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Special Issues
Individualized Antithrombotic Risk Assessment & Therapy
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Individualized Antithrombotic Risk Assessment & Therapy

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Methodology, Drug and Device Discovery".

Deadline for manuscript submissions: closed (20 April 2023) | Viewed by 4336

Special Issue Editors

Dr. Prahlad Ho

E-Mail Website
Guest Editor
1. Northern Clinical Diagnostics and ThrombovAscular Research (NECTAR) Center, Northern Health, Epping, Melbourne, VIC 3076, Australia
2. Diagnostic Services, Northern Health, Epping, Australia
3. Australian Centre for Blood Diseases, Monash University, Prahran, Melbourne, Australia
4. Department of Medicine, Northern Health, University of Melbourne, Epping, Australia
Interests: thrombosis; anticoagulation; venous thromboembolism; pulmonary embolism; hematology
Special Issues, Collections and Topics in MDPI journals
Dr. Amir Houshang Shemirani

E-Mail Website
Guest Editor
Division of Clinical Laboratory Science, Department of Laboratory Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
Interests: hematological indices in different diseases: environmental, inflammatory and genetic influences

Special Issue Information

Dear Colleagues,

One of the key challenges in the management of thrombotic and cardiovascular diseases is the need to carefully balance bleeding and thrombotic risk. This equilibrium is physiologically maintained by the careful counter-balancing of procoagulant and anticoagulant proteins and is in close relation with the endothelium and vessel flow. This homeostasis can be influenced by numerous risk factors and disrupted by a variety of pathophysiological events, resulting in thrombotic and cardiovascular diseases as well as bleeding. Anticoagulation as well as antiplatelet agents are some of the critical management strategies used in the attempt to restore the equilibrium. The management of anticoagulation and antiplatelet therapies in these conditions requires the careful identification of high-risk individuals and the individualisation of therapy to optimise anti-thrombotic effects while minimising bleeding complications. While the introduction of direct oral anticoagulants has improved both thrombotic and bleeding outcomes, further optimisation at the level of the individual is still required. The aim of this Special Issue is to explore the safety of current therapies as well as the ability of clinical risk assessment models and available diagnostic markers to effectuate an individualised approach for the prevention and treatment of thrombotic and cardiovascular diseases.

We invite original research articles and reviews on topics that may include but are not limited to:

  • Clinical risk assessment models in thrombotic and cardiovascular diseases.
  • Novel biomarkers, including global coagulation assays, proteomic markers, and other coagulation and/or endothelial biomarkers.
  • The management of anticoagulation and/or antiplatelet therapies, including monitoring and dose adjustment.
  • The management of rare thrombotic disorders, including cerebral venous thrombosis and splanchnic vein thrombosis.
  • The management of anticoagulation in:
    • Cancer patients;
    • Obese patients;
    • Antiphospholipid syndrome;
    • Venous thrombosis with clinical equipoise for long-term anticoagulation;
    • Peripheral vascular diseases, cerebral artery diseases, and/or coronary artery diseases.

Dr. Prahlad Ho
Dr. Amir Houshang Shemirani
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • anticoagulation
  • thrombosis
  • cardiovascular and peripheral vascular disease
  • coagulation biomarkers
  • thrombotic risk assessment

Published Papers (2 papers)

