Response to McWhirter et al (2020):
In their article, Performance validity test failure in clinical populations - a systematic review, McWhirter and colleagues (2020) present the ‘base rates’ of performance validity test (PVT) failure (or what are commonly referred to as effort tests) and offer an analysis of PVT performance from their perspective as neurologists and neuropsychiatrists.
As a group of senior practicing clinical neuropsychologists, we are pleased that they have drawn attention to an important issue, but we have significant concerns about the methodology used and with several of the conclusions drawn within the review. We present this response from the perspective of U.K. neuropsychology practice, and as practitioners involved in research and formulating clinical guidance on the use of PVTs. In preparing this response, we were aware of parallel concerns of our U.S. counterparts (Larrabee et al) but we have submitted separate responses due to the word limit.
The systematic review methodology used by McWhirter et al. has resulted in a limited number of papers being included, and there is no indication of the quality of the studies included. All of the literature search and analytic procedures appear to have been undertaken by one person alone, hence there was no apparent control for human error, bias, omission or inaccurate data extraction. Also, it is unclear to us to what extent McWhirter and colleagues had the knowle...
The systematic review methodology used by McWhirter et al. has resulted in a limited number of papers being included, and there is no indication of the quality of the studies included. All of the literature search and analytic procedures appear to have been undertaken by one person alone, hence there was no apparent control for human error, bias, omission or inaccurate data extraction. Also, it is unclear to us to what extent McWhirter and colleagues had the knowledge to determine what data constituted PVT failure, since no neuropsychologists appear to have been involved in their paper.
Whilst we welcome their scrutiny of PVT performance across a range of clinical settings and their drawing attention to the important matter of the base rates of failure without any obvious incentive to underperform at neuropsychological examination, this point is well understood in the existing literature and not in itself a novel finding. Most neuropsychologists will be familiar with such failures in their clinical practice, and these findings arise in a number of publications, including ones which McWhirter et al omitted to review1 2.
McWhirter et al.’s key conclusion is that in the case of PVT ‘failure rates are no higher in functional disorders than in other clinical conditions’. They then infer from this conclusion that it ‘raises important questions about the degree of objectivity afforded to neuropsychological tests in clinical practice and research’, but they do not expand on this generalisation. In reaching their key conclusion, McWhirter fall into the trap of ‘comparing apples with oranges', and not making reliable and valid comparisons. If we take one of the best documented functional conditions, Psychogenic Non-Epileptic Seizures (PNES), a proper comparison would be to take a group of well documented PNES patients, who only had psychogenic seizures with no lesion pathology discernible, and compare them to a group of patients who had well-documented organic seizures, with lesion pathology clearly defined. As well as matching on usual demographic variables such as age, sex and educational background, the two groups would be carefully matched for duration, frequency and severity of seizures, and for functional disability. It would then be meaningful to compare the performance of the two groups on PVT, and come to any conclusions as to whether rates are higher, lower or the same in the functional group compared to the organic group.
Whilst we have concerns about the lack of rigour in the search methodology, which resulted in an incomplete literature review which pooled data from studies of uncertain quality that may not be comparable, of more concern is that McWhirter and colleagues may lack the knowledge and expertise to interpret these data in a clinically meaningful way. The authors are dismissive of what is a still a developing PVT literature that has achieved a good deal in the last 15-20 years and resulted in an excellent consensus of the requirement to validate neuropsychological test performance with objective tests and symptom-based questionnaires. McWhirter’s et al interpretation of the findings does not provide adequate context to both the latest U.S. and the U.K. effort test / PVT interpretation guidelines, and does not reflect neuropsychological expertise or clinical neuropsychological practice. The authors do not cite the latest U.S. guidelines (Sherman et al, 2020) 3 and the U.K. guidelines are not mentioned (British Psychological Society: Professional Practice Board) 4.
A further key difficulty with the paper is that the authors report the failure rate on individual effort tests of different sensitivities without consideration of the various methodological and statistical techniques that clinical neuropsychologists use to interpret such findings. In clinical practice, a single test score is of little significance, and the authors appear to misunderstand this fundamental point in clinical neuropsychology practice. An effort test profile is obtained by the use of a combination of PVTs of different sensitivities, different cognitive domains, administered throughout the examination, subjected to statistical discrepancy analysis, often binomial probability analysis, placed in the context of positive and negative predictive power and in the context of the patients wider clinical presentation, which could include pain, fatigue, depression and anxiety and related effects on concentration. The paper by McWhirter et al. appears to show no discernible understanding of this statistical and clinical context. Current guidelines clearly identify the need to interpret the results of a failure and provide possible explanations, and it has never been a simple case of regarding pass / fail on a single effort test as diagnostic in its own right.
The authors also seem to misunderstand key concepts, including ‘profile analysis’, which is a technique to prevent misclassification PVT failure as low effort in the presence of bona fide cognitive problems, and this methodology is applicable to tests other than the Word Memory Test, including the TOMM. Failure to understand this and exclude below cut-off performance on effort tests when a ‘severe impairment profile’ is obtained will further distort the McWhirter et al findings, which are derived form a methodology that appears to fall short of the PRISMA standard and resulted in a partial review of the literature, without mention of quality criteria, no second rater and no method to resolve inter-rater discrepancies as would be expected of a well-conducted systematic review. In their Discussion section, the authors also appear to have confounded forced-choice testing, chance-level performance and intentionality.
In their review, McWhirter et al unfortunately group PVTs together and do not appear to readily distinguish between embedded measures and PVTs which have been specifically designed to detect poor cognitive effort. It is performance on the latter tests which need to be accorded greater significance, as it is those which form the basis of conclusions reached by neuropsychologists in their clinical practice when coming to a diagnosis of questionable effort.
In summary, we welcome the contribution of McWhirter et al to an important debate. However, their depiction of neuropsychology using PVTs alone, without clinical context and without methods of analyses to diagnose functional cognitive disorder or ‘malingering’, presents a ‘straw man’ argument because this does not align with what clinical neuropsychologists think or do. A clearer and more extensive review of the literature would have identified the role of PVTs and the complexity of their interpretation, and also allowed readers to have a more balanced understating of their role in clinical practice.
Professor Steven Kemp (UK)
Professor Narinder Kapur (UK)
Professor Gus Baker (UK)
Professor Martin Bunnage (UK)
Professor Liam Dorris (UK)
Dr Perry Moore (UK)
Mr Daniel Friedland (UK)
1 Schroeder R, Peck C, Buddin W. et al. (2012). The Coin-in-the-Hand test and dementia: More evidence for a screening test for neurocognitive symptom exaggeration. Cogn Behav Neurol; 25: 139-143.
2 Sieck B, Smith M, Duff K et al. (2013). Symptom validity test performance in the Huntington Disease clinic. Arch Clin Neuropsych; 28: 135-143.
