Care of the Post-Thrombectomy Patient
Bibliographic record
Abstract
M ultiple lines of evidence supporting endovascular stroke treatment (EVT) have propelled this treatment modality as the standard of care 1 with increased anticipated and observed utilization.In parallel, it has been recognized that optimal outcomes are reliant on processes across the disease continuum from first medical contact, prehospital triage, primary hospital treatment, interfacility transfer, destination hospital care, preprocedural planning, reperfusion therapy, post-thrombectomy care, and rehabilitation.In this review, we focus specifically on considerations in the care of the postthrombectomy patient.In particular, we address the common and critical complications as they occur over the spectrum of care from preprocedural, intraprocedural, and postprocedural management (Figure ). Key Issues in Patients Undergoing EVTComplications after EVT can be broadly considered as being inherent to issues surrounding the stroke itself (hyperglycemia, temperature dysregulation, arrhythmias, hemodynamic instability, aspiration, respiratory failure, and infection), as well as issues commonly encountered in all critically ill patients, such as stress ulcers, pressure ulcers, and peripheral venous thrombosis.Complications can also be secondarily related to the procedure (hemorrhagic conversion and malignant edema) or direct complications (volume overload, arteriotomy site complications, vessel perforation, vasospasm, device retention, and vessel reocclusion).Adverse events may further be different in reperfused versus nonreperfused patients.For instance, reperfusion injury is not a feature of nonreperfused patients, whereas infarct growth is.Key management decisions include blood pressure (BP) parameters, glucose target, fluid balance, medication use (ie, antithrombotics, anticoagulants, and antiepileptics), as well as necessity and timing of surgical interventions (eg, craniectomy, extraventricular drain placement, tracheostomy, and parenteral gastrostomy).Given the broad spectrum and complex nature of adverse events, the postoperative care should be directed in an intensive care unit with stroke-specialized nursing and physicians.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".