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Analysis of influencing factors and construction of risk prediction model for postoperative thrombocytopenia in critically ill patients with heart disease

Journal of Cardiothoracic Surgery volume 19, Article number: 516 (2024) Cite this article

Abstract

Objective

To analyze the influencing factors of postoperative thrombocytopenia in critically ill patients with heart disease and construct a nomogram prediction model.

Methods

From October 2022 to October 2023, 319 critically ill patients with heart disease who visited our hospital were collected and separated into postoperative thrombocytopenia group (n = 142) and no postoperative thrombocytopenia group (n = 177) based on their postoperative thrombocytopenia, Logistic regression analysis was applied to screen risk factors for postoperative thrombocytopenia in critically ill patients with heart disease; R software was applied to construct a nomogram for predicting postoperative thrombocytopenia in critically ill patients with heart disease, and ROC curves, calibration curves, and Hosmer-Lemeshow goodness of fit tests were applied to evaluate nomogram.

Results

A total of 142 out of 319 critically ill patients had postoperative thrombocytopenia, accounting for 44.51%. Logistic regression analysis showed that gender (95% CI 1.607–4.402, P = 0.000), age ≥ 60 years (95% CI 1.380–3.697, P = 0.001), preoperative antiplatelet therapy (95% CI 1.254–3.420, P = 0.004), and extracorporeal circulation time > 120 min (95% CI 1.681–4.652, P = 0.000) were independent risk factors for postoperative thrombocytopenia in critically ill patients with heart disease. The area under the ROC curve was 0.719 (95% CI: 0.663–0.774). The slope of the calibration curve was close to 1, and the Hosmer-Lemeshow goodness of fit test was χ2 = 6.422, P = 0.491.

Conclusion

Postoperative thrombocytopenia in critically ill patients with heart disease is influenced by gender, age ≥ 60 years, preoperative antiplatelet therapy, and extracorporeal circulation time > 120 min. A nomogram established based on above multiple independent risk factors provides a method for clinical prediction of the risk of postoperative thrombocytopenia in critically ill patients with heart disease.

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Introduction

Critical heart conditions are caused by multiple factors leading to impaired cardiac pump function, where the heart fails to provide sufficient blood flow, causing circulatory disturbances and subsequently dysfunction and irreversible damage to various organs [1]. Patients with critical heart conditions have a high risk of mortality and require urgent diagnosis and intervention [2]. For patients with severe cardiac conditions, the effectiveness of medication is often limited, making surgical intervention a common approach. Thrombocytopenia is an important issue that cannot be ignored in patients with critical heart conditions after surgery [3, 4]. Once thrombocytopenia occurs, it not only increases the risk of bleeding in patients with critical heart conditions but also prolongs the postoperative hospital stay, and in severe cases, can lead to death [5, 6]. Effective prevention of postoperative thrombocytopenia in patients with critical heart conditions has profound implications for prognosis, hence the management of postoperative thrombocytopenia in these patients should be strengthened. If accurate predictions of postoperative thrombocytopenia in patients with critical heart conditions can be made, it would provide reliable information for clinical decision-making and significantly improve patient outcomes. However,, there is scarce reporting on how to predict postoperative thrombocytopenia in patients with critical heart conditions. Nomograms, by integrating various independent risk factors selected through multifactorial regression analysis, are more readable. They not only show the interrelationships among various predictive indicators but also provide the probability of individual outcome events [7, 8]. This study selects patients with critical heart conditions as the subject, explores the independent risk factors for postoperative thrombocytopenia, and constructs an easy-to-understand and accurate nomogram to predict the risk of postoperative thrombocytopenia in these patients.

Data and methods

Study subjects

From October 2022 to October 2023, 319 patients with critical heart conditions treated at our hospital were selected. Inclusion criteria: [1] Indications for cardiac surgery; [2] Age > 18 years; [3] Admission to the ICU of our hospital. Exclusion criteria: [1] Preoperative thrombocytopenia; [2] Malignant tumors; [3] Hematological diseases.

