A cohort study of 676 patients indicates D-dimer is a critical risk factor for the mortality of COVID-19

Remdesivir plus dexamethasone is associated to improvement in the clinical outcome of COVID-19 hospitalized patients regardless of their vaccination status

INTRODUCTION

Remdesivir seems to reduce the risk of hospitalization and improve clinical outcome in hospitalized patients with COVID-19.

OBJECTIVES

To compare the clinical outcome of COVID-19 hospitalized patients treated with remdesivir plus dexamethasone versus dexamethasone alone, according to their vaccination status.

MATERIAL AND METHODS

A retrospective observational study was carried out in 165 patients hospitalized for COVID-19 from October 2021 to January 2022. Multivariate logistic regression, Kaplan-Meier and the log-rank tests were used to evaluate the event (need for ventilation or death).

RESULTS

Patients treated with remdesivir plus dexamethasone (n=87) compared with dexamethasone alone (n=78) showed similar age (60±16, 47-70 vs. 62±37, 51-74 years) and number of comorbidities: 1 (0-2) versus 1.5 (1-3). Among 73 fully vaccinated patients, 42 (47.1%) were in remdesivir plus dexamethasone and 31 (41%) in dexamethasone alone. Patients treated with remdesivir plus dexamethasone needed intensive care less frequently (17.2% vs. 31%; p=0.002), high-flow oxygen (25.3% vs. 50.0%; p=0.002) and non-invasive mechanical ventilation (16.1% vs. 47.4%; p<0.001). Furthermore, they had less complications during hospitalization (31.0% vs. 52.6%; p=0.008), need of antibiotics (32.2% vs. 59%; p=0.001) and radiologic worsening (21.8% vs. 44.9%; p=0.005). Treatment with remdesivir plus dexamethasone (aHR, 0.26; 95% CI: 0.14-0.48; p<0.001) and vaccination (aHR 0.39; 95% CI: 0.21-0.74) were independent factors associated with lower progression to mechanical ventilation or death.

CONCLUSIONS

Remdesivir in combination with dexamethasone and vaccination independently and synergistically protects hospitalized COVID-19 patients requiring oxygen therapy from progression to severe disease or dead.

Clinical Risk Factors of Need for Intensive Care Unit Admission of COVID-19 Patients; a Cross-sectional Study

Introduction

It could be beneficial to accelerate the hospitalization of patients with the identified clinical risk factors of intensive care unit (ICU) admission, in order to control and reduce COVID-19-related mortality. This study aimed to determine the clinical risk factors associated with ICU hospitalization of COVID-19 patients.

Methods

The current research was a cross-sectional study. The study recruited 7182 patients who had positive PCR tests between February 23, 2020, and September 7, 2021 and were admitted to Afzalipour Hospital in Kerman, Iran, for at least 24 hours. Their demographic characteristics, underlying diseases, and clinical parameters were collected. In order to analyze the relationship between the studied variables and ICU admission, multiple logistic regression model, classification tree, and support vector machine were used.

Results

It was found that 14.7 percent (1056 patients) of the study participants were admitted to ICU. The patients' average age was 51.25±21 years, and 52.8% of them were male. In the study, some factors such as decreasing oxygen saturation level (OR=0.954, 95%CI: 0.944-0.964), age (OR=1.007, 95%CI: 1.004-1.011), respiratory distress (OR=1.658, 95%CI: 1.410-1.951), reduced level of consciousness (OR=2.487, 95%CI: 1.721-3.596), hypertension (OR=1.249, 95%CI: 1.042-1.496), chronic pulmonary disease (OR=1.250, 95%CI: 1.006-1.554), heart diseases (OR=1.250, 95%CI: 1.009-1.548), chronic kidney disease (OR=1.515, 95%CI: 1.111-2.066), cancer (OR=1.682, 95%CI: 1.130-2.505), seizures (OR=3.428, 95%CI: 1.615-7.274), and gender (OR=1.179, 95%CI: 1.028-1.352) were found to significantly affect ICU admissions.