3.Sherman EMS, Daniel J. Slick DK and Iverson GL (2020). Multidimensional Malingering Criteria for Neuropsychological Assessment: A 20-Year Update of the Malingered Neuropsychological Dysfunction Criteria Archives of Clinical Neuropsychology 00. 1–30.
4. Assessment of Effort in Clinical Testing of Cognitive Functioning for Adults (2009). The British Psychology Society: Professional Practice Board.
Our findings demonstrate that serum C-reactive protein (CRP) does not predict survival in amyotrophic lateral sclerosis (ALS), neither in a univariate model nor in a multivariate model including other established prognostic factors for survival in ALS. In contrast, in a similar multivariate model, serum neurofilament light chain (NfL) is an independent predictor of survival in ALS. Further, we investigated the combination of serum CRP and NfL within the same multivariate survival model. The results indicated that elevated levels of serum NfL (Hazard ratio: 1.83 [95% CI: 1.23-2.74] p = 0.003), but not of serum CRP (Hazard ratio: 0.93 [95% CI = 0.63-1.37], p = 0.7), are associated with a shorter survival in ALS. From these data, we can conclude that there is no evidence that combining both markers would improve the prediction of survival in ALS.
Moreover, we determined the disease progression rate (DPR) at time of sampling for 368 patients with ALS. The DPR was calculated as (48 – ALS-FRS-R)/(disease duration). We found a significant correlation between the DPR and serum NfL levels (rs = 0.519 [95% CI = 0.437-0.592], p < 0.0001) as well as serum CRP levels (rs = 0.294 [95% CI = 0.194-0.387], p < 0.0001). Accordingly, patients with a DPR in the upper quartile had significantly elevated levels of serum NfL (median [range]: 183 [11.1-738] pg/mL vs. 67.9 [0.300-262] pg/mL, p < 0.0001) and serum CRP (median [range]: 0.336 [0.0150-30.0] mg/dL vs. 0.0775 [0.0150-2.7...
Moreover, we determined the disease progression rate (DPR) at time of sampling for 368 patients with ALS. The DPR was calculated as (48 – ALS-FRS-R)/(disease duration). We found a significant correlation between the DPR and serum NfL levels (rs = 0.519 [95% CI = 0.437-0.592], p < 0.0001) as well as serum CRP levels (rs = 0.294 [95% CI = 0.194-0.387], p < 0.0001). Accordingly, patients with a DPR in the upper quartile had significantly elevated levels of serum NfL (median [range]: 183 [11.1-738] pg/mL vs. 67.9 [0.300-262] pg/mL, p < 0.0001) and serum CRP (median [range]: 0.336 [0.0150-30.0] mg/dL vs. 0.0775 [0.0150-2.75] mg/dL, p < 0.0001) in comparison with patients with a DPR in the lower quartile.
The cross-sectional retrospective design of the study did not allow us to assess the change of serum serum NfL and CRP levels over time. However, recent publications indicate that serum NfL levels remain stable over time, confirming our observation in cerebrospinal fluid.[1–3] Furthermore, Benatar M. and colleagues have shown that baseline NfL measurements are predictive of ALSFRS-r decline. Recent studies with the experimental drug nusinersen in patients with spinal muscular atrophy and fingolimod in patients with multiple sclerosis show that neurofilament levels in blood respond to treatment.[4,5] These findings highlight the potential utility of neurofilaments as pharmacodynamic biomarkers. Interestingly, upon treatment of SOD1 ALS mice models with antisense oligonucleotides (ASO), the phosphorylated neurofilament heavy chain levels in serum were significantly lower in comparison to mice receiving the control treatment. Likewise, patients with ALS who were treated with the highest dose of Tofersen, an ASO for SOD1 mutation carriers, also showed a decrease in plasma neurofilaments upon treatment. Yet, these findings have to be confirmed in larger cohort of patients with ALS.
1 Benatar M, Zhang L, Wang L, et al. Validation of serum neurofilaments as prognostic and potential pharmacodynamic biomarkers for ALS. Neurology Published Online First: 8 May 2020. doi:10.1212/WNL.0000000000009559
2 Huang F, Zhu Y, Hsiao-Nakamoto J, et al. Longitudinal biomarkers in amyotrophic lateral sclerosis. Ann Clin Transl Neurol 2020;:1–14. doi:10.1002/acn3.51078
3 Poesen K, De Schaepdryver M, Stubendorff B, et al. Neurofilament markers for ALS correlate with extent of upper and lower motor neuron disease. Neurology 2017;88:2302–9. doi:10.1212/WNL.0000000000004029
4 Darras BT, Crawford TO, Finkel RS, et al. Neurofilament as a potential biomarker for spinal muscular atrophy. Ann Clin Transl Neurol 2019;6:932–44. doi:10.1002/acn3.779
5 Sormani MP, Haering DA, Kropshofer H, et al. Blood neurofilament light as a potential endpoint in Phase 2 studies in MS. Ann Clin Transl Neurol 2019;6:1081–9. doi:10.1002/acn3.795
6 McCampbell A, Cole T, Wegener AJ, et al. Antisense oligonucleotides extend survival and reverse decrement in muscle response in ALS models. J Clin Invest 2018;128:3558–67. doi:10.1172/JCI99081
7 Miller T, Cudkowicz M, Shaw PJ, et al. Phase 1–2 Trial of Antisense Oligonucleotide Tofersen for SOD1 ALS. N Engl J Med 2020;383:109–19. doi:10.1056/NEJMoa2003715
Brain Atrophy is Inevitable Following Deep Brain Stimulation and Not Likely Caused by the Lead
To the Editor,
We read the observational DBS cohort study by Kern DS et al with great interest. We agree that deep brain stimulation (DBS) implantation has been associated with brain atrophy. We previously published an experience that not cited in the present study and we wonder whether the authors accidentally cited one of our review articles rather than the primary source (2014). It is critical for the DBS field to be aware of the clinical implications of atrophy.
Kern DS et al analyzed 32 Parkinson’s disease (PD) patients who completed bilateral staged DBS implant surgeries targeting the subthalamic nucleus (STN)(1). The patients had an average duration between the two DBS surgeries of 141 days and this duration offered an opportunity to compare pre-post atrophy measures. The authors observed a significant reduction in whole brain volumes of the ipsilateral or first implanted side. Also, the authors noted that all basal ganglia-thalamocortical brain regions (BGTC) ipsilateral to the DBS implantation had significantly reduced volumes, whereas non-BGTC structures seemed to be unaffected. The authors suggested the possibility that intracranial volumetric changes may occur following STN DBS electrode implantation as a direct result of the implantation itself.
We believe it unlikely that DBS electrode implantation is a primary reason for volume loss. We...
