A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease

Background: Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated. Objectives: To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD. Methods: From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis < 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cytokines was measured with a multiplex flow cytometry assay. Through an XGBoost classifier combined with an explainable artificial intelligence tool (SHAP), we identified the most influential features in discriminating obstructive versus non-obstructive CAD. Results: Among the overall EVA cohort (n = 509), 311 individuals (mean age 67 ± 11 years, 38% females; 67% obstructive CAD) with complete data were analysed. The ML-based model (83% accuracy and 87% precision) showed that while obstructive CAD was associated with higher frailty index, older age and a cytokine signature characterized by IL-1β, IL-12p70 and IL-33, non-obstructive CAD was associated with a higher gender score (i.e., social characteristics traditionally ascribed to women) and with a cytokine signature characterized by IL-18, IL-8, IL-23. Conclusions: Integrating clinical, biological, and psycho-social features, we have optimized a sex- and gender-unbiased model that discriminates obstructive and non-obstructive CAD. Further mechanistic studies will shed light on the biological plausibility of these associations. Clinical trial registration: NCT02737982

The Sex-Specific Detrimental Effect of Diabetes and Gender-Related Factors on Pre-admission Medication Adherence Among Patients Hospitalized for Ischemic Heart Disease: Insights From EVA Study

Background: Sex and gender-related factors have been under-investigated as relevant determinants of health outcomes across non-communicable chronic diseases. Poor medication adherence results in adverse clinical outcomes and sex differences have been reported among patients at high cardiovascular risk, such as diabetics. The effect of diabetes and gender-related factors on medication adherence among women and men at high risk for ischemic heart disease (IHD) has not yet been fully investigated.Aim: To explore the role of sex, gender-related factors, and diabetes in pre-admission medication adherence among patients hospitalized for IHD.Materials and Methods: Data were obtained from the Endocrine Vascular disease Approach (EVA) (ClinicalTrials.gov Identifier: NCT02737982), a prospective cohort of patients admitted for IHD. We selected patients with baseline information regarding the presence of diabetes, cardiovascular risk factors, and gender-related variables (i.e., gender identity, gender role, gender relations, institutionalized gender). Our primary outcome was the proportion of pre-admission medication adherence defined through a self-reported questionnaire. We performed a sex-stratified analysis of clinical and gender-related factors associated with pre-admission medication adherence.Results: Two-hundred eighty patients admitted for IHD (35% women, mean age 70), were included. Around one-fourth of the patients were low-adherent to therapy before hospitalization, regardless of sex. Low-adherent patients were more likely diabetic (40%) and employed (40%). Sex-stratified analysis showed that low-adherent men were more likely to be employed (58 vs. 33%) and not primary earners (73 vs. 54%), with more masculine traits of personality, as compared with medium-high adherent men. Interestingly, women reporting medication low-adherence were similar for clinical and gender-related factors to those with medium-high adherence, except for diabetes (42 vs. 20%, p = 0.004). In a multivariate adjusted model only employed status was associated with poor medication adherence (OR 0.55, 95%CI 0.31–0.97). However, in the sex-stratified analysis, diabetes was independently associated with medication adherence only in women (OR 0.36; 95%CI 0.13–0.96), whereas a higher masculine BSRI was the only factor associated with medication adherence in men (OR 0.59, 95%CI 0.35–0.99).Conclusion: Pre-admission medication adherence is common in patients hospitalized for IHD, regardless of sex. However, patient-related factors such as diabetes, employment, and personality traits are associated with adherence in a sex-specific manner

Tibial Component Alignment May Improve By Setting The Extramedullary Instrumentation To The Proximal Tibia Only

BACKGROUND: A proper alignment of total knee arthroplasty (TKA) was found to influence knee biomechanics and long term survival of the implants. However, using standard instrumentation, varus-valgus malalignment of tibial component greater than 3° has been reported in 2% to 40% of cases. A major issue in achieving a correct coronal when extramedullary instrumentation are used for tibial cut, is tibial torsion, i.e., the axial rotation of the tibia along its longitudinal axis. As tibial torsion causes a rotational mismatch between proximal and distal ephiphysis, the anterior projection of mechanical axis at the distal tibia is externally rotated compared to the proximal one, whereby if the centre of intermalleolar axis is used ad distal reference for the extarmedullary road, a varus tibial cut is likely to occur. OBJECTIVE: In this study we investigated the accuracy of a new surgical technique in which the influence of tibial torsion on the alignment of the tibial component is bypassed by positioning the extramedullary guide in line with the proximal tibia only MATERIAL AND METHODS : Eighty-six patients (94 knees) with primary or secondary osteoarthritis of the knee who underwent underwent TKA were analysed. There were 49 women and 37 men with a mean age of 72 years (range 53-86 years). In the first 43 patients (47 knees) a standard procedure was used (group 1) while in the second 43 patients (47 knees) operated on in the following year, a modified surgical technique was performed (group 2). In particular, the extramedullary guide was set in line with the proximal alignment on the TT (medial 1/3), leaving the extramedullary rod locked in neutral alignment (varus-valgus= 0) in the malleolar clamp, without align it to any anatomical landamark. Limb and components alignment, including femoro-tibial alngke (FTA), femoro-tibial mechanical axis and femur and tibia component alignmnet was assessed on postoperative long-leg radiographs taken 3 months after surgery. A FTA between 2° to 8° of valgus and a component and FT mechanical axis alignment of 0± 3° of varus/valgus were considered within the normal range. RESULTS: A FTA within the normal range was found in 39 (83%) knees in gr 1 and in 41 (87%) of group 2 (p= 0.3). The mean FT mechanical axis was 3.4°± 1.9 in group 1 and 2.7 ± 1.8 in group 2 (p=0.07). Femoral component alignment averaged 2.1° ± 2.4 in group 1 and 1.7 ± 2.1 in group 2 (p=0.3) Tibial component alignment in the coronal plane averaged -2° ± 1.9 in group 1 and - 0.6° ± 1.8 in group 2 (p=0.0001). A varus malalignmnet of the tibial component (>3°) in the coronal plane was present in 16 and in 2 knees of group I and II, respectively (p=0.0008). CONCLUSIONS: The results of this study showed that, by setting the extramedullary road to the anterior projection of the mechanical axis at the proximal tibia and maintaining the same axial orientation of extramedullary road at the ankle joint, the effects of tibial torsion on the distal alignment of the extramedullary systems may be neutralized. This was found to improve the percentage of patients with neutral alignment and reduce significantly the rate of malalignment in varus of tibial component