Time-series analysis of multidimensional clinical-laboratory data by dynamic Bayesian networks reveals trajectories of COVID-19 outcomes.

BACKGROUND AND OBJECTIVE: COVID-19 severity spans an entire clinical spectrum from asymptomatic to fatal. Most patients who require in-hospital care are admitted to non-intensive wards, but their clinical conditions can deteriorate suddenly and some eventually die. Clinical data from patients' case series have identified pre-hospital and in-hospital risk factors for adverse COVID-19 outcomes. However, most prior studies used static variables or dynamic changes of a few selected variables of interest. In this study, we aimed at integrating the analysis of time-varying multidimensional clinical-laboratory data to describe the pathways leading to COVID-19 outcomes among patients initially hospitalised in a non-intensive care setting. METHODS: We collected the longitudinal retrospective data of 394 patients admitted to non-intensive care units at the University Hospital of Padova (Padova, Italy) due to COVID-19. We trained a dynamic Bayesian network (DBN) to encode the conditional probability relationships over time between death and all available demographics, pre-existing conditions, and clinical laboratory variables. We applied resampling, dynamic time warping, and prototyping to describe the typical trajectories of patients who died vs. those who survived. RESULTS: The DBN revealed that the trajectory linking demographics and pre-existing clinical conditions to death passed directly through kidney dysfunction or, more indirectly, through cardiac damage. As expected, admittance to the intensive care unit was linked to markers of respiratory function. Notably, death was linked to elevation in procalcitonin and D-dimer levels. Death was associated with persistently high levels of procalcitonin from admission and throughout the hospital stay, likely reflecting bacterial superinfection. A sudden raise in D-dimer levels 3-6 days after admission was also associated with subsequent death, possibly reflecting a worsening thrombotic microangiopathy. CONCLUSIONS: This innovative application of DBNs and prototyping to integrated data analysis enables visualising the patient's trajectories to COVID-19 outcomes and may instruct timely and appropriate clinical decisions.

In hospital risk factors for acute kidney injury and its burden in patients with Sars-Cov-2 infection: a longitudinal multinational study.

Acute kidney injury (AKI) is associated with increased mortality in most critical settings. However, it is unclear whether its mild form (i.e. AKI stage 1) is associated with increased mortality also in non-critical settings. Here we conducted an international study in patients hospitalized with SARS-CoV-2 infection aiming 1. to estimate the incidence of AKI at each stage and its impact on mortality 2. to identify AKI risk factors at admission (susceptibility) and during hospitalization (exposures) and factors contributing to AKI-associated mortality. We included 939 patients from medical departments in Moscow (Russia) and Padua (Italy). In-hospital AKI onset was identified in 140 (14.9%) patients, mainly with stage 1 (65%). Mortality was remarkably higher in patients with AKI compared to those without AKI (55 [39.3%] vs. 34 [4.3%], respectively). Such association remained significant after adjustment for other clinical conditions at admission (relative risk [RR] 5.6; CI 3.5- 8.8) or restricting to AKI stage 1 (RR 3.2; CI 1.8-5.5) or to subjects with AKI onset preceding deterioration of clinical conditions. After hospital admission, worsening of hypoxic damage, inflammation, hyperglycemia, and coagulopathy were identified as hospital-acquired risk factors predicting AKI onset. Following AKI onset, the AKI-associated worsening of respiratory function was identified as the main contributor to AKI-induced increase in mortality risk. In conclusion, AKI is a common complication of Sars-CoV2 infection in non-intensive care settings where it markedly increases mortality risk also at stage 1. The identification of hospital-acquired risk factors and exposures might help prevention of AKI onset and of its complications.

Effectiveness of In-Hospital Cholecalciferol Use on Clinical Outcomes in Comorbid COVID-19 Patients: A Hypothesis-Generating Study.