We believe it unlikely that DBS electrode implantation is a primary reason for volume loss. We previously reported three DBS cases (2 Parkinson’s disease and 1 essential tremor) with unexpected loss of benefit following DBS. After undergoing our routine clinical DBS troubleshooting protocol, we observed a substantial change in brain atrophy indices including the 3rd ventricular width, the Evans index, the ventricular index, and the the cella media index. The measured DBS lead location comparisons revealed a more lateral position compared to earlier scans(2). We concluded that the most likely explanation for the changes in clinical outcome was loss of brain volume. The atrophy also likely underpinned the changes in thresholds for benefits and side effects when attempting device reprogramming.
We also recently reported a postmortem analysis of a Huntington’s disease DBS case (2016) with similar atrophy occurring within basal ganglia structures.(3) Parkinson’s and Huntington’s disease both manifest expected atrophy. The volume loss in these cases will be faster and more severe than in control brains. The question that Kern asked is whether the DBS contributes to this atrophy in some unknown way. Though this study is interesting, there are a few concerning issues that must be considered.
The first observation is that preoperative volumes of BGTC and non-BGTC were generally similar or larger on the ipsilateral side of the first implant (contralateral to symptom onset) as compared to the side contralateral to the implant. With the typical asymmetry of PD symptoms, one may expect that the BGTC structures contralateral to side of onset would have lower volumes; however, previous studies have illustrated that these expected asymmetries are more apparent with shape analysis when compared to absolute volumetrics, highlighting the apparent inaccuracy of pure basal ganglia volumetrics in detecting these changes (4).
Second, a key claim regarding the authors’ hypothesis is that “the structures, susceptible to a change in volume were unique to the motoric network of the STN in PD and included the thalamus, caudate, putamen and pallidum.” Importantly, the regional volumetric changes reported were largely incompatible with this hypothesis as they did not manifest a strong predilection for the sensorimotor functional regions of the target nuclei (e.g., the sensorimotor posterior ventral pallidum and inferior lateral thalamus representing the ventral sensorimotor nuclei were less affected). In fact, it seems the regional volume changes may have more predilection for limbic portions of these nuclei, which is in line with the observation of progressive hippocampal atrophy noted by the authors and by others. The more anterior limbic portion of the STN and its respective subcortical connections (e.g. ansa subthalamica exiting the anterior pole of the STN) and limbic hyperdirect pathways that largely travel anteriorly into the anterior limb of the internal capsule would not be expected to be targeted either with lead implantation or with stimulation. Therefore, it would be difficult to attribute the atrophy directly to surgical implantation or to stimulation.
It is also important to better understand the surgical procedure in their study, particularly the use of perioperative anesthesia. Although not specifically addressed, drugs such as propofol have been shown to have a sustained effect on cortico-subcortical connectivity and in local field potentials. The effects of non-brain surgery and anesthesia alone have also been shown to result in a subsequent cognitive decline in PD patients, which could explain the findings of atrophy in these limbic regions reported in this study (see above discussion) (4). Likewise, since the majority of patients had the first implant on the more affected side, it is possible that the volume changes reflect disease progression that would be expected to occur in a similar asymmetric fashion.
The lack of a control group, given the strong selection bias in this cohort makes it challenging to prove these changes were simply a result of surgery or stimulation. Lastly, the sample size was small at only 32 patients. A much larger cohort taking into account errors introduced by imaging related methods and by lead artifacts should be performed to properly confirm or refute the author’s observation.
In summary, brain atrophy is an issue which will occur after DBS surgery and it has potential implications in DBS management and outcomes. However, the exact mechanism of such atrophy is not well understood making it difficult to know if the phenomenon is expected or even preventable after DBS surgery. The introduction of novel DBS devices capable of current shaping and steering may provide an opportunity for enhanced management of DBS side effects which may emerge from expected progressive brain atrophy(5).
Daniel Martinez-Ramirez, MD
Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Ave. Ignacio Morones Prieto 3000, Monterrey, N.L., México, 64710.
Erik H. Middlebrooks, MD
Departments of Radiology and Neurosurgery, Mayo Clinic, 4500 SW San Pablo Rd, Jacksonville, FL, USA, 32224.
Leonardo Almeida, M.D.
Norman Fixel Institute for Neurological Diseases, University of Florida Health, 3009 SW Williston Road, Gainesville, FL, USA, 32608.
Michael S. Okun, MD
Norman Fixel Institute for Neurological Diseases, University of Florida Health, 3009 SW Williston Road, Gainesville, FL, USA, 32608.
The authors have nothing to disclose.
1. Kern DS, Uy D, Rhoades R, et al. Discrete changes in brain volume after deep brain stimulation in patients with Parkinson's disease. Journal of neurology, neurosurgery, and psychiatry. 2020.
2. Martinez-Ramirez D, Morishita T, Zeilman PR, et al. Atrophy and other potential factors affecting long term deep brain stimulation response: a case series. PLoS One. 2014;9(10):e111561.
3. Vedam-Mai V, Martinez-Ramirez D, Hilliard JD, et al. Post-mortem Findings in Huntington's Deep Brain Stimulation: A Moving Target Due to Atrophy. Tremor Other Hyperkinet Mov (N Y). 2016;6:372.
4. Tanner JJ, McFarland NR and Price CC (2017) Striatal and Hippocampal Atrophy in Idiopathic Parkinson’s Disease Patients without Dementia: A Morphometric Analysis. Front. Neurol. 8:139. doi: 10.3389/fneur.2017.00139
5. Almeida L, Deeb W, Spears C, et al. Current Practice and the Future of Deep Brain Stimulation Therapy in Parkinson's Disease. Semin Neurol. 2017;37(2):205-14.
I read the article by Stefano et al with interest.1 Genetic predisposition per se cannot explain discrete self-limited recurrent attacks of headache and aura manifestations of hemiplegic migraine, with the state/clinical predisposition appearing and disappearing seemingly inexplicably over several decades or the life-time of a sufferer.2
More than two decades ago, I elucidated a fundamental clinico-theoretical principle for the understanding of migraine-linked physiologic mechanisms that has well-stood the test of time, technology and biologic commonsense: “No systemic influence can explain the characteristic lateralizing headache of migraine, unilateral, bilateral, side-shifting or side-locked”.3 Over the last fifty years, some of the "systemic" influences believed to play key pathogenetic roles in migraine include serotonin, platelets, catecholamines, calcitonin-gene related peptide, magnesium depletion, stress, post-stress state, and recurrent micro thrombo-embolisms across the patent foramen ovale at the level of the cardiac inter-atrial septum. 4,5,6 Little vertical and biologically-plausible robust generalizable progress, however, has been made in gestalt understanding of the disorder well into the 21st century.7 Trait-linked genetic association is also a “systemic” influence. Ion transporters – as well as the three main causative genes—CACNA1A, ATP1A2 and SCN1A—which encode for ion transporters1 do not offer clues to the mechanistic physiological b...
