Regarding "hemorrhagic transformation in patients with intravenous thrombolysis", these three points should be clear

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Highlights of the 2022 Temple of Heaven Fair

The key to the treatment of ischemic stroke is early reperfusion therapy.

On August 5, 2022, at the 8th Annual Academic Conference of the Chinese Stroke Society and the Tiantan International Cerebrovascular Disease Conference 2022, Professor Yang Yi from the First Hospital of Jilin University, combined with relevant research at home and abroad and his team, provided us Bring about the individualized evaluation of hemorrhagic transformation after thrombolysis and related influencing factors, let us learn together~

The concept and classification of hemorrhagic transformation after thrombolysis?

HT generally refers to intracranial hemorrhagic lesions that appear after thrombolytic therapy for ischemic stroke

• Classification according to the presence or absence of clinical symptoms:

1) No sICH

2) sICH:

Mild symptom hemorrhagic transformation-NIHSS score increased by 1 to 3 points

Severe symptomatic hemorrhagic transformation - NIHSS score increase of ≥4 points

• According to imaging classification (ECASS criteria):

1) Hemorrhagic cerebral infarction (Hemorrhagic Infarction, HI)

①HI-1 type: small speckle hemorrhage at the infarct edge
.

②HI-2 type: the bleeding in the infarct area fused into a sheet, but there is no mass effect
.

2) Parenchymal hemorrhage (Parenchymal Hematoma, PH)

①PH-1 type: the hematoma volume is less than or equal to 30% of the infarct volume, with a slight mass effect
.

②PH-2 type: hematoma volume > 30% of infarct volume, with obvious mass effect and bleeding far away from the infarct area
.

Professor Yang Yi said that in clinical practice, we need to pay more attention to PH-2 type, whose hemorrhagic transformation is closely related to the prognosis of patients
.

According to Professor Yang Yi, combined with some domestic and foreign studies, the incidence of hemorrhagic transformation after thrombolysis varies according to its definition, and its range fluctuates from 2% to 25%, as shown in Figure 1 and Figure 2
.

According to the research of Professor Yang Yi's team, based on the data of the Stroke Center of the First Hospital of Jilin University, the total hemorrhagic transformation rate of acute stroke patients after intravenous thrombolysis was 18.
14%, and the symptomatic hemorrhagic transformation rate was 1.
48%
.

In addition, the incidence of symptomatic intracerebral hemorrhage (sICH) was also related to the dose of alteplase, with a higher incidence of sICH at doses greater than 0.
9 mg/Kg and a lower incidence at 0.
6 mg/Kg.
Incidence of sICH
.

Figure 1: Results of domestic and foreign studies on HT (clinical characteristics)

Figure 2: Results of domestic and foreign studies on HT (incidence of sICH)

Factors associated with hemorrhagic transformation after thrombolysis?

The mechanism of hemorrhagic transformation after thrombolysis is complex, and it is related to recanalization of occluded vessels, reperfusion injury, establishment of collateral circulation, and alteplase-induced coagulation disorders
.

Evidence-based risk factors include: stroke severity, advanced age, hypertension, atrial fibrillation, diabetes mellitus, renal insufficiency, congestive heart failure, ischemic heart disease, use of antiplatelet drugs, presence of imaging infarcts, Cerebral microbleeds
.

According to the research of Professor Yang Yi's team, through multivariate analysis, it is shown that the risk factors affecting symptomatic bleeding are: baseline NIHSS, history of atrial fibrillation
.

Professor Yang Yi said: "These so-called risk factors with evidence in the study are actually difficult to use for individualized evaluation of patients in clinical practice, because the population and subgroup analysis of each study are different, and the level of evidence for various factors is also high and low.
Therefore, the predictive value of individual factors for hemorrhagic transformation is limited, and although aggregating factors into a scoring scale may improve its prediction, the overall specificity and sensitivity are still low
.

”

Based on this kind of thinking, Professor Yang Yi proposed that the ability to predict the risk of hemorrhagic transformation in patients can be improved through the accumulation of a large amount of clinical experience of doctors? Therefore, based on the evaluation of clinical events under complex factors, Professor Yang Yi's team constructed a corresponding model through artificial intelligence.
The results show that the accuracy of this neural network prediction model is significantly higher than that of existing scale scores.
Sensitivity and specificity
.

We have reason to believe that it is feasible to build a prediction model of hemorrhagic transformation after thrombolysis based on deep learning artificial neural network, which can play a certain guiding role in the decision-making of thrombolytic therapy in the future
.

In addition, Professor Yang Yi's team also analyzed the protein levels of clinical samples and found that specific activation of the tyrosine protein kinase receptor (AxL) pathway may reduce the incidence of hemorrhagic transformation
.

Common indicators of prognosis evaluation after thrombolysis?

The prognosis evaluation after thrombolysis is mainly based on three types of indicators, including hematological indicators, imaging indicators, and scale scores
.

A variety of hematological indicators can predict the clinical prognosis of patients with intravenous thrombolysis

Including blood routine indicators, triglyceride glycemic index, direct bilirubin, nitrogen-terminal precursor BNP (NT-proBNP),
etc.

Two kinds of imaging indicators can predict the clinical prognosis of patients with intravenous thrombolysis

For example, the high density sign of the middle cerebral artery can predict the poor prognosis of 3 months, white matter lesions, and 3 or more cerebral microbleeds can predict the poor prognosis of 3 months
.

3 The current prognostic indicators after intravenous thrombolysis are various and have great limitations.
Therefore, it is necessary to explore new evaluation indicators
.

Therefore, under the current situation, Professor Yang Yi's team conducted a related study on the characteristics of cerebral blood flow autoregulation function and prognosis in patients with acute cerebral ischemic stroke after rt-PA thrombolysis.
The results found: the patient's history of hypertension , Baseline NIHSS score and cerebral blood flow autoregulation are feasible to evaluate the prognosis of patients with thrombolysis
.

Professor Yang Yi said that the current brain injury markers in patients with acute ischemic stroke, serum GFAP and S100β have been shown to predict 3-month clinical outcomes in patients with cerebral infarction
.

At the same time, his team also explored the relationship between brain injury markers and prognosis in patients with acute ischemic stroke after intravenous thrombolysis with rt-PA.
The results showed that the brain injury marker PGP9.
5 (UCH-L1) 24 hours after intravenous thrombolysis The level is independently correlated with the 3-month clinical prognosis of patients, and can be used as one of the indicators for clinical prognosis evaluation
.

Summary:
Through this meeting, Professor Yang Yi, combined with his own team and research at home and abroad, explained the incidence of hemorrhagic transformation in patients with acute cerebral stroke, the related factors affecting hemorrhagic transformation, and the commonly used indicators for prognosis evaluation after thrombolysis.
The research of Professor Yang Yi’s team also showed that the evaluation index of vascular function (cerebral blood flow autoregulation function) and brain injury markers have a certain role in the prognosis evaluation of patients with intravenous thrombolysis, but these studies are still in the stage of scientific exploration.
To truly enter the clinic, we still need to explore more evidence
.

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Source of this articleNeurology Channel of the medical community This article is organized | This article is reviewed by the meeting record group of the medical community | Li Tuming Deputy Chief Physician Responsible EditorMr.
Lu Li Xiang Yu

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