The present study aimed to compare the significance of the Caprini and PADUA models in predicting PE in gynecological inpatients. The results validated the effectiveness and simplicity of the PADUA model as a RAM for predicting PE in this population. Additionally, this study analyzed various risk factors for PE, such as a history of VTE, immobilization, thrombophilia, hormonal treatment or oral contraceptives, and obesity. The Caprini model demonstrated superior predictive efficacy for mortality. Using the PADUA model proved beneficial in the identification of high-risk individuals for PE screening among gynecological inpatients. Conversely, the Caprini model showed exceptional proficiency in predicting mortality, thereby enabling the implementation of timely preventive measures.

Currently, there are several thrombosis RAMs, including the Caprini, PADUA, Khorana, and IMPROVE models, each with distinct areas of focus. The Khorana model is applicable to patients with malignancies [22]. While the Caprini model is primarily designed for assessing thrombosis risk in surgical patients [15], its predictive efficacy is limited when applied to non-surgical and gynecological patients [26, 30]. On the other hand, the PADUA model was validated in a cohort study by Barbar et al. [14]. However, there is limited research specifically validating the PADUA RAM in hospitalized patients [31]. The IMPROVE model predicts the risk of thrombosis formation in acutely hospitalized patients [32]. Gynecological inpatients, who encompass a distinct population comprising both surgical and non-surgical cases, necessitate the development of a specialized prediction model for postoperative PE. Within the scope of this investigation, a total of 309 individuals (87.0%) underwent surgical intervention among the cohort under examination. The PADUA and Caprini models were evaluated and contrasted to formulate an appropriate RAM tailored specifically for gynecological inpatients.

In the present study, both the PADUA and Caprini models demonstrated good predictive efficacy for PE, with AUC values of 0.757 (95% CI 0.698–0.817) and 0.756 (95% CI 0.700–0.813), respectively. The AUC curves of the two models showed no statistically significant disparity (P = 0.9542). In contrast to the Caprini model, the PADUA model includes fewer components, featuring a more straightforward age and surgery stratification. The PADUA model incorporates an additional factor of trauma occurring within a 30-day period. Existing research posits that the probability of trauma in females might be lower than in males due to the differences in occupation and environmental exposure [33, 34]. Hence, it can be inferred that the PADUA model demonstrates sufficient efficacy in predicting PE events in gynecological inpatients when compared to the more intricate Caprini model. Central PE poses a grave threat to life, even resulting in mortality [35], and has a significantly worse prognosis than peripheral PE. Barco et al. suggested that the recurrence and mortality risks of PDVT are higher than those of IDDVT [36]. Thus, the site of thrombus formation can be regarded as an indicator of VTE severity. In the present study, the PADUA model showed statistical differences in both groups, while the Caprini model only exhibited statistical differences in IDDVT and PDVT. Consequently, it seems that the PADUA model is more appropriate for predicting VTE severity. On the other hand, simplified PESI (sPESI) score is a practical validated score aimed to stratify 30-day mortality risk in acute PE [37]. The results of this study suggest that PADUA and Caprini models are linearly correlated with sPESI (P = 0.000,R > 0), indicating that these two models also can predict the prognosis of PE. Barbar et al. defined a score of ≥ 4 in the PADUA model as high risk for VTE [14]. In the present study, the optimal cutoff values for predicting PE in gynecological inpatients were 6 or 7. The study population encompassed several risk factors associated with VTE, such as surgical procedures (87.0%), active malignancy (49.3%), obesity (16.9%), and various other factors. The observed increase in the optimal cutoff values can be attributed to the enrollment of patients deemed to be at a heightened risk for VTE who underwent CTPA based on a physician's judgment.

The present study results indicate that a history of VTE, immobility, thrombophilia, hormonal treatment or oral contraceptives, and obesity (body mass index (BMI) ≥ 30) are independent risk factors for predicting PE in gynecological inpatients. Surgery and active cancer are recognized as high-risk factors for VTE [38], contributing significantly to the scores in various thrombosis assessment models. However, these factors were not identified as autonomous risk factors for predicting PE in gynecological inpatients within the scope of the present study.

An analysis of the Registro Informatizado Enfermedad Tromboembolica(RIETE) and Medicare databases revealed that gender potentially has an influence on the risk factors associated with PE, as women afflicted with PE exhibited a higher propensity for immobility or hormonal treatment in contrast to their male counterparts. Conversely, the prevalence of cancer and cardiovascular diseases was observed to be greater among men [8]. This aligns with the findings of the present study. Other studies have also identified hormonal treatment as a risk factor for PE [34]. Moreover, existing research has confirmed the association between immobility and VTE [13, 31]. The present study revealed that a significant proportion of patients (87.0%) underwent surgery, which was associated with prolonged surgical duration, and a considerable percentage of patients (49.3%) had active cancer, both of which are known to potentially impede mobility and result in an extended period of bed rest. Additionally, Kandagatla et al. provided evidence demonstrating that a prior occurrence of VTE serves as an independent risk factor for PE [13].

Previous research suggests that an increase in BMI is linked to an increase in factors that predispose individuals to thrombosis and a decrease in the capacity for fibrinolysis [39]. A large prospective cohort study by Kabrhel et al. demonstrated a strong linear relationship between a BMI increase and the incidence of PE in women, and this association was not limited to individuals with severe obesity [40]. Furthermore, a meta-analysis by Jamal et al. proposed that obese patients have a higher risk of PE compared to individuals with a normal BMI (hazard ratio: 2.24, 95% CI: 1.93–2.60) [41].

Existing research on thrombophilia is currently limited. The PADUA model involves deficiencies in proteins C, S, and antithrombin III, as well as factors like Factor V Leiden(FVL) and prothrombin G20210A mutation. It is noteworthy that genetic susceptibility can potentially hold equal significance as environmental and clinical factors in terms of the risk factor for PE [42]. According to previous reports, deficiencies in proteins C and S have been linked to an increased risk of PE compared to that in the general population [43]. The present study findings support this idea, as 9.0% of patients were found to have hereditary thrombophilia. Multifactorial logistic analysis results indicated a strong association with PE, with an odds ratio of 50.34(95% CI: 15.05–168.38). Stefano et al. also discovered that patients with thrombophilia have a higher recurrence rate of PE [44]. Therefore, further investigation is needed to gain a better understanding of the relationship between thrombophilia and PE.

In the present study, both the PADUA and Caprini models predicted mortality events. However, when considering the three- and six-month follow-ups, the Caprini model showed a higher AUC for predicting mortality events compared to the PADUA model. Furthermore, the AUC in the Caprini model exceeded 0.7 at both the three- and six-month time points, indicating its potential utility in predicting prognosis for gynecological inpatients. Zhou et al. [31] also found that the Caprini model accurately predicts the mortality rate in hospitalized patients, yet there is currently little research pertaining to this subject matter. Prospective studies are needed to investigate the association between the Caprini model and mortality among gynecological inpatients.