Risk factors for venous thromboembolism and evaluation of the modified Caprini score in patients undergoing lung resection

Predicting a failure of postoperative thromboprophylaxis in non-small cell lung cancer: A stacking machine learning approach

BACKGROUND

Non-small-cell lung cancer (NSCLC) and its surgery significantly increase the venous thromboembolism (VTE) risk. This study explored the VTE risk factors and established a machine-learning model to predict a failure of postoperative thromboprophylaxis.

METHODS

This retrospective study included patients with NSCLC who underwent surgery between January 2018 and November 2022. The patients were randomized 7:3 to the training and test sets. Nine machine learning models were constructed. The three most predictive machine-learning classifiers were chosen as the first layer of the stacking machine-learning model, and logistic regression was the second layer of the meta-learning model.

RESULTS

This study included 362 patients, including 58 (16.0%) with VTE. Based on the multivariable logistic regression analysis, age, platelets, D-dimers, albumin, smoking history, and epidermal growth factor receptor (EGFR) exon 21 mutation were used to develop the nine machine-learning models. LGBM Classifier, RandomForest Classifier, and GNB were chosen for the first layer of the stacking machine learning model. The area under the received operating characteristics curve (ROC-AUC), accuracy, sensitivity, and specificity of the stacking machine learning model in the training/test set were 0.984/0.979, 0.949/0.954, 0.935/1.000, and 0.958/0.887, respectively. In the validation set, the final stacking machine learning model demonstrated an ROC AUC of 0.983, accuracy of 0.937, sensitivity of 0.978, and specificity of 0.947. The decision curve analyses revealed high benefits.

CONCLUSION

The stacking machine learning model based on EGFR mutation and clinical characteristics had a predictive value for postoperative VTE in patients with NSCLC.

Perioperative inflammatory index differences between pulmonary squamous cell carcinoma and adenocarcinoma and their prognostic implications

Background

Perioperative inflammatory indices reflect systemic inflammatory responses and have been linked to cancer progression and prognosis. This study aims to explore the differences in perioperative inflammatory indices between lung squamous cell carcinoma (LSCC) and adenocarcinoma (LUAD) and their association with long-term outcomes.

Methods

This study included 287 lung cancer patients who underwent curative resection between June 2016 and December 2017, comprising 61 cases of LSCC and 226 cases of LUAD. Perioperative baseline information and inflammatory cell counts were collected. Patients were followed up for a median duration of 76 months, during which disease-free survival (DFS) and overall survival (OS) were recorded. Cox regression analysis was used to evaluate the prognostic significance of inflammatory factor levels.

Results

Significant differences were observed in white blood cell count and systemic inflammation response index (SIRI) between LSCC and LUAD (P < 0.05). Regression analysis identified age (OR=2.096, P=0.004), postoperative day 1 D-dimer level (OR=1.550, P<0.001), and Platelet-to-lymphocyte ratio (PLR) (OR=1.901, P=0.031) as independent risk factors for perioperative venous thromboembolism (VTE). Furthermore, open surgical approach (HR=2.437, P=0.016), tumor type (LSCC; HR=2.437, P=0.016), and PLR (HR=1.534, P=0.019) were independent risk factors for DFS.

Conclusion

Inflammatory index is key predictors of perioperative VTE and DFS in lung cancer, emphasizing their critical role in prognosis.

Development and validation of a novel screening tool for deep vein thrombosis in patients with spinal cord injury: A five-year cross-sectional study

STUDY DESIGN

Cross-sectional study.

OBJECTIVES

Deep vein thrombosis (DVT) presents a significant risk of complication in patients with spinal cord injury (SCI), necessitating accurate screening methods. While the Caprini Risk Assessment Model (Caprini RAM) has seen extensive use for DVT screening, its efficacy remains under scrutiny.

SETTING

First Affiliated Hospital of China University of Science and Technology.

METHODS

We created and evaluated three nomograms for their effectiveness in DVT screening. Model 1 incorporated variables such as age, D-dimer level, red blood cell (RBC) counts, platelet counts, presence of type 2 diabetes mellitus, high blood pressure, mode and level of injury, degree of impairments, and Caprini scores. Model 2 was derived from Caprini scores alone, and Model 3 focused on independent risk factors. We assessed these models using the area under the curve (AUC) of the receiver operating characteristic (ROC), calibration curves, and decision curve analysis (DCA), employing bootstrap resampling tests (500 iterations) to determine their accuracy, discriminative ability, and clinical utility. Internal validation was performed on a separate cohort. Nomogram was established with well-fitted calibration curves for model 1, 2 and 3(AUC = 0.808, 0.751 and 0.797; 95%CI = 0.76-0.86, 0.70-0.80 and 0.75-0.84; respectively), indicating model 1 outperformed the others in prediction DVT risk, followed by model 3 and 2. These findings were consistent in the validation cohort, with DCA further corroborating our conclusions.

