To scan or not to scan - D-dimers and computed tomography pulmonary angiography in the era of COVID-19

Clinico-radiological and pulmonary function assessment of post-COVID-19 patients with respiratory symptoms

Background

Respiratory symptoms may persist for several weeks following the initial coronavirus disease 2019 (COVID-19) infection. The aims and objectives were to assess the clinical symptoms, pulmonary functions, and radiological changes and to assess the cardio-vascular complications in post-COVID-19 patients.

Methods

This observational study was conducted in the Department of Pulmonary Medicine in collaboration with the Department of Cardiology, SCBMCH, Cuttack, from March 2021 to August 2022 on 75 post-COVID-19 patients with respiratory symptoms from 4 weeks to 2 years after treatment for COVID-19 infection. Post-COVID patients having previous respiratory diseases were excluded from the study.

Results

Among 75 patients, the most common age group was 18-30 years with a male-to-female ratio of 2.5:1. Based on O2 requirement, patients were divided into the mild symptomatic group and moderate to severe pneumonia group. The most common respiratory symptom was dyspnea, followed by cough with expectoration. Bilateral crepitations were found in 17% of cases. C-reactive protein (CRP) and D-dimer were increased in 38.6% and 32% of patients, respectively. 42.6% had abnormal chest X-ray, and the most common abnormal finding was reticular thickening. In spirometry, the restrictive pattern and mixed pattern were the predominant types documented in 49.3% and 13.3% of cases, respectively, which were significant in the moderate-severe group. Diffusion capacity of the lungs for carbon monoxide (DLCO) was performed in only 19 patients (mild group 13 and moderate-severe group 6). Twelve (63.2%) patients had abnormal DLCO. P- values were significant for RV (0.0482) and RV/TLC (0.0394). High-resolution computed tomography (HRCT) of the thorax was abnormal in 55.7% with the most common abnormalities as inter- and intra-lobular septal thickening. The left ventricular ejection fraction was preserved in all patients, with right atrium and right ventricle enlargement in 2.6% and pulmonary hypertension in 4.0% of participants.

Conclusion

All post-COVID-19 patients having respiratory symptoms after recovery from acute COVID-19 may be referred by family care physicians to a dedicated post-COVID center for further evaluation, management, and early rehabilitation to decrease the morbidity in recovered patients. Persistent increased blood parameters like TLC, N/L ratio, RBS, CRP, and D-dimer seen in recovered post-COVID-19 patients. The long-term impact of CT findings on respiratory symptoms, pulmonary functions, and quality of life is unknown. Cardiovascular abnormalities in post-COVID-19 patients are infrequent.

Construction and validation of risk prediction models for pulmonary embolism in hospitalized patients based on different machine learning methods

Objective

This study aims to apply different machine learning (ML) methods to construct risk prediction models for pulmonary embolism (PE) in hospitalized patients, and to evaluate and compare the predictive efficacy and clinical benefit of each model.

Methods

We conducted a retrospective study involving 332 participants (172 PE positive cases and 160 PE negative cases) recruited from Guangdong Medical University. Participants were randomly divided into a training group (70%) and a validation group (30%). Baseline data were analyzed using univariate analysis, and potential independent risk factors associated with PE were further identified through univariate and multivariate logistic regression analysis. Six ML models, namely Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Naive Bayes (NB), Support Vector Machine (SVM), and AdaBoost were developed. The predictive efficacy of each model was compared using the receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC). Clinical benefit was assessed using decision curve analysis (DCA).

Results

Logistic regression analysis identified lower extremity deep venous thrombosis, elevated D-dimer, shortened activated partial prothrombin time, and increased red blood cell distribution width as potential independent risk factors for PE. Among the six ML models, the RF model achieved the highest AUC of 0.778. Additionally, DCA consistently indicated that the RF model offered the greatest clinical benefit.

Conclusion

This study developed six ML models, with the RF model exhibiting the highest predictive efficacy and clinical benefit in the identification and prediction of PE occurrence in hospitalized patients.

Simple demographic, laboratory and chest radiograph variables can identify COVID-19 patients with pulmonary thromboembolism: a retrospective multicentre United Kingdom study

OBJECTIVES

To (1) identify discriminatory demographic, laboratory and initial CXR findings; (2) explore correlation between D-dimer and radiographic severity scores; and (3) assess accuracy of published D-dimer thresholds to identify pulmonary thromboembolism (PTE) in COVID-19 patients.

