BackgroundRecovery from stroke may often be incomplete, with unresolved issues persisting as unmet needs. However, the impact of these needs on both the health and wellbeing of people with stroke, subgroups, and their carers remains unclear.ObjectivesThis scoping review of reviews aimed to provide an overview of evidence on unmet needs and their impact on the wellbeing of people living in the community with stroke.MethodsRelevant databases (14) were searched from 2,000 onwards and included systematic, scoping, and umbrella reviews meeting criteria related to population, concept, and context, and reporting quantitative and/or qualitative data.ResultsOver 620 studies (including repeated studies across reviews) and 3.5 million participants were described in 28 eligible reviews. The needs and impacts were wide-ranging for the population as a whole and for sub-groups, e.g., with specific impairments (communication issues) or demographics (younger people who may have had a stroke or people who are culturally and linguistically diverse). No one framework covers the diversity of impacts on health and wellbeing—physical, emotional, and psychological health, as well as issues of relationships, inclusion, engagement, meaning, cultural and spiritual needs, financial, and other environmental domains.ConclusionOur findings provide important, often ignored insights and direction for people with stroke generally, as well as sub-groups. Ultimately, services and research should operate at multiple levels and address quality-of-life impacts, including social integration, sense of self, and life purpose.Systematic review registrationReview protocol registration: https://osf.io/efut8/.
Neurobehavioral dysregulation (NBD) is a core clinical feature of traumatic encephalopathy syndrome (TES), but its relationships with repetitive head impact (RHI) exposure, cognitive performance, and depressive symptoms remain unclear. This study examined clinical factors associated with NBD among former American football players with substantial RHI exposure. Cross-sectional baseline data were analyzed from 179 former American football players enrolled in the DIAGNOSE CTE Research Project, including 119 former professional and 60 former college players. NBD was assessed using measures of impulsivity, behavioral regulation, hostility, and emotional lability. Multivariate regression models evaluated associations of continuous NBD scores with depressive symptom dimensions, cognitive performance, playing level, and years of football participation, adjusting for demographic and clinical covariates. Secondary analyses evaluated dichotomized NBD outcomes using study-specific thresholds. Bonferroni-adjusted p-values were reported for multiple comparisons. Depressive symptoms demonstrated the most consistent associations with NBD. Greater neurovegetative depressive symptom burden was associated with greater impulsivity (estimate = 6.84; 95% CI = 4.45, 9.23; p-value < 0.0001), behavioral dysregulation (estimate = 11.63; 95% CI = 8.50, 14.76; p-value < 0.0001), hostility (estimate = 5.07; 95% CI = 2.32, 7.81; p-value = 0.0004), and emotional lability (estimate = 1.16; 95% CI = 0.12, 2.20; p-value = 0.0284). Greater agitated/reactive depressive symptom burden was associated with greater impulsivity (estimate = 3.42; 95% CI = 1.44, 5.41; p-value = 0.0008) and hostility (estimate = 5.11; 95% CI = 2.89, 7.32; p-value < 0.0001), while greater affective depressive symptom burden was associated with greater behavioral dysregulation (estimate = 3.09; 95% CI = 0.01, 6.18; p-value = 0.0494). Better verbal memory was associated with lower impulsivity (estimate = −2.02; 95% CI = -3.65, −0.40; p-value = 0.0149) and behavioral dysregulation (estimate = −2.64; 95% CI = −4.76, −0.52; p-value = 0.0150), while better executive speed was associated with lower behavioral dysregulation (estimate = −3.10; 95% CI = −5.11, −1.09; p-value = 0.0027). Years of football exposure was not independently associated with NBD outcomes. Among former American football players with substantial RHI exposure, depressive symptom burden was more consistently associated with NBD than football participation characteristics or cognitive performance. These findings support a heterogeneous clinical phenotype and underscore the importance of evaluating depressive symptoms when interpreting NBD in the context of TES.