Conclusions

As evidenced by the obtained results, blood oxygen saturation level, the patient's age, and their level of consciousness are crucial for ICU admission.

D-Dimer as a Sensitive Biomarker of Survival Rate in Patients with COVID-19

OBJECTIVE

The global case fatality rate of coronavirus disease 2019 is 2.16% as announced by the World Health Organization. In Indonesia, according to the Ministry of Health, the number is even higher, reaching a 2.8% case fatality rate. D-dimer levels were found to affect coronavirus disease 2019 patient's survival in several studies. The study aimed to determine whether the amount of D-dimer predicted survival in coronavirus disease 2019 patients.

MATERIALS AND METHODS

This research was performed in a retrospective cohort design and used survival analysis. From March 1, 2020, to August 31, 2020, the samples were collected from polymerase chain reaction-confirmed coronavirus disease 2019 patients at Mohammad Hoesin General Hospital in Palembang, South Sumatera, Indonesia. We used electronic medical records to obtain demographic (age and gender), coexisting condition, laboratory (coagulation and hematologic test), and outcome (non-survivors or survivors) data. The chi-square and Mann-Whitney tests were used to evaluate the results. The Kaplan-Meier method and the Mantel-Haenszel log-rank test were used to examine D-dimer levels and patient outcomes. Youden index was calculated to determine the optimal cut-off value of D-dimer.

RESULTS

There were 52 non-survivors and 235 survivors among the 287 patients who met the inclusion criterion. Non-survivors had D-dimer levels of more than 1.49 mg/L in 82.69%of cases. Males had lower cut-off compared to females (>1.49 mg/L vs. >2.2 mg/L). The researchers discovered a highly significant correlation between D-dimer levels and coronavirus disease 2019 mortality (P=.001). The c-index analysis showed that D-dimer (0.79, 95% CI: 0.73-0.83) ability for mortality prediction was the second-best compared with other laboratory markers.

CONCLUSION

D-dimer can be used as a predictor of coronavirus disease 2019 in-hospital mortality for early identification of coagulopathy.

Hemostatic system and COVID-19 crosstalk: A review of the available evidence

Since the discovery of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its resultant coronavirus disease 2019 (COVID-19) pandemic, respiratory manifestations have been the mainstay of clinical diagnosis, laboratory evaluations, and radiological investigations. As time passed, other pathological aspects of SARS-CoV-2 have been revealed. Various hemostatic abnormalities have been reported since the rise of the pandemic, which was sometimes superficial, transient, or fatal. Mild thrombocytopenia, thrombocytosis, venous, arterial thromboembolism, and disseminated intravascular coagulation are among the many hemostatic events associated with COVID-19. Venous thromboembolism necessitating therapeutic doses of anticoagulants is more frequently seen in severe cases of COVID-19, especially in patients admitted to intensive care units. Hemorrhagic complications rarely arise in COVID-19 patients either due to a hemostatic imbalance resulting from severe disease or as a complication of over anticoagulation. Although the pathogenesis of coagulation disturbance in SARS-CoV-2 infection is not yet understood, professional societies recommend prophylactic antithrombotic therapy in severe cases, especially in the presence of abnormal coagulation indices. The review article discusses the various available evidence on coagulation disorders, management strategies, outcomes, and prognosis associated with COVID-19 coagulopathy, which raises awareness about the importance of anticoagulation therapy for COVID-19 patients to guard against possible thromboembolic events.

Methodological Considerations on COVID-19 Mortality in Cancer Patients: A Systematic Review and Meta-Analysis

BACKGROUND

Patients with cancer are at risk for severe COVID-19. Previous studies examining mortality in cancer patients with COVID-19 have produced inconclusive results. Several published meta-analyses have aimed to estimate this association; however, because of methodological limitations in study selection and data aggregation, these studies do not reliably estimate the independent association between cancer and COVID-19 mortality. We conducted this systematic review and meta-analysis to determine whether cancer is an independent risk factor for COVID-19 mortality.

