high (I2 = 97%, p < 0.01). Discussion: We showed that cognitive functioning is evaluated in different ways with a variety of measurement tools. Studies evaluating language function in this population are scarce and the comprehensiveness of the testing is low. Additionally, a quantified definition of language impairment is often not reported. Our pooled prevalence indicated that almost half of the young adults with a stroke had a global cognitive impairment and about one fourth had a language impairment. Given that we could not analyze the data as a function of time post-onset, it is less straightforward to relate these numbers to prevalence numbers in the literature (Berthier, 2005; Engelter et al., 2006; Tang et al., 2018). A striking finding in our study was that nine out of the 26 studies that investigated cognitive functioning excluded people with aphasia. It is easier to exclude those patients because of potential problems with understanding the tests. However, this yields a skewed picture of the young-stroke population. We decided to take an inclusive approach for this systematic review because of the low number of eligible studies. We included studies with different stroke types (ischaemic stroke, intracranial hemorrhage, or transient ischaemic attack) and different time points post onset. We did not exclude studies of lower quality, which, for example, did not report how they measured language impairment. This is probably one of the reasons for the high heterogeneity for the prevalence of cognitive and language impairment, indicating that the estimate is not consistent across studies. Further exploratory analyses should reveal what sources of heterogeneity can explain these results. This literature review reveals a lack of studies investigating cognitive and language functioning in the young-stroke population. The main reason to exclude articles during full-text screening was because of the age range of the patients. Studies included patients from all ages, but did not report the results separately per age range. A step forward would be to report the results on cognitive and language functioning in the stroke population by different age groups, together with improving the quality of studies by using a more quantifiable definition of impairment across studies.