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for long­term oral anticoagulation—is rising, the number of stroke patients on oral anticoagulants is likely to increase. Importantly, 75% of patients with ischae­mic stroke who are receiving VKA are below the accepted thera peutic thresh­old for this treatment (INR <2) at the time of the stroke.8 In the GWTG study, 50% of patients with an INR ≤1.7 did not receive thrombolysis despite their eligibil­ity for treatment with tPA.4 This finding indicates a demand for improvement of emergency management in this important subpopulation of patients with stroke. Moreover, the matter of anticoagulation is also relevant for emergency management of patients of unknown coagulation status (such as patients with aphasia). Point­of­care INR testing can accelerate assessment and thrombolytic management of patients receiving VKA and of those with unknown VKA status.9

The long­term debate regarding safety of thrombolysis for stroke in the setting of anticoagulation with VKA has been settled, but new challenges are already apparent. An increasing number of patients receive novel oral anticoagu­lants (nOACs) instead of VKA. Given that ischaemic stroke is about as frequent with nOACs as with VKAs, the propor­tion of strokes in those receiving these new therapies will not decrease. Stroke in patients who are receiving one of these novel therapies poses diagnostic and thera­peutic challenges. First, standard coagula­tion testing (such as prothrombin time or activated partial thromboplastin time) is not sensitive and does not provide a reli­able estimate of the strength of anticoagu­lation. Point­of care coagulation testing is not available for these new substances, and central laboratory­ based (rather than local) blood assessment leads to delays for patients on nOACs or those with unknown coagulation status at presentation. Second, whether nOACs augment the risk of haemor rhagic complications after throm­bolysis is currently unknown. A highly consistent finding of all nOAC trials was a 40–70% reduction of the risk of ICH in patients treated with nOACs compared with warfarin. The pharmacodynamic reasons for this difference between VKA and nOACs remain to be elucidated.

Can we extrapolate this data from primary ICH to conclude that thrombo­lysis in ischaemia is safe? Recent preclinical animal model data suggest that thrombo lysis in ischaemic rodents that were pretreated

with nOACs does not cause excessive brain haemorrhage compared with non­ anticoagulated controls.10 Nevertheless, for the time being at least, recommendations for the clinical scenario of thrombolysis in patients with acute stroke who are receiv­ing nOACs should remain cautious. In future, however, expert opinion should be replaced by evidence—ideally, as done by Mazya et al.,3 through use of data from large prospective stroke registries.

Department of Neurology, University of Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (R. Veltkamp, T. Rizos). Correspondence to: R. Veltkamp roland.veltkamp@med.uni‑heidelberg.de

Competing interestsR. Veltkamp declares associations with the following companies: Apoplex Medical Technologies, Bayer, BMS/Pfizer, Boehringer Ingelheim, CSL Behring, Roche. See the article online for full details of the relationships. T. Rizos declares no competing interests.

1. Adams, H. P. et al. Guidelines for the Early Management of Adults with Ischemic Stroke: a guideline from the American Heart Association/American Stroke Association Stroke Council, Clinical Cardiology Council, Cardiovascular Radiology and Intervention Council, and the Atherosclerotic Peripheral Vascular Disease and Quality of Care Outcomes in Research Interdisciplinary Working Groups. Stroke 38, 1655–1711 (2007).

2. European Stroke Organisation (ESO) Executive Committee. Guidelines for management of ischaemic stroke and transient ischaemic attack 2008. Cerebrovasc. Dis. 25, 457–507 (2008).

3. Mazya, M. V. et al. Safety of IV thrombolysis for ischemic stroke in patients treated with warfarin. Ann. Neurol. http://doi.dx.org/ 10.1002/ana.23924.

4. Xiang, Y. et al. Risks of intracranial hemorrhage among patients with acute ischemic stroke receiving warfarin and treated with intravenous tissue plasminogen activator. JAMA 307, 2600–2608 (2012).

5. Diener, H. C. et al. Treatment of acute ischaemic stroke with thrombolysis or thrombectomy in patients receiving anti-thrombotic treatment. Lancet Neurol. 12, 677–688 (2013).

6. Frank, B. et al. Thrombolysis in stroke despite contraindications or warnings? Stroke 44, 727–733 (2013).

7. Rizos, T. et al. Oral anticoagulants—a frequent challenge for the emergency management of acute ischemic stroke. Cerebrovasc. Dis. 34, 411–418 (2012).

8. Gladstone. et al. Potentially preventable strokes in high-risk patients with atrial fibrillation who are not adequately anticoagulated. Stroke 40, 235–240 (2009).

9. Rizos, T. et al. Point-of-care international normalized ratio testing accelerates thrombolysis in patients with acute ischemic stroke using oral anticoagulants. Stroke 40, 3547–3551 (2009).

