Risk models for VTE and bleeding in medical inpatients: systematic identification and expert assessment

Venous thromboembolism performance measurement in the United States: An evolving landscape with many stakeholders

Venous thromboembolism (VTE), including deep vein thrombosis and pulmonary embolism, is a life-threatening, costly, and common preventable complication associated with hospitalization. Although VTE prevention strategies such as risk assessment and prophylaxis are available, they are not applied uniformly or systematically across US hospitals and healthcare systems. Hospital-level performance measurement has been used nationally to promote standardized approaches for VTE prevention and incentivize the adoption of guideline-based care management. Though most measures reflect care processes rather than outcomes, certain domains including diagnosis, treatment, and continuity of care remain unmeasured. In this article, we describe the development of VTE prevention measures from various stakeholders, measure strengths and limitations, publicly reported rates, the impact of technology and health policy on measure use, and perspectives on future options for surveillance and performance monitoring.

Comparison of the PADUA and IMPROVE scores in assessing venous thromboembolism risk in 42,257 medical inpatients in China

Venous thromboembolism (VTE) is a major contributor to hospital mortality and disability-adjusted life-year (DALY) loss. Multiple guidelines recommend using the Padua or IMPROVE scores to stratify VTE risk in hospitalized medical patients. However, the IMPROVE score is not recommended in Chinese guidelines, and there is very little evaluation of its clinical application and effectiveness in the Chinese population. The objective of this study is to compare the efficacy of the Padua and IMPROVE scoring models for assessing VTE risk in Chinese medical inpatients. We conducted a retrospective analysis of the clinical characteristics and thrombotic risk of 42,257 medical inpatients at a tertiary hospital in Guangdong, China, between 2021 and 2022. Logistic regression was used to assess thrombotic risk factors. The Receiver Operating Characteristic (ROC) curves, Area Under the Curve (AUC), sensitivity, and specificity were employed to evaluate the performance of the two models. Of the 42,257 patients included, 948 (2.24%) experienced VTE during hospitalization. According to the Padua score, 3,7513 (88.78%) of patients were considered low risk, while 4,744 (18.22%) were classified as high risk. The IMPROVE score identified 20,744 (49.09%) of patients as low risk, 20799(49.22%) as intermediate risk, and 714(1.69%) as high risk. The AUC for the Padua score was 0.735 (95% CI: 0.717-0.753), with a sensitivity of 49.4% and specificity of 89.6%. For the IMPROVE score, the AUC was 0.711 (95% CI: 0.693-0.729), with a sensitivity of 32.5% and specificity of 99.0%. The DeLong test, used to compare the AUCs, yielded a z-value of 1.886 with a P-value of 0.059, indicating no statistical difference. When assessing VTE risk in patients with stroke, cancer, nephrotic syndrome, and critical illness (ICU/CCU stay), both scoring models showed comparable predictive performance with AUCs ranging between 0.7 and 0.8. Both the Padua score and IMPROVE score have good predictive ability for VTE events during hospitalization in medical patients. Among them, the IMPROVE score has objective assessment items, simpler operation, and more detailed risk stratification, which is beneficial for clinicians to take physical and pharmacological preventive measures at different levels.ChiCTR2200056903, February 22, retrospectively registered.

Validation of the International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) risk scores for venous thromboembolism and bleeding in an independent population

Background

Multiple guidelines recommend assessment of bleeding and venous thromboembolism (VTE) risk in adult medical inpatients to inform prevention strategies. There is no agreed-upon method for VTE and bleeding risk assessment.

Objectives

To validate the International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) VTE and bleeding risk scores in an independent population.

Methods

In this retrospective study, we calculated the IMPROVE VTE and bleeding risk scores in medical inpatients admitted between 2010 and 2019 at the University of Vermont Medical Center (UVMMC). Patients were followed for in-hospital bleeding events while hospitalized and VTE events while hospitalized and for 3 months after discharge. We assessed calibration of the risk models by comparing the observed incidence of events in the UVMMC and IMPROVE populations across the published risk categories. We also assessed performance of the IMPROVE risk factors after refitting the models in the UVMMC population. Discrimination was assessed using the area under the receiver operating characteristic curve (AUC).

