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

Effect of colchicine on mortality in patients with COVID-19 - A systematic review and meta-analysis

BACKGROUND AND AIM

This systematic review and meta-analysis aimed to evaluate the latest evidence on the association between colchicine and mortality in patients with COVID-19.

METHODS

We performed a comprehensive literature search from the PubMed, Scopus, Embase, EuropePMC, and Clinicaltrials.gov up until 02 January 2022. We include randomized controlled trials (RCTs) and observational studies reporting colchicine use in patients with COVID-19 and mortality within 30 days. The intervention group was patients given colchicine during the course of treatment. The control group was patients given placebo or standard of care at the respective institutions. The outcome was mortality. The effect estimate was reported as risk ratio (RR).

RESULTS

There were 12 studies comprising of 6953 patients included in this meta-analysis. Mortality rate was 0.18 [95%CI 0.10, 0.26] in the colchicine group and 0.26 [95%CI 0.15, 0.38] in the control group. Colchicine was associated with reduction in mortality (RR 0.66 [95%CI 0.53, 0.83], p < 0.001; I²: 42%). Sensitivity analysis using fixed-effect model (RR 0.73 [95%CI 0.63, 0.83], p < 0.001; I²: 42%. Subgroup analysis on the four RCTs showed non-significant result (RR 0.81 [95%CI 0.54, 1.20], p = 0.29; I²: 10%). Meta-regression showed that the association between colchicine and reduced mortality was not affected by age (p = 0.613) [Fig. 3], sex (p = 0.915), diabetes (p = 0.795), and hypertension (p = 0.403).

CONCLUSION

Though the meta-analysis showed decreased mortality with colchicine in patients with COVID-19, the meta-analysis of randomized trials did not show any significant effect of colchicine on mortality.

COVID-19 Course in Allergic Asthma Patients: A Spanish Cohort Analysis

Purpose

The acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has had a high impact on patients with chronic diseases. In the literature, there are different perspectives on asthma as comorbidity or risk factor on COVID-19 severity.

Patients and Methods

The aim of this retrospective study across 13 allergy departments in Spain was to determine the severity of COVID-19 in asthmatic adults followed in allergy departments and its relationship with atopy, clinical and demographic characteristics, phenotypes and laboratory data. In addition, lung function test and asthma control test (ACT) before and after COVID-19 were analyzed. Data was obtained from electronic medical records from March 2020 to April 2021.

Results

Two hundred one asthmatic patients were diagnosed with COVID-19 infection by validated detection test. About 30% of the patients were admitted for bilateral pneumonia. Advanced age, elevated D-dimer, lower numbers of lymphocytes and eosinophils, heart diseases and hypertension were associated with severe COVID-19. Allergic and mixed allergic/eosinophilic phenotype and their biomarkers (total IgE, aeroallergens sensitizations, allergic rhinitis, and blood eosinophilia) were related to fewer hospital admissions. Poor control and lower forced expiratory volume in the first second (FEV₁) were related to worse prognosis of COVID-19.

Conclusion

Asthmatic patients with allergic and eosinophilic phenotype have a better evolution of COVID-19 and lower risk of admissions. Older patients, cardiovascular comorbidities, AERD and eosinopenia are related to severity COVID-19.

Role of Polypeptide Inflammatory Biomarkers in the Diagnosis and Monitoring of COVID-19

The COVID-19 (coronavirus disease 2019) pandemic that took over the world in December 2019 has had everlasting devastating impacts on the lives of people globally. It manifests a huge symptom spectrum ranging from asymptomatic to critically ill patients with an unpredictable outcome. Timely diagnosis and assessment of disease severity is imperative for effective treatment. Possibilities exist that by the time symptoms appear the viral load might increase beyond control. However, it is advisable to get adequately diagnosed as soon as the first symptom appears. There is an immediate requirement of reliable biomarkers of COVID-19 manifesting an early onset for effective clinical management, stratification of high risk patients and ensuring ideal resource allocation. In this review, we attempt to explore and describe important polypeptide inflammatory biomarkers, namely C-reactive protein, Procalcitonin, Ferritin, Lactate Dehydrogenase, Serum amyloid A, Interleukin-6, Tumor necrosis factor-alpha and LIGHT used in the detection and management of COVID-19. Viral pathogenesis and the role of these inflammatory biomarkers is highlighted, based on the evidences available till date. An integrative data monitoring along with their correlation with the natural disease progression is of utmost importance in the management of COVID-19. So further research and in-depth analysis of these biomarkers is warranted in the present scenario.