Little information is available on the beneficial effects of cholecalciferol treatment in comorbid patients hospitalized for COVID-19. The aim of this study was to retrospectively examine the clinical outcome of patients receiving in-hospital high-dose bolus cholecalciferol. Patients with a positive diagnosis of SARS-CoV-2 and overt COVID-19, hospitalized from 15 March to 20 April 2020, were considered. Based on clinical characteristics, they were supplemented (or not) with 400,000 IU bolus oral cholecalciferol (200,000 IU administered in two consecutive days) and the composite outcome (transfer to intensive care unit; ICU and/or death) was recorded. Ninety-one patients (aged 74 ± 13 years) with COVID-19 were included in this retrospective study. Fifty (54.9%) patients presented with two or more comorbid diseases. Based on the decision of the referring physician, 36 (39.6%) patients were treated with vitamin D. Receiver operating characteristic curve analysis revealed a significant predictive power of the four variables: (a) low (<50 nmol/L) 25(OH) vitamin D levels, (b) current cigarette smoking, (c) elevated D-dimer levels (d) and the presence of comorbid diseases, to explain the decision to administer vitamin D (area under the curve = 0.77, 95% CI: 0.67-0.87, p < 0.0001). Over the follow-up period (14 ± 10 days), 27 (29.7%) patients were transferred to the ICU and 22 (24.2%) died (16 prior to ICU and six in ICU). Overall, 43 (47.3%) patients experienced the combined endpoint of transfer to ICU and/or death. Logistic regression analyses revealed that the comorbidity burden significantly modified the effect of vitamin D treatment on the study outcome, both in crude (p = 0.033) and propensity score-adjusted analyses (p = 0.039), so the positive effect of high-dose cholecalciferol on the combined endpoint was significantly amplified with increasing comorbidity burden. This hypothesis-generating study warrants the formal evaluation (i.e., clinical trial) of the potential benefit that cholecalciferol can offer in these comorbid COVID-19 patients.

Cardiac injury and mortality in patients with Coronavirus disease 2019 (COVID-19): insights from a mediation analysis.

BACKGROUNDS: Patients at greatest risk of severe clinical conditions from coronavirus disease 2019 (COVID-19) and death are elderly and comorbid patients. Increased levels of cardiac troponins identify patients with poor outcome. The present study aimed to describe the clinical characteristics and outcomes of a cohort of Italian inpatients, admitted to a medical COVID-19 Unit, and to investigate the relative role of cardiac injury on in-hospital mortality. METHODS AND RESULTS: We analyzed all consecutive patients with laboratory-confirmed COVID-19 referred to our dedicated medical Unit between February 26th and March 31st 2020. Patients' clinical data including comorbidities, laboratory values, and outcomes were collected. Predictors of in-hospital mortality were investigated. A mediation analysis was performed to identify the potential mediators in the relationship between cardiac injury and mortality. A total of 109 COVID-19 inpatients (female 36%, median age 71 years) were included. During in-hospital stay, 20 patients (18%) died and, compared with survivors, these patients were older, had more comorbidities defined by Charlson comorbidity index ≥ 3(65% vs 24%, p = 0.001), and higher levels of high-sensitivity cardiac troponin I (Hs-cTnI), both at first evaluation and peak levels. A dose-response curve between Hs-cTnI and in-hospital mortality risk up to 200 ng/L was detected. Hs-cTnI, chronic kidney disease, and chronic coronary artery disease mediated most of the risk of in-hospital death, with Hs-cTnI mediating 25% of such effect. Smaller effects were observed for age, lactic dehydrogenase, and D-dimer. CONCLUSIONS: In this cohort of elderly and comorbid COVID-19 patients, elevated Hs-cTnI levels were the most important and independent mediators of in-hospital mortality.

SARS-CoV-2 identification and IgA antibodies in saliva: One sample two tests approach for diagnosis.