Results

VTE occurred in 270 (1.1%) of 23,873 admissions, with 92 (34%) occurring during admission, and bleeding occurred in 712 (4.7%) of 15,240 admissions. When the IMPROVE-VTE risk factors were refitted to the UVMMC data, the AUC was 0.64. When the IMPROVE bleeding risk factors were refitted to the UVMMC data, the AUC was 0.67. The IMPROVE-VTE score tended to overestimate risk at higher scores, and the IMPROVE bleeding score underestimated risk at lower scores and overestimated risk at higher scores.

Conclusion

While the refitted IMPROVE VTE and bleeding risk scores had reasonable model fit, the scores were poorly calibrated and did not reliably identify or differentiate patients at risk for VTE and bleeding. Different methods are needed for risk assessment of medical inpatients for VTE and bleeding risk.

Evaluation of venous thromboembolism risk assessment models for hospital inpatients: the VTEAM evidence synthesis

Background

Pharmacological prophylaxis during hospital admission can reduce the risk of acquired blood clots (venous thromboembolism) but may cause complications, such as bleeding. Using a risk assessment model to predict the risk of blood clots could facilitate selection of patients for prophylaxis and optimise the balance of benefits, risks and costs.

Objectives

We aimed to identify validated risk assessment models and estimate their prognostic accuracy, evaluate the cost-effectiveness of different strategies for selecting hospitalised patients for prophylaxis, assess the feasibility of using efficient research methods and estimate key parameters for future research.

Design

We undertook a systematic review, decision-analytic modelling and observational cohort study conducted in accordance with Enhancing the QUAlity and Transparency Of health Research (EQUATOR) guidelines.

Setting

NHS hospitals, with primary data collection at four sites.

Participants

Medical and surgical hospital inpatients, excluding paediatric, critical care and pregnancy-related admissions.

Interventions

Prophylaxis for all patients, none and according to selected risk assessment models.

Main outcome measures

Model accuracy for predicting blood clots, lifetime costs and quality-adjusted life-years associated with alternative strategies, accuracy of efficient methods for identifying key outcomes and proportion of inpatients recommended prophylaxis using different models.

Results

We identified 24 validated risk assessment models, but low-quality heterogeneous data suggested weak accuracy for prediction of blood clots and generally high risk of bias in all studies. Decision-analytic modelling showed that pharmacological prophylaxis for all eligible is generally more cost-effective than model-based strategies for both medical and surgical inpatients, when valuing a quality-adjusted life-year at £20,000. The findings were more sensitive to uncertainties in the surgical population; strategies using risk assessment models were more cost-effective if the model was assumed to have a very high sensitivity, or the long-term risks of post-thrombotic complications were lower. Efficient methods using routine data did not accurately identify blood clots or bleeding events and several pre-specified feasibility criteria were not met. Theoretical prophylaxis rates across an inpatient cohort based on existing risk assessment models ranged from 13% to 91%.

Limitations

Existing studies may underestimate the accuracy of risk assessment models, leading to underestimation of their cost-effectiveness. The cost-effectiveness findings do not apply to patients with an increased risk of bleeding. Mechanical thromboprophylaxis options were excluded from the modelling. Primary data collection was predominately retrospective, risking case ascertainment bias.

Conclusions

Thromboprophylaxis for all patients appears to be generally more cost-effective than using a risk assessment model, in hospitalised patients at low risk of bleeding. To be cost-effective, any risk assessment model would need to be highly sensitive. Current evidence on risk assessment models is at high risk of bias and our findings should be interpreted in this context. We were unable to demonstrate the feasibility of using efficient methods to accurately detect relevant outcomes for future research.

Future work

Further research should evaluate routine prophylaxis strategies for all eligible hospitalised patients. Models that could accurately identify individuals at very low risk of blood clots (who could discontinue prophylaxis) warrant further evaluation.