Acute management of COVID-19 in the emergency department: An evidence-based review

Coronavirus disease (COVID-19) has been relentlessly battering the world wave after wave in different countries at different rates and times. Emergency departments (EDs) around the globe have had to constantly adapt to this ever-changing influx of information and recommendations by various national and international health agencies. This review compiles the available evidence on the guidelines for triaging, evaluation, and management of critically ill patients with COVID-19 presenting to the ED and in need of emergency resuscitation. The quintessential components of resuscitation focus on airway, breathing, and circulation with good supportive care as the cornerstone of acute management of critically ill COVID-19 patients. Irrational investigations and therapeutics must be avoided during these times of medical uncertainty and antibiotic stewardship should be diligently followed.

Interaction of ACEI antihypertensive agent's administration with the inflammatory status at admission concerning COVID-19 clinical stay outcomes

Interactions between anti-hypertensive agents (ACEI), comorbidities, inflammation, and stress status may impact hospital stay duration in COVID-19 patients. This retrospective study analyzed epidemiological data, comorbidities, metabolic/inflammatory markers, and clinical information from 165 SARS-CoV-2 positive patients. In a multiple linear regression model, an IL-6 higher than 100 mg/L, glucose at admission (baseline levels at the hospital entry), and the interaction between ACEI administration and LDH predicted the days of hospital admission (P < 0.001). In conclusion, hypertensive patients suffering more severe inflammatory condition assessed by LDH levels clinically benefited more and reduced the hospital stay when prescribed ACEI agents than those with lower systemic baseline inflammation at admission.

Assessment of background levels of autoantibodies as a prognostic marker for severe SARS-CoV-2 infection

Background:

Patients with more severe forms of SARS-CoV-2 exhibit activation of immunological cascades. Participants (current or ex-smokers with at least 20 years pack history) in a trial (Early Diagnosis of Lung Cancer, Scotland [ECLS]) of autoantibody detection to predict lung cancer risk had seven autoantibodies measured 5 years before the pandemic. This study compared the response to Covid infection in study participants who tested positive and negative to antibodies to tumour-associated antigens: p53, NY-ESO-1, CAGE, GBU4-5, HuD, MAGE A4 and SOX2.

Methods:

Autoantibody data from the ECLS study was deterministically linked to the EAVE II database, a national, real-time prospective cohort using Scotland’s health data infrastructure, to describe the epidemiology of SARS-CoV-2 infection, patterns of healthcare use and outcomes. The strength of associations was explored using a network algorithm for exact contingency table significance testing by permutation.

Results:

There were no significant differences discerned between SARS-CoV-2 test results and EarlyCDT-Lung test results (p = 0.734). An additional analysis of intensive care unit (ICU) admissions detected no significant differences between those who tested positive and negative. Subgroup analyses showed no difference in COVID-19 positivity or death rates amongst those diagnosed with chronic obstructive pulmonary disease (COPD) with positive and negative EarlyCDT results.

Conclusions:

This hypothesis-generating study demonstrated no clinically valuable or statistically significant associations between EarlyCDT positivity in 2013-15 and the likelihood of SARS-CoV-2 positivity in 2020, ICU admission or death in all participants (current or ex-smokers with at least 20 years pack history) or in those with COPD or lung cancer.

Clinical characteristics and hematological parameters associated with disease severity in COVID-19 positive pregnant women undergoing cesarean section: A single-center experience

AIM

The study aimed to describe clinical characteristics and outcomes of pregnant women with COVID-19 undergoing cesarean section, and evaluated the association of blood values at admission with severe COVID-19 disease in this group of patients.

METHOD

We retrospectively analyzed the clinical data of 110 patients infected with COVID-19 who underwent cesarean section at Adana City Education and Research Hospital in Turkey. The COVID-19 severity of the patients was classified as either severe or nonsevere disease according to World Health Organization of COVID-19 clinical management guidance. We compared blood values, clinical characteristics, and outcomes between severe and nonsevere patients. Receiver operating characteristics (ROC) curves analyses and area under the ROC curve (AUC) value was calculated to evaluate the predictive value of blood parameters on the COVID-19 severity.

RESULTS

Of the 110 women, 12 were severe cases. Severe patients had higher ferritin, neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase (LDH), alanine transaminase (ALT), aspartate transaminase (AST), and procalcitonin levels on admission (p < 0.05). The ROC analysis demonstrated AUC of NLR, LDH, AST, ALT, ferritin, and procalcitonin was 0.757, 0.856, 0.840, 0.771, 0.821, and 0.698, respectively. The LDH had a maximum specificity (90.8%), with the cutoff value of 365. The O-blood group was more likely to have severe illness than the non-O-blood group (relative risk: 3.6; 95% confidence interval; 1.2-10.4).

