It has long been a topic of discussion in medical settings on how to prevent thromboembolism, particularly cardiac embolism. Researchers reported that patients with ventricular thrombus had a high risk of stroke or systemic embolism (SSE) more than 20% before being discharged despite anticoagulation [1, 2, 3], and studies indicated that the in-hospital mortality rate of patients with ventricular thrombus was higher compared to patients without ventricular thrombus [4, 5]. With the advanced technology in imaging tools, the incidence of ventricular thrombus has increased in recent years, with a range of 4%–10% [6, 7]. As thromboembolism is currently the most noteworthy severe outcome in patients with ventricular thrombus [8, 9], it is of vital importance to identify which patients are at a higher risk of thromboembolism, tending to decrease mortality or mobility. Prediction models in the prevention of atrial fibrillation (AF)-related stroke have been developed [10, 11, 12], up to date, there is no prediction model built on the theme of thromboembolism secondary to ventricular thrombus, especially focusing on hospitalized medical patients. In our study, we aimed to build a prediction model by analyzing potential predictors including clinical characteristics, laboratory data, or imaging measurements, to better help clinicians target early awareness in hospitalized patients with high-risk factors, as well as to provide provoking thoughts or evidence in the management of patients with ventricular thrombus.

Our study first conducted a prediction model established on Lasso regression to predict the risk of thromboembolism in hospitalized patients with ventricular thrombus. And we concluded that patients were more likely to experience thromboembolism in hospital, who had a medical history of SSE and DM, a lower BMI and LVEF but a higher diastolic blood pressure at baseline, along with protuberant thrombus and without antiplatelet therapy during hospitalization.

It is well established that DM and prior SSE have been widely used to stratify the risk of stroke, which were proved to be predictors of thromboembolism events in the study. Patients with DM had a higher risk of thrombotic events due to the pathophysiological underpinnings of endothelial dysfunction and vascular inflammation. Recurrent thromboembolism was more common among patients who had previously experienced it, and its incidence was seven times greater than that of newly discovered cases. Patients with a first PE had more than a two-fold risk of developing a second PE [22]. In the model built on the ROCKET-AF trial, prior thromboembolism was the strongest independent predictor of thromboembolism [10], which was similar to our results. Along with a history of DM and stroke, we observed a strong relationship between the history of HF and the occurrence of thromboembolism in univariate analysis, whereas HF has been identified as a risk factor for thromboembolic events in previous research [23, 24]. Patients who experienced HF or cardiac dysfunction (e.g., a high NT-proBNP, a low LVEF, or a large left ventricular end-diastolic volume) at baseline, faced a higher rate of thromboembolism, and it could be attributed to complex pathophysiological mechanisms such as neurohormonal activation or decreased myocardial contractility, resulting in an increased vulnerability to thromboses [25]. And the abnormal blood flow as well as other requirements of Virchow’s triad including hypercoagulability, and endothelial injury was satisfied in patients with HF [26, 27]. In a population-based 30-year cohort study, patients with HF had an increased risk of stroke compared with the general population group [28]. And by pooling 2 trials related to HF, researchers reported stroke occurrence in 4.7% of patients with AF and 3.4% of patients without AF [29]. A large prospective study reported that HF hospitalization increased the risk of MI or stroke [30], which provided the clear message that HF should no longer be considered a minor risk factor for thromboembolism.

In summary of studies that predicted the embolism events, factors including the level of D-dimer indicated a higher additional risk besides the major persistent risk factors [22, 23]. D-dimer and FDP levels at admission were significantly related to a high risk of embolism, otherwise, neither D-dimer nor FDP with more than a one-fold increase at discharge had a significant relationship with events in the study. Without a doubt, patients who had a high D-dimer had a higher risk of any embolism events since D-dimer was inherently an indicator of thrombus formation. Interestingly, another laboratory indicator also showed an opposite relationship with thromboembolism. The lower the level of lymphocyte count was, the risk of thromboembolism increased. Whether the level of lymphocyte count could indicate thromboembolism remained unknown, and more evidence or mechanism is needed to explore. It reported that in COVID-19 patients the lymphocyte count (p = 0.004) showed a lower value in the patients with PE compared with those without PE [31]. And previous studies have concluded that the increased inflammation increased the risk of thromboembolism as well, which mostly happened to patients who had inspiratory diseases [25, 32]. Moreover, researchers found that in 60 patients who developed left ventricular thrombus in COVID-19, 21.5% and 16.9% of patients had stroke events and PE separately, while 12.3% of patients had peripheral arterial embolism [33].

When assessing the effect of the amount or location of thrombus on the risk of thromboembolism, as most patients were diagnosed by echocardiographic assessments, it remained to explore a more accurate embolism rate in CMR or CT or contrast echo since CMR has been regarded as gold criteria could find small and more ventricular thrombus [9]. And patients who had biventricular thrombus were more likely to occur thromboembolism, and one of the reasons might be accounted that they had severe cardiac dysfunction as well as a complex inner condition at admission. In terms of thrombus morphology, protuberant or mobile thrombi were related to a higher risk of embolism compared with mural thrombi, though data on the subtype of thrombus were limited. Researchers demonstrated that transthoracic echocardiography implemented with pulsed wave tissue doppler imaging could provide a more precise definition of mass mobility over visual assessment, and concluded that a $\ge$10 cm/s mass peak Va was considered the most significant predictor of embolic risk in hospitalized patients [34]. In the 2022 statement for left ventricular thrombus [15], researchers suggest that for a protuberant thrombus as well as a newly diagnosed mural thrombus, it would be prudent to give anticoagulation therapy. And a shared decision-making approach is recommended for organized or calcified thrombi.