METHODS

A literature search was performed in PubMed to identify studies that compared COVID-19 mortality in adult patients with and without cancer. Selection criteria included polymerase chain reaction-confirmed COVID-19, multivariate adjustment and/or matching for mortality risk estimates, and inclusion of hospitalized noncancer controls. Adjusted odds ratios and/or hazard ratios for mortality based on cancer status were extracted. Odds ratio and hazard ratio estimates were pooled using a random effects model.

RESULTS

The analysis included 42 studies comprising 129 840 patients: 8612 cancer patients and 121 228 noncancer patients. Of these studies, 18 showed a null difference in survival between cancer and noncancer patients with COVID-19, and 24 studies showed statistically significantly worse survival in cancer patients with COVID-19. Meta-analysis revealed an increased risk of mortality in patients with cancer compared with noncancer patients with COVID-19 (odds ratio = 1.93, 95% confidence interval = 1.55 to 2.41; hazard ratio = 1.54, 95% confidence interval = 1.29 to 1.84).

CONCLUSION

We conclude that cancer is an independent risk factor for mortality in unvaccinated patients admitted for or diagnosed with COVID-19 during hospitalization.

Discrepancy between biomarkers of lung injury and 1-year mortality in COVID-19

BACKGROUND

COVID-19 global pandemic started in late 2019 with the first wave. In this cross-sectional and observational study, we evaluated the associations between the biomarkers, COVID-19 pneumonia severity and 1-year mortality.

METHODS

A sample of 276 polymerase chain reaction (PCR)-positive patients for SARS-CoV-2 was included. Computerized tomography severity score (CT-SS) was used to assess the severity of COVID-19 pneumonia in 222 cases. Multivariate analyses were performed to find the predictors of CT-SS, severe CT-SS (≥20) and 1-year mortality. Biomarkers of ferritin, high-sensitive C-reactive protein (CRP), lactate dehydrogenase (LDH), cardiac troponin (cTn), neutrophil-to-lymphocyte ratio (NLR), uric acid (UA) and d-dimer were routinely measured.

RESULTS

Severe CT-SS (>20) was observed in 86 (31.2%) cases. Mortality was observed in 75 (27.2%) patients at 1 year. LDH displayed the highest predictive accuracy for severe CT-SS (AUC 0.741, sensitivity = 81% and specificity = 68%, cut-off value: 360 mg/dl). Linear regression analysis displayed that LDH predicted CT-SS [B = 11 (95% CI for B = 5-17, p < .001)]. Age was the most significant parameter that was associated with severe CT-SS (OR 0.96, 95% CI 0.92-0.99, p = .015). d-dimer was the only biomarker that predicted with 1-year mortality (OR 1.62, 95% CI 1.08-2.42, p = .020).

CONCLUSION

LDH is a sensitive and specific biomarker to determine patients with severe lung injury in COVID-19. d-dimer is the only biomarker that predicts 1-year mortality. Neither LDH nor CT-SS is associated with 1-year mortality.

Prognostic value of elevated lactate dehydrogenase in patients with COVID-19: a systematic review and meta-analysis

PURPOSE

This meta-analysis aimed to evaluate the prognostic performance of elevated lactate dehydrogenase (LDH) in patients with COVID-19.

METHODS

A systematic literature search was performed using PubMed, Embase and EuropePMC on 19 November 2020. The outcome of interest was composite poor outcome, defined as a combined endpoint of mortality, severity, need for invasive mechanical ventilation and need for intensive care unit care. Severity followed the included studies' criteria.

