Combining personality traits with traditional risk factors for coronary stenosis: an artificial neural networks solution in patients with computed tomography detected coronary artery disease

Background. Coronary artery disease (CAD) is a complex, multifactorial disease in which personality seems to play a role but with no definition in combination with other risk factors. Objective. To explore the nonlinear and simultaneous pathways between traditional and personality traits risk factors and coronary stenosis by Artificial Neural Networks (ANN) data mining analysis. Method. Seventy-five subjects were examined for traditional cardiac risk factors and personality traits. Analyses were based on a new data mining method using a particular artificial adaptive system, the autocontractive map (AutoCM). Results. Several traditional Cardiovascular Risk Factors (CRF) present significant relations with coronary artery plaque (CAP) presence or severity. Moreover, anger turns out to be the main factor of personality for CAP in connection with numbers of traditional risk factors. Hidden connection map showed that anger, hostility, and the Type D personality subscale social inhibition are the core factors related to the traditional cardiovascular risk factors (CRF) specifically by hypertension. Discussion. This study shows a nonlinear and simultaneous pathway between traditional risk factors and personality traits associated with coronary stenosis in CAD patients without history of cardiovascular disease. In particular, anger seems to be the main personality factor for CAP in addition to traditional risk factors

Determinants of metabolic syndrome in obese workers: gender differences in perceived job-related stress and in psychological characteristics identified using artificial neural networks

Objective: The metabolic syndrome (MS) is a multifactorial disorder associated with a higher risk of developing cardiovascular diseases and type 2 diabetes. However, its pathophysiology and risk factors are still poorly understood. In this study, we investigated the associations among gender, psychosocial variables, job-related stress and the presence of MS in a cohort of obese Caucasian workers. Methods: A total of 210 outpatients (142 women, 68 men) from an occupational medicine service was enrolled in the study. Age, BMI, waist circumference, fasting glucose, blood pressure, triglycerides and HDL cholesterol were collected to define MS. In addition, we evaluated eating behaviors, depressive symptoms, and work-related stress. Data analyses were performed with an artificial neural network algorithm called Auto Semantic Connectivity Map (AutoCM), using all available variables. Results: MS was diagnosed in 54.4 and 33.1% of the men and women, respectively. AutoCM evidenced gender-specific clusters associated with the presence or absence of MS. Men with a moderate occupational physical activity, obesity, older age and higher levels of decision-making freedom at work were more likely to have a diagnosis of MS than women. Women with lower levels of decision-making freedom, and higher levels of psychological demands and social support at work had a lower incidence of MS but showed higher levels of binge eating and depressive symptomatology. Conclusion: We found a complex gender-related association between MS, psychosocial risk factors and occupational determinants. The use of these information in surveillance workplace programs might prevent the onset of MS and decrease the chance of negative long-term outcomes. Level of evidence: Level V, observational study

L'intelligenza artificiale al servizio dell'uomo e il controllo etico dell'algoritmo

