Functional cognitive disorder (FCD) describes cognitive dysfunction in the absence of an organic cause. It is increasingly prevalent in healthcare settings yet its key neuropsychological features ...have not been reported in large patient cohorts. We hypothesised that cognitive profiles in fibromyalgia (FM), chronic fatigue syndrome (CFS) and functional neurological disorders (FNDs) would provide a template for characterising FCD.
We conducted a systematic review of studies with cognition-related outcomes in FM, CFS and FND.
We selected 52 studies on FM, 95 on CFS and 39 on FND. We found a general discordance between high rates of subjective cognitive symptoms, including forgetfulness, distractibility and word-finding difficulties, and inconsistent objective neuropsychological deficits. Objective deficits were reported, including poor selective and divided attention, slow information processing and vulnerability to distraction. In some studies, cognitive performance was inversely correlated with pain, exertion and fatigue. Performance validity testing demonstrated poor effort in only a minority of subjects, and patients with CFS showed a heightened perception of effort.
The cognitive profiles of FM, CFS and non-cognitive FND are similar to the proposed features of FCD, suggesting common mechanistic underpinnings. Similar findings have been reported in patients with mild traumatic brain injury and whiplash. We hypothesise that pain, fatigue and excessive interoceptive monitoring produce a decrease in externally directed attention. This increases susceptibility to distraction and slows information processing, interfering with cognitive function, in particular multitasking. Routine cognitive processes are experienced as unduly effortful. This may reflect a switch from an automatic to a less efficient controlled or explicit cognitive mode, a mechanism that has also been proposed for impaired motor control in FND. These experiences might then be overinterpreted due to memory perfectionism and heightened self-monitoring of cognitive performance.
In The Lancet Neurology, Gaël Chételat and colleagues present a Personal View on the order in which use of PET-enabled dementia biomarkers should be considered in clinical practice.1 The authors ...advocate the use of these biomarkers largely on the basis of diagnostic specificity established in controlled research conditions, rather than of added value for patient outcomes in real-life settings. ...the authors promote the increased clinical use of PET-biomarkers in two ways. ...by suggesting that biomarkers might be indicated in populations beyond those covered by current so-called appropriate use criteria.2 Consequently, the Personal View contributes to the further normalisation of biomarkers as routine diagnostic tests, which in our view might be premature. The past performance of drug developers is poor, however, and the principal modifiers of the lived experience of dementia remain social, not medical. ...promoting clinical biomarker testing in anticipation of effective biomarker-based treatment conflates the value of research with benefit for individual patients.
Mild cognitive impairment (MCI) represents a liminal state between full cognitive health and dementia. The diagnosis is applied unevenly and cannot be accurately prognosticated, even with the use of ...biomarkers, and there is no established intervention to reduce risk of progression to dementia. Owing to the limited benefit and potential for iatrogenic harm associated with an MCI diagnosis, a better understanding of its psychosocial consequences is needed. In the linked paper, Munawar and colleagues provide cautious optimism; their patients were generally unharmed by an MCI diagnosis. However, the majority of patients and families either did not recall or did not fully understand the implications for future dementia risk. Only 20% made lifestyle changes, and the number receiving hearing aids was very low. These data demonstrate the poor return on using the clinic as the setting for improving ‘brain health’. Initiatives to prevent dementia are more effectively and equitably applied at population level.
An increasing proportion of cognitive difficulties are recognized to have a functional cause, the chief clinical indicator of which is internal inconsistency. When these symptoms are impairing or ...distressing, and not better explained by other disorders, this can be conceptualized as a cognitive variant of functional neurological disorder, termed functional cognitive disorder (FCD). FCD is likely very common in clinical practice but may be under-diagnosed. Clinicians in many settings make liberal use of the descriptive term mild cognitive impairment (MCI) for those with cognitive difficulties not impairing enough to qualify as dementia. However, MCI is an aetiology-neutral description, which therefore includes patients with a wide range of underlying causes. Consequently, a proportion of MCI cases are due to non-neurodegenerative processes, including FCD. Indeed, significant numbers of patients diagnosed with MCI do not 'convert' to dementia. The lack of diagnostic specificity for MCI 'non-progressors' is a weakness inherent in framing MCI primarily within a deterministic neurodegenerative pathway. It is recognized that depression, anxiety and behavioural changes can represent a prodrome to neurodegeneration; empirical data are required to explore whether the same might hold for subsets of individuals with FCD. Clinicians and researchers can improve study efficacy and patient outcomes by viewing MCI as a descriptive term with a wide differential diagnosis, including potentially reversible components such as FCD. We present a preliminary definition of functional neurological disorder-cognitive subtype, explain its position in relation to other cognitive diagnoses and emerging biomarkers, highlight clinical features that can lead to positive diagnosis (as opposed to a diagnosis of exclusion), and red flags that should prompt consideration of alternative diagnoses. In the research setting, positive identifiers of FCD will enhance our recognition of individuals who are not in a neurodegenerative prodrome, while greater use of this diagnosis in clinical practice will facilitate personalized interventions.
To enable application of non-Gaussian diffusion magnetic resonance imaging (dMRI) techniques in large-scale clinical trials and facilitate translation to clinical practice there is a requirement for ...fast, high contrast, techniques that are sensitive to changes in tissue structure which provide diagnostic signatures at the early stages of disease. Here we describe a new way to compress the acquisition of multi-shell b-value diffusion data, Quasi-Diffusion MRI (QDI), which provides a probe of subvoxel tissue complexity using short acquisition times (1–4 min). We also describe a coherent framework for multi-directional diffusion gradient acquisition and data processing that allows computation of rotationally invariant quasi-diffusion tensor imaging (QDTI) maps.
