Predictive analytics for cardiovascular patient readmission and mortality: An explainable approach

Background: Cardiovascular patients experience high rates of adverse outcomes following discharge from hospital, which may be preventable through early identification and targeted action. This study aimed to investigate the effectiveness and explainability of machine learning algorithms in predicting unplanned readmission and death in cardiovascular patients at 30 days and 180 days from discharge. Methods: Gradient boosting machines were trained and evaluated using data from hospital electronic medical records linked to hospital administrative and mortality data for 39,255 patients admitted to four hospitals in New South Wales, Australia between 2017 and 2021. Sociodemographic variables, admission history, and clinical information were used as potential predictors. The performance was compared to LASSO regression, as well as the HOSPITAL and LACE risk score indices. Important risk factors identified by the gradient-boosting machine model were explored using Shapley values. Results: The models performed well, especially for the mortality outcomes. Area under the receiver operating characteristic curve values were 0.70 for readmission and 0.87–0.90 for mortality using the full gradient boosting machine algorithms. Among the top predictors for 30-day and 180-day readmission were increased red cell distribution width, old age (especially above 80 years), high measured troponin and urea levels, not being married or in a relationship, and low albumin levels. For mortality, these included increased red cell distribution width, old age (especially older than 70 years), high measured troponin and urea levels, high neutrophil and monocyte counts, and low eosinophil and lymphocyte counts. The Shapley values gave clear insight into the dynamics of decision-tree-based models. Conclusions: We demonstrated an explainable predictive algorithm to identify cardiovascular patients who are at high risk of readmission or death at discharge from the hospital and identified key risk factors

Genetic and clinical features of hemoglobin H disease in Chinese patients

Background. Normally, one pair of each of the two α-globin genes, α1 and α2, resides on each copy of chromosome 16. In hemoglobin H disease, three of these four α-globin genes are affected by a deletion, a mutation, or both. We studied the α-globin gene abnormalities and the clinical and hematologic features of Chinese patients with hemoglobin H disease in Hong Kong. Methods. We assessed the clinical features, hematologic values, serum ferritin levels, and liver function of 114 patients with hemoglobin H disease. We also performed echocardiography and magnetic resonance imaging of the liver and examined the two pairs of α-globin genes. Results. Hemoglobin H disease in 87 of the 114 patients (76 percent) was due to the deletion of three of the four α-globin genes (--/-α), a combination termed the deletional type of hemoglobin H. The remaining 27 patients (24 percent) had the nondeletional type of hemoglobin H disease, in which two α-globin genes are deleted and a third is mutated (--/αα(T)). All 87 patients with the deletional type of hemoglobin H were double heterozygotes in whom there was a deletion of both α-globin genes from one chromosome, plus a deletion of the α1 or α2 gene from the other chromosome (--/α- or --/-α). A variety of mutated α-globin genes was found in the patients with nondeletional type of hemoglobin H disease. Patients with the nondeletional type of the H disease had more symptoms at a younger age, more severe hemolytic anemia, and larger spleens and were more likely to require transfusions than patients with deletional hemoglobin H disease. The severity of iron overload was not related to the genotype. Conclusions. Chinese patients in Hong Kong with the nondeletional type of hemoglobin H disease have more severe disease than those with the deletional type of the disease. Iron overload is a major cause of disability in both forms of the disease. (C) 2000, Massachusetts Medical Society.published_or_final_versio

A new and automated risk prediction of coronary artery disease using clinical endpoints and medical imaging-derived patient-specific insights: protocol for the retrospective GeoCAD cohort study