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Research

12 pages, 805 KiB  
Article
High Neutrophil–Lymphocyte Ratio and Low Lymphocyte–Monocyte Ratio Combination after Thrombolysis Is a Potential Predictor of Poor Functional Outcome of Acute Ischemic Stroke
by Farzaneh Sadeghi, Ferenc Sarkady, Katalin S. Zsóri, István Szegedi, Rita Orbán-Kálmándi, Edina G. Székely, Nikolett Vasas, Ervin Berényi, László Csiba, Zsuzsa Bagoly and Amir H. Shemirani
J. Pers. Med. 2022, 12(8), 1221; https://doi.org/10.3390/jpm12081221 - 27 Jul 2022
Cited by 9 | Viewed by 2019
Abstract
(1) Background: Ischemic stroke is one of the leading causes of death and disability. An inflammatory response is observed in multiple stages of cerebral ischemia, particularly in the acute phase. Recent publications revealed that the neutrophil–lymphocyte ratio (NLR) and lymphocyte–monocyte ratio (LMR) may [...] Read more.
(1) Background: Ischemic stroke is one of the leading causes of death and disability. An inflammatory response is observed in multiple stages of cerebral ischemia, particularly in the acute phase. Recent publications revealed that the neutrophil–lymphocyte ratio (NLR) and lymphocyte–monocyte ratio (LMR) may be used to predict long-term prognosis in acute ischemic stroke (AIS) after thrombolysis. To test whether there is a relationship between the combination of these parameters and long-term prognosis, we analyzed the NLR–LMR combination in AIS patients treated with intravenous recombinant tissue plasminogen activator (rtPA); (2) Methods: The study included 285 adults with a diagnosis of AIS and rtPA treatment within a 4.5 h time window. Blood samples were obtained at admission and 24 h after thrombolysis to calculate pre- and post-thrombolysis NLR and LMR. Clinical data, including NIHSS was registered on admission and day 1. The long-term outcome was defined 90 days post-event by the modified Rankin Scale (mRS). Therapy-associated intracranial hemorrhage (ICH) was classified according to ECASS II. Receiver operating characteristic curve (ROC) analysis was performed to determine optimal cutoffs of NLR and LMR as predictors of therapy outcomes; (3) Results: Patients were stratified by cutoffs of 5.73 for NLR and 2.08 for LMR. The multivariate logistic regression model, including all possible confounders, displayed no significant association between NLR or LMR with 3-months functional prognosis. The combination of high NLR–low LMR vs. low NRL–high LMR as obtained 24 h after thrombolysis was found to be an independent predictor of poor 3-months functional outcome (mRS ≥ 2; OR 3.407, 95% CI 1.449 to 8.011, p = 0.005). The proportion of patients between low NLR–high LMR and high NLR–low LMR groups from admission to day 1 showed no significant change in the good outcome group. On the other hand, in the poor outcome group (mRS ≥ 2), low NLR–high LMR and high NLR–low LMR groups displayed a significant shift in patient proportions from 67% and 21% at admission (p = 0.001) to 36% and 49% at 24 h after thrombolysis (p < 0.001), respectively; (4) Conclusions: Our study demonstrated for the first time that a high NLR–low LMR combination as observed at 24 h after thrombolysis can serve as an independent predictor of 3-months poor outcome in AIS patients. This simple and readily available data may help clinicians to improve the prognostic estimation of patients and may provide guidance in selecting patients for personalized and intensified care post-thrombolysis. Full article
(This article belongs to the Special Issue Individualized Antithrombotic Risk Assessment & Therapy)
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17 pages, 1111 KiB  
Article
Nonlinear Machine Learning in Warfarin Dose Prediction: Insights from Contemporary Modelling Studies
by Fengying Zhang, Yan Liu, Weijie Ma, Shengming Zhao, Jin Chen and Zhichun Gu
J. Pers. Med. 2022, 12(5), 717; https://doi.org/10.3390/jpm12050717 - 29 Apr 2022
Cited by 3 | Viewed by 1688
Abstract
Objective: This study aimed to systematically assess the characteristics and risk of bias of previous studies that have investigated nonlinear machine learning algorithms for warfarin dose prediction. Methods: We systematically searched PubMed, Embase, Cochrane Library, Chinese National Knowledge Infrastructure (CNKI), China Biology [...] Read more.
Objective: This study aimed to systematically assess the characteristics and risk of bias of previous studies that have investigated nonlinear machine learning algorithms for warfarin dose prediction. Methods: We systematically searched PubMed, Embase, Cochrane Library, Chinese National Knowledge Infrastructure (CNKI), China Biology Medicine (CBM), China Science and Technology Journal Database (VIP), and Wanfang Database up to March 2022. We assessed the general characteristics of the included studies with respect to the participants, predictors, model development, and model evaluation. The methodological quality of the studies was determined, and the risk of bias was evaluated using the Prediction model Risk of Bias Assessment Tool (PROBAST). Results: From a total of 8996 studies, 23 were assessed in this study, of which 23 (100%) were retrospective, and 11 studies focused on the Asian population. The most common demographic and clinical predictors were age (21/23, 91%), weight (17/23, 74%), height (12/23, 52%), and amiodarone combination (11/23, 48%), while CYP2C9 (14/23, 61%), VKORC1 (14/23, 61%), and CYP4F2 (5/23, 22%) were the most common genetic predictors. Of the included studies, the MAE ranged from 1.47 to 10.86 mg/week in model development studies, from 2.42 to 5.18 mg/week in model development with external validation (same data) studies, from 12.07 to 17.59 mg/week in model development with external validation (another data) studies, and from 4.40 to 4.84 mg/week in model external validation studies. All studies were evaluated as having a high risk of bias. Factors contributing to the risk of bias include inappropriate exclusion of participants (10/23, 43%), small sample size (15/23, 65%), poor handling of missing data (20/23, 87%), and incorrect method of selecting predictors (8/23, 35%). Conclusions: Most studies on nonlinear-machine-learning-based warfarin prediction models show poor methodological quality and have a high risk of bias. The analysis domain is the major contributor to the overall high risk of bias. External validity and model reproducibility are lacking in most studies. Future studies should focus on external validity, diminish risk of bias, and enhance real-world clinical relevance. Full article
(This article belongs to the Special Issue Individualized Antithrombotic Risk Assessment & Therapy)
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