METHODS

Retrospective study including all COVID-19 patients admitted from 1st to 30th April 2020 meeting inclusion criteria from 25 (blinded) hospitals. Demographics, blood results, CXR and CTPA findings were compared between positive and negative PTE cohorts using uni- and multivariable logistic regression. Published D-dimer cut-offs were applied.

RESULTS

389 patients were included [median age 63; 237 males], of which 26.2% had a PTE. Significant univariable discriminators for PTE were peak D-dimer, sex, neutrophil count at the time of the D-dimer and at admission, abnormal CXR, and CXR zonal severity score. Only neutrophil count at peak D-dimer remained significant for predicting PTE on multivariable analysis (p = 0.008). When compared with the published literature, sensitivity for PTE were lower than those published at all cut-off values, however specificity at different cut-offs was variable.

CONCLUSIONS

In this multicentre COVID-19 cohort, univariable admission factors that could indicate pulmonary thromboembolism were male sex, high neutrophil count and abnormal CXR with a greater CXR zonal severity score. The accuracy levels of published D-dimer thresholds were not reproducible in our population.

ADVANCES IN KNOWLEDGE

This is a large multicentre study looking at the discriminatory value of simple variables to determine if a patient with COVID-19 has PTE or not, in addition to comparing D-dimer cut off values against published values.

Assessment and Monitoring of Coagulation in Patients with COVID-19: A Review of Current Literature

Coagulation abnormalities are common in patients with COVID-19 and associated with high morbidity and mortality. It became a daily challenge to navigate through these abnormal laboratory findings and deliver the best possible treatment to the patients. The unique character of COVID-19-induced coagulopathy necessitates not only a dynamic follow-up of the patients in terms of hemostatic findings but also the introduction of new diagnostic methods to determine the overall function of the coagulation system in real time. After the recognition of the high risk of thromboembolism in COVID-19, several professional societies published their recommendations regarding anticoagulation in patients with COVID-19. This review summarizes common hemostatic findings in COVID-19 patients and presents the societal recommendations regarding the use of coagulation laboratory findings in clinical decision-making. Although several studies have investigated coagulation parameters in patients with COVID-19, the methodological shortcomings of published studies as well as the differences in employed anticoagulation regimens that have changed over time, depending on national and international guidelines, limit the applicability of these findings in other clinical settings. Accordingly, evidence-based recommendations for diagnostics during acute COVID-19 infection are still lacking. Future studies should verify the role of coagulation parameters as well as viscoelastic methods in the management of patients with COVID-19.

D-Dimer as a Sensitive Biomarker of Survival Rate in Patients with COVID-19

OBJECTIVE

The global case fatality rate of coronavirus disease 2019 is 2.16% as announced by the World Health Organization. In Indonesia, according to the Ministry of Health, the number is even higher, reaching a 2.8% case fatality rate. D-dimer levels were found to affect coronavirus disease 2019 patient's survival in several studies. The study aimed to determine whether the amount of D-dimer predicted survival in coronavirus disease 2019 patients.

MATERIALS AND METHODS

This research was performed in a retrospective cohort design and used survival analysis. From March 1, 2020, to August 31, 2020, the samples were collected from polymerase chain reaction-confirmed coronavirus disease 2019 patients at Mohammad Hoesin General Hospital in Palembang, South Sumatera, Indonesia. We used electronic medical records to obtain demographic (age and gender), coexisting condition, laboratory (coagulation and hematologic test), and outcome (non-survivors or survivors) data. The chi-square and Mann-Whitney tests were used to evaluate the results. The Kaplan-Meier method and the Mantel-Haenszel log-rank test were used to examine D-dimer levels and patient outcomes. Youden index was calculated to determine the optimal cut-off value of D-dimer.

RESULTS

There were 52 non-survivors and 235 survivors among the 287 patients who met the inclusion criterion. Non-survivors had D-dimer levels of more than 1.49 mg/L in 82.69%of cases. Males had lower cut-off compared to females (>1.49 mg/L vs. >2.2 mg/L). The researchers discovered a highly significant correlation between D-dimer levels and coronavirus disease 2019 mortality (P=.001). The c-index analysis showed that D-dimer (0.79, 95% CI: 0.73-0.83) ability for mortality prediction was the second-best compared with other laboratory markers.

CONCLUSION

D-dimer can be used as a predictor of coronavirus disease 2019 in-hospital mortality for early identification of coagulopathy.