Study registration

This study is registered as PROSPERO CRD42020165778 and Researchregistry5216.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: NIHR127454) and will be published in full in Health Technology Assessment; Vol. 28, No. 20. See the NIHR Funding and Awards website for further award information.

Development and validation of a risk model for hospital-acquired venous thrombosis: the Medical Inpatients Thrombosis and Hemostasis study

BACKGROUND

Regulatory organizations recommend assessing hospital-acquired (HA) venous thromboembolism (VTE) risk for medical inpatients.

OBJECTIVES

To develop and validate a risk assessment model (RAM) for HA-VTE in medical inpatients using objective and assessable risk factors knowable at admission.

METHODS

The development cohort included people admitted to medical services at the University of Vermont Medical Center (Burlington, Vermont) between 2010 and 2019, and the validation cohorts included people admitted to Hennepin County Medical Center (Minneapolis, Minnesota), University of Michigan Medical Center (Ann Arbor, Michigan), and Harris Health Systems (Houston, Texas). Individuals with VTE at admission, aged <18 years, and admitted for <1 midnight were excluded. We used a Bayesian penalized regression technique to select candidate HA-VTE risk factors for final inclusion in the RAM.

RESULTS

The development cohort included 60 633 admissions and 227 HA-VTE, and the validation cohorts included 111 269 admissions and 651 HA-VTE. Seven HA-VTE risk factors with t statistics ≥1.5 were included in the RAM: history of VTE, low hemoglobin level, elevated creatinine level, active cancer, hyponatremia, increased red cell distribution width, and malnutrition. The areas under the receiver operating characteristic curve and calibration slope were 0.72 and 1.10, respectively. The areas under the receiver operating characteristic curve and calibration slope were 0.70 and 0.93 at Hennepin County Medical Center, 0.70 and 0.87 at the University of Michigan Medical Center, and 0.71 and 1.00 at Harris Health Systems, respectively. The RAM performed well stratified by age, sex, and race.

CONCLUSION

We developed and validated a RAM for HA-VTE in medical inpatients. By quantifying risk, clinicians can determine the potential benefits of measures to reduce HA-VTE.

Prediction of bleeding in patients being considered for venous thromboembolism prophylaxis

BACKGROUND

Venous thromboembolism (pulmonary embolism and deep vein thrombosis) is an important preventable cause of in-hospital death. Prophylaxis with low doses of anticoagulants reduces the incidence of venous thromboembolism but can also cause bleeding. It is, therefore, important to stratify the risk of bleeding for hospitalized patients when considering pharmacologic prophylaxis. The IMPROVE (international medical prevention registry on venous thromboembolism) and Consensus risk assessment models (RAMs) are the two tools available for such patients. Few studies have evaluated their ability to predict bleeding in a large, unselected cohort of patients. We assessed the ability of the IMPROVE and Consensus bleeding RAMs to predict bleeding within 90 days of hospitalization in a comprehensive analysis encompassing all hospitalized patients, regardless of surgical vs nonsurgical status.

METHODS

We analyzed consecutive first hospital admissions of 1,228,448 unique surgical and nonsurgical patients to 1298 Veterans Affairs facilities nationwide between January 2016 and December 2021. IMPROVE and Consensus scores were generated using data from a repository of their common electronic medical records. We assessed the ability of the two RAMs to predict bleeding within 90 days of admission. We used area under the receiver operating characteristic curves to determine the prediction of bleeding by each RAM.