RESULTS

There are 10 399 patients from 21 studies. Elevated LDH was present in 44% (34%-53%) of the patients. Meta-regression analysis showed that diabetes was correlated with elevated LDH (OR 1.01 (95% CI 1.00 to 1.02), p=0.038), but not age (p=0.710), male (p=0.068) and hypertension (p=0.969). Meta-analysis showed that elevated LDH was associated with composite poor outcome (OR 5.33 (95% CI 3.90 to 7.31), p<0.001; I2: 77.5%). Subgroup analysis showed that elevated LDH increased mortality (OR 4.22 (95% CI 2.49 to 7.14), p<0.001; I2: 89%). Elevated LDH has a sensitivity of 0.74 (95% CI 0.60 to 0.85), specificity of 0.69 (95% CI 0.58 to 0.78), positive likelihood ratio of 2.4 (95% CI 1.9 to 2.9), negative likelihood ratio of 0.38 (95% CI 0.26 to 0.55), diagnostic OR of 6 (95% CI 4 to 9) and area under curve of 0.77 (95% CI 0.73 to 0.80). Elevated LDH would indicate a 44% posterior probability and non-elevated LDH would in indicate 11% posterior probability for poor prognosis. Meta-regression analysis showed that age, male, hypertension and diabetes did not contribute to the heterogeneity of the analyses.

CONCLUSION

LDH was associated with poor prognosis in patients with COVID-19.

PROSPERO REGISTRATION NUMBER

CRD42020221594.

The Difference Coagulopathy Factor and Interleukin-6 between Survival and Non-survival Patients COVID-19

Background: Coronavirus disease 2019 (COVID-19) was caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus. SARS-CoV-2 infection can result in coagulopathy and an increase in inflammatory responses. Numerous studies have shown a significant difference in interleukin levels and coagulopathy parameters such as platelet, aPTT, PT, and D- dimer between survivor and non-survivor patient COVID-19. Aim: The purpose of this study is to compare the age, coagulopathy characteristics, and interleukin-6 levels of non-survival versus survival patients. COVID-19. Methods: A cross-sectional retrospective study was conducted on COVID-19 patients. The diagnostic criteria are based on the Indonesian Ministry of Health's recommendations. The patient's blood was analyzed in the hospital's central laboratory. Patients are classified into two groups based on their likelihood of surviving: non-survival and survival. SPSS version 22 was used to analyze the data. Results: A total of 557 patients with COVID-19 were included in this study. Patients were categorized into 146 non-survival and 411 survival subgroups. There was a significant difference in the mean age, coagulopathy parameters, and interleukin-6 expect platelets between non-survival and survival outcomes in COVID-19 patients. Conclusion: This study demonstrated a statistically significant difference in PT, aPTT, D-Dimer, and interleukin-6 levels between the non-survival and survival groups of COVID-19.

Novel prognostic determinants of COVID-19-related mortality: A pilot study on severely-ill patients in Russia

COVID-19 pandemic has posed a severe healthcare challenge calling for an integrated approach in determining the clues for early non-invasive diagnostics of the potentially severe cases and efficient patient stratification. Here we analyze the clinical, laboratory and CT scan characteristics associated with high risk of COVID-19-related death outcome in the cohort of severely-ill patients in Russia. The data obtained reveal that elevated dead lymphocyte counts, decreased early apoptotic lymphocytes, decreased CD14+/HLA-Dr+ monocytes, increased expression of JNK in PBMCs, elevated IL-17 and decreased PAI-1 serum levels are associated with a high risk of COVID-19-related mortality thus suggesting them to be new prognostic factors. This set of determinants could be used as early predictors of potentially severe course of COVID-19 for trials of prevention or timely treatment.

Mortality Predictors in Severe COVID-19 Patients from an East European Tertiary Center: A Never-Ending Challenge for a No Happy Ending Pandemic