ObjectiveTo evaluate the effects of adjunctive hyperbaric oxygen therapy (HBOT) on cognitive, neurological, and functional outcomes in patients with post-stroke cognitive impairment (PSCI), and explore potential sources of heterogeneity.MethodsEight databases were searched from inception to July 15, 2026. Randomized controlled trials (RCTs) evaluating adjunctive HBOT in patients with PSCI were included. The primary outcome was the Montreal Cognitive Assessment (MoCA); secondary outcomes included the Mini-Mental State Examination (MMSE), National Institutes of Health Stroke Scale (NIHSS), Modified Barthel Index (MBI), and Barthel Index (BI). Random-effects meta-analyses, prespecified subgroup analyses, and meta-regression were performed. Sensitivity analyses, funnel plots, Egger’s tests, and GRADE assessments were conducted.ResultsThirty-five RCTs involving 3,036 participants, all conducted in China, were included. Adjunctive HBOT was associated with higher MoCA scores (MD = 2.90, 95% CI: 2.47–3.33; p < 0.00001; I2 = 84%) and MMSE scores (MD = 2.68, 95% CI: 2.20–3.16; p < 0.00001; I2 = 83%). Improvements were also observed in NIHSS (MD = −2.61, 95% CI: −3.34 to −1.89; p < 0.00001; I2 = 93%), MBI (MD = 6.64, 95% CI: 3.76–9.52; p < 0.00001; I2 = 82%), and BI (MD = 8.77, 95% CI: 4.72–12.82;p < 0.00001; I2 = 82%). No statistically significant subgroup differences were observed for MoCA (p = 0.10) or MMSE (p = 0.43). Higher baseline MoCA scores tended to be associated with smaller treatment effects in meta-regression (β = −0.1411, p = 0.0637; R2 = 15.42%). Substantial heterogeneity remained largely unexplained. Evidence certainty was low for MoCA, MMSE, and MBI and very low for NIHSS and BI.ConclusionAdjunctive HBOT may provide cognitive and functional benefits in patients with PSCI. However, substantial unexplained heterogeneity, low-to-very-low certainty of evidence, and the exclusively Chinese evidence base warrant cautious interpretation and limit generalizability. Further well-designed RCTs involving diverse populations are needed.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/view/CRD420261473579, PROSPERO, CRD420261473579.
PurposeMigraine is characterized by heterogeneous manifestations, with pain being its most disabling feature. Although the International Classification of Headache Disorders, 3rd edition (ICHD-3), defines diagnostic criteria for migraine, it does not incorporate temporal dynamics of pain. While studies have described attack-level pain trajectory patterns, the translation of these dynamic features into patient-level stratification remains unexplored. This study aimed to classify individuals with episodic migraine according to pain trajectories and to characterise the clinical features of the resulting groups.Patients and methodsPatients fulfilling ICHD-3 criteria for episodic migraine participated in a prospective real-time study using a smartphone application to record migraine attacks. Pain onset, duration, intensity, and associated premonitory, concomitant, and postdromic symptoms were documented. A total of 344 migraine attacks from 51 patients were analyzed. Attack-level pain trajectories identified in earlier work were used to construct patient-level feature vectors representing the proportional distribution of attack types. These vectors were clustered using a K-means algorithm to identify patient subgroups.ResultsFifty-one patients (mean age: 38.8 ± 10.9 years; 90.2% women) recorded 344 migraine attacks. Five patient profiles were identified from the combination of four previously established pain trajectories: high-intensity, mixed pattern, acute-onset, prolonged-intense, and low-intensity. The mixed profile was the most frequent (39.2%), while the remaining profiles showed a clearer predominance of a specific attack type. Most conventional demographic and clinical variables, including age, sex, baseline diagnosis, and monthly migraine frequency, did not differ across profiles. Concomitant symptom burden differed across profiles, with significant differences in nausea, photophobia, and osmophobia after accounting for within-patient clustering and multiple comparisons. The low-intensity profile showed a lower premonitory symptom burden than the high-intensity, mixed, and prolonged-intense profiles, whereas the prolonged-intense profile showed a greater postdromic symptom burden than the low-intensity profile.ConclusionOur findings suggest that the way migraine pain evolves over time may help identify clinically distinct patient profiles. Considering pain trajectory adds a dynamic dimension to migraine phenotyping that is not captured by traditional diagnostic criteria and may contribute to improved phenotyping and hypothesis generation for personalized therapeutic strategies. Further studies in larger cohorts are needed to clarify its potential clinical relevance.
BackgroundResearch in chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is constrained by low prevalence, limited data sharing, and privacy regulations. Disease registries mitigate some of these barriers, yet the reuse of individual-level data remains challenging. Artificial intelligence– and regression-based synthetic data (SD) generation may offer a privacy-preserving solution, provided analytical validity is maintained. We aimed to validate SD derived from the Italian CIDP Registry using a published case–control study as a reference framework.MethodsWe analyzed a matched case–control dataset including 195 CIDP cases and 195 controls to examine lifestyle and dietary factors associated with CIDP risk. SD were generated using sequential conditional models stratified by sex. Fidelity was assessed by comparing real and SD in terms of marginal distributions, data distinguishability (propensity score mean squared error), and preservation of associations with CIDP risk using univariable and multivariable logistic regression.ResultsSD preserved the original case–control balance and sex distribution. Marginal distributions showed high concordance between real and SD, with minor smoothing in a small number of multi-level dietary variables. Distinguishability analyses indicated low separability between real and synthetic records. Univariable associations with CIDP risk were closely replicated, including the protective effects of higher fish and rice intake. Multivariable models demonstrated highly concordant effect estimates between datasets.ConclusionSD derived from the Italian CIDP Registry accurately reproduces key analytical properties of real-world data while preserving patient privacy. This approach enables reproducible and shareable CIDP research and may support future applications, including synthetic standard-of-care comparator cohorts and precision medicine–oriented investigations.