CONCLUSION

A nomogram integrating clinical data with Caprini RAM provides a superior option for DVT screening in SCI patients within rehabilitation settings, outperforming Caprini RAM.

Nomogram model combined thrombelastography for venous thromboembolism risk in patients undergoing lung cancer surgery

Background: The aim of this study was to develop a nomogram model in combination with thromboelastography (TEG) to predict the development of venous thromboembolism (VTE) after lung cancer surgery. Methods: The data of 502 patients who underwent surgical treatment for lung cancer from December 2020 to December 2022 were retrospectively analyzed. Patients were then randomized into training and validation groups. Univariate and multivariate logistic regression analyses were carried out in the training group and independent risk factors were included in the nomogram to construct risk prediction models. The predictive capability of the model was assessed by the consistency index (C-index), receiver operating characteristic curves (ROC), the calibration plot and decision curve analysis (DCA). Results: The nomogram risk prediction model comprised of the following five independent risk factors: age, operation time, forced expiratory volume in one second and postoperative TEG parameters k value(K) and reaction time(R). The nomogram model demonstrated better predictive power than the modified Caprini model, with the C-index being greater. The calibration curve verified the consistency of nomogram between the two groups. Furthermore, DCA demonstrated the clinical value and potential for practical application of the nomogram. Conclusion: This study is the first to combine TEG and clinical risk factors to construct a nomogram to predict the occurrence of VTE in patients after lung cancer surgery. This model provides a simple and user-friendly method to assess the probability of VTE in postoperative lung cancer patients, enabling clinicians to develop individualized preventive anticoagulation strategies to reduce the incidence of such complications.

A nomogram model to predict the acute venous thromboembolism risk after surgery in patients with glioma

INTRODUCTION

Postoperative venous thromboembolism (VTE) is a common complication for glioma patients, with an incidence rate of about 20 %. The purpose of this study was to explore the risk factors of acute VTE after glioma surgery, which may provide an essential reference for clinical guidance on the prevention of acute VTE.

MATERIALS AND METHODS

A total of 435 patients who underwent glioma surgery from 2012 to 2021 were included in this study. Duplex ultrasonography was performed routinely 3-5 days after the surgery to define VTE. Univariate and multivariate logistic regression analyses were performed to explore the independent predictor of acute VTE after glioma surgery and use these selected risk factors to construct and validate a nomogram.

RESULTS

Several risk factors for predicting acute VTE after glioma surgery were identified and used to build the nomogram: age, operation time, systemic immune-inflammation index (SII), hypertension, and diabetes mellitus. The area under the curve of the nomogram was 0.834, indicating good discrimination. Hosmer-Lemeshow of the calibration curve was 3.05 (P = 0.98), showing a high degree of agreement between the prediction and actual outcome. Decision curve analysis indicated that the nomogram model was helpful when the incidence of VTE was 5-80 %.

CONCLUSIONS

A nomogram to predict acute VTE after glioma surgery was constructed and validated. Clinicians can use this predictive model to achieve risk assessment and take different treatment measures to prevent acute postoperative VTE and improve patients' quality of life effectively.

Systematic review of venous thromboembolism risk categories derived from Caprini score

OBJECTIVE

Hospital-acquired venous thromboembolism (VTE, including pulmonary embolism [PE] and deep vein thrombosis [DVT]) is a preventable cause of hospital death. The Caprini risk assessment model (RAM) is one of the most commonly used tools to assess VTE risk. The RAM is operationalized in clinical practice by grouping several risk scores into VTE risk categories that drive decisions on prophylaxis. A correlation between increasing Caprini scores and rising VTE risk is well-established. We assessed whether the increasing VTE risk categories assigned on the basis of recommended score ranges also correlate with increasing VTE risk.

METHODS

We conducted a systematic review of articles that used the Caprini RAM to assign VTE risk categories and that reported corresponding VTE rates. A Medline and EMBASE search retrieved 895 articles, of which 57 fulfilled inclusion criteria.