INTRODUCTION: Coronary artery disease (CAD) is the leading cause of death worldwide. More than a quarter of cardiovascular events are unexplained by current absolute cardiovascular disease risk calculators, and individuals without clinical risk factors have been shown to have worse outcomes. The 'anatomy of risk' hypothesis recognises that adverse anatomical features of coronary arteries enhance atherogenic haemodynamics, which in turn mediate the localisation and progression of plaques. We propose a new risk prediction method predicated on CT coronary angiography (CTCA) data and state-of-the-art machine learning methods based on a better understanding of anatomical risk for CAD. This may open new pathways in the early implementation of personalised preventive therapies in susceptible individuals as a potential key in addressing the growing burden of CAD. METHODS AND ANALYSIS: GeoCAD is a retrospective cohort study in 1000 adult patients who have undergone CTCA for investigation of suspected CAD. It is a proof-of-concept study to test the hypothesis that advanced image-derived patient-specific data can accurately predict long-term cardiovascular events. The objectives are to (1) profile CTCA images with respect to variations in anatomical shape and associated haemodynamic risk expressing, at least in part, an individual's CAD risk, (2) develop a machine-learning algorithm for the rapid assessment of anatomical risk directly from unprocessed CTCA images and (3) to build a novel CAD risk model combining traditional risk factors with these novel anatomical biomarkers to provide a higher accuracy CAD risk prediction tool. ETHICS AND DISSEMINATION: The study protocol has been approved by the St Vincent's Hospital Human Research Ethics Committee, Sydney-2020/ETH02127 and the NSW Population and Health Service Research Ethics Committee-2021/ETH00990. The project outcomes will be published in peer-reviewed and biomedical journals, scientific conferences and as a higher degree research thesis

Effect of remote ischemic preConditioning on liver injury in patients undergoing liver resection: the ERIC-LIVER trial

OBJECTIVE: Novel hepatoprotective strategies are needed to improve clinical outcomes during liver surgery. There is mixed data on the role of remote ischemic preconditioning (RIPC). We investigated RIPC in partial hepatectomy for primary hepatocellular carcinoma (HCC). METHODS: This was a Phase II, single-center, sham-controlled, randomized controlled trial (RCT). The primary hypothesis was that RIPC would reduce acute liver injury following surgery indicated by serum alanine transferase (ALT) 24 h following hepatectomy in patients with primary HCC, compared to sham. Patients were randomized to receive either four cycles of 5 min/5 min arm cuff inflation/deflation immediately prior to surgery, or sham. Secondary endpoints included clinical, biochemical and pathological outcomes. Liver function measured by Indocyanine Green pulse densitometry was performed in a subset of patients. RESULTS: 24 and 26 patients were randomized to RIPC and control groups respectively. The groups were balanced for baseline characteristics, except the duration of operation was longer in the RIPC group. Median ALT at 24 h was similar between groups (196 IU/L IQR 113.5-419.5 versus 172.5 IU/L IQR 115-298 respectively, p = 0.61). Groups were similar in secondary endpoints. CONCLUSION: This RCT did not demonstrate beneficial effects with RIPC on serum ALT levels 24 h after partial hepatectomy

Intracellular interferons in fish : a unique means to combat viral infection

Peer reviewedPublisher PD

Automated segmentation of normal and diseased coronary arteries – The ASOCA challenge

Cardiovascular disease is a major cause of death worldwide. Computed Tomography Coronary Angiography (CTCA) is a non-invasive method used to evaluate coronary artery disease, as well as evaluating and reconstructing heart and coronary vessel structures. Reconstructed models have a wide array of for educational, training and research applications such as the study of diseased and non-diseased coronary anatomy, machine learning based disease risk prediction and in-silico and in-vitro testing of medical devices. However, coronary arteries are difficult to image due to their small size, location, and movement, causing poor resolution and artefacts. Segmentation of coronary arteries has traditionally focused on semi-automatic methods where a human expert guides the algorithm and corrects errors, which severely limits large-scale applications and integration within clinical systems. International challenges aiming to overcome this barrier have focussed on specific tasks such as centreline extraction, stenosis quantification, and segmentation of specific artery segments only. Here we present the results of the first challenge to develop fully automatic segmentation methods of full coronary artery trees and establish the first large standardized dataset of normal and diseased arteries. This forms a new automated segmentation benchmark allowing the automated processing of CTCAs directly relevant for large-scale and personalized clinical applications

Impact of incomplete percutaneous revascularization in patients with multi-vessel coronary artery disease: a systematic review and meta-analysis