RESULTS

Of 1,228,448 hospitalized patients, 324,959 (26.5%) were surgical and 903,489 (73.5%) were nonsurgical. Of these patients, 68,372 (5.6%) had a bleeding event within 90 days of admission. The Consensus RAM scores ranged from -5.60 to -1.21 (median, -4.93; interquartile range, -5.60 to -4.93). The IMPROVE RAM scores ranged from 0 to 22 (median, 3.5; interquartile range, 2.5-5). Both showed good calibration, with higher scores associated with higher bleeding rates. The ability of both RAMs to predict 90-day bleeding was low (area under the receiver operating characteristic curve 0.61 for the IMPROVE RAM and 0.59 for the Consensus RAM). The predictive ability was also low at 30 and 60 days for surgical and nonsurgical patients, patients receiving prophylactic, therapeutic, or no anticoagulation, and patients hospitalized for ≥72 hours. Prediction was also low across different bleeding outcomes (ie, any bleeding, gastrointestinal bleeding, nongastrointestinal bleeding, and bleeding or death).

CONCLUSIONS

In this large, unselected, nationwide cohort of surgical and nonsurgical hospital admissions, increasing IMPROVE and Consensus bleeding RAM scores were associated with increasing bleeding rates. However, both RAMs had low ability to predict bleeding at 0 to 90 days after admission. Thus, the currently available RAMs require modification and rigorous reevaluation before they can be applied universally.

Application of artificial neural network in daily prediction of bleeding in ICU patients treated with anti-thrombotic therapy

OBJECTIVES

Anti-thrombotic therapy is the basis of thrombosis prevention and treatment. Bleeding is the main adverse event of anti-thrombosis. Existing laboratory indicators cannot accurately reflect the real-time coagulation function. It is necessary to develop tools to dynamically evaluate the risk and benefits of anti-thrombosis to prescribe accurate anti-thrombotic therapy.

METHODS

The prediction model,daily prediction of bleeding risk in ICU patients treated with anti-thrombotic therapy, was built using deep learning algorithm recurrent neural networks, and the model results and performance were compared with clinicians.

RESULTS

There was no significant statistical discrepancy in the baseline. ROC curves of the four models in the validation and test set were drawn, respectively. One-layer GRU of the validation set had a larger AUC (0.9462; 95%CI, 0.9147-0.9778). Analysis was conducted in the test set, and the ROC curve showed the superiority of two layers LSTM over one-layer GRU, while the former AUC was 0.8391(95%CI, 0.7786-0.8997). One-layer GRU in the test set possessed a better specificity (sensitivity 0.5942; specificity 0.9300). The Fleiss' k of junior clinicians, senior clinicians, and machine learning classifiers is 0.0984, 0.4562, and 0.8012, respectively.

CONCLUSIONS

Recurrent neural networks were first applied for daily prediction of bleeding risk in ICU patients treated with anti-thrombotic therapy. Deep learning classifiers are more reliable and consistent than human classifiers. The machine learning classifier suggested strong reliability. The deep learning algorithm significantly outperformed human classifiers in prediction time.

Venous thromboembolism prophylaxis for hospitalized adult patients: a survey of US health care providers on attitudes and practices

Background

Venous thromboembolism (VTE) is a leading cause of preventable mortality among hospitalized patients, but appropriate risk assessment and thromboprophylaxis remain underutilized or misapplied.

Objectives

We conducted an electronic survey of US health care providers to explore attitudes, practices, and barriers related to thromboprophylaxis in adult hospitalized patients and at discharge.

Results

A total of 607 US respondents completed the survey: 63.1% reported working in an academic hospital, 70.7% identified as physicians, and hospital medicine was the most frequent specialty (52.1%). The majority of respondents agreed that VTE prophylaxis is important (98.8%; 95% CI: 97.6%-99.5%) and that current measures are safe (92.6%; 95% CI: 90.2%-94.5%) and effective (93.8%; 95% CI: 91.6%-95.6%), but only half (52.0%; 95% CI: 47.9%-56.0%) believed that hospitalized patients at their institution are on appropriate VTE prophylaxis almost all the time. One-third (35.4%) reported using a risk assessment model (RAM) to determine VTE prophylaxis need; 44.9% reported unfamiliarity with RAMs. The most common recommendation for improving rates of appropriate thromboprophylaxis was to leverage technology. A majority of respondents (84.5%) do not reassess a patient's need for VTE prophylaxis at discharge, and a minority educates patients about the risk (16.2%) or symptoms (18.9%) of VTE at discharge.

