Dr Bruchanski: Thrombolytic Therapy for Acute Ischemic Stroke(Click the title to listen to a recording of the talk)
Dr. Bruchanski presented a review of thrombolytic therapy in acute ischemic stroke. The paper, from the NEJM's Clinical Therapeutics series, reviews the evidence that thrombolytic therapy with recombinant tissue plasminogen activator (rt-PA) can improve neurological outcomes in patients presenting with early thromboembolic CVA.
Here's a brief summary: the FDA approved rt-TPA in 1996, partly on the basis of the National Insitute of Neurological Disorders and Stroke Recombinant Tissue Plasminogen Activator study (NINDS rt-PA). The first part of the NINDS study (N=261) showed no difference in the primary end point of neurologic recovery or improvement at 24 hours. However, the second part of the study (N=333) looked at complete recovery at 90 days and did detect a benefit from rt-PA therapy (odds ratio 1.7; 95% CI, 1.2-2.6; P=0.008). Three subsequent trials, (the European Cooperative Acute Stroke Study (ECASS), ECASS II, and the Alteplase Thrombolysis for Acute Noninterventional Therapy in Ischemic Stroke (ATLANTIS) studies failed to replicate these results. The main difference between ATLANTIS, ECASS and ECASS II and the NINDS study was the timing of therapy. In the former three trials, patients could be enrolled within 6 hours of their stroke and less than 20% were treated within three hours, whereas in the NINDS study almost all patients were treated within three hours of symptom onset and almost 50% were treated within 90 minutes. The ECASS III, which treated patients earlier in their disease course and looked at a dichotomized measure of disability at 90 days, did seem to confirm the findings of the NINDS study (odds ratio 1.34, 95% CI 1.02-1.76, P=0.04). This would seem to suggest that there is a significant benefit associated with rt-PA therapy in acute stroke so long as it's initiated pretty quickly, and this is reflected in the American Heart Association and the European Stroke Association's guidelines for treatment of acute stroke. This is also supported by a concise graph Dr. Bruchanski showed from a 2004 meta-analysis published in the Lancet (the full article is in the Attendings folder).
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| Figure 3 from the Lancet meta-analysis plotting adjusted odds ratio of favorable outcome against onset-to-treatment time. |
In the case of thrombolytic therapy for acute stroke as studied in the NINDS trial, the ARI for acute intracranial hemorrhage was 6% (see above). In the original 1995 paper, the investigators reported the ABI as 11%-13%. So, using the formula above, we can say that for rt-PA as studied by the NINDS group:
NNH = 1/0.06 = 17 patients who need to be treated to cause one symptomatic ICH
NNT = 1/0.12 (roughly) = 9 patients need to be treated for one good outcome at 90 days (as defined by the study).
(NNT and NNH are rounded up to the nearest whole number)
You can also put this in terms of the "likelihood of being helped or harmed" (or LHH), which is just he ratio of the ABI to the ARI. In this case,
LHH = 0.12/0.06 = 2
Thus you can say, when obtaining informed consent for thrombolysis in acute stroke, that the treatment is twice as likely to help the patient as it is to hurt them. Note, however, that while the NNT and NNH give you some sense of the magnitude of the effect, the LHH is just a ratio. If the NNT was 10,000 and the NNH was 5,000, both effects would be epidemiologically trivial, but the LHH would still be 2.
Dr. Bruchanski's presentation sparked a lively discussion. Several people including Dr. Cho and Dr. Lahsaeizadeh expressed concerns about generalizing these results to Highland, since one would imagine we see a disproportionate volume of acute stroke related to cocaine and methamphetamine use relative to the centers where the ECASS and NINDS trials were done. Since these strokes presumably have a vasospastic rather than a thrombotic etiology, giving rt-PA would expose patients to all the risk of hemorrhage and none of the potential benefit of thrombolysis. Dr. Desai suggested that a history of recent stimulant use should be considered an exclusion criterion. While it's sometimes difficult to obtain an accurate substance history, Dr. Abramowitz reminded us that it's a lot easier when the clinical importance of this information is explained to patients in a compassionate and non-judgemental fashion. Dr. Acharya concluded the discussion by emphasizing that, given the substantial risk of severe harm assocaited with rt-PA, it is especially vital to be completely sure that a patient meets the inclusion criteria of the population for which benefit has been demonstrated and has none of the exclusion criteria published in major guidelines.