(1) Background: There are limited clinical data in patients from the Eastern European regions hospitalized for a severe form of Coronavirus disease 2019 (COVID-19). This study aims to identify risk factors associated with intra-hospital mortality in patients with COVID-19 severe pneumonia admitted to a tertiary center in Iasi, Romania. (2) Methods: The study is of a unicentric retrospective observational type and includes 150 patients with severe COVID-19 pneumonia divided into two subgroups, survivors and non-survivors. Demographic and clinical parameters, as well as comorbidities, laboratory and imaging investigations upon admission, treatments, and evolution during hospitalization were recorded. First, we sought to identify the risk factors associated with intra-hospital mortality using logistic regression. Secondly, we assessed the correlations between D-Dimer and C-reactive protein and predictors of poor prognosis. (3) Results: The predictors of in-hospital mortality identified in the study are D-dimers >0.5 mg/L (p = 0.002), C-reactive protein >5 mg/L (p = 0.001), and heart rate above 100 beats per minute (p = 0.001). The biomarkers were also significantly correlated the need for mechanical ventilation, admission to intensive care unit, or multiple organ dysfunction syndrome. By area under the curve (AUC) analysis, we noticed that both D-Dimer (AUC 0.741) and C-reactive protein (AUC 0.707) exhibit adequate performance in predicting a poor prognosis in patients with severe viral infection. (4) Conclusions: COVID-19's outcome is significantly influenced by several laboratory and clinical factors. As mortality induced by severe COVID-19 pneumonia is considerable, the identification of risk factors associated with negative outcome coupled with an early therapeutic approach are of paramount importance, as they may significantly improve the outcome and survival rates.

Predictors of intubation and mortality in COVID-19 patients: a retrospective study

Background

Estimating the risk of intubation and mortality among COVID-19 patients can help clinicians triage these patients and allocate resources more efficiently. Thus, here we sought to identify the risk factors associated with intubation and intra-hospital mortality in a cohort of COVID-19 patients hospitalized due to hypoxemic acute respiratory failure (ARF).

Results

We included retrospectively a total of 187 patients admitted to the subintensive and intensive care units of the University Hospital “Maggiore della Carità” of Novara between March 1st and April 30th, 2020. Based on these patients’ demographic characteristics, early clinical and laboratory variables, and quantitative chest computerized tomography (CT) findings, we developed two random forest (RF) models able to predict intubation and intra-hospital mortality. Variables independently associated with intubation were C-reactive protein (p < 0.001), lactate dehydrogenase level (p = 0.018) and white blood cell count (p = 0.026), while variables independently associated with mortality were age (p < 0.001), other cardiovascular diseases (p = 0.029), C-reactive protein (p = 0.002), lactate dehydrogenase level (p = 0.018), and invasive mechanical ventilation (p = 0.001). On quantitative chest CT analysis, ground glass opacity, consolidation, and fibrosis resulted significantly associated with patient intubation and mortality. The major predictors for both models were the ratio between partial pressure of arterial oxygen and fraction of inspired oxygen, age, lactate dehydrogenase, C-reactive protein, glycemia, CT quantitative parameters, lymphocyte count, and symptom onset.

Conclusions

Altogether, our findings confirm previously reported demographic, clinical, hemato-chemical, and radiologic predictors of adverse outcome among COVID-19-associated hypoxemic ARF patients. The two newly developed RF models herein described show an overall good level of accuracy in predicting intra-hospital mortality and intubation in our study population. Thus, their future development and implementation may help not only identify patients at higher risk of deterioration more effectively but also rebalance the disproportion between resources and demand.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44158-021-00016-5.

CRP, SAA, LDH, and DD predict poor prognosis of coronavirus disease (COVID-19): a meta-analysis from 7739 patients

Understanding factors associated with disease severity and mortality from coronavirus disease (COVID-19) was critical for effective risk stratification. We aimed to investigate the association between biomarkers of clinical laboratory tests, including serum C-reactive protein (CRP), serum amyloid protein (SAA), lactate dehydrogenase (LDH), and D-dimer (DD) and poor prognosis of COVID-19. We have searched many studies on COVID-19 on PubMed (Medline), Web of Science and Cochrane until 1 March 2021. The interest of this study was original articles reporting on laboratory testing projects and outcome of patients with COVID-19 that comprises mortality, acute respiratory distress syndrome (ARDS), need for care in an intensive care unit (ICU), and severe COVID-19. After synthesizing all data, we performed meta-analysis of random effects, and determined mean difference (MD) and standard mean difference at the biomarker level for different disease severity. A total of 7,739 patients with COVID-19 were pooled from 32 studies. CRP was significantly associated with poor prognosis of COVID-19 (SMD = 0.98, 95% CI = (0.85, 1.11), p < .001). Elevated SAA was associated with an increased composite poor outcome in COVID-19 (SMD = 1.06, 95% CI = (0.39, 1.72), p = .002). An elevated LDH was associated with a composite poor outcome (SMD = 1.18, 95% CI = (1.00, 1.36), p < .001). Patients with a composite poor outcome had a higher DD level (SMD = 0.91, 95% CI = (0.79, 1.02), p < .001). This meta-analysis showed that elevated serum CRP, SAA, LDH, and DD were associated with a poor outcome in COVID-19.