Conclusion

Despite guideline recommendations to use RAMs, the majority of providers in our survey do not use them. A majority of respondents believed that technology could help improve VTE prophylaxis rates. A majority of respondents do not reassess the risk of VTE at discharge or educate patients about this risk of VTE at discharge.

Epidemiology and prevention of venous thromboembolism

Venous thromboembolism, that consists of the interrelated conditions deep-vein thrombosis and pulmonary embolism, is an under-appreciated vascular disease. In Western regions, approximately 1 in 12 individuals will be diagnosed with venous thromboembolism in their lifetime. Rates of venous thromboembolism are lower in Asia, but data from other regions are sparse. Numerous risk factors for venous thromboembolism have been identified, which can be classified as acute or subacute triggers (provoking factors that increase the risk of venous thromboembolism) and basal or acquired risk factors (which can be modifiable or static). Approximately 20% of individuals who have a venous thromboembolism event die within 1 year (although often from the provoking condition), and complications are common among survivors. Fortunately, opportunities exist for primordial prevention (prevention of the development of underlying risk factors), primary prevention (management of risk factors among individuals at high risk of the condition) and secondary prevention (prevention of recurrent events) of venous thromboembolism. In this Review, we describe the epidemiology of venous thromboembolism, including the incidence, risk factors, outcomes and opportunities for prevention. Meaningful health disparities exist in both the incidence and outcomes of venous thromboembolism. We also discuss these disparities as well as opportunities to reduce them.

Biomarker derived risk scores predict venous thromboembolism and major bleeding among patients with COVID-19

Background

Venous thromboembolism (VTE) risk is increased in patients with COVID-19 infection. Understanding which patients are likely to develop VTE may inform pharmacologic VTE prophylaxis decision making. The hospital-associated venous thromboembolism-Intermountain Risk Score (HA-VTE IMRS) and the hospital-associated major bleeding-Intermountain Risk Score (HA-MB IMRS) are risk scores predictive of VTE and bleeding that were derived from only patient age and data found in the complete blood count (CBC) and basic metabolic panel (BMP).

Objectives

We assessed the HA-VTE IMRS and HA-MB IMRS for predictiveness of 90-day VTE and major bleeding, respectively, among patients diagnosed with COVID-19, and further investigated if adding D-dimer improved these predictions. We also reported 30-day outcomes.

Patients/Methods

We identified 5047 sequential patients with a laboratory confirmed diagnosis of COVID-19 and a CBC and BMP between 2 days before and 7 days following the diagnosis of COVID-19 from March 12, 2020, to February 28, 2021. We calculated the HA-VTE IMRS and the HA-MB IMRS for all patients. We assessed the added predictiveness of D-dimer obtained within 48 hours of the COVID test.

Results

The HA-VTE IMRS yielded a c-statistic of 0.70 for predicting 90-day VTE and adding D-dimer improved the c-statistic to 0.764 with the corollary sensitivity/specificity/positive/negative predictive values of 49.4%/75.7%/6.7%/97.7% and 58.8%/76.2%/10.9%/97.4%, respectively. Among hospitalized and ambulatory patients separately, the HA-VTE IMRS performed similarly. The HA-MB IMRS predictiveness for 90-day major bleeding yielded a c-statistic of 0.64.

Conclusion

The HA-VTE IMRS and HA-MB IMRS predict 90- and 30-day VTE and major bleeding among COVID-19 patients. Adding D-dimer improved the predictiveness of the HA-VTE IMRS for VTE.

Thrombotic and Hemorrhagic Incidences in Patients After Discharge from COVID-19 Infection: A Systematic Review and Meta-Analysis

Background

The association between coronavirus infection 2019 (COVID-19) and thrombosis has been explicitly shown through numerous reports that demonstrate high rates of thrombotic complications in infected patients. Recently, much evidence has shown that patients who survived COVID-19 might have a high thrombotic risk after hospital discharge. This current systematic review and meta-analysis was conducted to better understand the incidence of thrombosis, bleeding, and mortality rates among patients discharged after COVID-19 hospitalization.

