Artificial intelligence-based preventive, personalized and precision medicine for cardiovascular disease/stroke risk assessment in rheumatoid arthritis patients: a narrative review

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Abstract

The challenges associated with diagnosing and treating cardiovascular disease (CVD)/Stroke in Rheumatoid arthritis (RA) arise from the delayed onset of symptoms. Existing clinical risk scores are inadequate in predicting cardiac events, and conventional risk factors alone do not accurately classify many individuals at risk. Several CVD biomarkers consider the multiple pathways involved in the development of atherosclerosis, which is the primary cause of CVD/Stroke in RA. To enhance the accuracy of CVD/Stroke risk assessment in the RA framework, a proposed approach involves combining genomic-based biomarkers (GBBM) derived from plasma and/or serum samples with innovative non-invasive radiomic-based biomarkers (RBBM), such as measurements of synovial fluid, plaque area, and plaque burden. This review presents two hypotheses: (i) RBBM and GBBM biomarkers exhibit a significant correlation and can precisely detect the severity of CVD/Stroke in RA patients. (ii) Artificial Intelligence (AI)-based preventive, precision, and personalized (aiP3) CVD/Stroke risk AtheroEdge™ model (AtheroPoint™, CA, USA) that utilizes deep learning (DL) to accurately classify the risk of CVD/stroke in RA framework. The authors conducted a comprehensive search using the PRISMA technique, identifying 153 studies that assessed the features/biomarkers of RBBM and GBBM for CVD/Stroke. The study demonstrates how DL models can be integrated into the AtheroEdge™-aiP3 framework to determine the risk of CVD/Stroke in RA patients. The findings of this review suggest that the combination of RBBM with GBBM introduces a new dimension to the assessment of CVD/Stroke risk in the RA framework. Synovial fluid levels that are higher than normal lead to an increase in the plaque burden. Additionally, the review provides recommendations for novel, unbiased, and pruned DL algorithms that can predict CVD/Stroke risk within a RA framework that is preventive, precise, and personalized.

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Learning long-term dependencies with gradient descent is difficult.

Y Bengio, P. Simard, P Frasconi (1994)

Recurrent neural networks can be used to map input sequences to output sequences, such as for recognition, production or prediction problems. However, practical difficulties have been reported in training recurrent neural networks to perform tasks in which the temporal contingencies present in the input/output sequences span long intervals. We show why gradient based learning algorithms face an increasingly difficult problem as the duration of the dependencies to be captured increases. These results expose a trade-off between efficient learning by gradient descent and latching on information for long periods. Based on an understanding of this problem, alternatives to standard gradient descent are considered.

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Inflammation and atherosclerosis.

Peter Libby, Paul Ridker, Attilio Maseri (2002)

Atherosclerosis, formerly considered a bland lipid storage disease, actually involves an ongoing inflammatory response. Recent advances in basic science have established a fundamental role for inflammation in mediating all stages of this disease from initiation through progression and, ultimately, the thrombotic complications of atherosclerosis. These new findings provide important links between risk factors and the mechanisms of atherogenesis. Clinical studies have shown that this emerging biology of inflammation in atherosclerosis applies directly to human patients. Elevation in markers of inflammation predicts outcomes of patients with acute coronary syndromes, independently of myocardial damage. In addition, low-grade chronic inflammation, as indicated by levels of the inflammatory marker C-reactive protein, prospectively defines risk of atherosclerotic complications, thus adding to prognostic information provided by traditional risk factors. Moreover, certain treatments that reduce coronary risk also limit inflammation. In the case of lipid lowering with statins, this anti-inflammatory effect does not appear to correlate with reduction in low-density lipoprotein levels. These new insights into inflammation in atherosclerosis not only increase our understanding of this disease, but also have practical clinical applications in risk stratification and targeting of therapy for this scourge of growing worldwide importance.

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0.9% saline versus Plasma-Lyte as initial fluid in children with diabetic ketoacidosis (SPinK trial): a double-blind randomized controlled trial

Vijai Williams, Muralidharan Jayashree, Karthi Nallasamy … (2020)

Background Acute kidney injury (AKI) is an important complication encountered during the course of diabetic ketoacidosis (DKA). Plasma-Lyte with lower chloride concentration than saline has been shown to be associated with reduced incidence of AKI in adults with septic shock. No study has compared this in DKA. Methods This double-blind, parallel-arm, investigator-initiated, randomized controlled trial compared 0.9% saline with Plasma-Lyte-A as initial fluid in pediatric DKA. The study was done in a tertiary care, teaching, and referral hospital in India in children (> 1 month–12 years) with DKA as defined by ISPAD. Children with cerebral edema or known chronic kidney/liver disease or who had received pre-referral fluids and/or insulin were excluded. Sixty-six children were randomized to receive either Plasma-Lyte (n = 34) or 0.9% saline (n = 32). Main outcomes Primary outcome was incidence of new or progressive AKI, defined as a composite outcome of change in creatinine (defined by KDIGO), estimated creatinine clearance (defined by p-RIFLE), and NGAL levels. The secondary outcomes were resolution of AKI, time to resolution of DKA (pH > 7.3, bicarbonate> 15 mEq/L & normal sensorium), change in chloride, pH and bicarbonate levels, proportion of in-hospital all-cause mortality, need for renal replacement therapy (RRT), and length of ICU and hospital stay. Results Baseline characteristics were similar in both groups. The incidence of new or progressive AKI was similar in both [Plasma-Lyte 13 (38.2%) versus 0.9% saline 15 (46.9%); adjusted OR 1.22; 95% CI 0.43–3.43, p = 0.70]. The median (IQR) time to resolution of DKA in Plasma-Lyte-A and 0.9% saline were 14.5 (12 to 20) and 16 (8 to 20) h respectively. Time to resolution of AKI was similar in both [Plasma-Lyte 22.1 versus 0.9% saline 18.8 h (adjusted HR 1.72; 95% CI 0.83–3.57; p = 0.14)]. Length of hospital stay was also similar in both [Plasma-Lyte 9 (8 to 12) versus 0.9% saline 10 (8.25 to 11) days; p = 0.39]. Conclusions The incidence of new or progressive AKI and resolution of AKI were similar in both groups. Plasma-Lyte-A was similar to 0.9% Saline in time to resolution of DKA, need for RRT, mortality, and lengths of PICU and hospital stay. Trial registration Clinical trial registry of India, CTRI/2018/05/014042 (ctri.nic.in) (Retrospectively registered).