10. Sun, L., Zhou, W., Ploen, R., Zorn, M. & Veltkamp, R. Anticoagulation with dabigatran does not increase secondary intracerebral haemorrhage after thrombolysis in experimental cerebral ischaemia. Thromb. Haemost. 110, 153–161 (2013).

DEMENTIA

Mild cognitive impairment —amyloid and beyondPhilip Scheltens

Recently developed criteria for diagnosis of mild cognitive impairment due to Alzheimer disease make use of clinical and biomarker information. A new study reports that these criteria apply in both community and research settings; however, results from the community-based cohort conflict with a proposed biomarker-based model of disease progression.Scheltens, P. Nat. Rev. Neurol. 9, 493–495 (2013); published online 23 July 2013; doi:10.1038/nrneurol.2013.147

The term mild cognitive impairment (MCI) was first coined by Petersen in the late 1990s,1 but the phenomenon was rec­ognized long before then under different terminologies. MCI is thought to be a stage between normal ageing and dementia, and many studies have investigated factors that predict progression from MCI to demen­tia and Alzheimer disease (AD). Recent insights into the use of biomarkers to

predict underlying AD pathology have led to establishment of diagnostic criteria that incorporate clinical and biomarker find­ings. Biomarkers can be broadly divided into two categories: those for underlying amyloid pathology (cerebrospinal fluid [CSF] amyloid­β or amyloid­PET) or those for neurodegeneration (hippocam­pal atrophy on MRI, CSF tau and fluoro­deoxyglucose [FDG]­PET). Two sets of

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diagnostic cri teria are available: one from the International Working Group pub­lished in 2007 and revised in 2010;2 and one published by the National Institute on Aging and the Alzheimer Association (NIA­AA).3 These criteria were devel­oped mainly for research purposes, such as for use in clinical trials and observa­tional studies, but their use is slowly being adopted in the clinic.

In a new study, published in Annals of Neurology, Petersen et al.4 examined the performance of diagnostic criteria for MCI due to AD and associated biomarkers in a community­based cohort. They applied the NIA­AA criteria for MCI due to AD to data obtained from two separate cohorts: one from The Mayo Clinic Study of Aging (MCSA), a population­based longitudinal study of nondemented individuals aged 70–89 years from Olmsted County, MN, USA; and a sample from the Alzheimer’s Disease Neuroimaging Init iat ive 1 (ADNI 1), a research­based cohort of indi­viduals from the USA, of whom a substan­tial proportion are likely to progress to AD. From the MCSA cohort, 126 individuals who fulfilled the criteria for amnestic MCI (aMCI) but who had not been diagnosed with dementia were selected for inclusion. A set of 58 patients from the ADNI cohort who fulfilled criteria for aMCI was used as a comparator group.

In each cohort, information was obtained on amyloid deposition by Pittsburgh com­pound B (PIB)­PET imaging, as well as on neurodegenerative biomarkers through use of MRI and FDG­PET imaging. Patients were then allocated to one of four groups on the basis of pathology: neurodegenera­tion only; amyloid only; both amyloid and neurodegeneration; or none (Table 1). Some marked differences in baseline characteris­tics of each population were evident; for example, judging by the Clinical Dementia Rating scores, patients from the ADNI study were in a more advanced stage of disease than were patients from the Mayo Clinic cohort. Despite such differences in charac teristics, the biomarker data did not

significantly differ between the two cohorts. As patients in both groups fulfilled cri­teria for aMCI—the type of MCI thought to be closest to AD—the similarities in biomarker findings is not surprising but, rather, reassuring.

Two observations of Petersen et al.4 deserve further comment. First, both the ADNI and Mayo Clinic cohorts included symptomatic patients who had no amyloid pathology and only neurodegenerative fea­tures (Table 1). This finding is in contrast with the proposed biomarker model by Jack et al.5 in which both amyloid pathol­ogy and neurodegeneration are assumed to be present in the symptomatic stage of AD, with amyloid deposition becoming apparent first. The results of Petersen and colleagues4 are, however, supported by findings of another study,6 in which 26% of patients with MCI also did not fit the Jack et al. model.5 Furthermore, in a 2013 publication7 CSF tau and MRI hippocam­pal volume were shown to enable predic­tion of cognitive decline to an equal extent as CSF amyloid­β in patients with aMCI. Collectively, these findings provide support for the hypothesis that factors other than amyloid can drive progression from MCI to AD, and suggest that diseases other than AD could also have an aMCI prelude. In contrast to the situation in those who were diagnosed with MCI, CSF amyloid­β was a better biomarker than were CSF tau and MRI for prediction of cognitive decline in patients with memory complaints who did not yet meet criteria for MCI.8

The second point of note is that, had Petersen and colleagues4 applied the International Working Group criteria to their cohorts, patients with MCI who were positive for only amyloid or only neuro­degeneration biomarkers would have been designated as ‘prodromal AD’. Their use of the NIA­AA criteria, however, meant that such a combination of findings was deemed to be uninformative. The differences between the two diagnostic criteria were highlighted in a 2012 comment,9 which drew attention to the consequences of such

discrepancies with regard to trial design and inclusion of patients in clinical trials.