Methods

Using a search strategy that included terms for postdischarge, thrombosis, and COVID-19, 2 investigators independently searched for published articles indexed in the MEDLINE, Embase, and Scopus databases that were published before August 2021. Pooled incidences and 95% confidence intervals were calculated using the DerSimonian-Laird random-effects model with a double arcsine transformation.

Results

Twenty articles were included in the meta-analysis. They provided a total of 19 461 patients discharged after COVID-19 hospitalization. The weighted pooled incidence of overall thrombosis among the patients was 1.3% (95 CI, 0. 6-2; I² 90.5), with a pooled incidence of venous thrombosis of 0.7% (95 CI, 0. 4-1; I² 73.9) and a pooled incidence of arterial thrombosis of 0.6% (95 CI, 0. 2-1; I² 88.1). The weighted pooled incidences of bleeding and mortality were 0.9% (95 CI, 0. 1-1.9; I² 95.1) and 2.8% (95 CI, 0. 6-5; I² 98.2), respectively.

Conclusions

The incidences of thrombosis and bleeding in patients discharged after COVID-19 hospitalization are comparable to those of medically ill patients.

Risk-assessment models for VTE and bleeding in hospitalized medical patients: an overview of systematic reviews

Multiple risk-assessment models (RAMs) for venous thromboembolism (VTE) in hospitalized medical patients have been developed. To inform the 2018 American Society of Hematology (ASH) guidelines on VTE, we conducted an overview of systematic reviews to identify and summarize evidence related to RAMs for VTE and bleeding in medical inpatients. We searched Epistemonikos, the Cochrane Database, Medline, and Embase from 2005 through June 2017 and then updated the search in January 2020 to identify systematic reviews that included RAMs for VTE and bleeding in medical inpatients. We conducted study selection, data abstraction and quality assessment (using the Risk of Bias in Systematic Reviews [ROBIS] tool) independently and in duplicate. We described the characteristics of the reviews and their included studies, and compared the identified RAMs using narrative synthesis. Of 15 348 citations, we included 2 systematic reviews, of which 1 had low risk of bias. The reviews included 19 unique studies reporting on 15 RAMs. Seven of the RAMs were derived using individual patient data in which risk factors were included based on their predictive ability in a regression analysis. The other 8 RAMs were empirically developed using consensus approaches, risk factors identified from a literature review, and clinical expertise. The RAMs that have been externally validated include the Caprini, Geneva, IMPROVE, Kucher, and Padua RAMs. The Padua, Geneva, and Kucher RAMs have been evaluated in impact studies that reported an increase in appropriate VTE prophylaxis rates. Our findings informed the ASH guidelines. They also aim to guide health care practitioners in their decision-making processes regarding appropriate individual prophylactic management.

Factors predicting successful vaginal birth after caesarean section: protocol for evidence-based consensus recommendations using a Delphi survey

INTRODUCTION

With the wide adoption of the two-child policy in China since 2016, a large percentage of women with a history of caesarean delivery plan to have a second child. Accordingly, the rate of vaginal birth after caesarean (VBAC) delivery is increasing. Women attempting repeat VBAC may experience multiple morbidities, which is also one of the leading causes of maternal and perinatal mortality. However, it remains to be addressed how we evaluate factors for successful VBAC. This study aims to use a novel approach to identify a set of potential predictive factors for successful VBAC, especially for Chinese women, to be included in prediction models which can be most applicable to pregnant women in China. We plan to assess all potential predictive factors collected through a comprehensive literature review. Then the certainty of the evidence for the identified potential predictive factors will be assessed using the Grading of Recommendations Assessment, Development and Evaluation process. Finally, a two-round international Delphi survey will be conducted to determine the level of consensus.