More than two decades ago, I elucidated a fundamental clinico-theoretical principle for the understanding of migraine-linked physiologic mechanisms that has well-stood the test of time, technology and biologic commonsense: “No systemic influence can explain the characteristic lateralizing headache of migraine, unilateral, bilateral, side-shifting or side-locked”.3 Over the last fifty years, some of the "systemic" influences believed to play key pathogenetic roles in migraine include serotonin, platelets, catecholamines, calcitonin-gene related peptide, magnesium depletion, stress, post-stress state, and recurrent micro thrombo-embolisms across the patent foramen ovale at the level of the cardiac inter-atrial septum. 4,5,6 Little vertical and biologically-plausible robust generalizable progress, however, has been made in gestalt understanding of the disorder well into the 21st century.7 Trait-linked genetic association is also a “systemic” influence. Ion transporters – as well as the three main causative genes—CACNA1A, ATP1A2 and SCN1A—which encode for ion transporters1 do not offer clues to the mechanistic physiological basis of lateralizing headache.8
Ultimately, sui generis increased susceptibility to cortical spreading depression (CSD) is widely believed to underlie the migraine pathogenetic influence of ion transporter gain-of-function imbalances induced by genetic mutations.1 CSD is a fundamentally-flawed serendipitous neurophysiologic finding that has no nociceptive influence in experimental animals.4 Conversely, CSD has a well-defined neuronal and vascular adaptive/protective effect.4,7,8,9 CSD is the weakest link in the chain-of-assumptions that surround the biologic significance of genetic mutations in hemiplegic migraine. Verapamil and magnesium do not readily cross the blood-brain barrier and are not known to influence CSD in animals.4,10
1. Di Stefano V , Rispoli MG, Pellegrino N, et al. Diagnostic and therapeutic aspects of hemiplegic migraine. J Neurol Neurosurg Psychiatry 2020;91:764–771.
2. Gupta VK. What is the practical value of genetic analysis to comprehension of migraine? Neurology. Published April 01, 2018. Available at : https://n.neurology.org/content/what-practical-value-genetic-analysis-co...
3. Gupta VK. Nitric oxide and migraine: another systemic influence postulated to explain a lateralizing disorder. Eur J Neurol 1996;3:172--173.
4. Gupta VK. CSD, BBB and MMP-9 elevations: animal experiments versus clinical phenomenon in migraine. Expert Rev Neurother 2009;9:
5. Gupta VK. Patent foramen ovale closure and migraine: science and sensibility, Expert Rev Neurother 2010;10: 1409-1422. (OPEN ACCESS)
6. Gupta VK. Reader response: potential for treatment benefit of small molecule CGRP receptor antagonist plus monoclonal antibody in migraine therapy. Neurology. Published January 14, 2020. Available at: https://n.neurology.org/content/reader-response-potential-treatment-bene...
7. Gupta VK. Pathophysiology of migraine: an increasingly complex narrative to 2020. Future Neurol 2019. Published Online: 24 May 2019. (OPEN ACCESS) Available at: https://doi.org/10.2217/fnl-2019-0003
8. Gupta VK [Editor]. Adaptive Mechanisms in Migraine. A Comprehensive Synthesis in Evolution. Breaking the Migraine Code. Nova Science Publishers, New York, 2009.
9. Gupta VK [Editorial Commentary]. Cortical-spreading depression: at the razor’s edge of scientific logic. J Headache Pain 2011;12:45–46.
10. Gupta VK. Pharmacotherapeutics of migraine and the blood-brain barrier: serendipity, empiricism, hope, and hype. MedGenMed 2006; 8: 89 (OPEN ACCESS).
We thank Dr Venketasubramanian for their interest in our paper and for their considered response. We agree that some of our patients had alternative causes for stroke in addition to the marked prothrombotic and inflammatory state related to COVID-19, and that this point is relevant to interpreting our findings.
We also agree that it can be difficult to define one specific “cause” for an ischaemic stroke despite detailed investigation, since many patients have a complex combination of risk factors (e.g. diabetes, hypertension, dyslipidaemia), disease processes (e.g. atherosclerosis, cerebral small vessel disease, atrial fibrillation), and potential mechanisms (e.g. large artery thrombo-embolism, cardiac embolism, small vessel occlusion). Nevertheless, our key observation was that a 16-day period we saw 6 strikingly similar patients, all with large vessel occlusions, elevated D-dimer, ferritin and CRP, 8-24 days following proven COVID-19 illness (and in one patient during the asymptomatic phase (1), suggesting the emergence of a distinct pattern of cerebral ischaemia associated with a prothrombotic inflammatory state.
As correctly identified, Patient 2 had atrial fibrillation and previous mitral valve repair (not a metallic valve), but stroke occurred despite above-therapeutic anticoagulation with INR 3.6; this is unusual, so we concluded that the clear thrombotic state may therefore have been contributory (D-dimer 7,750). Similarly, al...
As correctly identified, Patient 2 had atrial fibrillation and previous mitral valve repair (not a metallic valve), but stroke occurred despite above-therapeutic anticoagulation with INR 3.6; this is unusual, so we concluded that the clear thrombotic state may therefore have been contributory (D-dimer 7,750). Similarly, although patient 3 had atrial fibrillation, the D- dimer 16,100 is well in excess of what has previously been described in AF-related ischaemic stroke and seemed likely to be relevant.
We agree that a detailed investigation for other potential causes and mechanisms is important, even in the presence of evidence of a prothrombotic state associated with COVID-19. All six patients had prolonged ward cardiac monitoring and - apart from the known atrial fibrillation in patients 2 and 3 - none of them had relevant rhythm abnormalities. Moreover, all patients had complete vascular imaging from aortic arch to the intracranially vessels, and no contributory vascular stenosis was identified in any of the patients. These findings strongly support a prothrombotic state as being relevant to the large-vessel occlusions we observed. Furthermore, our observations are consistent with several other recent reports (2-5).
We acknowledge the research and clinical value of the TOAST (trial of ORG 10172 in acute stroke treatment) classification, which would probably categorise patients 2 and 3 as undetermined. However, we suggest that the prothrombotic and inflammatory syndrome seen after or during COVID-19 might interact with conventional vascular risk factors, disease processes and mechanism to result in large-vessel occlusion. Thus, acute treatment should be tailored to all relevant factors identified wherever possible. Therapeutic anticoagulation might be indicated but the intracranial bleeding risk needs to be considered in the presence of recent cerebral infarction.
Further data are urgently needed to confirm whether the pattern of stroke that we reported in association with COVID-19 is consistently seen in other populations. Case-control studies of COVID-19 associated stroke and non-COVID-19 associated ischaemic stroke could be informative in determining whether, and if so, how, COVID-19 modifies the clinical manifestations of acute cerebrovascular disease.
