Correlations of CT scan with high-sensitivity C-reactive protein and D-dimer in patients with coronavirus disease 2019

Association between biochemical and hematologic factors with COVID-19 using data mining methods

BACKGROUND AND AIM

Coronavirus disease (COVID-19) is an infectious disease that can spread very rapidly with important public health impacts. The prediction of the important factors related to the patient's infectious diseases is helpful to health care workers. The aim of this research was to select the critical feature of the relationship between demographic, biochemical, and hematological characteristics, in patients with and without COVID-19 infection.

METHOD

A total of 13,170 participants in the age range of 35-65 years were recruited. Decision Tree (DT), Logistic Regression (LR), and Bootstrap Forest (BF) techniques were fitted into data. Three models were considered in this study, in model I, the biochemical features, in model II, the hematological features, and in model II, both biochemical and homological features were studied.

RESULTS

In Model I, the BF, DT, and LR algorithms identified creatine phosphokinase (CPK), blood urea nitrogen (BUN), fasting blood glucose (FBG), total bilirubin, body mass index (BMI), sex, and age, as important predictors for COVID-19. In Model II, our BF, DT, and LR algorithms identified BMI, sex, mean platelet volume (MPV), and age as important predictors. In Model III, our BF, DT, and LR algorithms identified CPK, BMI, MPV, BUN, FBG, sex, creatinine (Cr), age, and total bilirubin as important predictors.

CONCLUSION

The proposed BF, DT, and LR models appear to be able to predict and classify infected and non-infected people based on CPK, BUN, BMI, MPV, FBG, Sex, Cr, and Age which had a high association with COVID-19.

Use of data mining approaches to explore the association between type 2 diabetes mellitus with SARS-CoV-2

BACKGROUND AND OBJECTIVE

Corona virus causes respiratory tract infections in mammals. The latest type of Severe Acute Respiratory Syndrome Corona-viruses 2 (SARS-CoV-2), Corona virus spread in humans in December 2019 in Wuhan, China. The purpose of this study was to investigate the relationship between type 2 diabetes mellitus (T2DM), and their biochemical and hematological factors with the level of infection with COVID-19 to improve the treatment and management of the disease.

MATERIAL AND METHOD

This study was conducted on a population of 13,170 including 5780 subjects with SARS-COV-2 and 7390 subjects without SARS-COV-2, in the age range of 35-65 years. Also, the associations between biochemical factors, hematological factors, physical activity level (PAL), age, sex, and smoking status were investigated with the COVID-19 infection.

RESULT

Data mining techniques such as logistic regression (LR) and decision tree (DT) algorithms were used to analyze the data. The results using the LR model showed that in biochemical factors (Model I) creatine phosphokinase (CPK) (OR: 1.006 CI 95% (1.006,1.007)), blood urea nitrogen (BUN) (OR: 1.039 CI 95% (1.033, 1.047)) and in hematological factors (Model II) mean platelet volume (MVP) (OR: 1.546 CI 95% (1.470, 1.628)) were significant factors associated with COVID-19 infection. Using the DT model, CPK, BUN, and MPV were the most important variables. Also, after adjustment for confounding factors, subjects with T2DM had higher risk for COVID-19 infection.

CONCLUSION

There was a significant association between CPK, BUN, MPV and T2DM with COVID-19 infection and T2DM appears to be important in the development of COVID-19 infection.

Relationship between chest CT scan findings with SOFA score, CRP, comorbidity, and mortality in ICU patients with COVID-19

OBJECTIVE

This study aimed to investigate the relationship between chest computed tomography (CT) scan findings with sequential organ failure assessment (SOFA) score, C-reactive protein (CRP), comorbidity, and mortality in intensive care unit (ICU) patients with coronavirus disease 19 (COVID-19).

METHOD

Adult patients (≥18 years old) with COVID-19 who were consecutively admitted to the Imam-Reza Hospital, Tabriz, East-Azerbaijan Province, North-West of Iran between March 2020 and August 2020 were screened and total of 168 patients were included. Demographic, clinical, and mortality data were gathered. Severity of disease was evaluated using the SOFA score system. CRP levels were measured and chest CT scans were performed.

RESULTS

Most of patients had multifocal and bilateral ground glass opacity (GGO) pattern in chest CT scan. There were significant correlations between SOFA score on admission with multifocal and bilateral GGO (P = .010 and P = .011, respectively). Significant relationships were observed between unilateral and bilateral GGO patterns with CRP (P = .049 and P = .046, respectively). There was significant relationship between GGO patterns with comorbidities including overweight/obesity, heart failure, cardiovascular diseases, and malignancy (P < .05). No significant relationships were observed between chest CT scan results with mortality (P > .05).

CONCLUSION

Multifocal bilateral GGO was the most common pattern. Although chest CT scan characteristics were significantly related with SOFA score, CRP, and comorbidity in ICU patients with COVID-19, a relationship with mortality was not significant.

Impact of persistent D-dimer elevation following recovery from COVID-19

BACKGROUND

Elevated D-dimer is known as predictor for severity of SARS-CoV2-infection. Increased D-dimer is associated with thromboembolic complications, but it is also a direct consequence of the acute lung injury seen in COVID-19 pneumonia.