RESULTS

Forty-eight (84%) of the articles were cohort studies, 7 (12%) were case-control studies, and 2 (4%) were cross-sectional studies. The populations varied from postsurgical to medical patients. There was variability in the number of VTE risk categories assigned by individual studies (6 used 5 risk categories, 37 used 4, 11 used 3, and 3 used 2), and in the cutoff scores defining the risk categories (scores from 0 alone to 0-10 for the low-risk category; from ≥5 to ≥10 for high risk). The VTE rates reported for similar risk categories also varied across studies (0%-12.3% in the low-risk category; 0%-40% for high risk). The Caprini RAM is designed to assess composite VTE risk; however, two studies reported PE or DVT rates alone, and many of the other studies did not specify the types of DVTs analyzed. The Caprini RAM predicts VTE at 30 days after assessment; however, only 17 studies measured outcomes at 30 days; the remaining studies had either shorter or longer follow-ups (0-180 days).

CONCLUSIONS

The usefulness of the Caprini RAM is limited by heterogeneity in its implementation across centers. The score-derived VTE risk categorization has significant variability in the number of risk categories being used, the cutpoints used to define the risk categories, the outcome being measured, and the follow-up duration. This factor leads to similar risk categories being associated with different VTE rates, which impacts the clinical and research implications of the results. To enhance generalizability, there is a need for studies that validate the RAM in a broad population of medical and surgical patients, identify standardized risk categories, define risk of DVT and PE as distinct end points, and measure outcomes at standardized follow-up time points.

Incidence of venous thromboembolism after surgery for adenocarcinoma in situ and the validity of the modified Caprini score: A propensity score-matched study

Background

Recently, the new World Health Organization (WHO) tumor classification removed adenocarcinoma in situ (AIS) from the diagnosis of lung cancer. However, it remains unclear whether the “malignancy” item should be assessed when the modified Caprini Risk Assessment Model (RAM) is used to assess venous thromboembolism (VTE) risk in AIS. The purpose of our study is to assess differences between AIS and stage IA adenocarcinoma (AD) from a VTE perspective.

Methods

A retrospective study was performed on AIS and IA adenocarcinoma in our hospital from January 2018 to December 2021, and divided into AIS group and AD group. Propensity score matching (PSM) was used to compare the incidence of VTE and coagulation function, and to analyze whether the RAM is more effective when the “malignancy” item is not evaluated in AIS.

Results

491 patients were included after screening, including 104 patients in the AIS group and 387 patients in the AD group. After PSM, 83 patients were matched. The incidence of VTE and D-dimer in the AIS group was significantly lower than that in the AD group (P<0.05).When using the RAM to score AIS, compared with retaining the “malignancy” item, the incidence of VTE in the intermediate-high-risk group was significantly higher after removing the item (7.9% vs. 36.4%, P=0.018), which significantly improved the stratification effect of the model.

Conclusions

The incidence of postoperative VTE in AIS was significantly lower than that in stage IA adenocarcinoma. The stratification effect was more favorable when the “malignancy” item was not evaluated in AIS using the RAM.

Risk factors for venous thromboembolism (VTE) after adrenalectomy for adrenal cortical neoplasms

BACKGROUND

Incidence of venous thromboembolism (VTE) after adrenalectomy for adrenal cortical carcinoma (ACC) is unknown. Herein, we aim to identify the relative incidence and risk factors of VTE after adrenalectomy for ACC.

METHODS

The American College of Surgeons National Surgical Quality Improvement Program database was queried to identify patients who underwent adrenalectomy for ACC, Cushing syndrome (CS), and benign adrenal cortical syndromes (BACS). Univariable and multivariable analyses were used to determine clinical characteristics, 30-day postoperative VTE occurrences, and associated risk factors. Khorana oncologic risk score (KRS) for VTE was calculated and compared between groups.

RESULTS

A total of 5896 patients were analyzed: 576 ACC, 371 CS, and 4949 BACS. Postoperative VTE occurred 0.9%, with the highest rate occurring in ACC (2.6% ACC vs. 1.6% CS vs. 0.7% BACS, p < 0.001). Forty percent of VTEs in the ACC cohort were diagnosed postdischarge. ACC patients with KRS ≥ 2 had a 9.6% incidence of VTE (p = 0.007). Multivariable analysis identified increased age (p = 0.03), presence of adrenal cancer (p = 0.01), and KRS ≥ 2 (p = 0.005) as risk factors for VTE after adrenalectomy.

CONCLUSIONS

Postoperative VTE after adrenalectomy occurs most frequently for ACC. ACC patients with increased age and/or Khorana score ≥2 should be considered for extended VTE prophylaxis.

Prevalence of venous thromboembolism and evaluation of a modified caprini risk assessment model: a single-centre, prospective cohort study involving patients undergoing lung resections for bronchiectasis

Background

Venous thromboembolism (VTE) is a common postoperative complication in general thoracic surgery, but the incidence of patients undergoing surgery for bronchiectasis was not known. The purpose of our study was to investigate the incidence of VTE in bronchiectasis patients undergoing lung resection and to evaluate the risk stratification effect of the modified caprini risk assessment model (RAM).