CONCLUSION

This study shows that LDH values at admission are an early and powerful predictor of severe infection for pregnant women with COVID-19 who will undergo a cesarean section.

Mortality Prediction of COVID-19 Patients at Intensive Care Unit Admission

Background

Coronavirus-2019 (COVID-19) patients admitted to the intensive care unit (ICU) have mortality rates between 30%-50%. Identifying patient factors associated with mortality can help identify critical patients early and treat them accordingly.

Patients and methods

In this retrospective study, the records of patients admitted to the COVID-19 ICU in a single tertiary care hospital from April 2020 to September 2020 were analysed. The clinical and laboratory parameters between patients who were discharged from the hospital (survival cohort) and those who died in the hospital (mortality cohort) were compared. A multivariate logistic regression model was constructed to identify parameters associated with mortality. 

Results

A total of 147 patients were included in the study. The age of the patients was 55 (45, 64), median (IQR), years. At admission, 23 (16%) patients were on mechanical ventilation and 73 (50%) were on non-invasive ventilation. Sixty patients (40%, 95% CI: 32.8 to 49.2%) had died. Patients who died had a higher Charlson comorbidity index (CCI): 3 (2, 4) vs. 2 (1, 3), p = 0.0019, and a higher admission sequential organ failure assessment (SOFA) score: 5 (4, 7) vs. 4 (3, 4), p < 0.001. Serum urea, serum creatinine, neutrophils on differential leukocyte count, neutrophil to lymphocyte ratio (N/L ratio), D-dimer, serum lactate dehydrogenase (LDH), and C-reactive protein were higher in the mortality cohort. The ratio of partial pressure of arterial oxygen to fraction of inspired oxygen, platelet count, lymphocytes on differential leukocyte count, and absolute lymphocyte count was lower in the mortality cohort. The parameters and cut-off values used for the multivariate logistic regression model included CCI > 2, SOFA score > 4, D-dimer > 1346 ng/mL, LDH > 514 U/L and N/L ratio > 27. The final model had an area under the curve of 0.876 (95% CI: 0.812 to 0.925), p < 0.001 with an accuracy of 78%. All five parameters were found to be independently associated with mortality. 

Conclusions

CCI, SOFA score, D-dimer, LDH, and N/L ratio are independently associated with mortality. A model incorporating the combination of these clinical and laboratory parameters at admission can predict COVID-19 ICU mortality with good accuracy.

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.

Herpes Simplex Virus Re-Activation in Patients with SARS-CoV-2 Pneumonia: A Prospective, Observational Study

Background: Herpes simplex 1 co-infections in patients with COVID-19 are considered relatively uncommon; some reports on re-activations in patients in intensive-care units were published. The aim of the study was to analyze herpetic re-activations and their clinical manifestations in hospitalized COVID-19 patients, performing HSV-1 PCR on plasma twice a week. Methods: we conducted a prospective, observational, single-center study involving 70 consecutive patients with severe/critical SARS-CoV-2 pneumonia tested for HSV-1 hospitalized at Azienda Ospedaliero-Universitaria of Modena. Results: of these 70 patients, 21 (30.0%) showed detectable viremia and 13 (62%) had clinically relevant manifestations of HSV-1 infection corresponding to 15 events (4 pneumonia, 5 herpes labialis, 3 gingivostomatitis, one encephalitis and two hepatitis). HSV-1 positive patients were more frequently treated with steroids than HSV-1 negative patients (76.2% vs. 49.0%, p = 0.036) and more often underwent mechanical ventilation (IMV) (57.1% vs. 22.4%, p = 0.005). In the unadjusted logistic regression analysis, steroid treatment, IMV, and higher LDH were significantly associated with an increased risk of HSV1 re-activation (odds ratio 3.33, 4.61, and 16.9, respectively). The association with the use of steroids was even stronger after controlling for previous use of both tocilizumab and IMV (OR = 5.13, 95% CI:1.36–19.32, p = 0.016). The effect size was larger when restricting to participants who were treated with high doses of steroids while there was no evidence to support an association with the use of tocilizumab Conclusions: our study shows a high incidence of HSV-1 re-activation both virologically and clinically in patients with SARS-CoV-2 severe pneumonia, especially in those treated with steroids.