Research methods

Data Collection: [1] Demographic data: Gender, age; [2]Preoperative health information: body mass index, cardiac function classification, left ventricular end-diastolic diameter, left ventricular ejection fraction, presence of hypertension, presence of diabetes, smoking status, presence of chronic obstructive pulmonary disease, presence of atrial fibrillation, peripheral vascular intervention treatment, preoperative antiplatelet therapy, history of cardiac surgery, preoperative white blood cell count, preoperative hemoglobin, preoperative platelet count, preoperative hematocrit, preoperative serum creatinine; [4] Postoperative health information: duration of surgery, use of extracorporeal circulation, extracorporeal circulation time > 120 min, type of surgery, postoperative 24-hour APACHE II score, postoperative drainage, transfusion of blood products, postoperative sternotomy for hemostasis, postoperative infection, ventilator use time, ICU stay, ICU stay > 72 h, and length of hospital stay.

Postoperative Thrombocytopenia in Patients with Critical Heart Conditions [9]

Based on the presence or absence of postoperative thrombocytopenia, patients were divided into a postoperative thrombocytopenia group (n = 142, platelet count < 100 × 109/L) and a non-thrombocytopenia group (n = 177, platelet count ≥ 100 × 109/L).

Statistical methods

Statistical analysis was conducted using SPSS 25.0, with P < 0.05 considered statistically significant. Count data were described using frequency (%) and analyzed using chi-square tests. Measurement data that followed a normal distribution and had homogeneity of variances were described using mean ± standard deviation and analyzed using t-tests. Logistic regression analysis was used to screen for risk factors of postoperative thrombocytopenia in patients with critical heart conditions. Independent risk factors influencing postoperative thrombocytopenia in these patients were introduced into R3.6.3 software and the rms package to construct a nomogram for predicting postoperative thrombocytopenia. The discriminative ability of the nomogram was evaluated by plotting ROC curves, and its calibration was assessed using calibration curves and the Hosmer-Lemeshow goodness-of-fit test.

Results

Postoperative Thrombocytopenia in patients with critical heart conditions

Out of 319 patients with critical heart conditions, 142 experienced postoperative thrombocytopenia, accounting for 44.51%.

Univariate analysis

As is displayed in Table 1 only significant differences were observed in gender, age, body mass index, presence of hypertension, presence of atrial fibrillation, preoperative antiplatelet therapy, preoperative white blood cell count, preoperative platelet count, extracorporeal circulation time > 120 min, postoperative drainage, transfusion of plasma, transfusion of platelets, postoperative sternotomy for hemostasis, postoperative infection, ventilator use time, ICU stay, ICU stay > 72 h, and length of hospital stay (P < 0.05). Table 1.

Table 1 Univariate Analysis example (%)/(\(\bar x\) ± s)
Full size table

Multivariate analysis

Using the status of postoperative thrombocytopenia in patients with critical heart conditions as the dependent variable (postoperative thrombocytopenia = 1, no postoperative thrombocytopenia = 0), and the variables from Table 1 that showed significant differences as independent variables, logistic regression analysis was performed. The results indicated that being female (95%CI 1.607–4.402, P = 0.000), age ≥ 60 years (95%CI 1.380–3.697, P = 0.001), preoperative antiplatelet therapy (95%CI 1.254–3.420, P = 0.004), and extracorporeal circulation time > 120 min (95%CI 1.681–4.652, P = 0.000) were independent risk factors for postoperative thrombocytopenia in patients with critical heart conditions. Table 2.

Table 2 Multivariate analysis
Full size table

Nomogram model development

A nomogram model was developed to predict postoperative thrombocytopenia in patients with critical heart conditions. See Fig. 1; Table 3.