Background Up to half of patients undergoing percutaneous coronary intervention have multivessel coronary artery disease (MVD) with conflicting data regarding optimal revascularization strategy in such patients. This paper assesses the evidence for complete revascularization (CR) versus incomplete revascularization in patients undergoing percutaneous coronary intervention, and its prognostic impact using meta‐analysis. Methods and Results A search of PubMed, EMBASE, MEDLINE, Current Contents Connect, Google Scholar, Cochrane library, Science Direct, and Web of Science was conducted to identify the association of CR in patients with multivessel coronary artery disease undergoing percutaneous coronary intervention with major adverse cardiac events and mortality. Random‐effects meta‐analysis was used to estimate the odds of adverse outcomes. Meta‐regression analysis was conducted to assess the relationship with continuous variables and outcomes. Thirty‐eight publications that included 156 240 patients were identified. Odds of death (OR 0.69, 95% CI 0.61‐0.78), repeat revascularization (OR 0.60, 95% CI 0.45‐0.80), myocardial infarction (OR 0.64, 95% CI 0.50‐0.81), and major adverse cardiac events (OR 0.63, 95% CI 0.50‐0.79) were significantly lower in the patients who underwent CR. These outcomes were unchanged on subgroup analysis regardless of the definition of CR. Similar findings were recorded when CR was studied in the chronic total occlusion (CTO) subgroup (OR 0.65, 95% CI 0.53‐0.80). A meta‐regression analysis revealed a negative relationship between the OR for mortality and the percentage of CR. Conclusion CR is associated with reduced risk of mortality and major adverse cardiac events, irrespective of whether an anatomical or a score‐based definition of incomplete revascularization is used, and this magnitude of risk relates to degree of CR. These results have important implications for the interventional management of patients with multivessel coronary artery disease

Brief Overview of Bioinformatics Activities in Singapore

10.1371/journal.pcbi.1000508PLoS Computational Biology5

A phase I trial of preoperative radiotherapy and capecitabine for locally advanced, potentially resectable rectal cancer

The purpose of the study was to determine the maximum-tolerated dose (MTD) of oral capecitabine, combined with concurrent, standard preoperative pelvic radiotherapy, when given twice daily, from Monday to Friday throughout the course of radiotherapy, for locally advanced potentially resectable rectal cancer. Maximum-tolerated dose was defined as the total (given in two equally divided doses) oral dose of capecitabine that caused treatment-related grade 3 or 4 toxicity in one-third or more of the patients treated. Radiotherapy involved 50.4 Gy given in 28 fractions in 5 weeks and 3 days. Eligible patients had a newly diagnosed clinical stage T3–4 N0–2 M0 rectal adenocarcinoma located within 12 cm of the anal verge suitable for curative resection. Surgery was performed 4–6 weeks from completion of preoperative chemoradiotherapy. In all, 28 patients were enrolled in the study at predefined dose levels: 850 mg m−2 day−1 (n=3), 1000 mg m−2 day−1 (n=6), 1250 mg m−2 day−1 (n=3), 1650 mg m−2 day−1 (n=3), 1800 mg m−2 day−1 (n=8) and 2000 mg m−2 day−1 (n=5). The mean age was 62.3 years (range: 33–80 years). Five patients were female and 23 male. The median distance of tumour from the anal verge was 6 cm (range: 1–11 cm). Endorectal ultrasound was performed in 93% of patients. A total of 26 patients (93%) had T3 disease and two patients had resectable T4 disease. Dose-limiting toxicity (DLT) developed in one patient at dose level 1000 mg m−2 day−1 (RTOG grade 3 cystitis). Two of the five patients at dose level 2000 mg m−2 day−1 had a total of three DLT (grade 3 perineal skin reaction, grade 3 diarrhoea and grade 3 dehydration). Dose escalation of capecitabine was ceased at 2000 mg m−2 day−1 after reaching MTD. None of the eight patients at dose level 1800 mg m−2 day−1 developed DLT. All except one patient underwent surgery. A total of 15 patients had the clinical T stage reduced by at least one stage in pathologic specimens. Five patients (19%) achieved a pathologic complete response. We conclude that the MTD of capecitabine was reached at a dose level of 2000 mg m−2 day−1, given as 1000 mg m−2 twice daily, from Monday to Friday throughout the course of preoperative pelvic irradiation of 50.4 Gy. For patients with resectable rectal cancer receiving concurrent, full dose radiotherapy, the recommended dose of capecitabine for further study is 1800 mg m−2 day−1 when given in this schedule