OBJECTIVES

To evaluate the rate of persistent elevated D-dimer and its association with thromboembolic complications and persistent ground glass opacities (GGO) after recovery from COVID-19.

METHODS

In this post hoc analysis of a prospective multicenter trial, patients underwent blood sampling, measurement of diffusion capacity, blood gas analysis, and multidetector computed tomography (MDCT) scan following COVID-19. In case of increased D-dimer (>0,5 μg/ml), an additional contrast medium-enhanced CT was performed in absence of contraindications. Results were compared between patients with persistent D-dimer elevation and patients with normal D-dimer level.

RESULTS

129 patients (median age 48.8 years; range 19-91 years) underwent D-Dimer assessment after a median (IQR) of 94 days (64-130) following COVID-19. D-dimer elevation was found in 15% (19/129) and was significantly more common in patients who had experienced a severe SARS-CoV2 infection that had required hospitalisation compared to patients with mild disease (p = 0.049). Contrast-medium CT (n = 15) revealed an acute pulmonary embolism in one patient and CTEPH in another patient. A significant lower mean pO2 (p = 0.015) and AaDO2 (p = 0.043) were observed in patients with persistent D-Dimer elevation, but the rate of GGO were similar in both patient groups (p = 0.33).

CONCLUSION

In 15% of the patients recovered from COVID-19, persistent D-dimer elevation was observed after a median of 3 months following COVID-19. These patients had experienced a more severe COVID and still presented more frequently a lower mean pO2 and AaDO2.

Longitudinal changes in COVID-19 clinical measures and correlation with the extent of CT lung abnormalities

Rationale: To assess the longitudinal changes and relationships of clinical measures and extent of CT lung abnormalities in COVID-19. Methods: 81 patients with COVID-19 were prospectively enrolled and followed until discharge. CT scores were quantified on a basis of a CT scoring system where each lung was divided into 3 zones: upper (above the carina), middle, and lower (below the inferior pulmonary vein) zones; each zone was evaluated for percentage of lung involvement on a scale of 0-4 (0, 0%; 1, 0-24%; 2, 25% - 49%; 3, 50% -74%; 4, >74%).Temporal trends of CT scores and the laboratory parameters characteristic of COVID-19 were analyzed. Correlations between the two were determined at three milestones (initial presentation, worst CT manifestation, and recovery finding before discharge). Their correlations with duration to worst CT manifestation and discharge from symptom onset were evaluated. Results: CT scores peaked during illness days 6-11 (median: 5), and stayed steady. C-reactive protein and lactate dehydrogenase increased, peaked on illness days 6-8 and 8-11 (mean: 23.5 mg/L, 259.9 U/L), and gradually declined. Continual decrease and increase were observed in hemoglobin and lymphocyte count, respectively. Albumin reduced and remained at low levels with a nadir on illness days 12-15 (36.6 g/L). Both initial (r = 0.58, 0.64, p < 0.05) and worst CT scores (r = 0.47, 0.65, p < 0.05) were correlated with C-reactive protein and lactate dehydrogenase; and CT scores before discharge, only with albumin (r = -0.41, p < 0.05). Duration to worst CT manifestation was associated with initial and worst CT scores (r = 0.33, 0.29, p < 0.05). No parameters were related to timespan to discharge. Conclusion: Our results illustrated the temporal changes of characteristic clinical measures and extent of CT lung abnormalities in COVID-19. CT scores correlated with some important laboratory parameters, and might serve as prognostic factors.

Predicting In-Hospital Mortality in COVID-19 Older Patients with Specifically Developed Scores

BACKGROUND/OBJECTIVES

Several scoring systems have been specifically developed for risk stratification in COVID-19 patients.

DESIGN

We compared, in a cohort of confirmed COVID-19 older patients, three specifically developed scores with a previously established early warning score. Main endpoint was all causes in-hospital death.

SETTING

This is a single-center, retrospective observational study, conducted in the Emergency Department (ED) of an urban teaching hospital, referral center for COVID-19.

PARTICIPANTS

We reviewed the clinical records of the confirmed COVID-19 patients aged 60 years or more consecutively admitted to our ED over a 6-week period (March 1st to April 15th, 2020). A total of 210 patients, aged between 60 and 98 years were included in the study cohort.

MEASUREMENTS

International Severe Acute Respiratory Infection Consortium Clinical Characterization Protocol-Coronavirus Clinical Characterization Consortium (ISARIC-4C) score, COVID-GRAM Critical Illness Risk Score (COVID-GRAM), quick COVID-19 Severity Index (qCSI), National Early Warning Score (NEWS).

RESULTS

Median age was 74 (67-82) and 133 (63.3%) were males. Globally, 42 patients (20.0%) deceased. All the score evaluated showed a fairly good predictive value with respect to in-hospital death. The ISARIC-4C score had the highest area under ROC curve (AUROC) 0.799 (0.738-0.851), followed by the COVID-GRAM 0.785 (0.723-0.838), NEWS 0.764 (0.700-0.819), and qCSI 0.749 (0.685-0.806). However, these differences were not statistical significant.

CONCLUSION

Among the evaluated scores, the ISARIC-4C and the COVID-GRAM, calculated at ED admission, had the best performance, although the qCSI had similar efficacy by evaluating only three items. However, the NEWS, already widely validated in clinical practice, had a similar performance and could be appropriate for older patients with COVID-19.