Oral anticoagulant management of patients with mechanical heart valves at the Salam Centre of Khartoum:Observations on quality of anticoagulation and thrombotic risk

IntroductionRheumatic heart disease with mechanical heart valve (MHV) replacement is common in Africa. However, MHV requires long-life anticoagulation and managing this can be challenging.Methods and resultsWe report data of a prospective observational study conducted between August 2018 and September 2019 in MHV patients in the Salam Centre for Cardiac Surgery built in Khartoum, by Emergency, an Italian Non-Governmental Organization, to evaluate the quality of anticoagulation control and the risk of thrombotic complications.ResultsWe studied 3647 patients (median age 25.1 years; 53.9 % female). Median Time in Therapeutic Range (TTR) was 53 % (interquartile range 37 % to 67 %) and 70 thrombotic events (rate 1.8 × 100 pt-years [95 % CI 1.38-2.23]) were recorded. Among patients in the first quartile of TTR (≤37 %), we recorded 34/70 (48.6 %) of all thrombotic events (rate 3.7 × 100 pt-years [95 % CI 2.5-5.1]), with a high mortality rate (2.2 × 100 pt-years [95 % CI 1.3-3.3]). In patients with guideline-recommended TTR (≥65 %) the event rate was 0.8 × 100 pt-years for thrombotic events [95 % CI 0.3-1.5] and 0.4 × 100 pt-years for mortality [95 % CI 0.1-0.9]. Multivariable analysis showed that having a TTR in the lowest quartile (≤37 %) and being noncompliant are significantly associated with increased thrombotic risk. Aspirin use or different valve type did not influence the thrombotic risk. Almost 40 % of all thromboembolic complications could have been potentially prevented by further improving VKA management to obtain a TTR > 37 %.ConclusionThe thrombotic risk of MHV patients on VKAs living in a low-income country like Sudan is associated with low quality of anticoagulation control. Efforts should be made to decrease the number of non-compliant patients and to reach a guideline-recommended TTR of ≥65 %

Electrochemically active water repelling perfluorinated polyaniline films

Water repelling, perfluorinated, polyanilines and their composites with multi-wall carbon nanotubes are synthesized using interfacial polymerization in either flake-like or fibrillar shapes. This class of polyanilines exhibits electrochemical activity, capacitive behaviour, and a contact angle of 119–125° with water. The addition of multi-wall carbon nanotubes facilitates the control of the polymer morphology and increases the specific capacitance of the material. We obtained microfibers or flake-like morphologies depending on the amount of multiwall carbon nanotubes added in the organic phase and through cyclic voltammetry, impedance spectroscopy and galvanostatic charge-discharge, we evaluated the effect of the backbone geometry and the addition of nanotubes on the electrochemical properties of the composites and the pristine polymers. The capacitance of the linear 3-perfluoroctyl polyaniline is consistently better than the cross-linked 4-perfluoroctyl polyaniline, where the para position relative to the amine group is blocked by fluorocarbon chains

Rates and Determinants of Hospital-Acquired Infection among ICU Patients Undergoing Cardiac Surgery in Developing Countries: Results from EMERGENCY’NGO’s Hospital in Sudan

Introduction. Knowledge of local and regional antimicrobial resistance (AMR) is crucial in clinical decision-making, especially with critically ill patients. The aim of this study was to investigate the rate and pattern of infections in valvular heart disease patients admitted to the intensive care unit (ICU) at the Salam Centre for Cardiac Surgery in Khartoum, Sudan (run by EMERGENCY NGO). Methods. This is a retrospective, observational study from a single, large international referral centre (part of a Regional Programme), which enrolled patients admitted to the ICU between 1 January and 31 December 2019. Data collected for each patient included demographic data, operating theatre/ICU data and microbiological cultures. Results. Over the study period, 611 patients were enrolled (elective surgery n = 491, urgent surgery n = 34 and urgent medical care n = 86). The infection rate was 14.2% and turned out to be higher in medical than in surgical patients (25.6% vs. 12.4%; p = 0.002; OR = 2.43) and higher in those undergoing urgent surgery than those undergoing elective (29.4% vs. 11.2%; p = 0.004; OR = 3.3). Infection was related to (a) SOFA score (p < 0.001), (b) ICU length of stay (p < 0.001) and (c) days from ICU admission to OT (p = 0.003). A significant relationship between the type of admission (elective, urgent surgery or medical) and the presence of infections was found (p < 0.001). The mortality rate was higher among infected patients (infected vs. infection-free: 10.3% vs. 2.1%; p < 0.001; OR = 5.38; 95% CI: 2.16–13.4; p < 0.001). Conclusions. Hospital-acquired infections remain a relevant preventable cause of mortality in our particular population