1. Beyrouti R, Adams ME, Benjamin L, et al. Characteristics of ischaemic stroke associated with COVID-19. J Neurol Neurosurg Psychiatry 2020 doi: 10.1136/jnnp-2020-323586 [published Online First: 2020/05/02]
2. Oxley TJ, Mocco J, Majidi S, et al. Large-Vessel Stroke as a Presenting Feature of Covid-19 in the Young. N Engl J Med 2020 doi: 10.1056/NEJMc2009787 [published Online First: 2020/04/29]
3. Avula A, Nalleballe K, Narula N, et al. COVID-19 presenting as stroke. Brain Behav Immun 2020 doi: 10.1016/j.bbi.2020.04.077 [published Online First: 2020/05/04]
4. Viguier A, Delamarre L, Duplantier J, et al. Acute ischemic stroke complicating common carotid artery thrombosis during a severe COVID-19 infection. J Neuroradiol 2020 doi: 10.1016/j.neurad.2020.04.003 [published Online First: 2020/05/04]
5. Moshayedi P, Ryan TE, Mejia LLP, et al. Triage of Acute Ischemic Stroke in Confirmed COVID-19: Large Vessel Occlusion Associated With Coronavirus Infection. Front Neurol 2020;11:353. doi: 10.3389/fneur.2020.00353 [published Online First: 2020/04/21]
Alain Buguet1, Manny W. Radomski2, Jacques Reis3, Raymond Cespuglio4, Peter S. Spencer5, Gustavo C. Román6
• UMR 5246 CNRS, Claude-Bernard Lyon-1 University, Villeurbanne, France
• Physiology, Faculty of Medicine, University of Toronto, Canada
• Faculté de Médecine, Université de Strasbourg, Strasbourg, France
• Neurocampus Michel Jouvet, Claude-Bernard Lyon-1 University, Lyon, France
• Department of Neurology, School of Medicine, Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, Oregon, USA
• Department of Neurology, Neurological Institute, Houston Methodist Hospital, USA, and Weill Cornell Medical College, Cornell University, New York, NY, USA
• Correspondence to Prof. Alain Buguet, Malaria Research Unit, UMR 5246 CNRS, Claude-Bernard Lyon-1 University, 69622 Villeurbanne, France; email@example.com
We read with interest the Post-Script comment by Liu et al. highlighting the neurological manifestations of SARS-CoV-2 infection. We would like to contribute additional information on the neurology of COVID-19, as recently published by our group at the World Federation of Neurology.1 In addition to the reported disorders affecting central and peripheral nervous system as well as muscle, we add sleep-wake disorders to the list of conditions that may be associated with COVID-19 both during and fol...
We read with interest the Post-Script comment by Liu et al. highlighting the neurological manifestations of SARS-CoV-2 infection. We would like to contribute additional information on the neurology of COVID-19, as recently published by our group at the World Federation of Neurology.1 In addition to the reported disorders affecting central and peripheral nervous system as well as muscle, we add sleep-wake disorders to the list of conditions that may be associated with COVID-19 both during and following SARS-CoV-2 infection.
Sleep disorders and influenza pandemics
The Spanish flu pandemic caused by the H1N1 influenza virus of avian origin spread worldwide during the years 1918-1919. Throughout World War I, between 1915 and 1917, Jean-René Cruchet and Constantin von Economo described the occurrence of sleep-wake disorders following the initial pharyngitis. von Economo coined the name encephalitis lethargica for this condition characterized by an initial phase of hypersomnia (“somnolent ophthalmoplegia” or “sopor”).2 He also observed insomnia associated with basal ganglia “choreatic” dysfunction, circadian sleep disruption (“inversion of sleep”), sleep paralysis (“dissociation of cerebral and body sleep” and “akinetic cases”), and “somnambulism.” Identification of the clinical and neuropathological features of these disorders by von Economo launched the search for sleep-wake regulatory networks. He described the “centre for regulation of sleep” in the anterior hypothalamus and the “wake centre” in the posterior hypothalamus.2
During more recent pandemics such as the H2N2 influenza type A 1957-1958 Asian flu, or the influenza B in Japan,3 sporadic cases of Kleine-Levin syndrome were reported. This is a rare disorder characterized by recurrent episodes of excessive daytime sleepiness (hypersomnia) along with cognitive and behavioural changes. However, sleep reports were lacking after the subsequent re-emergence in 1968-1969 of the Hong-Kong flu pandemic attributed to H3N2 influenza type A virus. Four to six months after the 2009-2010 H1N1 influenza epidemic, narcoleptic syndromes were reported in Chinese children, 4 and seasonal distribution of narcoleptic syndromes was suspected after winter upper respiratory infections.
Pathways used by neurotropic influenza viruses and coronaviruses
The probable transmission pathway of H1N1 was elucidated in intranasally-infected mice that developed narcolepsy-like syndromes. 5 The virus infected the olfactory nerves (CN I) crossed the olfactory epithelium and cribriform plate (day 0 post-infection), olfactory bulb glomerular layer (day 14), and mitral and granular cells (day 28). From the olfactory bulb, the virus progressed retrogradely to orexin- and melanin-concentrating-hormone nuclei located in the lateral hypothalamus (day 28). The virus then spread to the pontine dorsal raphe and locus coeruleus nuclei.
Neurotropic coronaviruses may reach their central nervous system targets by transynaptic transmission, as shown in porcine HEV 67N coronavirus and avian bronchitis virus infections. 5 Another route is the trigeminal pathway, either from collateral nerve endings in the nasal mucosa or directly from the buccal mucosa to the cranial nerve V (CN V) nucleus. 5
Do coronaviruses behave in a similar manner? In humans, a shortcut for influenza and other viruses is considered to be through the olfactory pathway to the brain. Following SARS-CoV-1 infection patients suffered from nonrestorative sleep related to sleep instability. Sleep alterations may relate to the reported presence of cytoplasmic viral particles and viral genome sequences in hypothalamic neurons.1 Transit of viruses can occur from blood by crossing the blood-brain barrier (BBB) or via the weaker BBB of the median eminence, but neural pathways appear to be more direct.
Anosmia and ageusia represent two clinical symptoms that support the diagnosis of COVID-19. These two manifestations may occur in 86% to 88% of the cases before the appearance of the general symptoms associated with COVID-19 infection.1 The neurotropic potential of SARS-CoV-2 infection is enhanced by the presence of angiotensin-converting enzyme 2 (ACE2) receptors in neurons and glial cells. ACE2 receptors are the main attachment point for the spike S glycoprotein that mediates coronavirus entry into the host. Therefore, the above clinical symptoms in the absence of nasal congestion and rhinorrhoea implicate involvement of the olfactory nerve (CN I) and gustatory nerves. The latter nerve tracts come from the tongue and the oral cavity (CN VII and IX) and from the pharynx (CN X). Most probably, the virus may use cranial nerve tracts to enter the CNS, reaching preferentially some specific neuronal networks, notably basal ganglia, hypothalamic regulatory networks of hunger, thirst or body temperature, and sleep-wake networks (anterior and posterior hypothalamus, and mesencephalon-pontine nuclei).6 Neural invasion from infected lungs via CNs IX-X has also been postulated. Involvement of brainstem respiratory centres may be responsible for the extremely high case-fatality rate (49%) of COVID-19 patients in critical condition requiring respiratory support.1
Based on the foregoing observations, we propose that sleep specialists around the world remain aware of the possibility of COVID-19-related sleep disorders now and into the future. We also propose that patients exhibiting symptoms suggestive of cerebral invasion undergo sleep investigation. Such information should provide a better understanding of the impact of COVID-19 on the brain and assist in the clinical evaluation and the development of treatment strategies.
