Optimizing Patient Selection for Interhospital Transfer and Endovascular Therapy in Acute Ischemic Stroke: Real-World Data From a Supraregional, Hub-and-Spoke Neurovascular Network in Germany
Bibliographic record
Abstract
Background: Interhospital transfer for endovascular treatment (EVT) within neurovascular networks might result in transfer of patients who will not undergo EVT (futile transfer). Limited evidence exists on factors associated with the primary patient selection for interhospital transfer from primary stroke centers (PSCs) to comprehensive stroke centers (CSCs), or EVT-workflow parameters that may render a transfer futile. Methods: A prospective, registry-based study was performed between July 1, 2017 and June 30, 2018, at a hub-and-spoke neurovascular network in southwest Germany, comprising 12 referring PSCs and one designated CSC providing round-the-clock EVT at the University Hospital Tübingen. Patients with acute ischemic stroke due to suspected large artery occlusion (LAO) were included upon emergency interhospital transfer inquiry (ITI). Results: ITI was made for 154 patients, 91 (59%) of whom were transferred to the CSC. Non-transferred patients (41%) had significantly higher premorbid modified Rankin scale scores (mRS) compared to transferred patients [median (IQR): 2 (1–3) vs. 0 (0–1), p < 0.001]. Interhospital transfer was denied due to: distal vessel occlusion (44.4%), or non-verifiable LAO (33.3%) in computed tomography angiography (CTA) upon teleconsultation by CSC neuroradiologists; limited Stroke-Unit or ventilation capacity (9.5%), or limited neuroradiological capacity at the CSC (12.7%). The CT-to-ITI interval was significantly longer in patients denied interhospital transfer [median (IQR): 43 (29–56) min] compared to transferred patients [29 (15–55), p = 0.029]. No further differences in EVT-workflow, and no differences in the 3-month mRS outcomes were noted between non-transferred and transferred patients [median (IQR): 2 (0–5) vs. 3 (1–4), p = 0.189]. After transfer to the CSC, 44 (48%) patients underwent EVT. The Alberta stroke program early CT score [ORadj (95% CI): 1.786 (1.573–2.028), p < 0.001] and the CT-to-ITI interval [0.994 (0.991–0.998), p = 0.001] were significant predictors of the likelihood of EVT performance. Conclusion: Our findings show that hub-and-spoke neurovascular network infrastructures efficiently enable access to EVT to patients with AIS due to LAO, who are primarily admitted to PSCs without on-site EVT availability. As in real-world settings optimal allocation of EVT resources is warranted, teleconsultation by experienced endovascular interventionists and prompt interhospital-transfer-inquiries are crucial to reduce the futile transfer rates and optimize patient selection for EVT within neurovascular networks.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".