Platelet count and risk of major bleeding in venous thromboembolism

Establishing reflex test rules for platelet fluorescent counting method using machine learning models on Sysmex XN-series hematology analyzer

INTRODUCTION

The platelet fluorescent counting (PLT-F) method is utilized as a reflex test method following the initial test of the platelet impedance counting (PLT-I) method in clinical practice on the Sysmex XN-series automated hematology analyzer. Our aim is to establish reflex test rules for the PLT-F method by combining multiple parameters provided by the "CBC + DIFF" mode of the Sysmex XN-series automated hematology analyzer.

METHODS

We tested 120 samples to evaluate the baseline bias between the PLT-F and PLT-I methods. Then, we selected 1256 samples to establish and test reflex test rules using seven machine learning models (decision Tree, random forest, neural network, logistic regression, k-nearest neighbor, support vector machine, and Naive Bayes). The training set and test set were divided at a ratio of 7:3. We evaluated the performance of machine learning models on the test set using various metrics to select the most valuable model.

RESULTS

The PLT-F method exhibited a high degree of correlation with the PLT-I method (r = 0.998). The random forest model emerged as the most valuable, boasting an accuracy of 0.893, an area under the curve of 0.954, an F1 score of 0.771, a recall of 0.719, a precision of 0.831, and a specificity of 0.950. The most important variable in the random forest model was mean cell volume, weighted at 15.09%.

CONCLUSION

The random forest model, which demonstrated high efficiency in our study, can be used to establish PLT reflex test rules based on the PLT-F method for the Sysmex XN-series automated hematology analyzer.

Platelet count has a U-shaped association with mortality in hemodialysis patients

Our previous manuscript showed that thrombocytopenia predicts all-cause mortality in Chinese hemodialysis (HD) patients. Based on the role of platelets in coagulation, clot formation, and systemic inflammation, we speculate that high platelets increase risk of thrombo-embolic events, hence the mortality. However, research evidence is currently lacking. Therefore, we utilized data from a very large international cohort study to explore the association of platelet counts with mortality and cardiovascular (CV) death in hemodialysis (HD) patients. International data from 396 facilities enrolled in the Dialysis Outcomes and Practice Patterns Study (DOPPS) phase 5 (2012-2015) were analyzed. Participants were divided into 3 groups according to their platelet counts (low: <100, normal: 100-300, high: >300*109). Associations between platelet counts and all-cause and CV mortality were analyzed using Cox regression, adjusted for confounders. There were 13,631 patients with median age of 65 years old. Males accounted for 61.2%. Mean platelet count was 205*109/L overall and ranged from 173 *109/L in China to 227 *109/L in Sweden. Overall, 2,348 (17.2%) patients died and 1017 (7.5%) died from CV disease. Both low (HR:1.48, 95% CI 1.21-1.80, p < 0.001) and high (HR:1.17, 95% CI 1.00- 1.35, p = 0.044) platelet counts were associated with higher all-cause mortality after adjustment for covariates; results for CV death were consistent. Platelet count has a U-shaped association with all-cause and CV mortality in HD patients, and thus may be used as an outcome predictor that is readily available among HD patients.

Baseline platelet count and long-term clinical outcomes in patients with acute venous thromboembolism: a prospective cohort study

An abnormal platelet count (PC) is common in acute venous thromboembolism (VTE) but its relationship with clinical outcomes remains ill-defined. We aimed to explore the association between baseline PC and the long-term risk of clinically relevant outcomes in a prospective cohort of 991 patients with acute VTE. We classified patients into four PC groups: very low (< 100 G/l), low (≥ 100 to < 150 G/l), normal (≥ 150 G/l to ≤ 450 G/l), and high (> 450 G/l). The primary outcome was major bleeding (MB), secondary outcomes were recurrent VTE and overall mortality. We examined the association between PC and clinical outcomes, adjusting for confounders, competing risk for mortality, and periods of anticoagulation. After a median follow-up of 30 months, 132 (13%) of patients experienced MB, 122 (12%) had recurrent VTE, and 206 (21%) died. Compared to patients with a normal PC, patients with a very low PC had a sub-distribution hazard ratio (SHR) for MB of 1.23 (95% confidence interval [CI] 0.52-2.91) and those with a high PC a SHR of 1.87 (95%CI 0.82-4.29). Patients with a low PC had a twofold increased VTE recurrence risk (SHR 2.05, 95%CI 1.28-3.28). Patients with low and very low PC had a hazard ratio for mortality of 1.43 (95%CI 0.99-2.08) and of 1.55 (95%CI 0.80-2.99), respectively. Our findings do not suggest a consistent relationship between baseline PC and long-term clinical outcomes in patients with VTE.

Broad-Spectrum Antiviral Peptides and Polymers

As the human cost of the pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still being witnessed worldwide, the development of broad-spectrum antiviral agents against emerging and re-emerging viruses is seen as a necessity to hamper the spread of infections. Various targets during the viral life-cycle can be considered to inhibit viral infection, from viral attachment to viral fusion or replication. Macromolecules represent a particularly attractive class of therapeutics due to their multivalency and versatility. Although several antiviral macromolecules hold great promise in clinical applications, the emergence of resistance after prolonged exposure urges the need for improved solutions. In the present article, the recent advancement in the discovery of antiviral peptides and polymers with diverse structural features and antiviral mechanisms is reviewed. Future perspectives, such as, the development of virucidal peptides/polymers and their coatings against SARS-CoV-2 infection, standardization of antiviral testing protocols, and use of artificial intelligence or machine learning as a tool to accelerate the discovery of antiviral macromolecules, are discussed.

Combined effects of plasma von Willebrand factor and platelet measures on the risk of incident venous thromboembolism

Plasma von Willebrand factor (VWF) and platelet reactivity are both risk factors for venous thromboembolism (VTE), and VWF can promote hemostasis by interaction with platelets. In this study, we explored the combined effects of plasma VWF and platelet measures on the risk of incident VTE. A population-based nested case-control study with 403 cases and 816 controls was derived from the Tromsø Study. VWF, platelet count and mean platelet volume (MPV) were measured in blood samples drawn at baseline. Odds ratios (ORs) with 95% confidence intervals (CIs) for VTE were estimated across VWF tertiles, within predefined MPV (<8.5, 8.5-9.5, ≥9.5 fL) and platelet count (<230, 230-299, ≥300·109 L-1) strata. Here, participants with VWF levels in the highest tertile and MPV ≥9.5 fL had an OR of 1.98 (95% CI 1.17-3.36) for VTE compared with those in the lowest VWF tertile and with MPV <8.5 fL in the age- and sex-adjusted model. In the joint exposure group, 48% (95% CI 15% to 96%) of VTEs were attributable to the biological interaction between VWF and MPV. Similarly, individuals with VWF in the highest tertile and platelet count ≥300·109 L-1 had an OR of 2.91 (95% CI 1.49-5.67) compared with those with VWF in the lowest tertile and platelet count <230, and 39% (95% CI -2% to 97%) of VTEs in the joint exposure group were explained by the interaction. Our results suggest that both platelet reactivity and platelet count interact biologically with high plasma VWF, resulting in an increased risk of incident VTE.