1. Román CG, Spencer PS, Reis J, et al. The neurology of COVID-19 revisited: A proposal from the Environmental Neurology Specialty Group of the World Federation of Neurology to implement international neurological registries. J Neurol Sci [published online 2020 May 6]. doi: 10.1016/j.jns.2020.116884
2. Von Economo C. Sleep as a problem of localization. J Nerv Ment Dis 1930;71:249-259. doi: 10.1097/00005053-193003000-00001
3. Kodaira M, Yamamoto K. First attack of Kleine-Levin syndrome triggered by influenza B mimicking influenza-associated encephalopathy. Intern Med 2012;51:1605-8. doi: 10.2169/internalmedicine.51.7051
4. Han F, Lin L, Warby SC, et al. Narcolepsy onset is seasonal and increased following the 2009 pandemic in China. Ann Neurol 2011;70:410-417. doi: 10.1002/ana.22587
5. Tesoriero C, Codita A, Zhang M-D, et al. H1N1 influenza virus induces narcolepsy-like sleep disruption and targets sleep-wake regulatory neurons in mice. Proc Natl Acad Sci U S A 2016;113:E368-E377. doi: 10.1073/pnas.1521463112
6. Li YC, Bai WZ, Hashikawa T. The neuroinvasive potential of SARS-CoV2 may play a role in the respiratory failure of COVID-19 patients. J Med Virol.2020;92(6) [published online 2020 Feb 27]. doi: 10.1002/jmv.25728
Contributors: All authors are lead authors. AB proposed and drafted the manuscript for intellectual concept; AB, MWR, JR, RC, PSS, GCR: conceptualisation, literature search and analysis; AB, MWR, JR, RC, PSS, GCR: writing and revision of the manuscript for intellectual content. GCR is Chair, Environmental Neurology Specialty Group of the World Federation of Neurology of which AB, JR and PSS are members.
Funding: GCR’s research is funded by the Wareing Family Fund, Houston Texas, USA.
Competing Interests: None declared.
Patient consent for publication: Not required.
Provenance and peer review: Not commissioned; externally peer reviewed.
It is with great interest that I read the excellent paper by Beyrouti R, et al, on the characteristics of ischaemic stroke among patients with COVID-19(1). There is great interest in the prothromotic state seen in this illness – in this series, high D-dimer and fibrinogen levels in 6/6, positive lupus anticoagulant in 4/5, moderate anti-cardiolipin titres in 1/6.
But I note that there are still some traditional mechanisms in these patients that may have been the cause of the stroke that may not have been fully elucidated, or if they were, were not reported in the paper. I see that patients 2 and 3 had atrial fibrillation, on warfarin, with supra-therapeutic (3.6, artificial heart valve) and sub-therapeutic (1.03) INRs respectively. The results of echocardiography and cardiac rhythm monitoring were not reported for any patient. Thus cardioembolism is still possible as a cause of stroke. Patients 2 to 5 had hypertension and at least one other atherosclerotic vascular risk factor (eg diabetes mellitus, hypercholesterolaemia, smoking, stroke). All patients save 1 was above 60 years of age. Vascular imaging was only reported for 2 cases (5 - CTA and 6 - MRA). Atherothromboelbolism may have caused stroke in some of the patients.
I refer to case series of stroke seen during the 2002-2204 SARS epidemic, also due to a corona virus (2); all had large artery ischaemic strokes, at least 2 of 4 assessed patients had a cardioembolic source, with anot...
I refer to case series of stroke seen during the 2002-2204 SARS epidemic, also due to a corona virus (2); all had large artery ischaemic strokes, at least 2 of 4 assessed patients had a cardioembolic source, with another having a recent myocardial infarction. I feel there is value in doing as full an evaluation as is reasonably possible to determine the cause of stroke.
The TOAST criteria are widely used in clinical practice, classifying ischaemic stroke mechanisms into 1) large-artery atherosclerosis, 2) cardioembolism, 3) small-vessel occlusion, 4) stroke of other determined etiology, and 5) stroke of undetermined etiology (3). The last category includes those who had more than 1 determined cause, had no determined cause despite extensive investigation, or who had an incomplete aetiological evaluation. Thus, each case requires a full evaluation before cause is assigned; else they will be of undetermined origin.
I hope the authors could kindly provide follow-up information on the results of these investigations, when they are available, so that we may better understand the cause of the stroke in all their patients.
Thank you again for a most interesting paper.
1. Beyrouti R, Adams ME, Benjamin L, Cohen H, Farmer SF, Goh YY, Humphries F,
Jäger HR, Losseff NA, Perry RJ, Shah S, Simister RJ, Turner D, Chandratheva A,
Werring DJ. Characteristics of ischaemic stroke associated with COVID-19. J
Neurol Neurosurg Psychiatry. 2020 Apr 30. pii: jnnp-2020-323586
2. Umapathi T, Kor AC, Venketasubramanian N, Lim CC, Pang BC, Yeo TT, Lee CC, Lim
PL, Ponnudurai K, Chuah KL, Tan PH, Tai DY, Ang SP. Large artery ischaemic stroke
in severe acute respiratory syndrome (SARS). J Neurol. 2004 Oct;251(10):1227-31.
3. Adams HP Jr, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, Marsh EE
3rd. Classification of subtype of acute ischemic stroke. Definitions for use in a
multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment.
Stroke. 1993 Jan;24(1):35-41
The editorial by Manji et al.1 on the neurology of the COVID-19 pandemic cites Mao et al2.’s report describing 5 ischemic strokes in 214 COVID-19 patients. Helms et al3,. and Zhang et al4. have also since reported ischemic stroke in patients with severe SARS-CoV-2 infection, with the latter linking stroke to antiphospholipid antibodies4. In addition, Oxley et al. describe large-vessel stroke in 5 young patients5. In this context, I would like to highlight our 2003 study of ischemic stroke in severe SARS-CoV-1 infection, the corona virus responsible for Severe Acute Respiratory Syndrome (SARS)6. Five out of a total of 206 SARS patients in the country developed large artery ischemic stroke7, four of whom were critically ill. They were not significantly older (56±13 years) than other critically-ill SARS patients (50±16 years, Anova p=0.45). Besides episodes of hypotension, we suspected thromboembolism as a possible mechanism of stroke. Four of the eight SARS patients, who had autopsy examination, revealed evidence of pulmonary thromboemboli8. One was a 39-year-old man, with no stroke risk factors, who died two weeks after contracting SARS; his autopsy revealed unilateral occipital lobe infarction, sterile vegetations on multiple valves, deep venous thrombosis and pulmonary embolism. This prompted the subsequent use of low molecular weight heparin (LMWH) in critically-ill patients, at doses to achieve anti-Xa levels of 0.5-1.0IU/ml. Nevertheless, one-thir...
