Diagnostic accuracy of a novel optical coherence tomography-based fractional flow reserve algorithm for assessment of coronary stenosis significance

Background: This study aimed to introduce a novel optical coherence tomography-derived fractional flow reserve (FFR) computational approach and assess the diagnostic performance of the algorithm for assessing physiological function. Methods: The fusion of coronary optical coherence tomography and angiography was used to generate a novel FFR algorithm (AccuFFRoct) to evaluate functional ischemia of coronary stenosis. In the current study, a total of 34 consecutive patients were included, and AccuFFRoct was used to calculate the FFR for these patients. With the wire-measured FFR as the reference standard, we evaluated the performance of our approach by accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results: Per vessel accuracy, sensitivity, specificity, PPV, and NPV for AccuFFRoct in identifying hemodynamically significant coronary stenosis were 93.8%, 94.7%, 92.3%, 94.7%, and 92.3%, respectively, were found. Good correlation (Pearson’s correlation coefficient r = 0.80, p < 0.001) between AccuFFRoct and FFR was observed. The Bland-Altman analysis showed a mean difference value of –0.037 (limits of agreement: –0.189 to 0.115). The area under the receiver-operating characteristic curve (AUC) of AccuFFRoct in identifying physiologically significant stenosis was 0.94, which was higher than the minimum lumen area (MLA, AUC = 0.91) and significantly higher than the diameter stenosis (%DS, AUC = 0.78). Conclusions: This clinical study shows the efficiency and accuracy of AccuFFRoct for clinical implementation when using invasive FFR measurement as a reference. It could provide important insights into coronary imaging superior to current methods based on the degree of coronary artery stenosis

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Predictive value of machine learning algorithm of coronary artery calcium score and clinical factors for obstructive coronary artery disease in hypertensive patients

Abstract Background The addition of coronary artery calcium score (CACS) to prediction models has been verified to improve performance. Machine learning (ML) algorithms become important medical tools in an era of precision medicine, However, combined utility by CACS and ML algorithms in hypertensive patients to forecast obstructive coronary artery disease (CAD) on coronary computed tomography angiography (CCTA) is rare. Methods This retrospective study was composed of 1,273 individuals with hypertension and without a history of CAD, who underwent dual-source computed tomography evaluation. We applied five ML algorithms, coupled with clinical factors, imaging parameters, and CACS to construct predictive models. Moreover, 80% individuals were randomly taken as a training set on which 5-fold cross-validation was done and the remaining 20% were regarded as a validation set. Results 16.7% (212 out of 1,273) of hypertensive patients had obstructive CAD. Extreme Gradient Boosting (XGBoost) posted the biggest area under the receiver operator characteristic curve (AUC) of 0.83 in five ML algorithms. Continuous net reclassification improvement (NRI) was 0.55 (95% CI (0.39–0.71), p < 0.001), and integrated discrimination improvement (IDI) was 0.04 (95% CI (0.01–0. 07), p = 0.0048) when the XGBoost model was compared with traditional Models. In the subgroup analysis stratified by hypertension levels, XGBoost still had excellent performance. Conclusion The ML model incorporating clinical features and CACS may accurately forecast the presence of obstructive CAD on CCTA among hypertensive patients. XGBoost is superior to other ML algorithms

Triglyceride glucose index is associated with obstructive coronary artery disease in hypertensive patients

Abstract Background Hypertension is a leading risk of coronary artery disease (CAD). Triglyceride glucose index (TyG) is a surrogate of insulin resistance (IR). Few studies explore the association between TyG and the incidence of obstructive CAD (OCAD) in hypertensive patients. Methods We retrospectively screened 1841 hypertensive subjects who were free of a history of CAD and underwent coronary computed tomography angiography (CCTA) because of chest pain. TyG index was calculated as ln (fasting TG [mg/dL] * fasting glucose [mg/dL]/2). The outcome of this research was OCAD, which was defined as the presence of diameter stenosis ≥ 50% in any of the four major epicardial coronary arteries detected on CCTA. Results A total of 310 (16.8%) patients developed obstructive CAD. The restricted cubic spline (RCS) analysis showed a J-shaped relationship between TyG and OCAD and the OR for OCAD increased as the TyG rose over 8.61 (OR perSD) 1.64, 95% CI 1.13–2.54, p = 0.008). After full adjustments for confounding covariates, patients with TyG index in tertile 3 (T3) had 2.12 times (95% CI 1.80 to 3.81) and in T2 had 2.01 times (95% CI 1.40 to 2.88) as high as the risk of OCAD compared with patients in T1 (p for trend = 0.001). When regarding TyG as a continuous variable, 1-SD increase elevated 49% (OR (95%CI), 1.49 (1.30–1.74)) risk of obstructive CAD (p = 0.007). This positive effect was still consistent across the subgroups (p for interaction > 0.05). Conclusion TyG index was associated with the incidence of obstructive CAD in hypertensive patients