QDI is a quantitative technique that is based on a special case of the Continuous Time Random Walk model of diffusion dynamics and assumes the presence of non-Gaussian diffusion properties within tissue microstructure. QDI parameterises the diffusion signal attenuation according to the rate of decay (i.e. diffusion coefficient, D in mm2 s−1) and the shape of the power law tail (i.e. the fractional exponent, α). QDI provides analogous tissue contrast to Diffusional Kurtosis Imaging (DKI) by calculation of normalised entropy of the parameterised diffusion signal decay curve, Hn, but does so without the limitations of a maximum b-value.
We show that QDI generates images with superior tissue contrast to conventional diffusion imaging within clinically acceptable acquisition times of between 84 and 228 s. We show that QDI provides clinically meaningful images in cerebral small vessel disease and brain tumour case studies. Our initial findings suggest that QDI may be added to routine conventional dMRI acquisitions allowing simple application in clinical trials and translation to the clinical arena.
Abstract
We previously hypothesized that functional cognitive disorder is characterized by heightened subjective mental effort, exhausted attentional reserve and metacognitive failure.
To test this ...hypothesis, we administered a Stroop colour-word task in which attentional demand was varied by task difficulty (congruent versus incongruent cues) and the presence of a secondary auditory stimulus (passive or active listening to an oddball-type paradigm). We measured subjective mental effort, objective performance (reaction times and accuracy), metacognition and EEG-based biomarkers of mental workload.
We tested 19 functional cognitive disorder patients and 23 healthy controls. Patients reported higher levels of depression, anxiety, fatigue, pain, sleep disruption, dissociation and obsessiveness. They rated their memory as significantly poorer than healthy controls; however, accuracy did not differ between groups in any condition. In contrast to healthy controls, patients rated their performance as poorer on the congruent Stroop task with background noise compared to silent conditions. Functional cognitive disorder was consistently associated with slower reaction times but this was not exacerbated by increased attentional demand. Patients but not healthy controls reported greater mental workload in noisy conditions but EEG biomarkers were similar between groups, regardless of task difficulty.
Functional cognitive disorder has significant syndromic overlap with mood disorders and chronic fatigue and pain. It is associated with global metacognitive failure whereas local (task-specific) metacognition is only selectively impaired. Patients were slower than healthy controls, which might contribute to the ‘brain fog’ reported in this condition. Although subjective mental effort was increased in noisy conditions, we found no evidence of attentional exhaustion in functional cognitive disorder. Our results indicate that functional cognitive disorder is a multisystem condition affecting reaction time, subjective mental effort and global metacognition.
Teodoro et al. report that patients with functional cognitive disorder (FCD) show motor slowness, which may underpin the sensation of ‘brain fog’, along with heightened subjective mental effort and global metacognitive failure, but not attentional exhaustion. They propose a syndromic overlap between FCD and mood disorders, chronic fatigue and pain.
Abstract
Given considerable variation in diagnostic and therapeutic practice, there is a need for national guidance on the use of neuroimaging, fluid biomarkers, cognitive testing, follow-up and ...diagnostic terminology in mild cognitive impairment (MCI). MCI is a heterogenous clinical syndrome reflecting a change in cognitive function and deficits on neuropsychological testing but relatively intact activities of daily living. MCI is a risk state for further cognitive and functional decline with 5–15% of people developing dementia per year. However, ~50% remain stable at 5 years and in a minority, symptoms resolve over time. There is considerable debate about whether MCI is a useful clinical diagnosis, or whether the use of the term prevents proper inquiry (by history, examination and investigations) into underlying causes of cognitive symptoms, which can include prodromal neurodegenerative disease, other physical or psychiatric illness, or combinations thereof. Cognitive testing, neuroimaging and fluid biomarkers can improve the sensitivity and specificity of aetiological diagnosis, with growing evidence that these may also help guide prognosis. Diagnostic criteria allow for a diagnosis of Alzheimer’s disease to be made where MCI is accompanied by appropriate biomarker changes, but in practice, such biomarkers are not available in routine clinical practice in the UK. This would change if disease-modifying therapies became available and required a definitive diagnosis but would present major challenges to the National Health Service and similar health systems. Significantly increased investment would be required in training, infrastructure and provision of fluid biomarkers and neuroimaging. Statistical techniques combining markers may provide greater sensitivity and specificity than any single disease marker but their practical usefulness will depend on large-scale studies to ensure ecological validity and that multiple measures, e.g. both cognitive tests and biomarkers, are widely available for clinical use. To perform such large studies, we must increase research participation amongst those with MCI.
Background
The COVID‐19 pandemic impacted on the provision of care and routine activity of all National Health Service (NHS) services. While General Practitioner referrals to memory services in ...England have returned to pre‐pandemic levels, the estimated dementia diagnosis rate (DDR) fell by 5.4% between March 2020 and February 2023.
Methods
In this paper we explore whether this reduction is accurate or is an artefact of the way the NHS collects data.
Results
We explore the processes that may have affected national dementia diagnosis rates during and following the COVID‐19 pandemic.
Conclusions
We discuss what action could be taken to improve the DDR in the future.
Key points
Despite General Practitioner (GP) referrals to memory services in England returning to levels seen before the pandemic, there was a decline of 5.4% in the estimated dementia diagnosis rate (DDR) from March 2020 to February 2023.
This paper explores the factors which may have affected the national DDR reduction. These include a backlog in dementia referrals, a reduction in coding of diagnoses, or a decrease in true dementia prevalence secondary to excess COVID‐19 deaths which has yet to be reflected in the DDR denominator.
Further work is suggested to accurately capture dementia prevalence in the United Kingdom (UK). These include an up‐to‐date multicentre population‐based cohort study and adjusting the DDR denominator for factors known to affect dementia susceptibility such as deprivation, rurality, and ethnicity.
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