Generally, patients with ventricular thrombus ought to be governed by anticoagulation in the absence of contraindications. More than 70% of patients received oral anticoagulation and nearly 50% were on heparin in hospital. Patients who had no history of AF were less likely to be pretreated with anticoagulants, which increased the risk of thromboembolism without long-term anticoagulation [8]. In a pooled meta-analysis of studies of ventricular thrombus after MI, the use of anticoagulants (either warfarin or heparin) reduced the risk of stroke by 81% [35]. On the other hand, the results of studies that compared the use of NOACs to vitamin K antagonists in the prevention of embolism risk were controversial [36, 37, 38], requiring more randomized clinical trials (RCTs) to provide robust evidence. Antiplatelet therapy and anticoagulation therapy, which have different targets, both have an effect on reducing the risk of thromboembolism [39, 40]. Upon the topic of antiplatelet therapy secondary to anticoagulation treatment in the field of prevention of thromboembolism, studies have demonstrated that antiplatelet therapy was effective for the primary prevention of embolism events [41, 42, 43]. Other large RCTs have demonstrated a significant reduction ranging from 20% to 69% in recurrent thromboembolism with aspirin versus placebo after anticoagulants were discontinued in patients with a history of embolic events [44, 45]. But the treatment of triple antithrombotic therapy which was associated with a higher rate of bleeding remained unknown for patients with ventricular thrombus [46]. Personalized management for the prevention and treatment of ventricular thrombus should be developed to take into account of patient characteristics.

Concerning other predictors in the final model of this study, we outlined the findings as follows. A high risk of thromboembolism was linked to higher diastolic blood pressure. In the RE-LY trial’s subgroup analysis, patients with high diastolic blood pressure ($\ge$90 mmHg) had a high risk of developing SSE [47]. The elevated diastolic blood pressure was found to be significantly associated with an increased risk of stroke in another RCT with 22,672 patients, with a 1.5-fold risk for diastolic blood pressure of 80–89 mmHg and a 4-fold risk for 90 mmHg or more [48]. Likewise, a remarkable correlation was observed between the BMI and the outcome of the study. Previous results from three RCT trials (ARISTOTLE [49], ROCKET-AF [50], and ENGAGE AF-TIMI 48 [51]) showed that a higher BMI was independently related to a decreased risk of SSE. The reason for the apparent protective effect of obesity is unclear, and we hypothesized that patients in the higher BMI categories are offered earlier and more intensive treatments to manage the risk of stroke events.

Several limitations were as followed. First, the validation set was based on the same dataset with a small sample, which restricted the power and the practical utility of our model. Second, limited to patient resources, the result of the study could not greatly expand to a large population. Third, even if ventricular thrombus mobility is a major prognostic determinant of increased thromboembolism [34], this retrospective analysis did not include a detailed assessment of thrombotic mass mobility. Additionally, it was also undetermined whether or when to implement a strategy to prevent embolism, since this study focused on developing a novel prediction model to identify patients who were at high risk of embolism.

This study conducted a prediction model by selecting seven factors based on the Lasso algorithm, aiming to identify the risk prediction of thromboembolism in hospitalized patients with ventricular thrombus. Patients who had a medical history of SSE and DM, a lower level of BMI and LVEF but a higher diastolic blood pressure at baseline, along with protuberant thrombus and without antiplatelet therapy during hospitalization, were more likely to experience thromboembolism in hospital. More prospective clinical trials are required to develop and validate models, and individualized discussion and shared decision-making are of critical importance in managing patients with ventricular thrombus.

SSE, stroke or systemic embolism; CT, computer tomography; CMR, cardiac magnetic resonance; BMI, body mass index; VTE, venous thromboembolism; PE, pulmonary embolism; AF, atrial fibrillation; HF, heart failure; MI, myocardial infarction; LVEF, left ventricular ejection fraction; FDP, fibrin degradation products; CrCl, creatinine clearance; NT-proBNP, N-Terminal pro-brain natriuretic peptide; SD, standard deviation; IQR, interquartile range; OR, odds ratio; CI, confidence interval; AUROC, area under the receiver operating characteristic curve; DCA, decision curve analysis; NOACs, non-vitamin K antagonist oral anticoagulants.

The data will be shared on reasonable request to the corresponding author.

QY and XQ extracted the data, and XL contributed to data analysis; QY drafted the manuscript; XL performed the statistical analysis; YL reviewed and corrected the manuscript; QY and YL discussed the results and contributed to the final manuscript; All authors read and approved the manuscript.

The study protocol was approved by the Ethics Committees of Fuwai Hospital (approval No. 2022-1757) with a waiver for informed consent for this retrospective analysis.

We are indebted to all authors of the study we have included in our paper.

This research received no external funding.

The authors declare no conflict of interest.