Common cardiovascular risk factors and in-hospital mortality in 3,894 patients with COVID-19: survival analysis and machine learning-based findings from the multicentre Italian CORIST Study

Castelnuovo, Augusto Di; Bonaccio, Marialaura; Costanzo, Simona; Gialluisi, Alessandro; Antinori, Andrea; Berselli, Nausicaa; Blandi, Lorenzo; Bruno, Raffaele; Cauda, Roberto; Guaraldi, Giovanni; My, Ilaria; Menicanti, Lorenzo; Parruti, Giustino; Patti, Giuseppe; Perlini, Stefano; Santilli, Francesca; Signorelli, Carlo; Stefanini, Giulio G.; Vergori, Alessandra; Abdeddaim, Amina; Ageno, Walter; Agodi, Antonella; Agostoni, Piergiuseppe; Aiello, Luca Maria; Moghazi, Samir Al; Aucella, Filippo; Barbieri, Greta; Bartoloni, Alessandro; Bologna, Carolina; Bonfanti, Paolo; Brancati, Serena; Cacciatore, Francesco; Caiano, Lucia; Cannata, F.; Carrozzi, Laura; Cascio, Antonio; Cingolani, Antonella; Cipollone, Francesco; Colomba, Claudia; Crisetti, Annalisa; Crosta, Francesca; Danzi, Gian Battista; D’Ardes, Damiano; Donati, Katleen de Gaetano; Gennaro, Francesco Di; Palma, Gisella Di; Tano, Giuseppe Di; Fantoni, Massimo; Filippini, Tommaso; Fioretto, Paola

doi:10.1016/j.numecd.2020.07.031

Cited by 150 publications

(120 citation statements)

References 29 publications

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“…Of note, cardiovascular disease includes hypertension, history of myocardial infarction, stroke, congestive heart failure, and other forms of heart disease. Its low effect on predicting mortality is consistent with the observations in [32].…”

Section: Discussionsupporting

confidence: 89%

Physiological and socioeconomic characteristics predict COVID-19 mortality and resource utilization in Brazil

et al. 2020

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Background Given the severity and scope of the current COVID-19 pandemic, it is critical to determine predictive features of COVID-19 mortality and medical resource usage to effectively inform health, risk-based physical distancing, and work accommodation policies. Non-clinical sociodemographic features are important explanatory variables of COVID-19 outcomes, revealing existing disparities in large health care systems.

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Section: Discussionsupporting

confidence: 89%

Physiological and socioeconomic characteristics predict COVID-19 mortality and resource utilization in Brazil

et al. 2020

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“…This national retrospective observational study was conceived, coordinated and analyzed within the CORIST Collaboration Project (ClinicalTrials.gov ID: NCT04318418). The CORIST Collaboration is a set of multicenter observational studies launched in March 2020, and aimed at testing the association of inhibitors of the renin-angiotensin system, risk factors and therapies with severity and mortality of COVID-19 hospitalized patients [13]. The study was approved by the institutional Ethics Board of the Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Neuromed, Pozzilli, and of all recruiting centers.…”

Section: Settingmentioning

confidence: 99%

“…Clinical data were abstracted at one-time point from electronic medical records or charts, and collected using either a centrally-designed electronic worksheet or a centralized web-based database. Collected data included patients' demographics, laboratory test results, medication administration, historical and current medication lists, historical and current diagnoses, and clinical notes [13]. In addition, specific information on the most severe manifestation of COVID-19 that occurred during hospitalization was retrospectively captured.…”

Section: Data Sourcesmentioning

confidence: 99%

RAAS inhibitors are not associated with mortality in COVID-19 patients: Findings from an observational multicenter study in Italy and a meta-analysis of 19 studies