Fig. 1
figure 1

Nomogram model

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Table 3 Nomogram model scoring table
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Evaluation of the nomogram model

Discrimination: The area under the ROC curve was 0.719 (95% CI: 0.663–0.774), see Fig. 2A. Calibration: The calibration curve slope was close to 1 (Fig. 2B), and the Hosmer-Lemeshow goodness-of-fit test yielded χ2 = 6.422, P = 0.491.

Fig. 2
figure 2

Evaluation of the Nomogram Model A: ROC Curve; B: Calibration Curve

Full size image

Discussion

Platelets, one of the formed elements of blood, play a crucial role in coagulation and hemostasis [10, 11]. Cardiac surgery, especially in patients with critical heart conditions, is associated with significant trauma and often leads to a reduction in platelet counts postoperatively, causing numerous clinical issues [12, 13]. In this study, 142 out of 319 patients with critical heart conditions experienced postoperative thrombocytopenia, accounting for 44.51%. This incidence is similar to the findings reported by Ali [14] and Boonyawat [15], but higher than the 35% reported by Stéphan [16]. The inconsistency in the occurrence of postoperative thrombocytopenia among patients with critical heart conditions may be due to differences in target study populations, sample sizes, etc. This highlights the significant issue of postoperative thrombocytopenia in these patients and the need for active management.

There are numerous factors that influence postoperative thrombocytopenia in patients with critical heart conditions. This study identified four independent risk factors: [1] Female gender (95%CI 1.607–4.402, P = 0.000). A predictive scoring system scoring 95.1 for postoperative thrombocytopenia in critically ill cardiac patients has been developed. Literature has suggested that gender may influence platelet function [17]. Combined with the results of this study analysis, compared to males, females tend to have a higher level of immune response activity, which may lead to hindered platelet release and enhanced elimination of platelets, thus lowering platelet levels and increasing the likelihood of thrombocytopenia. It is recommended to monitor the postoperative platelet count dynamically in female patients with critical heart conditions and initiate platelet transfusion therapy as needed. [2] Age ≥ 60 years (95%CI 1.380–3.697, P = 0.001) contributes to an increased predictive score of 79.2 for postoperative thrombocytopenia in critically ill cardiac patients, similar to findings in studies by Keles [18] and Yan [19]. As age increases, there’s a decline in the function of various organs and immune system, diminishing the capability to produce platelets, especially compared to younger individuals. Elevated platelet activation and faster consumption lead to an imbalance in platelet production and destruction, resulting in a greater likelihood of thrombocytopenia. Additionally, patients aged over 60 generally have weaker gastrointestinal functions and more fragile blood vessels, increasing the risk of bleeding, which may indirectly cause postoperative thrombocytopenia. It is advisable to monitor platelet changes in patients aged ≥ 60 years closely. If platelet counts drop below the surgical target threshold, corresponding treatments should be implemented. [3] Preoperative antiplatelet therapy (95%CI 1.254–3.420, P = 0.004) contributes to an increased predictive score of 70.4 for postoperative thrombocytopenia in critically ill cardiac patients. A significant portion of patients with critical heart conditions undergo antiplatelet therapy. Drugs like clopidogrel, commonly used in such treatments, can interact with anticoagulant enzymes for thrombosis prevention. However, antiplatelet therapy reduces platelet aggregation and, with prolonged therapy and higher drug dosages, may elevate the risk of thrombocytopenia. Given that patients receiving preoperative antiplatelet therapy face increased bleeding risks if continued during the perioperative period and heightened thromboembolic risks if discontinued, it is essential to objectively assess both bleeding and thrombotic risks before surgery. Based on this assessment, enhance the management of perioperative antiplatelet medications accordingly. [4] Extracorporeal circulation time > 120 min (95%CI 1.681–4.652, P = 0.000) contributes to a predictive score of 100.0 for postoperative thrombocytopenia in critically ill cardiac patients. This is because extracorporeal circulation directly impacts platelets, reducing their count and impairing their function [20, 21]. Thus, longer durations of extracorporeal circulation significantly increase the risk of postoperative thrombocytopenia in these patients. In addition to reducing extracorporeal circulation time, it is important to enhance the management of anticoagulant medications. Objective assessment of the benefits and risks of anticoagulation therapy should be conducted, along with dynamic monitoring of platelet counts. Prompt adjustments to medication should be made upon detection of thrombocytopenia.

