- Department of Neurology, First Hospital of Shanxi Medical University, Taiyuan, China
Purpose: This study aimed to investigate the risk
factors of prognosis and hemorrhagic transformation after mechanical
thrombectomy (MT) in patients with posterior circulation acute ischemic
stroke (PC-AIS) caused by large vessel occlusion. We sought to develop a
nomogram for predicting the risk of poor prognosis and symptomatic
intracerebral hemorrhage (sICH) in patients with PC-AIS.
Methods: A retrospective analysis was conducted
on 81 patients with PC-AIS who underwent MT treatment. We collected
clinical information from the patients to assessed sICH and prognosis
based on CT results and National Institutes of Health Stroke Scale
(NIHSS) scores. Subsequently, they were followed up for 3 months, and
their prognosis was assessed using the Modified Rankin Scale. We used
the least absolute shrinkage and selection operator (LASSO) and
multivariate logistic regression to determine the factors affecting
prognosis to construct a nomogram. The nomogram’s performance was
assessed through receiver operating characteristic curves, calibration
curves, decision curve analysis, and clinical impact curves.
Results: Among the 81 patients with PC-AIS, 33
had a good prognosis, 48 had a poor prognosis, 19 presented with sICH,
and 62 did not present with sICH. The results of the LASSO regression
indicated that variables, including HPT, baseline NIHSS score, peak SBP,
SBP CV, SBP SD, peak SBP, DBP CV, HbA1c, and BG SD, were predictors of
patient prognosis. Variables such as AF, peak SBP, and peak DBP
predicted the risk of sICH. Multivariate logistic regression revealed
that baseline NIHSS score (OR = 1.115, 95% CI 1.002–1.184), peak SBP
(OR = 1.060, 95% CI 1.012–1.111), SBP CV (OR = 1.296, 95% CI
1.036–1.621) and HbA1c (OR = 3.139, 95% CI 1.491–6.609) were independent
risk factors for prognosis. AF (OR = 6.823, 95% CI 1.606–28.993), peak
SBP (OR = 1.058, 95% CI 1.013–1.105), and peak DBP (OR = 1.160, 95% CI
1.036–1.298) were associated with the risk of sICH. In the following
step, nomograms were developed, demonstrating good discrimination,
calibration, and clinical applicability.
Conclusion: We constructed nomograms to predict
poor prognosis and risk of sICH in patients with PC-AIS undergoing MT.
The model exhibited good discrimination, calibration, and clinical
applicability.
1 Introduction
Acute ischemic stroke (AIS) is the leading cause of disability and mortality, posing a severe threat to human well-being (1).
Research on the Chinese population reveals that, in 2020, there were
15.5 million cases of ischemic stroke among adults >40 years, with a
prevalence rate of approximately 2.3/100 people (2). Over 30% of AIS cases result from large vessel occlusion (LVO) (3).
LVO causes ischemia and hypoperfusion in the affected area, and timely
restoration of perfusion to the ischemic area can maintain brain cell
activity. Thrombolysis treatment by intravenous recombinant tissue
plasminogen activator is accessible within a 4.5 h window from the onset
of symptoms. However, it is not always feasible owing to missed time
windows or contraindications. In recent years, mechanical thrombectomy
(MT) development has provided new treatment options for patients with
AIS. MT treatment is safe and effective for patients with anterior
circulation AIS (AC-AIS), extending the treatment time to 6–24 h (4).
Compared with AC-AIS, posterior circulation AIS (PC-AIS)
occurs in the vertebrobasilar system-supplied area, resulting in a
worse prognosis (5).
The early symptoms of PC-AIS are mild and unspecific, making
identification challenging. Therefore, patients with PC-AIS have a lower
rate of benefit from intravenous thrombolysis than those with anterior
circulation AIS, with only 1/6 of patients benefiting from this
treatment (6).
It indicates that MT is an important treatment for patients with
PC-AIS. However, the outcome of MT treatment in PC-AIS remains
controversial, with significant differences observed in four randomized
controlled trials (RCTs). In the BEST and BASIC studies, no significant
difference was observed in prognostic outcomes between the MT and drug
therapy alone groups.
In contrast, the BAOCHE and ATTENTION studies indicated a more favorable prognosis for patients who underwent MT treatment (7–10). Most patients with PC-AIS can achieve revascularization after MT treatment; however, only 38% experience a good prognosis (11).
Therefore, exploring the factors influencing prognosis can help
clinicians identify patients at high risk of poor prognosis and provide
more timely interventions. There are fewer studies on the factors
influencing the prognosis of PC-AIS patients undergoing MT treatment. A
meta-analysis revealed that hypertension and diabetes were associated
with poor prognosis (12).
Gao et al.’s study identified baseline National Institutes of Health
Stroke Scale (NIHSS) score, posterior circulation acute stroke prognosis
early computed tomography (PC-ASPECT) score, and modified thrombolysis
in cerebral infarction (mTICI) classification as independent risk
factors affecting patients’ prognosis (13).
Notably, no study investigates the impact of
post-operative medical management on the risk of patients’ prognosis,
and predictive models for poor prognosis and sICH are yet to be
constructed. This study addresses these gaps by investigating factors
affecting the prognosis and sICH of patients with PC-AIS undergoing MT
and constructs a nomogram applicable to clinical practice. We aimed to
guide targeted clinical interventions to improve the management of
patients with PC-AIS and enhance their post-treatment prognosis.