Castelnuovo¹,

Costanzo²,

Antinori³

et al. 2020

Vascular Pharmacology

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The hypothesis that been set forward that use of Renin Angiotensin Aldosterone System (RAAS) inhibitors is associated with COVID−19 severity. We setup a multicenter Italian collaboration (CORIST Project, ClinicalTrials.gov ID: NCT04318418) to retrospectively investigate the relationship between RAAS inhibitors and COVID−19 in-hospital mortality. We also carried out an updated meta-analysis on the relevant studies. Methods: We analyzed 4069 unselected patients with laboratory-confirmed SARS-CoV-2 infection and hospitalized in 34 clinical centers in Italy from February 19, 2020 to May 23, 2020. The primary end-point in a time-to event analysis was in-hospital death, comparing patients who received angiotensin-converting-enzyme inhibitors (ACEeI) or angiotensin-receptor blockers (ARB) with patients who did not. Articles for the meta-analysis were retrieved until July 13th, 2020 by searching in web-based libraries, and data were combined using the general variance-based method. Results: Out of 4069 COVID−19 patients, 13.5% and 13.3% received ACE-I or ARB, respectively. Use of neither ACE-I nor ARB was associated with mortality (multivariable hazard ratio (HR) adjusted also for COVID−19 treatments: 0.96, 95% confidence interval 0.77-1.20 and HR = 0.89, 0.67-1.19 for ACE-I and ARB, respectively). Findings were similar restricting the analysis to hypertensive (N = 2057) patients (HR = 1.00, 0.78-1.26 and HR = 0.88, 0.65-1.20) or when ACE-I or ARB were considered as a single group. Results from the meta-analysis (19 studies, 29,057 COVID−19 adult patients, 9700 with hypertension) confirmed the absence of association. Conclusions: In this observational study and meta-analysis of the literature, ACE-I or ARB use was not associated with severity or in-hospital mortality in COVID−19 patients.

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“…Many of the poorer outcomes, including increased mortality due to COVID-19 have been related to cardiovascular comorbid conditions [37][38][39]. However, a large multicentre study conducted in Italy contrasts this finding and reports on factors such as age, renal impairment and high C-reactive protein levels to have strong predictive roles for mortality [40]. Another important aspect to look out for especially in sub-Sahara Africa is the occurrence of COVID-19 and malaria incidence.…”

Section: Plos Onementioning

confidence: 99%

Epidemiological profile of SARS-CoV-2 among selected regions in Ghana: A cross-sectional retrospective study

et al. 2020

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Background Global cases of COVID-19 continue to rise, causing havoc to several economies. So far, Ghana has recorded 48,643 confirmed cases with 320 associated deaths. Although summaries of data are usually provided by the Ministry of Health, detailed epidemiological profile of cases are limited. This study sought to describe the socio-demographic features, pattern of COVID-19 spread and the viral load dynamics among subjects residing in northern, middle and part of the southern belt of Ghana. Methods This was a cross-sectional retrospective study that reviewed records of samples collected from February to July, 2020. Respiratory specimens such as sputum, deep-cough saliva and nasopharyngeal swabs were collected from suspected COVID-19 subjects in 12 regions of Ghana for laboratory analysis and confirmation by real-time reverse transcription polymerase chain reaction (RT-PCR). Results A total of 72,434 samples were collected during the review period, with majority of the sampled individuals being females (37,464; 51.9%). The prevalence of SARS-CoV-2 identified in the study population was 13.2% [95%CI: 12.9, 13.4). Males were mostly infected (4,897; 51.5%) compared to females. Individuals between the ages 21–30 years recorded the highest number of infections (3,144, 33.4%). Symptomatic subjects had higher viral loads (1479.7 copies/μl; IQR = 40.6–178919) than asymptomatic subjects (49.9; IQR = 5.5–3641.6). There was significant association between gender or age and infection with SARS-CoV-2 (p<0.05). Among all the suspected clinical presentations, anosmia was the strongest predictor of SARS-CoV-2 infection (Adj. OR (95%CI): 24.39 (20.18, 29.49). We observed an average reproductive number of 1.36 with a minimum of 1.28 and maximum of 1.43. The virus trajectory shows a gradual reduction of the virus reproductive number. Conclusion This study has described the epidemiological profile of COVID-19 cases in northern, middle and part of the southern belt of Ghana, with males and younger individuals at greater risk of contracting the disease. Health professionals should be conscious of individuals presenting with anosmia since this was seen as the strongest predictor of virus infection.

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Common cardiovascular risk factors and in-hospital mortality in 3,894 patients with COVID-19: survival analysis and machine learning-based findings from the multicentre Italian CORIST Study

Cited by 150 publications

References 29 publications

Physiological and socioeconomic characteristics predict COVID-19 mortality and resource utilization in Brazil

Physiological and socioeconomic characteristics predict COVID-19 mortality and resource utilization in Brazil

RAAS inhibitors are not associated with mortality in COVID-19 patients: Findings from an observational multicenter study in Italy and a meta-analysis of 19 studies

Epidemiological profile of SARS-CoV-2 among selected regions in Ghana: A cross-sectional retrospective study

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