Stiamo vivendo un cambiamento epocale. La vitalità, i valori e lo spirito sono quelli di sempre, ma l’evoluzione tecnologica sta andando velocemente oltre gli schemi sino ad oggi conosciuti, e noi ci sentiamo un po’ disallineati rispetto al mondo che gira sempre più veloce, con sistemi massivi che non riusciamo a governare appieno. È nostro dovere essere informati e “formati”, al fine di affrontare uno sviluppo inarrestabile con un approccio necessariamente antropocentrico ed un controllo “etico” che tuteli noi e le generazioni che verranno, nell’eterno antagonismo tra la libertà di iniziativa privata (art. 41 Cost.) e la necessaria regolazione del fenomeno, al fine di salvaguardare i diritti fondamentali dell’uomo e quelli del consumatore finale. In un momento in cui è centrale porre in essere tutte le azioni possibili per salvaguardare il pianeta in un’ottica di sostenibilità ed economia circolare, fin dalla fase di progettazione dei prodotti, l’Intelligenza Artificiale può rappresentare l’occasione di non perdere l’opportunità di salvare il pianeta dalla fame, dall’inquinamento, dai cambiamenti climatici, dalla povertà, dalle barbarie. Sebbene, infatti, la capacità di una macchina di mettere in correlazione grandi quantità di informazioni e dati, elaborarli secondo una determinata formula preconfezionata (l’algoritmo) e dare il risultato previsto e richiesto, può dirsi essere assimilabile all’intelligenza umana, è fuori di dubbio che alla stessa manchi la capacità del c.d. “discernimento”. Vale a dire, la capacità, tutta umana, di valutare e adattarsi alle molteplici variabili impreviste e/o imprevedibili. Conseguentemente, il giurista è chiamato a “interpretare” e “regolare” tale fenomeno, vieppiù tenuto conto della inevitabile dicotomia tra libertà di iniziativa economica privata e salvaguardia dei diritti inviolabili dell’uomo. È intuibile ed evidente che - nonostante la potenza elaborativa, la precisione e la velocità di esecuzione delle macchine consentirà un progresso esponenzialmente nei prossimi anni in quasi tutti i settori (i.e. sanità, medicina, agricoltura, ambiente, finanza, impresa, sicurezza, mobilità) - potranno determinarsi non trascurabili stravolgimenti e problematiche connessi, tra l’altro, al pericolo del cd. digital divide, al diritto del lavoro, alla cybersecurity, alla privacy ecc. Occorre, quindi, necessariamente riflettere e considerare la necessità di un “controllo etico” dell’algoritmo nonché di una sua “regolazione”. Ed invero, già vi sono ad oggi, pronunce dei giudici amministrativi (Cons. Stato, Sez. VI; Sent. 8 aprile 2019, n. 2270) che hanno confermato la necessità di trasparenza, accessibilità e “giustiziabilità” dell’algoritm

Pregnancy risk factors in autism: a pilot study with artificial neural networks

Autism is a multifactorial condition in which a single risk factor can unlikely provide comprehensive explanation for the disease origin. Moreover, due to the complexity of risk factors interplay, traditional statistics is often unable to explain the core of the problem due to the strong inherent nonlinearity of relationships. The aim of this study was to assess the frequency of 27 potential risk factors related to pregnancy and peri-postnatal period

Short-term effectiveness of dapagliflozin versus DPP-4 inhibitors in elderly patients with type 2 diabetes: a multicentre retrospective study

Aim To compare effectiveness of dapagliflozin versus DPP-4 inhibitors on individualized HbA1c targets and extra-glycaemic endpoints among elderly patients with type 2 diabetes (T2D).Methods This was a multicentre retrospective study on patients aged 70-80 years with HbA1c above individualized target and starting dapagliflozin or DPP-4 inhibitors in 2015-2017. The primary outcome was the proportion reaching individualized HbA1c targets. Confounding by indication was addressed by inverse probability of treatment weighting (IPTW), multivariable adjustment (MVA), or propensity score matching (PSM).Results Patients initiating dapagliflozin (n = 445) differed from those initiating DPP-4i (n = 977) and balance between groups was achieved with IPTW or PSM. The median follow-up was 7.5 months and baseline HbA1c was 8.3%. A smaller proportion of patients initiating dapagliflozin attained individualized HbA1c target as compared to those initiating DPP-4 inhibitors (RR 0.73, p < 0.0001). IPTW, MVA, and PSM yielded similar results. Between-group difference in the primary outcome was observed among patients with lower eGFR or longer disease duration. Dapagliflozin allowed greater reductions in body weight and blood pressure than DPP-4 inhibitors.Conclusions Elderly patients with T2D initiating dapagliflozin had a lower probability of achieving individualized HbA1c targets than those initiating DPP-4 inhibitors but displayed better improvements in extra-glycaemic endpoints