The editorial by Manji et al.1 on the neurology of the COVID-19 pandemic cites Mao et al2.’s report describing 5 ischemic strokes in 214 COVID-19 patients. Helms et al3,. and Zhang et al4. have also since reported ischemic stroke in patients with severe SARS-CoV-2 infection, with the latter linking stroke to antiphospholipid antibodies4. In addition, Oxley et al. describe large-vessel stroke in 5 young patients5. In this context, I would like to highlight our 2003 study of ischemic stroke in severe SARS-CoV-1 infection, the corona virus responsible for Severe Acute Respiratory Syndrome (SARS)6. Five out of a total of 206 SARS patients in the country developed large artery ischemic stroke7, four of whom were critically ill. They were not significantly older (56±13 years) than other critically-ill SARS patients (50±16 years, Anova p=0.45). Besides episodes of hypotension, we suspected thromboembolism as a possible mechanism of stroke. Four of the eight SARS patients, who had autopsy examination, revealed evidence of pulmonary thromboemboli8. One was a 39-year-old man, with no stroke risk factors, who died two weeks after contracting SARS; his autopsy revealed unilateral occipital lobe infarction, sterile vegetations on multiple valves, deep venous thrombosis and pulmonary embolism. This prompted the subsequent use of low molecular weight heparin (LMWH) in critically-ill patients, at doses to achieve anti-Xa levels of 0.5-1.0IU/ml. Nevertheless, one-third of severe SARS patients developed venous thromboembolism including pulmonary embolism6,7. Three of the 5 stroke patients had also received LMWH. Three patients had unremarkable procoagulant work-up. While we did not measure D-dimer systematically 2 had evidence of disseminated intravascular coagulation, both whom died. Mao et al. and Oxley et al. highlight the possible significance of raised D-dimer in COVID-19 patients who developed stroke2,5. Furthermore, intravenous immunoglobulin (IVIg) was given empirically to 3 of our patients, at 2, 5 and 16 days before stroke onset, that could have compounded the thromboembolic risk.
Experimental, albeit conflicting, evidence suggests that the SARS-CoV1 virus, which causes SARS, could activate transcription of a prothrombinase gene, coding Fibrinogen-like 2 (FGL2)9. FGL2 is a multi-functional protein that activates prothrombin to generate thrombin that in turn converts fibrinogen into fibrin, possibly explaining the extensive fibrin deposition in the lungs of SARS patients as well as inducing a prothrombotic state. Interestingly, the proteolytic activity of FGL2 is independent of factor X and cannot be inhibited by antithrombin III9, perhaps explaining LMWH’s apparent lack of efficacy in our patients.
Ischemic stroke appears to be an infrequent complication of corona virus infections, occurring mainly in the very ill patients with multiple contributory co-morbidities. However, in contrast to SARS, which affected fewer than 9000 people globally COVID-19 has already infected more than 2 million, a sizeable proportion of whom are critically ill. Our experience with SARS prompts us to recommend vigilance against thromboembolism in general and specifically as a mechanism for ischemic stroke, particularly if empirical treatment with IVIg or convalescent plasma is attempted.
1) Manji H, Carr AS, Brownlee WJ. Neurology in the time of covid-19. J Neurol Neurosurg Psychiatry. 2020 Apr 20. pii: jnnp-2020-323414.
2) Ling Mao1; Huijuan Jin; Mengdie Wang1; et al. Neurologic Manifestations of Hospitalized Patients With Coronavirus Disease 2019 in Wuhan, China. JAMA Neurol. Published online.
3) Helms J, Kremer S, Merdji H. Neurologic Features in Severe SARS-CoV-2 Infection.N Engl J Med. 2020 Apr 15. doi: 10.1056/NEJMc2008597.
4) Zhang Y, Xiao M, Zhang S. Coagulopathy and Antiphospholipid Antibodies in Patients with Covid-19.N Engl J Med. 2020 Apr 8.
5) Oxley TJ, Mocco J, Majidi S, et al. Large-Vessel Stroke as a Presenting Feature of Covid-19 in the Young. N Engl J Med. 2020 Apr 28.
6) Umapathi T, Kor AC, Venketasubramanian N,et al. Large artery ischaemic stroke in severe acute respiratory syndrome (SARS). J Neurol. 2004;251(10):1227-31.
7) Lew TW, Kwek TK, Tai D, et al. Acute respiratory distress syndrome in critically ill patients with severe acute respiratory syndrome. JAMA 2003; 290(3):374-80.
8) Chong PY, Chui P, Ling AE, Franks TJ,et al. Analysis of deaths during the severe acute respiratory syndrome (SARS) epidemic in Singapore: challenges in determining a SARS diagnosis. Arch Pathol Lab Med 128:195–204
9) Yang G, Hooper WC. Physiological functions and clinical implications of fibrinogen-like 2: A review World J Clin Infect Dis. 2013 Aug 25;3(3):37-46.
Obsessive-compulsive disorder (OCD) is a neuropsychiatric disease characterized by distressing thoughts or urges that often require repetitive behaviors to suppress. OCD affects 2-3% of the general population and can have debilitating effects on normal functioning. While most cases of OCD can be addressed through psychotherapy and/or medication, about 10% remain refractory, requiring neurosurgical intervention, such as neuroablation (ABL) or deep brain stimulation (DBS). These options possess their own respective advantages and disadvantages. ABL lacks the hardware concerns of DBS (e.g. device failure, battery replacement, etc.) and may be incisionless (e.g. stereotactic radiosurgery). Alternatively, DBS is non-lesional, and stimulation parameters can be titrated. While both ABL and DBS appear to be effective for refractory OCD, there is no clear consensus on their relative superiority/non-inferiority.
Our group previously sought to address this question by comparing the two treatments’ relative utility.  Using a random-effects, inverse-variance weighted meta-analysis of 56 studies, utility was calculated from Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores and adverse event (AE) incidence. In our analysis, no significant differences were found between stereotactic radiosurgery and radiofrequency ablation, so their studies were combined and all considered under ABL. Ultimately, ABL yielded a significantly greater utility compared to...
Our group previously sought to address this question by comparing the two treatments’ relative utility.  Using a random-effects, inverse-variance weighted meta-analysis of 56 studies, utility was calculated from Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores and adverse event (AE) incidence. In our analysis, no significant differences were found between stereotactic radiosurgery and radiofrequency ablation, so their studies were combined and all considered under ABL. Ultimately, ABL yielded a significantly greater utility compared to DBS (0.189±0.03 vs. 0.167±0.04, respectively; P<0.001). Due to perceived advantages of DBS over ABL, this result was surprising and inquiries were raised about the reliability of the analysis. A primary concern was whether study rigor could have impacted our finding. In this follow-up study, we performed an in-depth assessment of rigor of the ABL vs. DBS studies that previously met criteria for inclusion.