A meta-analysis on the risk factors adjusted association between cardiovascular disease and COVID-19 severity

BACKGROUND

Cardiovascular disease (CVD), one of the most common comorbidities of coronavirus disease 2019 (COVID-19), has been suspected to be associated with adverse outcomes in COVID-19 patients, but their correlation remains controversial.

METHOD

This is a quantitative meta-analysis on the basis of adjusted effect estimates. PubMed, Web of Science, MedRxiv, Scopus, Elsevier ScienceDirect, Cochrane Library and EMBASE were searched comprehensively to obtain a complete data source up to January 7, 2021. Pooled effects (hazard ratio (HR), odds ratio (OR)) and the 95% confidence intervals (CIs) were estimated to evaluate the risk of the adverse outcomes in COVID-19 patients with CVD. Heterogeneity was assessed by Cochran's Q-statistic, I2test, and meta-regression. In addition, we also provided the prediction interval, which was helpful for assessing whether the variation across studies was clinically significant. The robustness of the results was evaluated by sensitivity analysis. Publication bias was assessed by Begg's test, Egger's test, and trim-and-fill method.

RESULT

Our results revealed that COVID-19 patients with pre-existing CVD tended more to adverse outcomes on the basis of 203 eligible studies with 24,032,712 cases (pooled ORs = 1.41, 95% CIs: 1.32-1.51, prediction interval: 0.84-2.39; pooled HRs = 1.34, 95% CIs: 1.23-1.46, prediction interval: 0.82-2.21). Further subgroup analyses stratified by age, the proportion of males, study design, disease types, sample size, region and disease outcomes also showed that pre-existing CVD was significantly associated with adverse outcomes among COVID-19 patients.

CONCLUSION

Our findings demonstrated that pre-existing CVD was an independent risk factor associated with adverse outcomes among COVID-19 patients.

Correlation of olfactory dysfunction with lung involvement and severity of COVID-19

Background

Olfactory dysfunction (OD) is a significant symptom of COVID-19 and may be the earliest symptom, or it may sometimes be the only manifestation of the disease.

Aims

To investigate whether OD is correlated with chest computed tomography (CT) findings, blood test parameters, and disease severity in COVID-19 patients.

Methods

The files of COVID-19 patients were retrospectively reviewed, and the ones who had information about smelling status and CT were taken into consideration. A total of 180 patients were divided into two groups: the OD group consisted of 89 patients with self-reported OD, and the No-OD group consisted of 91 subjects who did not complain of OD. The two groups were compared for the amount of lung consolidation on CT, intensive care unit (ICU) admission, and blood test parameters (complete blood count, alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatine kinase (CK), lactate dehydrogenase (LDH), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), ferritin, D-dimer, interleukin-6 (IL-6)).

Results

The amount of lung consolidation and ICU admission were significantly higher in the No-OD group (p < 0.001 for both). White blood cell (p = 0.06), monocyte (p = 0.26), and platelet (p = 0.13) counts and hemoglobin (p = 0.63), ALT (p = 0.89), and D-dimer (p = 0.45) levels of the two groups were similar. Lymphocyte count (p = 0.01), neutrophil count (p = 0.01), and AST (p = 0.03), CK (p = 0.01), LDH (p < 0.001), CRP (p < 0.001), ESR (p < 0.001), ferritin (p < 0.001), and IL-6 (p < 0.001) levels were significantly higher in the No-OD group.

