Mathematical multi-scale model of the cardiovascular system including mitral valve dynamics. Application to ischemic mitral insufficiency

Valve dysfunction is a common cardiovascular pathology. Despite significant clinical research, there is little formal study of how valve dysfunction affects overall circulatory dynamics. Validated models would offer the ability to better understand these dynamics and thus optimize diagnosis, as well as surgical and other interventions. A cardiovascular and circulatory system (CVS) model has already been validated in silico, and in several animal model studies. It accounts for valve dynamics using Heaviside functions to simulate a physiologically accurate “open on pressure, close on flow” law. However, it does not consider real-time valve opening dynamics and therefore does not fully capture valve dysfunction, particularly where the dysfunction involves partial closure. This research describes an updated version of this previous closed-loop CVS model that includes the progressive opening of the mitral valve, and is defined over the full cardiac cycle. Simulations of the cardiovascular system with healthy mitral valve are performed, and, the global hemodynamic behaviour is studied compared with previously validated results. The error between resulting pressure-volume (PV) loops of already validated CVS model and the new CVS model that includes the progressive opening of the mitral valve is assessed and remains within typical measurement error and variability. Simulations of ischemic mitral insufficiency are also performed. Pressure-Volume loops, transmitral flow evolution and mitral valve aperture area evolution follow reported measurements in shape, amplitude and trends. The resulting cardiovascular system model including mitral valve dynamics provides a foundation for clinical validation and the study of valvular dysfunction in vivo. The overall models and results could readily be generalised to other cardiac valves

Organ failure and tight glycemic control in the SPRINT study

INTRODUCTION: Intensive care unit mortality is strongly associated with organ failure rate and severity. The sequential organ failure assessment (SOFA) score is used to evaluate the impact of a successful tight glycemic control (TGC) intervention (SPRINT) on organ failure, morbidity, and thus mortality. METHODS: A retrospective analysis of 371 patients (3,356 days) on SPRINT (August 2005 - April 2007) and 413 retrospective patients (3,211 days) from two years prior, matched by Acute Physiology and Chronic Health Evaluation (APACHE) III. SOFA is calculated daily for each patient. The effect of the SPRINT TGC intervention is assessed by comparing the percentage of patients with SOFA 2) are also compared. Cumulative time in 4.0 to 7.0 mmol/L band (cTIB) was evaluated daily to link tightness and consistency of TGC (cTIB >/=0.5) to SOFA /=0.5 (37% Pre-SPRINT) reaching 100% by Day 7 (50% Pre-SPRINT). Conditional and joint probabilities indicate tighter, more consistent TGC under SPRINT (cTIB >/=0.5) increased the likelihood SOFA /=0.5 metric provides a first benchmark linking TGC quality to organ failure. These results support other physiological and clinical results indicating the role tight, consistent TGC can play in reducing organ failure, morbidity and mortality, and should be validated on data from randomised trials

Validation of a model-based virtual trials method for tight glycemic control in intensive care

peer reviewedBACKGROUND: In-silico virtual patients and trials offer significant advantages in cost, time and safety for designing effective tight glycemic control (TGC) protocols. However, no such method has fully validated the independence of virtual patients (or resulting clinical trial predictions) from the data used to create them. This study uses matched cohorts from a TGC clinical trial to validate virtual patients and in-silico virtual trial models and methods. METHODS: Data from a 211 patient subset of the Glucontrol trial in Liege, Belgium. Glucontrol-A (N = 142) targeted 4.4-6.1 mmol/L and Glucontrol-B (N = 69) targeted 7.8-10.0 mmol/L. Cohorts were matched by APACHE II score, initial BG, age, weight, BMI and sex (p > 0.25). Virtual patients are created by fitting a clinically validated model to clinical data, yielding time varying insulin sensitivity profiles (SI(t)) that drives in-silico patients.Model fit and intra-patient (forward) prediction errors are used to validate individual in-silico virtual patients. Self-validation (tests A protocol on Group-A virtual patients; and B protocol on B virtual patients) and cross-validation (tests A protocol on Group-B virtual patients; and B protocol on A virtual patients) are used in comparison to clinical data to assess ability to predict clinical trial results. RESULTS: Model fit errors were small (<0.25%) for all patients, indicating model fitness. Median forward prediction errors were: 4.3, 2.8 and 3.5% for Group-A, Group-B and Overall (A+B), indicating individual virtual patients were accurate representations of real patients. SI and its variability were similar between cohorts indicating they were metabolically similar.Self and cross validation results were within 1-10% of the clinical data for both Group-A and Group-B. Self-validation indicated clinically insignificant errors due to model and/or clinical compliance. Cross-validation clearly showed that virtual patients enabled by identified patient-specific SI(t) profiles can accurately predict the performance of independent and different TGC protocols. CONCLUSIONS: This study fully validates these virtual patients and in silico virtual trial methods, and clearly shows they can accurately simulate, in advance, the clinical results of a TGC protocol, enabling rapid in silico protocol design and optimization. These outcomes provide the first rigorous validation of a virtual in-silico patient and virtual trials methodology

First pilot trial of the STAR-Liege protocol for tight glycemic control in critically ill patients

peer reviewe

Pravastatin for early-onset pre-eclampsia:a randomised, blinded, placebo-controlled trial