Dr. Kari: Imaging in Headache
(Click the title to listen to a recording of the talk)
Dr. Kari presented a prospective observational study which looked at the frequency of significant intracranial abnormalities on imaging in patients referred to a specialist headache unit in Birmingham. The authors reported that out of 3,655 referrals over a five year period, they referred 530 for neuroimaging (14.5%). They found a staggering total of 11 abnormal results (2.1% of patients imaged) which were thought to be clinically significant. The rate of abnormal imaging findings was even lower in patients with a primary diagnosis of migraine (1.2%) and tension headache (0.9%)
In their discussion, the authors note that their results cohere well with previous studies which looked at the rate of detection of significant abnormalities in people with migraine headaches but no other worrying signs, and in normal volunteers who were imaged with MRI. Specifically, they cite a meta analysis of 16 studies of MRI in healthy volunteers which found a 0.7% prevalence of intracranial neoplasm and a 2% prevalence of non-neoplastic abnormalities (including cerebrovascular disease). This implies that the incidence of abnormal findings in patients with headaches is similar to that in the general population. Moreover, most people would think they actually over-reported the incidence of abnormal findings, since they counted studies done on people who were already known to have intracranial abnormalities (e.g. moyamoya disease) - if these are left out, then the prevalence of abnormal findings falls to 1.5%.
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| Imaging should always be considered for headache patients who present with "red flag" symptoms and signs. |
On the other hand, when intracranial pathology was suspected on the basis of red flags ("symptoms or signs of raised intracranial pressure, focal neurological signs, epilepsy, cognitive disturbance or recent diagnosis of cancer") the prevalence of significant abnormalities was 5.5%.
Dr. Acharya pointed out that, while these results are consistent with other major studies, it's worth noting that this is a highly selected patient population. These are people who've already been referred to neurologists by their general practitioner, had that referral vetted by a neurologist, and seen a specialist headache nurse. This means there are (theoretically) some built in selection bias - it could be, for example, that the reason the neurologists aren't seeing brain tumors in headache patients is because they've all been diagnosed already by general practitioners. However, this seems unlikely and this study does seem to support the idea that chronic headache in the absence of concerning findings is unlikely to be diagnostically elucidated by imaging studies.
Dr. Wang: Vascular Risk Factors and Alzheimer's Dementia
(Click the title to listen to a recording of the talk)
Their results did demonstrate a correlation between vascular risk factors and the progression of MCI to AD, and they also showed that treatment for VRF were correlated with a reduced incidence of progression over the course of the study. They reported statistically significant differences between those who stayed in MCI and those who progressed to AD in terms of diabetes, hypertension, and cerebrovascular disease. However, one of the most striking differences was that those who progressed to AD were, on average, about five years older than those who didn't. Recall that the study period was five years; so age is a majro potential confounder here, since it's perfectly possible that the reason the non-progressors didn't progress druing the study period was taht they were all five years younger, and that after the study (when they would have been, on average, as old as the people in the group who did progress to AD,) they developed AD at the same rate.
Dr. Acharya expressed some doubt about the diagnostic utility of MCI as a category, and Dr. Desai noted that the onset of dementia is extraordinarily difficult to pin down since people can often compensate well for cognitive deficits for a long time before cognitively decompensating. However, both agreed that if this observational study spurs further prospective work which confirms their findings, it may ultimately help us slow the development of dementia through treatment of VRF.
The authors reported their results as hazard ratios. Hazard ratios are a commonly used metric in survival analysis. In statistics, the "hazard rate" refers to the rate of an event (for all practical purposes, the incidence) at a given moment in time. The hazard ratio is the hazard rate in the study group (i.e. the group who have the exposure of interest or are being treated with the experimental drug) and the control group. In this case, the hazard ratios reported refer to the ratio of the incidence of progression to AD among people with a given risk factor to the incidence of progression to AD among people without that risk factor. These "crude hazard ratios" are then adjusted for potential confounding factors to give the "adjusted hazard ratios" they report. You can see that the hazard ratio is something like the relative risk (AKA risk ratio), although they're calculated differently.
What the hazard ratio tells you is the odds, for any moment in time, that someone in the experimental group will experience the endpoint in question before someone in the control group. To take a specific example, when the authors say that the adjusted hazard ratio for AD among patients with diabetes is 1.62, what they mean is that at any given instant during the study period people with diabetes were 1.62 times more likely to develop AD than people without diabetes.
If you're interested, there's a good article explaining HRs in more detail here.
Special thanks to Dr. Schafhalter-Zoppoth and Dr. Ren for helping us understand the statistics in this article.