Assessment of rigor requires the selection of a grading scale. However, as rigor scales are designed for a specific type of study, a single type of scale is incapable of properly assessing the variety of analyzed study types (e.g., RCT, cohort, and case series). To circumvent this issue, we decided to score only case series because they were the most common study type in both treatment groups. These studies were assessed with the Institute of Health Economics (IHE) quality appraisal checklist, which is a validated scale designed exclusively for case series.[2,3] These rigor scores were then used as covariates to a mixed-effects model of treatment against outcome (i.e. Y-BOCS score, adverse event (AE) incidence, and overall utility).
There were a total of 20 DBS and 17 ABL case series used in the meta-analysis; they represent 71.4% and 94.4%, respectively, of all studies in each treatment group. For overall number of patients, case series contribute 68.7% (125/182) and 97.7% (347/355) to DBS and ABL groups, respectively. In addition, they represent 40% (4/10) and 83.3% (10/12) of DBS and ABL studies that report AE incidence. DBS studies had significantly higher rigor scores than ABL studies (13.5/20 versus 11.0/20, respectively; p<0.001).
Similar to the results of Kumar et al., ABL still imparts a significantly higher utility than DBS with rigor as covariate in the mixed-effects model of treatment (p<0.0001). AE incidence was also significantly lower in ABL case studies (p=0.0024). For Y-BOCS score, ABL case series report greater percent reduction compared to DBS studies, though it was only marginally significant (p=0.0609). When rigor added to the mixed-effects model of treatment against outcome, neither the treatment group nor the rigor scores were significant predictors of % Y-BOCS score reduction (p=0.2261 and 0.4179, respectively). Similarly, neither treatment group nor rigor was a significant predictor of AE incidence (p=0.2223 and 0.4602, respectively). When considered as the sole predictor, rigor was not found to be significant predictor of % Y-BOCS score reduction (p = 0.1115). However, higher rigor scores were predictive of higher AE incidence (p = 0.0064).
Rigor is an important consideration as it may lend insight to a study’s validity and robustness. One hypothesis of ABL’s superiority over DBS was that ABL studies were less rigorous, producing outcomes that may be less reflective of reality. As rigor was not a significant covariate for utility, it suggests that Kumar et al.’s original conclusion of ABL superiority is accurate. However, even though rigor is not a significant covariate of % Y-BOCS score reduction, it is a significant predictor for AE incidence. Higher rigor studies generally had a higher reported AE incidence.
A notable limitation to this analysis is the exclusive use of case series. The mixed collection of study types precluded the perfect fit of a single scale to all studies. Since case series only represent a portion of all studies, our calculations slightly vary from those reported previously in Kumar et al. Nevertheless, case series represent the vast majority of studies and patients in both DBS and ABL groups. Though not a perfect facsimile, they are still highly representative. Regarding AE incidence, DBS case series constitute only 40% of overall DBS studies with AE reports. Yet, they were sufficient in establishing the significant association of high rigor and AE incidence. Given that the remaining DBS studies likely have even higher rigor (i.e. RCTs and cohort studies), an even stronger association with their inclusion is not an unreasonable inference. Furthermore, although treatment types were no longer significant predictors, this may be a consequence of working with fewer studies and overfitting data.
While study rigor was not a significant covariate for the current utility calculation, it is nevertheless an important consideration for similar meta-analyses, especially when assessing older and newer technologies. As the field of functional neurosurgery advances, there will be a greater need for similar comparisons to evaluate and guide clinical decision-making and adoption of novel techniques. Developments in DBS technologies can all plausibly improve DBS utility for OCD, necessitating further studies. Despite its limitations as an imperfect measure, study rigor may provide valuable insight into the reliability of reported data.
1. Kumar KK, Appelboom G, Lamsam L, et al. Comparative effectiveness of neuroablation and deep brain stimulation for treatment-resistant obsessive-compulsive disorder: A meta-analytic study. J Neurol Neurosurg Psychiatry 2019;90:469–73. doi:10.1136/jnnp-2018-319318
2. Institute of Health Economics. Quality Appraisal Checklist for Case Series Studies. 2014;:1–2.
3. Guo B, Moga C, Harstall C, et al. A principal component analysis is conducted for a case series quality appraisal checklist. J Clin Epidemiol 2016;69:199–207.e2. doi:10.1016/j.jclinepi.2015.07.010
De Schaepdryver et al. assessed the prognostic ability of serum neurofilament light chain (NfL) and C-reactive protein (CRP) in patients with amyotrophic lateral sclerosis (ALS) (1). Although two indicators can significantly predict the prognosis, the superiority by the combination of NfL and CRP should be checked for the analysis. I want to discuss NfL and ALS prognosis from recent publications.
Verde et al. conducted a prospective study to determine the diagnostic and prognostic performance of serum NfL in patients with ALS (2). Serum NfL positively correlated with disease progression rate in patients with ALS, and higher levels were significantly associated with shorter survival. In addition, serum NfL did not differ among patients in different ALS pathological stages, and NfL levels were stable over time within each patient.
Regarding the first query, Thouvenot et al. reported that serum NfL could be used as a prognostic marker for ALS at the time of diagnosis (3). Gille et al. recognized the relationship of serum NfL with motor neuron degeneration in patients with ALS (4). They described that serum NfL was significantly associated with disease progression rate and survival, and it could be recommended as a surrogate biomarker of ALS. These two papers presented no information whether NfL can be used for monitoring of ALS progression in each patient.
De Schaepdryver et al. used two indicators, and I suspect that the authors can present information r...
De Schaepdryver et al. used two indicators, and I suspect that the authors can present information regarding the monitoring ability for ALS progression. In combination with clinical findings, biological monitoring method might be important for medication efficacy.
1. De Schaepdryver M, Lunetta C, Tarlarini C, et al. Neurofilament light chain and C reactive protein explored as predictors of survival in amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry. 2020;91(4):436-437. doi: 10.1136/jnnp-2019-322309
2. Verde F, Steinacker P, Weishaupt JH, et al. Neurofilament light chain in serum for the diagnosis of amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry. 2019 Feb;90(2):157-164. doi: 10.1136/jnnp-2018-318704
3. Gille B, De Schaepdryver M, Goossens J, et al. Serum neurofilament light chain levels as a marker of upper motor neuron degeneration in patients with amyotrophic lateral sclerosis. Neuropathol Appl Neurobiol. 2019;45(3):291-304. doi: 10.1111/nan.12511
4. Thouvenot E, Demattei C, Lehmann S, et al. Serum neurofilament light chain at time of diagnosis is an independent prognostic factor of survival in amyotrophic lateral sclerosis. Eur J Neurol. 2020;27(2):251-257. doi: 10.1111/ene.14063