Objective: Women with pre-eclampsia have elevated circulating levels of soluble fms-like tyrosine kinase-1 (sFlt-1). Statins can reduce sFlt-1 from cultured cells and improve pregnancy outcome in animals with a pre-eclampsia-like syndrome. We investigated the effect of pravastatin on plasma sFlt-1 levels during pre-eclampsia. Design: Blinded (clinician and participant), proof of principle, placebo-controlled trial. Setting: Fifteen UK maternity units. Population: We used a minimisation algorithm to assign 62 women with early-onset pre-eclampsia (24 +0–31 +6 weeks of gestation) to receive pravastatin 40 mg daily (n = 30) or matched placebo (n = 32), from randomisation to childbirth. Primary outcome: Difference in mean plasma sFlt-1 levels over the first 3 days following randomisation. Results: The difference in the mean maternal plasma sFlt-1 levels over the first 3 days after randomisation between the pravastatin (n = 27) and placebo (n = 29) groups was 292 pg/ml (95% CI −1175 to 592; P = 0.5), and over days 1–14 was 48 pg/ml (95% CI −1009 to 913; P = 0.9). Women who received pravastatin had a similar length of pregnancy following randomisation compared with those who received placebo (hazard ratio 0.84; 95% CI 0.50–1.40; P = 0.6). The median time from randomisation to childbirth was 9 days [interquartile range (IQR) 5–14 days] for the pravastatin group and 7 days (IQR 4–11 days) for the placebo group. There were three perinatal deaths in the placebo-treated group and no deaths or serious adverse events attributable to pravastatin. Conclusions: We found no evidence that pravastatin lowered maternal plasma sFlt-1 levels once early-onset pre-eclampsia had developed. Pravastatin appears to have no adverse perinatal effects. Tweetable abstract: Pravastatin does not improve maternal plasma sFlt-1 or placental growth factor levels following a diagnosis of early preterm pre-eclampsia #clinicaltrial finds

Combining Next-Generation Sequencing and Immune Assays: A Novel Method for Identification of Antigen-Specific T Cells

<div><p>In this study, we combined a novel sequencing method, which can identify individual clonotypes based on their unique T cell receptor (TCR) rearrangement, with existing immune assays to characterize antigen-specific T cell responses. We validated this approach using three types of assays routinely used to measure antigen-specific responses: pentamers which enable identification of T cells bearing specific TCRs, activation marker expression following antigen stimulation and antigen-induced proliferation to identify cytomegalovirus (CMV) specific clonotypes. In one individual, 8 clonotypes were identified using a pentamer reagent derived from the CMV pp65 protein. The same 8 clonotypes were also identified following sequencing of cells that upregulated an activation marker following incubation with an identical peptide derived from pp65. These 8 and an additional 8 clonotypes were identified using a more sensitive CFSE-based proliferation assay. We found clear sequence homology among some of the clonotypes identified, and the CDR3 region in one clonotype was identical to a previously published pp65-specific clonotype sequence. Many of these CMV-specific clonotypes were present at frequencies below 10⁻⁵ which are undetectable using standard flow-cytometric methods. These studies suggest that an immune response is comprised of a diverse set of clones, many of which are present at very low frequencies. Thus, the combination of immune assays and sequencing depicts the richness and diversity of an immune response at a level that is not possible using standard immune assays alone. The methods articulated in this work provide an enhanced understanding of T cell-mediated immune responses at the clonal level.</p></div

Efficacy and side effects of doxycycline versus minocycline in the three-dose melarsomine canine adulticidal heartworm treatment protocol

Abstract Background The American Heartworm Society currently recommends the use of a monthly macrocyclic lactone, a 28-day course of 10 mg/kg doxycycline BID, and the 3-dose protocol of melarsomine dihydrochloride for the treatment of canine heartworm disease. Doxycycline is necessary for the reduction of the bacterium Wolbachia, found in all heartworm life-stages. Previous price increases and decreasing availability prompted us to evaluate alternative tetracycline antibiotics, i.e. minocycline, for the reduction of Wolbachia during canine heartworm treatment. Methods Thirty-two heartworm-positive dogs were randomized to receive 10 mg/kg or 5 mg/kg of either doxycycline or minocycline for 28 days BID, for a total of 8 dogs per experimental group. All dogs received 6 months of Heartgard Plus® (ivermectin/pyrantel) and the 3-dose protocol of 2.5 mg/kg melarsomine dihydrochloride. Blood samples were collected prior to the initiation of treatment, every 7 days throughout tetracycline treatment, and then monthly thereafter until the dog tested negative for the presence of heartworm antigen. DNA was isolated from circulating microfilarial samples and qPCR was performed on each sample. Results A greater number of dogs in the 10 mg/kg doxycycline and minocycline treated groups experienced gastrointestinal side effects as compared to the 5 mg/kg doxycycline and minocycline treated groups. All eight dogs in the 10 mg/kg doxycycline-treated group tested negative for the presence of Wolbachia DNA by 28 days post-tetracycline treatment. A total of two dogs in both the 5 mg/kg doxycycline- and 10 mg/kg minocycline-treated groups and three dogs in the 5 mg/kg minocycline-treated group remained positive for the presence of Wolbachia DNA by the end of tetracycline treatment. Conclusions No lung pathology was assessed in this clinical trial, therefore the clinical effect of the remaining Wolbachia DNA in the 10 mg/kg minocycline-, 5 mg/kg doxycycline- and 5 mg/kg minocycline-treated groups cannot be determined. Owner compliance in the proper administration of these tetracyclines may be impacted by the increased severe gastrointestinal side effects reported for the 10 mg/kg doxycycline- and minocycline-treated groups. We recommend that veterinarians prescribe the recommended 10 mg/kg doxycycline for canine heartworm treatment and reduce the dosage to 5 mg/kg in cases of severe gastrointestinal side effects in order to improve owner compliance in administration of medications