AIM: This study aims to verify whether standardized saliva collection is suitable for SARS-CoV-2 molecular detection and IgA measurement. METHODS: 43 COVID-19 inpatients and 326 screening subjects underwent naso-pharyngeal (NP)-swab and saliva collection (Salivette). Inpatients also underwent repeated blood collections to evaluate inflammation and organs involvement. In all patients and subjects, SARS-CoV-2 (gene E) rRT-PCR was undertaken in saliva and NP-swabs. Salivary IgA and serum IgA, IgG, IgM were measured on inpatients' samples. RESULTS: NP-swabs and saliva were both SARS-CoV-2 positive in 7 (16%) or both negative in 35 (82%) out of 43 patients successfully included in the study. NP-swabs and saliva results did not perfectly match in one patient (saliva positive, NP-swab negative). Positive molecular results were significantly associated with disease duration (p = 0.0049). 326/326 screening subjects were SARS-CoV-2 negative on both NP-swabs and saliva. Among the 27 saliva samples tested for IgA, 18 were IgA positive. Salivary IgA positivity was associated with pneumonia (p = 0.002) and CRP values (p = 0.0183), not with other clinical and molecular data, or with serum immunoglubulins. CONCLUSIONS: A standardized saliva collection can be adopted to detect SARS-CoV-2 infection in alternative to NP-swabs. Preliminary data on salivary IgA support the use of saliva also for patient monitoring.

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.

BACKGROUND AND AIMS: There is poor knowledge on characteristics, comorbidities and laboratory measures associated with risk for adverse outcomes and in-hospital mortality in European Countries. We aimed at identifying baseline characteristics predisposing COVID-19 patients to in-hospital death. METHODS AND RESULTS: Retrospective observational study on 3894 patients with SARS-CoV-2 infection hospitalized from February 19th to May 23rd, 2020 and recruited in 30 clinical centres distributed throughout Italy. Machine learning (random forest)-based and Cox survival analysis. 61.7% of participants were men (median age 67 years), followed up for a median of 13 days. In-hospital mortality exhibited a geographical gradient, Northern Italian regions featuring more than twofold higher death rates as compared to Central/Southern areas (15.6% vs 6.4%, respectively). Machine learning analysis revealed that the most important features in death classification were impaired renal function, elevated C reactive protein and advanced age. These findings were confirmed by multivariable Cox survival analysis (hazard ratio (HR): 8.2; 95% confidence interval (CI) 4.6-14.7 for age ≥85 vs 18-44 y); HR = 4.7; 2.9-7.7 for estimated glomerular filtration rate levels <15 vs ≥ 90 mL/min/1.73 m2; HR = 2.3; 1.5-3.6 for C-reactive protein levels ≥10 vs ≤ 3 mg/L). No relation was found with obesity, tobacco use, cardiovascular disease and related-comorbidities. The associations between these variables and mortality were substantially homogenous across all sub-groups analyses. CONCLUSIONS: Impaired renal function, elevated C-reactive protein and advanced age were major predictors of in-hospital death in a large cohort of unselected patients with COVID-19, admitted to 30 different clinical centres all over Italy.

Newly-diagnosed diabetes and admission hyperglycemia predict COVID-19 severity by aggravating respiratory deterioration.

AIMS: We investigated whether pre-existing diabetes, newly-diagnosed diabetes, and admission hyperglycemia were associated with COVID-19 severity independently from confounders. METHODS: We retrospectively analyzed data on patients with COVID-19 hospitalized between February and April 2020 in an outbreak hospital in North-East Italy. Pre-existing diabetes was defined by self-reported history, electronic medical records, or ongoing medications. Newly-diagnosed diabetes was defined by HbA1c and fasting glucose. The primary outcome was a composite of ICU admission or death. RESULTS: 413 subjects were included, 107 of whom (25.6%) had diabetes, including 21 newly-diagnosed. Patients with diabetes were older and had greater comorbidity burden. The primary outcome occurred in 37.4% of patients with diabetes compared to 20.3% in those without (RR 1.85; 95%C.I. 1.33-2.57; p < 0.001). The association was stronger for newly-diagnosed compared to pre-existing diabetes (RR 3.06 vs 1.55; p = 0.004). Higher glucose level at admission was associated with COVID-19 severity, with a stronger association among patients without as compared to those with pre-existing diabetes (interaction p < 0.001). Admission glucose was correlated with most clinical severity indexes and its association with adverse outcome was mostly mediated by a worse respiratory function. CONCLUSION: Newly-diagnosed diabetes and admission hyperglycemia are powerful predictors of COVID-19 severity due to rapid respiratory deterioration.