Methods

We prospectively enrolled patients with bronchiectasis who underwent lung resection surgery between July 2016 and July 2020.The postoperative duplex lower-extremity ultrasonography or(and) computed tomographic pulmonary angiography (CTPA) was performed to detect VTE. The clinical characteristics and caprini scores of VTE patients and non-VTE patients would be compared and analyzed. Univariate logistic regression was performed to evaluate whether higher Caprini scores were associated with postoperative VTE risk.In addition, We explored the optimal cutoff for caprini score in patients with bronchiectasis by using the receiver operating characteristic (ROC) curve.

Results

One hundred and seventeen patients were eligible based on the prospective study criteria. The postoperative VTE incidence was 8.5% (10/117). By comparing the clinical characteristics and Caprini scores of VTE and non-VTE patients, the median preoperative hospitalization (7 vs 5 days, P = 0.028) and Caprini score (6.5 vs 3,P < 0.001) were significantly higher in VTE patients. In univariate logistic regression, a higher Caprini score was associated with higher odds ratio (OR) for VTE of 1.7, 95% confidence interval (CI) was from 1.2 to 2.5 (P = 0.001), C-statistics was 0.815 in the modified caprini RAM for predicting VTE. In a multivariable analysis adjusting for preoperative hospitalization, a higher Caprini score was associated with higher odds OR for VTE of 1.8 (95%CI: 1.2–2.6, P = 0.002), C-statistics was 0.893 in the caprini RAM for predicting VTE. When taking the Caprini score as 5 points as the diagnostic threshold, the Youden index is the largest.

Conclusions

The postoperative VTE incidence in patients undergoing lung resection for bronchiectasis was 8.5%.The modified caprini RAM effectively stratified bronchiectasis surgery patients for risk of VTE and showed excellent predictive power for VTE. The patients with postoperative caprini scores = 5, should be recommended to take positive measures to prevent postoperative VTE.

Trial Registration

Chinese Clinical Trial Register: ChiCTR-EOC-17010577.

Development and validation of a nomogram to assess postoperative venous thromboembolism risk in patients with stage IA non-small cell lung cancer

BACKGROUND

Venous thromboembolism (VTE) is a common postoperative complication in patients with lung cancer that seriously affects prognosis and quality of life. At present, the detection rate of patients with early-stage lung cancer is increasing, but there are few studies on the risk factors for postoperative venous thromboembolism (VTE) in patients with stage IA non-small cell lung cancer (NSCLC). This study aimed to establish a nomogram for predicting the probability of postoperative VTE risk in patients with stage IA NSCLC.

METHODS

The clinical data of 452 patients with stage IA NSCLC from January 2017 to January 2022 in our center were retrospectively analyzed and randomly divided into a training set and a validation set at a ratio of 7:3. Independent risk factors were identified by univariate and multivariate logistic regression analyses, and a nomogram was established based on the results and internally validated. The predictive power of the nomogram was evaluated by receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).

RESULTS

The nomogram prediction model included three risk factors: age, preoperative D-dimer, and intermuscular vein dilatation. The areas under the ROC curve of this predictive model were 0.832 (95% CI: 0.732-0.924) and 0.791 (95% CI: 0.668-0.930) in the training and validation sets, respectively, showing good discriminative power. In addition, the probability of postoperative VTE occurrence predicted by the nomogram was consistent with the actual occurrence probability. In the decision curve, the nomogram model had a better net clinical benefit at a threshold probability of 5%-90%.

CONCLUSION

This study is the first to develop a nomogram for predicting the risk of postoperative VTE in patients with stage IA NSCLC; this nomogram can accurately and intuitively evaluate the probability of VTE in these patients and help clinicians make decisions on prevention and treatment.

Postoperative venous thromboembolism after surgery for stage IA non-small-cell lung cancer: A single-center, prospective cohort study

BACKGROUND

Venous thromboembolism (VTE) is a common postoperative complication of lung cancer, but the incidence and risk stratification of postoperative VTE in stage IA non-small-cell lung cancer (NSCLC) patients remains unclear, therefore we conducted a single-center prospective study.

METHODS

A total of 314 consecutive patients hospitalized for lung cancer surgery and diagnosed with stage IA NSCLC from January 2017 to July 2021 were included. The patients were divided into the VTE group and the non-VTE group according to whether VTE occurred after the operation. The patient's age, operation time, D-dimer (D-D) value, tumor pathology, and Caprini score were recorded. The different items were compared and included in logistic regression analysis to obtain independent risk factors, and the area under the receiver operating characteristics curve (AUC) was calculated.