Conclusions

The patients presenting to the hospital with self-reported OD may have less lung involvement and a milder disease course compared to patients without OD on admission.

Course of COVID-19 Based on Admission D-Dimer Levels and Its Influence on Thrombosis and Mortality

Background

Arterial and venous thrombosis is one of the major complications of coronavirus disease 2019 (COVID-19) infection. Studies have not assessed the difference in D-dimer levels between patients who develop thrombosis and those who do not.

Methods

Our study retrospectively assessed D-dimer levels in all virus confirmed hospitalized patients between May to September, 2020. Patients were divided into three groups: group 1 with normal D-dimer of < 0.5 µg/mL, group 2 with elevation up to six folds, and group 3 with more than six-fold elevation. Statistical analysis was done using SPSS software 23.0.

Results

Seven hundred twenty patients (group1 (n = 414), group 2 (n = 284) and group 3 (n = 22)) were studied. Eight thrombotic events were observed. Events were two with stroke, two non-ST elevation myocardial infarction and one each of ST elevation myocardial infarction, superior mesenteric artery thrombosis with bowel gangrene, arteriovenous fistula thrombus and unstable angina. No significant difference (P = 0.11) was observed between median D-dimer levels among patients who developed thrombosis (1.34) and those who did not develop thrombosis (0.91). Twenty-nine patients died. The adjusted odds of death among those with a six-fold or higher elevation in D-dimer was 128.4 (95% confidence interval (CI): 14.2 - 446.3, P < 0.001), while adjusted odds of developing clinical thrombosis was 1.96 (95% CI: 0.82 - 18.2, P = 0.18).

Conclusions

Our study observed a 1.1% in-hospital incidence of clinical thrombosis. While, a six-fold elevation in D-dimer was significantly associated with death; the same was not a strong predictor of thrombosis; an observation which implies that dose of anticoagulation should not be based on absolute D-dimer level.

Clinical Characteristics and Outcomes of a Cohort of Pediatric Oncohematologic Patients With COVID-19 Infection in the City of Bogotá, Colombia

BACKGROUND

In children, the complications of severe acute respiratory syndrome coronavirus 2 infection occur less frequently than in adults but the characteristics of this disease in oncology patients are not well characterized.

METHODS

This was a retrospective study in patients younger than 18 years of age with coronavirus disease 2019 (COVID-19) and cancer diagnoses between April and September 2020. Demographic variables, laboratory, and radiologic findings and complications of each case were identified. A descriptive analysis was performed.

RESULTS

A total of 33 patients were identified; the median age was 10 years. Fifteen patients (42%) were in chemotherapy at the time of the infection diagnosis, in two patients the chemotherapy protocol was permanently suspended. The most common symptom was fever in 20 patients (60%). Seven patients (21.2%) showed mild pneumonia, four patients (12.1%) severe pneumonia, and three cases (9.0%) were classified as critical. In the evaluated cohort, five patients (15.1%) died, and in two of those, death was caused by COVID-19 infection.

CONCLUSIONS

Children with an oncologic disease, the search for COVID cases should be oriented to patients with fever, including febrile neutropenia, the presence of respiratory symptoms, and the search for epidemiologic contact. A higher frequency of complications and mortality attributed to COVID-19, two in pediatric oncohematologic patients was found. Institutional strategies to detect the infection early and lower institutional infection are indicated.