This study created a nomogram based on factors such as female gender, age ≥ 60 years, preoperative antiplatelet therapy, and extracorporeal circulation time > 120 min, to predict the risk of postoperative thrombocytopenia in patients with critical heart conditions. This nomogram clearly displays the predicted risk of postoperative thrombocytopenia for each patient, aiding in the identification of high-risk individuals. Further evaluation of its predictive effectiveness was conducted. The results of the calibration curve and Hosmer-Lemeshow goodness-of-fit test indicate that the predicted probabilities of the nomogram are essentially consistent with the actual probabilities of postoperative thrombocytopenia in these patients. The area under the ROC curve is 0.719 (95% CI: 0.663–0.774), suggesting reasonable discriminative ability of the nomogram.

Limitations of this study include: Firstly, it is a single-center, retrospective study with a relatively small sample size of only 319 patients with critical heart conditions. Secondly, some potential factors influencing postoperative thrombocytopenia in these patients were not included in the study. Thirdly, the nomogram for predicting postoperative thrombocytopenia in patients with critical heart conditions was built using only four predictive indicators. Finally, external validation of the nomogram was not conducted. These limitations also provide guidance for future research directions. Future studies should be multi-centered and involve larger samples, aim to identify independent risk factors for postoperative thrombocytopenia in patients with critical heart conditions, further refine the nomogram, and implement external validation to enhance its representativeness and generalizability.

In summary, the risk of postoperative thrombocytopenia in patients with critical heart conditions is influenced by factors such as female gender, age ≥ 60 years, preoperative antiplatelet therapy, and extracorporeal circulation time > 120 min. The nomogram developed based on these multiple independent risk factors offers a method for clinical prediction of postoperative thrombocytopenia risk in these patients.

Data availability

No datasets were generated or analysed during the current study.

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Author notes

  1. Changjun Song and Yicai Wu contributed equally to this work.

Authors and Affiliations

  1. Department of Emergency, Ganzhou People’s Hospital, Ganzhou City, Jiangxi Province, 341000, China

    Changjun Song, Jun Zhang, Jingliang Peng & Yuming Zhou

  2. Department of Nephrology, Ganzhou People’s Hospital, Ganzhou City, Jiangxi Province, 341000, China

    Yicai Wu

  3. Department of Obstetrics, Ganzhou People’s Hospital, Ganzhou City, Jiangxi Province, 341000, China

    Yuanyuan Liu

  4. Department of Rheumatology, Ganzhou People’s Hospital, No. 17 Hongqi Avenue, Zhanggong District, Ganzhou City, Jiangxi Province, 341000, China

    Lulu Yi

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  1. Changjun Song
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Contributions

Ch S, Y W: Data analysis, Manuscript writing; Y L, J Zh, J P: Data collection, Acquired data, Y Zh: Data analysis; L Y; Project development, Data analysis, Manuscript editing.

Corresponding author

Correspondence to Lulu Yi.

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The studies involving human participants were reviewed and approved by the Ethics Committee of Ganzhou People, s Hospital.Written informed consent to participate in this study was provided by the participants.

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Song, C., Wu, Y., Liu, Y. et al. Analysis of influencing factors and construction of risk prediction model for postoperative thrombocytopenia in critically ill patients with heart disease. J Cardiothorac Surg 19, 516 (2024). https://doi.org/10.1186/s13019-024-03017-x

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Keywords

Journal of Cardiothoracic Surgery

ISSN: 1749-8090

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