METHODS AND ANALYSIS

This study will apply a methodology through an evidence-based approach. A long list of potential predictive factors for successful VBAC will be extracted and identified through the following stages: First, an up-to-date systematic review of the published literature will be conducted to extract identified potential predictive factors for successful VBAC. Second, an online Delphi survey will be performed to achieve expert consensus on which factors should be included in future prediction models. The online questionnaires will be developed in the field of patient, maternal and fetal-related factors. A two-round international Delphi survey will be distributed to the expert panel in the field of perinatal medicine using Google Forms. Experts will be asked to score each factor using the 9-point Likert rating scale to establish potential predictive factors for the successful VBAC. The expert panel will determine on whether to include, potentially include or exclude predictive factors, based on a systematic review of clinical evidence and the Delphi method.

ETHICS AND DISSEMINATION

The study was approved by the Institutional Review Board of the Jiaxing Maternity and Children Healthcare Hospital (approval number: 2019-79). The results of this study will be submitted to international peer-reviewed journals or conferences in perinatal medicine or obstetrics.

Post-hospital discharge venous thromboembolism prophylaxis in medically ill patients

There is a widely expressed concern about an unmet need for post hospitalization venous thromboembolism (VTE) prophylaxis in medically ill patients, however, physicians and hospitals have been slow to implement this measure. Recommendations against extended VTE prophylaxis in medical patients from the American Society of Hematology (ASH) in 2018 and the withholding of approval of betrixiban by the European Medicines Agency also in 2018 may have been influential in this regard. Furthermore, rivaroxaban the other drug approved for this indication in the U.S has not yet been approved in Europe. In addition, hospital administrators, those monitoring expenses in the U.S, have been reluctant to support a treatment which will mostly involve outpatients. Internal medicine physicians, hospitalists and nursing home physicians have not shared the fervor for post hospital VTE prophylaxis, whether with anticoagulants or aspirin, that their orthopedic surgery colleagues have, particularly in hip and knee arthroplasty. This is despite an increased risk of post hospital discharge thrombosis in both groups of patients. Enter hospitalized patients with COVID-19, a potentially severe medical illness with high hospitalization related thrombosis risk, and questions arise as to whether these medical patients, who are clearly more hypercoagulable during hospitalization than those in previous studies, should warrant post hospital discharge prophylaxis.

SARS-COV-2-associated coagulopathy and thromboembolism prophylaxis in children: A single-center observational study

BACKGROUND

Multiple investigators have described an increased incidence of thromboembolic events in SARS-CoV-2-infected individuals. Data concerning hemostatic complications in children hospitalized for COVID-19/multisystem inflammatory syndrome in children (MIS-C) are scant.

OBJECTIVES

To share our experience in managing SARS-CoV-2-associated pro-coagulant state in hospitalized children.

METHODS

D-dimer values were recorded at diagnosis in children hospitalized for SARS-CoV-2-related manifestations. In moderately to critically ill patients and MIS-C cases, coagulation and inflammatory markers were checked at multiple time points and median results were compared. Pro-thrombotic risk factors were appraised for each child and thromboprophylaxis was started in selected cases.

RESULTS

Thirty-five patients were prospectively enrolled. D-dimer values did not discriminate COVID-19 of differing severity, whereas were markedly different between the COVID-19 and the MIS-C cohorts. In both cohorts, D-dimer and C-reactive protein levels increased upon clinical worsening but were not accompanied by decreased fibrinogen or platelet values, with all parameters returning to normal upon disease resolution. Six patients had multiple thrombotic risk factors and were started on pharmacological thromboprophylaxis. No deaths or thrombotic or bleeding complications occurred.

CONCLUSIONS

COVID-19 pediatric patients show mildly altered coagulation and inflammatory parameters; on the other hand, MIS-C cases showed laboratory signs of an inflammatory driven pro-coagulant status. Universal anticoagulant prophylaxis in hospitalized children with SARS-CoV-2-related manifestations is not warranted, but may be offered to patients with other pro-thrombotic risk factors in the context of a multi-modal therapeutic approach.