The hazard of (sub)therapeutic doses of anticoagulants in non-critically ill patients with Covid-19: The Padua province experience.

BACKGROUND: Coronavirus Disease 2019 (COVID-19) is responsible for a worldwide pandemic, with a high rate of morbidity and mortality. The increasing evidence of an associated relevant prothrombotic coagulopathy has resulted in an increasing use of antithrombotic doses higher than usual in COVID-19 patients. Information on the benefit/risk ratio of this approach is still lacking. OBJECTIVE: To assess the incidence of relevant bleeding complications in association with the antithrombotic strategy and its relationship with the amount of drug. METHODS: Consecutive COVID-19 patients admitted between February and April 2020 were included in a retrospective analysis. Major bleedings (MB) and clinically relevant non-major bleeding (CRNMB) were obtained from patient medical records and were adjudicated by an independent committee. RESULTS: Of the 324 patients who were recruited, 240 had been treated with prophylactic doses and 84 with higher doses of anticoagulants. The rate of the composite endpoint of MB or CRNMB was 6.9 per 100-person/months in patients who had been given prophylactic doses, and 26.4 per 100-person/months in those who had been prescribed higher doses (hazard ratio, 3.89; 95% confidence interval, 1.90-7.97). The corresponding rates for overall mortality were 12.2 and 20.1 per 100-person/months, respectively. CONCLUSIONS: The rate of relevant bleeding events was high in patients treated with (sub)therapeutic doses of anticoagulants. In the latter group, overall mortality did not differ from that of patients treated with standard prophylactic doses and was even higher. Our result does not support a strategy of giving (sub)therapeutic doses of anticoagulants in non-critically ill patients with COVID-19.

Exposure to dipeptidyl-peptidase-4 inhibitors and COVID-19 among people with type 2 diabetes: A case-control study.

Because other coronaviruses enter the cells by binding to dipeptidyl-peptidase-4 (DPP-4), it has been speculated that DPP-4 inhibitors (DPP-4is) may exert an activity against severe acute respiratory syndrome coronavirus 2. In the absence of clinical trial results, we analysed epidemiological data to support or discard such a hypothesis. We retrieved information on exposure to DPP-4is among patients with type 2 diabetes (T2D) hospitalized for COVID-19 at an outbreak hospital in Italy. As a reference, we retrieved information on exposure to DPP-4is among matched patients with T2D in the same region. Of 403 hospitalized COVID-19 patients, 85 had T2D. The rate of exposure to DPP-4is was similar between T2D patients with COVID-19 (10.6%) and 14 857 matched patients in the region (8.8%), or 793 matched patients in the local outpatient clinic (15.4%), 8284 matched patients hospitalized for other reasons (8.5%), and when comparing 71 patients hospitalized for COVID-19 pneumonia (11.3%) with 351 matched patients with pneumonia of another aetiology (10.3%). T2D patients with COVID-19 who were on DPP-4is had a similar disease outcome as those who were not. In summary, we found no evidence that DPP-4is might affect hospitalization for COVID-19.

SARS-CoV-2 RNA identification in nasopharyngeal swabs: issues in pre-analytics.

