MétaCan
Menu
Back to cohort
Record W4315434436 · doi:10.1093/ageing/afac321

Are falls a manifestation of brain failure? Revisited 40 years later

2023· article· en· W4315434436 on OpenAlexafffund
Manuel Montero‐Odasso

Bibliographic record

VenueAge and Ageing · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsParkwood InstituteLawson Health Research InstituteWestern University
FundersCanadian Institutes of Health ResearchWestern UniversityWeston Family FoundationConsortium canadien en neurodégénérescence associée au vieillissement
KeywordsMedicineIntensive care medicinePediatrics

Abstract

fetched live from OpenAlex

Editorial to accompany: Gait and falls in cerebral small vessel disease: a systematic review and meta-analysis [5]. Vascular brain burden, evaluated as white matter hyperintensities (WMH), is associated with gait disorders and falls in older adults. Intensive hypertension management can reverse WMH, opening an opportunity for preventing ‘brain failure’ in older adults. Gait disorders and falls in older adults may be prevented by treating covert cerebrovascular disease and hypertension. More than four decades ago, Professor Bernard Isaacs postulated in this journal that to attribute falls in older individuals only to muscular-articular and sensory impairments and their effect on gait and balance was overly simplistic [1]. Rather, a failure of our sophisticated system of brain motor control plays a capital role in triggering falls [2]. Since his seminal article, clinical and research evidence have established that brain motor control of gait arises from specific cortical and subcortical brain areas and networks that share complex cognitive functions, such as executive function (Figure 1). Due to their particular watershed vascularisation (border-zone regions in the brain supplied by the major cerebral arteries where blood supply is decreased), these shared brain networks are highly susceptible to microvascular ischemia and the effects of hypertension that, when damaged, may lead to both gait impairments and falls and to severe cognitive decline [3]. Thus, white matter hyperintensities (WMH) may impair gait performance directly, by disrupting motor-related networks, or indirectly, by disrupting networks responsible for executive function that is fundamental for high-attentional motor control of gait [3]. Cognitive function and gait performance decline with ageing, and may lead to dementia and falls (gray lines). Low cognition not only predicts dementia, but also mobility decline and falls, whereas mobility decline and slow gait predict cognitive deterioration and progression to dementia (dotted lines). These simultaneous declines may occur due to burden in shared common brain networks. Factors and diseases damaging brain areas and brain network integrity, which are important for maintaining gait and cognition, are shown in red. From Montero-Odasso et al. [3]. The LADIS cohort study was one of the first to establish that covert cerebral small vessel disease (CSVD), expressed as WMH, is associated with gait impairments, falls and future disability [4]. In this issue of the Age and Ageing journal, Smith et al. present a systematic review and meta-analysis (SR & MA) that confirms this finding and adds evidence that other expressions of CSVD, including lacunar infarcts, cerebral microbleeds and enlarged perivascular spaces, are likewise associated with gait impairments, mainly slowing gait speed and falls [5]. Importantly, this SR & MA shows longitudinal associations between CSVD and further gait speed decline and falls, suggesting a causal role. WMH are highly prevalent in older adults, rising from about 5% for people aged 50 years to nearly 100% for people aged 90 years [6]. They are seen in brain MRI T2-weighted sequences and are supposed to represent CSVD, which are thought to result from ischaemia due to occlusive lesions of deep penetrating arteries, a phenomenon strongly associated with hypertension. However, the occurrence of WMH throughout the whole brain militates against ischemia being their sole cause, and other mechanisms such blood–brain barrier dysfunction due to degradation of tight junctions, brain venular stasis, endothelial dysfunction and chronic low grade of systemic/brain inflammation have been proposed [7, 8]. Interestingly, hypertension per se can cause endothelial dysfunction, blood–brain barrier dysfunction, and trigger low-grade systemic and vascular inflammation, as well as activation of microglia, which are also associated with CSVD [9]. Large cohort studies, including the Cardiovascular Health Study, the Mobilize Boston Study and the Gait and Brain Study, have shown that presence of WMH and their specific brain anatomic locations are associated with hypertension and with slowing gait, greater dual-task cost on gait, and falls [10, 11, 12]. As Smith et al. acknowledge, methodological differences in the original publications restricted their meta-analysis to just WMH volume. Future meta-analyses should address WMH anatomical locations and their association with gait impairments and fall risk. The integrity of white matter tracts seems to deteriorate early, before manifesting as WMH, as diffusion tensor imaging studies have shown that low white matter integrity in the corpus callosum, forceps minor and the left inferior fronto-occipital fasciculus were significantly associated with gait impairment and future falls in a small sample of older adults with mild cognitive impairment [13]. Besides CSVD, other potential brain changes and mechanisms underlying the causes of gait decline and increased falls have been described, including brain atrophy of selected cortical and subcortical areas, amyloid-β deposition burden, and accentuated depletion of neurotransmitters [14–19, 20]. The close proximity of frontal subcortical networks that control both motor and cognitive functions may explain why frontal atrophy and WMH may simultaneously cause dysfunction involving memory, executive function, gait and balance in older adults. Future research should address the relative contribution of CSVD in gait decline and falls compared with regional brain atrophy and/or brain amyloid-ß deposition. The authors’ findings also support treating manageable vascular risk factors and hypertension, especially when they represent early manifestations of brain damage, as such interventions have the potential to be a complementary method to prevent the loss of mobility and falls in older adults. The fact that three well-conducted clinical trials (SPRINT-MIND, PRoFESS and SCOPE) have shown that intensive antihypertensive treatment resulted in significantly less progression of WMH [21] suggests that antihypertensive treatments may also prevent or delay mobility decline and falls associated with impairments in gait and motor control. However, fluctuations of blood pressure and acute hypotension that can happen with intensive treatment can harm the brain. Therefore, those who might benefit the most, such as older adults with multimorbidity or frailty, should be carefully selected to avoid harm. In summary, This SR & MA present high-quality evidence to support the hypothesis [15] that WMH burden is associated with gait disorders in the course of ageing and future falls. Although important details require further study, our collective research findings, reinforced and enriched by the current study, strongly suggest that microvascular ischemic changes affecting our most complex organ, the brain, and contribute to the mobility decline associated with ageing. This could give rise to new strategies for the prevention of gait disorders and falls in older adults based on the management of cerebrovascular risk factors and hypertension to prevent ‘brain failure’. None declared. Manuel Montero-Odasso’s Program in Gait and Brain Health is supported by grants from the CIHR (MOP 211220, PJT 153100), the Weston Family Foundation (BH210118), the Ontario Neurodegenerative Disease Research Initiative (OBI 34739), the Canadian Consortium on Neurodegeneration in Aging (FRN CNA 137794) and the Department of Medicine Program of Experimental Medicine Research Award at the University of Western Ontario (POEM768915).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.248
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractno

Explore more

Same venueAge and AgeingSame topicMitochondrial Function and PathologyFrench-language works237,207