Metabolic heterogeneity on baseline 18FDG-PET/CT scan is a predictor of outcome in primary mediastinal B-cell lymphoma

An important unmet need in the management of primary mediastinal B-cell lymphoma (PMBCL) is to identify the patients for whom first line therapy will fail, in order to intervene before the lymphoma becomes refractory. High heterogeneity of intratumoral 18F-fluorodeoxyglucose (18FDG) uptake distribution on positron emission tomography/computed tomography (PET/CT) scans has been suggested as a possible marker of chemo-resistance in solid tumors. In the present study, we investigated the prognostic value of metabolic heterogeneity (MH) in 103 PMBCL patients prospectively enrolled in the International Extranodal Lymphoma Study Group (IELSG) 26 study, aimed at clarifying the role of PET in this lymphoma subtype. MH was estimated using the area under curve of cumulative SUV-volume histogram (AUC-CSH) method. Progression-free survival (PFS) at 5 years was 94% versus 73% in low and high MH groups, respectively (p=0.0001). In a Cox model of progression-free survival including dichotomized MH, metabolic tumor volume (MTV), total lesion glycolysis (TLG), international prognostic index (IPI) and tumor bulk (mediastinal mass >10 cm), as well as age as a continuous variable, only TLG (p<0.001) and MH (p<0.001) retained statistical significance. Using these two features to construct a simple prognostic model resulted in early and accurate (PPV=89% and NPV≥90%) identification of patients at high risk of progression, at a point that would allow the use of risk-adapted treatments. This may provide an important opportunity for the design of future trials, aimed at helping the minority of patients who harbor chemorefractory PMBCL. The study is registered to www.clinicaltrials.gov as NCT00944567

Automated Prediction of Kidney Failure in IgA Nephropathy with Deep Learning from Biopsy Images

Background and objectives Digital pathology and artificial intelligence offer new opportunities for automatic histologic scoring. We applied a deep learning approach to IgA nephropathy biopsy images to develop an automatic histologic prognostic score, assessed against ground truth (kidney failure) among patients with IgA nephropathy who were treated over 39 years. We assessed noninferiority in comparison with the histologic component of currently validated predictive tools. We correlated additional histologic features with our deep learning predictive score to identify potential additional predictive features. Design, setting, participants, &amp; measurements Training for deep learning was performed with randomly selected, digitalized, cortical Periodic acid-Schiff-stained sections images (363 kidney biopsy specimens) to develop our deep learning predictive score. We estimated noninferiority using the area under the receiver operating characteristic curve (AUC) in a randomly selected group (95 biopsy specimens) against the gold standard Oxford classification (MEST-C) scores used by the International IgA Nephropathy Prediction Tool and the clinical decision supporting system for estimating the risk of kidney failure in IgA nephropathy. We assessed additional potential predictive histologic features against a subset (20 kidney biopsy specimens) with the strongest and weakest deep learning predictive scores. Results We enrolled 442 patients; the 10-year kidney survival was 78%, and the study median follow-up was 6.7 years. Manual MEST-C showed no prognostic relationship for the endocapillary parameter only. The deep learning predictive score was not inferior to MEST-C applied using the International IgA Nephropathy Prediction Tool and the clinical decision supporting system (AUC of 0.84 versus 0.77 and 0.74, respectively) and confirmed a good correlation with the tubolointerstitial score (r50.41, P,0.01). We observed no correlations between the deep learning prognostic score and the mesangial, endocapillary, segmental sclerosis, and crescent parameters. Additional potential predictive histopathologic features incorporated by the deep learning predictive score included (1) inflammation within areas of interstitial fibrosis and tubular atrophy and (2) hyaline casts. Conclusions The deep learning approach was noninferior to manual histopathologic reporting and considered prognostic features not currently included in MEST-C assessment