Objectives: The direct identification of SARS-CoV-2 RNA in nasopharyngeal swabs is recommended for diagnosing the novel COVID-19 disease. Pre-analytical determinants, such as sampling procedures, time and temperature storage conditions, might impact on the end result. Our aim was to evaluate the effects of sampling procedures, time and temperature of the primary nasopharyngeal swabs storage on real-time reverse-transcription polymerase chain reaction (rRT-PCR) results. Methods: Each nasopharyngeal swab obtained from 10 hospitalized patients for COVID-19 was subdivided in 15 aliquots: five were kept at room temperature; five were refrigerated (+4 °C); five were immediately mixed with the extraction buffer and refrigerated at +4 °C. Every day and for 5 days, one aliquot per condition was analyzed (rRT-PCR) for SARS-CoV-2 gene E and RNaseP and threshold cycles (Ct) compared. To evaluate manual sampling, 70 nasopharyngeal swabs were sampled twice by two different operators and analyzed separately one from the other. Results: A total of 6/10 swabs were SARS-CoV-2 positive. No significant time or storage-dependent variations were observed in SARS-CoV-2 Ct. Re-sampling of swabs with SARS-CoV-2 Ct lower than 33 resulted in highly reproducible results (CV=2.9%), while a high variability was observed when Ct values were higher than 33 (CV=10.3%). Conclusions: This study demonstrates that time and temperature of nasopharyngeal swabs storage do not significantly impact on results reproducibility. However, swabs sampling is a critical step, and especially in case of low viral load, might be a potential source of diagnostic errors.

Obesity and COVID-19: An Italian Snapshot.

OBJECTIVE: The clinical manifestations of coronavirus disease (COVID-19) run from asymptomatic disease to severe acute respiratory syndrome. Older age and comorbidities are associated to more severe disease. A role of obesity is suspected. METHODS: Patients hospitalized in the medical COVID-19 ward with severe acute respiratory syndrome coronavirus 2-related pneumonia were enrolled. The primary outcome of the study was to assess the relationship between the severity of COVID-19 and obesity classes according to BMI. RESULTS: A total of 92 patients (61.9% males; age 70.5 [13.3] years) were enrolled. Patients with overweight and obesity were younger than patients with normal weight (68.0 [12.6] and 67.0 [12.6] years vs. 76.1 [13.0] years, P < 0.01). A higher need for assisted ventilation beyond pure oxygen support (invasive mechanical ventilation or noninvasive ventilation) and a higher admission to intensive or semi-intensive care units were observed in patients with overweight and obesity (P < 0.01 and P < 0.05, respectively) even after adjusting for sex, age, and comorbidities (P < 0.05 and P < 0.001, respectively) or when patients with dementia or advanced cancer were removed from the analysis (P < 0.05). CONCLUSIONS: Patients with overweight and obesity admitted in a medical ward for severe acute respiratory syndrome coronavirus 2-related pneumonia, despite their younger age, required more frequently assisted ventilation and access to intensive or semi-intensive care units than normal weight patients.

Arrhythmic profile and 24-hour QT interval variability in COVID-19 patients treated with hydroxychloroquine and azithromycin.

BACKGROUND: Hydroxychloroquine and azithromycin combination therapy is often prescribed for coronavirus disease 2019 (COVID-19). Electrocardiographic (ECG) monitoring is warranted because both medications cause corrected QT-interval (QTc) prolongation. Whether QTc duration significantly varies during the day, potentially requiring multiple ECGs, remains to be established. METHODS: We performed 12­lead ECGs and 12­lead 24-h Holter ECG monitoring in all patients aged <80 years admitted to our medical unit for COVID-19, in oral therapy with hydroxychloroquine (200 mg, twice daily) and azithromycin (500 mg, once daily) for at least 3 days. A group of healthy individuals matched for age and sex served as control. RESULTS: Out of 126 patients, 22 (median age 64, 82% men) met the inclusion criteria. ECG after therapy showed longer QTc-interval than before therapy (450 vs 426 ms, p = .02). Four patients had a QTc ≥ 480 ms: they showed higher values of aspartate aminotransferase (52 vs 30 U/L, p = .03) and alanine aminotransferase (108 vs 33 U/L, p < .01) compared with those with QTc < 480 ms. At 24-h Holter ECG monitoring, 1 COVID-19 patient and no control had ≥1 run of non-sustained ventricular tachycardia (p = .4). No patients showed "R on T" premature ventricular beats. Analysis of 24-h QTc dynamics revealed that COVID-19 patients had higher QTc values than controls, with no significant hourly variability. CONCLUSION: Therapy with hydroxychloroquine and azithromycin prolongs QTc interval in patients with COVID-19, particularly in those with high levels of transaminases. Because QTc duration remains stable during the 24 h, multiple daily ECG are not recommendable.