In Reply: Blood Pressure Targets After Aneurysmal Subarachnoid Hemorrhage: Is Lower Better?
Bibliographic record
Abstract
To the Editor: We thank Hawkes et al for their thoughtful appraisal of our article entitled “Blood Pressure Targets After Aneurysmal Subarachnoid Hemorrhage: Is Lower Better?”1,2 Their commentary highlights key physiological considerations and methodological limitations that may influence the applicability of our results in clinical practice. We are pleased our article has prompted discussion and hope it will stimulate efforts to generate high-level evidence on optimal blood pressure (BP) targets in patients with aneurysmal subarachnoid hemorrhage (SAH). The first point raised concerns the exclusion of patients with rebleeding in our data set. Although it is true that these patients are the ones postulated to benefit most from systolic blood pressure (sBP) reduction, this omission strengthens the results. If there are no patients who rebleed, then this variable is removed as a source of poor outcome. Therefore, it will be easier to detect the effects of sBP on outcome. Our work found that, despite excluding the patients who are hypothesized to benefit most from sBP reduction, lower sBP before the aneurysm treatment was associated with improved outcomes. The omitted variable bias works in favor of our findings. We agree that single measurements of sBP are imperfect and that fluctuations and spurious readings are common. However, the data from the Clazosentan to Overcome Neurological Ischemia and Infarction Occurring After Subarachnoid Hemorrhage (CONSCIOUS-1) study was collected from mostly “high-volume” centers experienced in recording data on case report forms. Having collaborated with the study authors (R.L.M.) on several other SAH clinical trials, we are confident that the authors of this critical appraisal can attest to the robustness of the data collection process in these large studies. It is worth noting that the concept of “spurious” readings could, in principle, be applied to question almost any variable in any data set. Second, the authors raise the possibility that elevated sBP in the setting of aSAH may be a compensatory response secondary to raised intracranial pressure to maintain cerebral perfusion pressure (CPP). This is an important consideration and is one of the many limitations of our post hoc analysis. There are a lot of variables in the CONSCIOUS-1 data set, but it would be challenging to figure out why the BP was at a given level at a certain time. As noted earlier, the investigators in CONSCIOUS-1 were drawn from high-volume centers with extensive experience in managing these patients and in maintaining adequate CPP. It therefore seems unlikely that they would intentionally lower sBP to a level that could compromise perfusion. One could take the opposite view and stipulate that because these patients were treated by experienced teams, the occurrence of a known low CPP would be less likely, potentially making it easier to detect a threshold sBP in our post hoc analysis. This reasoning would also apply to the sentence at the end of the second-to-last paragraph regarding differences in lower sBP between previously normotensive and hypertensive patients. Third, we agree that excluding patients who are vulnerable to hypoperfusion such as patients with poor World Federation of Neurological Surgeons (WFNS) grades, chronic kidney disease and persistently low BP may artificially minimize the harms of low BP. As with excluding patients who rebleed, excluding these patients limits the generalizability of the results but could be argued to decrease the number of variables that could affect detection of a threshold sBP. Finally, and importantly, BP management was not standardized in CONSCIOUS-1. We believe that the lack of standardized management for patients with SAH remains one of the fundamental challenges in the field. Previous studies have achieved very little standardization in the perioperative care of these patients,3-7 which has made it difficult to design study protocols for SAH that go beyond aneurysm repair. As a result, there are relatively few well-controlled randomized clinical trials in this area, and there have been almost no evidence-based advances in SAH management between the last two American Heart Association SAH guidelines.8,9 SAH may be the only major stroke subtype that does not have any large, multicenter, randomized clinical trials addressing BP targets. We agree that aggressive BP reduction could have varying effects depending on baseline BP, although this remains speculative. Regarding the suggestion that BP variability is associated with poor outcome, we find the previously published data to be interesting and warranting further investigation. However, the current data are limited in its ability to confirm this association, particularly considering the many other variables influencing outcome, as discussed above. This paper was an exploratory analysis of prospectively collected data and was not an interventional study. The genesis of our study was not to prove that lower blood pressure leads to better outcomes after SAH but to interrogate the concern that lower sBP, within reason, before aneurysm treatment, leads to secondary brain injuries from hypoperfusion. Therefore, we, too, were somewhat surprised by our findings. Hence, we can reassure the readership that our results and conclusions were, indeed, data driven. Although it is common for papers of this nature to conclude with a call for additional data and randomized clinical trials, we hope that our results will lead to such future efforts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.031 | 0.044 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".