RESULTS

The incidence of VTE was 7.3%. Significant differences in age, operation time, preoperative and postoperative day 1 D-D value, neuron-specific enolase value, forced expiratory volume in 1 second, maximum ventilation, carbon monoxide diffusion capacity, and pathological diameter were noted between the two groups. Age (95% confidence interval [CI] 1.056-1.216) and postoperative day 1 D-D value (95% CI 1.125-1.767) were independent risk factors. The incidence of VTE in the low-, medium-, and high-risk groups with Caprini scores was 0%, 7.3%, and 11.5%, respectively. The AUC of the Caprini score was 0.704 (p < 0.05).

CONCLUSIONS

The incidence of postoperative VTE in patients with stage IA NSCLC was 7.3%. Age and postoperative day 1 D-D value were independent risk factors for VTE. The Caprini score has a certain value in the diagnosis of postoperative VTE of stage IA NSCLC.

Validation of a modified Caprini risk assessment model in lung cancer patients undergoing surgery: Results of a multicenter cross-sectional observational study

BACKGROUND AND OBJECTIVES

Lung cancer patients slated for surgery are at high risk of venous thromboembolism (VTE). Precise risk assessment is necessary for providing proper thromboprophylaxis and reducing morbidity and mortality of VTE.

METHODS

A multicenter, observational, cross-sectional cohort study, involving patients with primary lung cancer undergoing surgery, was carried out from August 2016 to December 2019. All patients were assessed according to the Caprini risk assessment model (RAM) and a modified scoring system incorporating elevated D-dimer and new stratification of surgical time. The endpoint was confirmed VTE or patient discharge.

RESULTS

Out of 1205 patients, 87 (7.2%) were diagnosed with VTE. The area under the curve of modified scores for VTE was 0.759, which was larger than that of the original one (0.589) (p < 0.05). By modified Caprini scoring system, a higher score was associated with increased VTE risk (odds ratio [OR], 1.345; 95% confidence interval [CI], 1.197-1.512; p < 0.001), and there was an increased OR of 4.090 (95% CI, 2.472-6.768, p < 0.001) for VTE in high-risk category patients.

CONCLUSION

Modified Caprini RAM showed an improved prediction of high-risk patients with an elevated likelihood of postoperative VTE compared to the original one.

Temporal profile of the pro- and anti-inflammatory responses to severe hemorrhage in patients with venous thromboembolism: Findings from the PROPPR trial

BACKGROUND

The Pragmatic Randomized Optimal Platelet and Plasma Ratios (PROPPR) trial showed that 15% of patients developed venous thromboembolism (VTE) following hemorrhage, but the mechanisms are unknown. Since inflammation is associated with hypercoagulability and thrombosis, our goal was to compare the temporal inflammatory profile following hemorrhagic shock in patients with and without VTE.

STUDY DESIGN

Secondary analysis was performed on data collected from PROPPR. Blood samples collected at 0 hour, 2 hours, 4 hours, 6 hours, 12 hours, 24 hours, 48 hours, and 72 hours following admission were assayed on a 27-target cytokine panel, and compared between VTE (n = 83) and non-VTE (n = 475) patients. p < 0.05 indicated significance.

RESULTS

Over time, both groups exhibited elevations in proinflammatory mediators interleukin (IL)-6, IL-8, IL-10, granulocyte colony-stimulating factor 57, monocyte chemoattractant protein 1 and macrophage inflammatory protein 1β, and anti-inflammatory mediators IL-1ra and IL-10 (p < 0.05 vs. admission). Venous thromboembolism patients showed amplified responses for IL-6 (6-72 hours) and IL-8 (6-24 hours), which peaked at later time points, and granulocyte colony-stimulating factor 57 (12-24 hours), monocyte chemoattractant protein 1 (6-72 hours), and macrophage inflammatory protein-1 β (2-12 hours) (p < 0.05 vs. non-VTE per time point) that peaked at similar time points to non-VTE patients. The anti-inflammatory responses were similar between groups, but the interleukin-mediated proinflammatory responses continued to rise after the peak anti-inflammatory response in the VTE group. The occurrence rate of adverse events was higher in VTE (97%) versus non-VTE (87%, p = 0.009) and was associated with higher inflammation.

CONCLUSION

Patients with VTE following hemorrhagic shock exhibited a prolonged and amplified proinflammatory responses mediated by select interleukin, chemotactic, and glycoprotein cytokines that are not antagonized by anti-inflammatory mediators. This response is not related to randomization group, injury severity or degree of shock, but may be linked to adverse events.

LEVEL OF EVIDENCE

Prognostic, level III.