Petersen et al.4 conclude that the NIA­AA criteria work equally well in research and community­based settings. However, dif­ferences in the two populations require further attention. The observation that 43% of the patients from the MCSA cohort were amyloid (PIB) negative compared with only 33% of patients in the ADNI cohort again supports the suggestion that indi­viduals from the MCSA group were in an earlier stage of MCI than were those from the ADNI cohort. This finding might be expected owing to the community base of the Mayo Clinic study cohort—that is, the patients had not yet sought inclusion in an AD study—but it also stresses that not all patients with MCI who meet criteria for aMCI are at a comparable stage.

Similar discrepancies between the two populations were seen at follow­up, although the authors do not point exten­sively to these data in their report. In the MCSA cohort, only 16% of individuals who were positive for both biomarkers (amyloid and neurodegenera tion) pro­gressed to dementia, compared with 42% of the ADNI cohort. The slight difference in follow­up time (12 months in ADNI versus 15 months in MCSA) does not account for this difference, but differences in the stage of disease of participants in each cohort most probably do. Strikingly, none of the patients in either cohort who was positive only for amyloid progressed to demen­tia. This finding provides support for the hypothesis that neuro degenerative factors play a part in the rate of progression from MCI to AD,10 and cautions against making predictions about time to progression to dementia when assessing individuals with MCI who have an abnormal amyloid scan.

Where to go from here? I can only echo the sentiments of Petersen et al.4 that more longitudinal study observations are needed to further understand the exact role of both amyloid and neurodegenera­tion biomarkers in the evolution of AD. Further delineation of the role of each biomarker, both separately and in concert, may provide important clues for patient selection in research and, ultimately, in clinical practice.

Table 1 | Summary of biomarker findings from Petersen et al.4

Sample n Biomarker finding

Neurodegeneration* only (%)

Amyloid‡ only (%)

Both (%)

None (%)

Mayo Clinic Study of Aging 126 29 14 43 14

Alzheimer’s Disease Neuroimaging Initiative 58 17 12 55 16

*PET or MRI. ‡Amyloid PET.

‘‘…these findings … suggest that diseases other than AD could also have an aMCI prelude’’

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Alzheimer Centre, Department of Neurology, Neuroscience Campus, VU University, De Boelelaan, 1118 1081 HZ Amsterdam, Netherlands. p.scheltens@vumc.nl

Competing interestsThe author declares no competing interests.

1. Petersen, R. C. Clinical practice. Mild cognitive impairment. N. Engl. J. Med. 364, 2227–2234 (2011).

2. Cummings, J. L., Dubois, B., Molinuevo, J. L. & Scheltens, P. International work group criteria for the diagnosis of Alzheimer disease. Med. Clin. North Am. 97, 363–368 (2013).

3. Albert, M. S. et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging and the Alzheimer Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 7, 270–279 (2011).

4. Petersen, R. C. et al. Criteria for mild cognitive impairment due to Alzheimer’s disease in the community. Ann. Neurol. http://dx.doi.org/ 10.1002/ana.23931.

5. Jack, C. R. Jr et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 12, 207–216 (2013).

6. Prestia, A. et al. Prediction of dementia in MCI patients based on core diagnostic markers for Alzheimer disease. Neurology 80, 1048–1056 (2013).

7. Vos, S. J. et al. Prediction of Alzheimer disease in subjects with amnestic and nonamnestic MCI. Neurology 80, 1124–1132 (2013).

8. van Harten, A. C. et al. Cerebrospinal fluid Aβ42 is the best predictor of clinical progression in patients with subjective complaints. Alzheimers Dement. http://dx.doi.org/10.1016/ j.jalz.2012.08.004.

9. Visser, P. J., Vos, S., van Rossum, I. & Scheltens, P. Comparison of International Working Group criteria and National Institute on Aging-Alzheimer’s Association criteria for Alzheimer’s disease. Alzheimers Dement. 8, 560–563 (2012).

10. van Rossum, I. A. et al. Injury markers predict time to dementia in subjects with MCI and amyloid pathology. Neurology 79, 1809–1816 (2012).

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