Clinical Significance of Plasma D-Dimer in COVID-19 Mortality

It is not clear whether D-dimer can be an independent predictor of coronavirus disease 2019 (COVID-19) mortality, and the cut-off of D-dimer for clinical use remains to be determined. Therefore, a comprehensive analysis is still necessary to illuminate the clinical significance of plasma D-dimer in COVID-19 mortality. We searched PubMed, Embase, Cochrane Library, and Scopus databases until November 2020. STATA software was used for all the statistical analyses. The identifier of systematic review registration was PROSPERO CRD42020220927. A total of 66 studies involving 40,614 COVID-19 patients were included in our meta-analysis. Pooled data showed that patients in high D-dimer group had poor prognosis than those in low D-dimer group [OR = 4.52, 95% CI = (3.61, 5.67), P < 0.001; HR = 2.81, 95% CI = (1.85, 4.27), P < 0.001]. Sensitivity analysis, pooled data based on different effect models and the Duval and Tweedie trim-and-fill method did not change the conclusions. Subgroup analyses stratified by different countries, cutoffs, sample size, study design, and analysis of OR/HR still keep consistent conclusions. D-dimer was identified as an independent predictor for COVID-19 mortality. A series of values including 0.5 μg/ml, 1 μg/ml, and 2 μg/ml could be determined as cutoff of D-dimer for clinic use. Measurement and monitoring of D-dimer might assist clinicians to take immediate medical actions and predict the prognosis of COVID-19.

Correlation of Coagulation Parameters With Clinical Outcomes During the Coronavirus-19 Surge in New York: Observational Cohort

Importance

COVID-19 has caused a worldwide illness and New York became the epicenter of COVID-19 in the United States from Mid-March to May 2020.

Objective

To investigate the coagulopathic presentation of COVID and its natural course during the early stages of the COVID-19 surge in New York. To investigate whether hematologic and coagulation parameters can be used to assess illness severity and death.

Design

Retrospective case study of positive COVID inpatients between March 20, 2020-March 31, 2020.

Setting

Montefiore Health System main hospital, Moses, a large tertiary care center in the Bronx.

Participants

Adult inpatients with positive COVID tests hospitalized at MHS.

Exposure (for observational studies)

Datasets of participants were queried for demographic (age, sex, socioeconomic status, and self-reported race and/or ethnicity), clinical and laboratory data.

Main Outcome and Measures

Relationship and predictive value of measured parameters to mortality and illness severity.

Results

Of the 225 in this case review, 75 died during hospitalization while 150 were discharged home. Only the admission PT, absolute neutrophil count (ANC) and first D-Dimer could significantly differentiate those who were discharged alive and those who died. Logistic regression analysis shows increased odds ratio for mortality by first D-Dimer within 48 hrs. of admission. The optimal cut-point for the initial D-Dimer to predict mortality was found to be 2.1 μg/mL. 15% of discharged patients required readmission and more than a third of readmitted patients died (5% of all initially discharged).

Conclusion

We describe here a comprehensive assessment of hematologic and coagulation parameters in COVID-19 and examine the relationship of these to mortality. We demonstrate that both initial and maximum D-Dimer values are biomarkers that can be used for survival assessments. Furthermore, D-Dimer may be useful to follow up discharged patients.

Evaluation and characterization of HSPA5 (GRP78) expression profiles in normal individuals and cancer patients with COVID-19

HSPA5 (BiP, GRP78) has been reported as a potential host-cell receptor for SARS-Cov-2, but its expression profiles on different tissues including tumors, its susceptibility to SARS-Cov-2 virus and severity of its adverse effects on malignant patients are unclear. In the current study, HSPA5 has been found to be expressed ubiquitously in normal tissues and significantly increased in 14 of 31 types of cancer tissues. In lung cancer, mRNA levels of HSPA5 were 253-fold increase than that of ACE2. Meanwhile, in both malignant tumors and matched normal samples across almost all cancer types, mRNA levels of HSPA5 were much higher than those of ACE2. Higher expression of HSPA5 significantly decreased patient overall survival (OS) in 7 types of cancers. Moreover, systematic analyses found that 7.15% of 5,068 COVID-19 cases have malignant cancer coincidental situations, and the rate of severe events of COVID-19 patients with cancers present a higher trend than that for all COVID-19 patients, showing a significant difference (33.33% vs 16.09%, p<0.01). Collectively, these data imply that the tissues with high HSPA5 expression, not low ACE2 expression, are susceptible to be invaded by SARS-CoV-2. Taken together, this study not only indicates the clinical significance of HSPA5 in COVID-19 disease and cancers, but also provides potential clues for further medical treatments and managements of COVID-19 patients.