Prognostic parameters of in-hospital mortality in COVID-19 patients-An Italian experience

Background During COVID-19 outbreak, Italy was the first country in Europe to be heavily affected with an intensive care unit mortality of 26%. In order to reduce this percentage, physicians should establish clear and objective criteria to stratify COVID-19 patients at high risk of in-hospital death. Thus, the aim has been to test a large spectrum of variables ranging from clinical evaluation to laboratory biomarkers to identify which parameter would best predict all-cause in-hospital mortality in COVID-19 patients. Design observational study. Results Multivariate Cox regression analysis showed that each 5 years of increase in age corresponded to a hazard ratio (HR) of 1.28 (95% CI 1.00-1.65, P = .050); each increment of 803 ng/L of N-terminal pro-B-type natriuretic peptide (NT-proBNP) corresponded to a HR of 1.24 (95% CI 1.11-1.39, P < .001); each increment of 58 ng/L of interleukin (IL)-6 corresponded to a HR of 1.23 (95% CI 1.09-1.40, P < .001), and each increment of 250 U/L of lactate dehydrogenase (LDH) corresponded to a HR of 1.23 (95% CI 1.10-1.37, P < .001). According to the calculated cut-points for age (≥70 years), NT-proBNP (≥803 ng/L), IL-6 (≥58 ng/L) and LDH (≥371 U/L) when 2 out of these 4 were overcome, the HR was 2.96 (95% CI 1.97-4.45, P < .001). Conclusion In COVID-19 patients, besides age, the evaluation of three biochemical parameters, available in few hours after hospital admission can predict in-hospital mortality regardless of other comorbidities.

COVID-19 in young and middle-aged adults: predictors of poor outcome and clinical differences

Introduction

Young and middle-aged adults are the largest group of patients infected with SARS-CoV-2 and some of them develop severe disease.

Objective

To investigate clinical manifestations in adults aged 18–65 years hospitalized for COVID-19 and identify predictors of poor outcome. Secondary objectives: to explore differences compared to the disease in elderly patients and the suitability of the commonly used community-acquired pneumonia prognostic scales in younger populations.

Methods

Multicenter prospective registry of consecutive patients hospitalized for COVID-19 pneumonia aged 18–65 years between March and May 2020. We considered a composite outcome of “poor outcome” including intensive care unit admission and/or use of noninvasive ventilation, continuous positive airway pressure or high flow nasal cannula oxygen and/or death.

Results

We identified 513 patients < 65 years of age, from a cohort of 993 patients. 102 had poor outcomes (19.8%) and 3.9% died. 78% and 55% of patients with poor outcomes were classified as low risk based on CURB and PSI scores, respectively.

A multivariate Cox regression model identified six independent factors associated with poor outcome: heart disease, absence of chest pain or anosmia, low oxygen saturation, high LDH and lymphocyte count < 800/mL.

Conclusions

COVID-19 in younger patients carries significant morbidity and differs in some respects from this disease in the elderly. Baseline heart disease is a relevant risk factor, while anosmia and pleuritic pain are associated to better prognosis. Hypoxemia, LDH and lymphocyte count are predictors of poor outcome. We consider that CURB and PSI scores are not suitable criteria for deciding admission in this population.

Individual Characteristics as Prognostic Factors of the Evolution of Hospitalized COVID-19 Romanian Patients: A Comparative Observational Study between the First and Second Waves Based on Gaussian Graphical Models and Structural Equation Modeling

This study examines the role played by individual characteristics and specific treatment methods in the evolution of hospitalized patients with coronavirus disease 2019 (COVID-19), through the lens of an observational study performed in a comparative approach between the first and second waves of coronavirus pandemic in Romania. The research endeavor is configured on a two-fold approach, including a detailed observation of the evolution of 274 hospitalized patients with COVID-19 (145 in the first wave and 129 in the second wave of infection) according to specific treatment methods applied and patients’ individual features, as well as an econometric (quantitative) analysis through structural equation modeling and Gaussian graphical models designed to acknowledge the correlations and causal relationship between all considered coordinates. The main results highlight that the specific treatment methods applied had a positive influence on the evolution of COVID-19 patients, particularly in the second wave of coronavirus pandemic. In case of the first wave of COVID-19 infection, GGM results entail that there is a strong positive correlation between the evolution of the patients and the COVID-19 disease form, which is further positively correlated with the treatment scheme. The evolution of the patients is strongly and inversely correlated with the symptomatology and the ICU hospitalization. Moreover, the disease form is strongly and inversely correlated with oxygen saturation and the residence of patients (urban/rural). The symptomatology at first appearance also strongly depends on the age of the patients (positive correlation) and of the fact that the patient is a smoker or non-smoker and has other comorbidities. Age and gender are also important credentials that shape the disease degree and patient evolution in responding to treatment as well, our study attesting strong interconnections between these coordinates, the form of disease, symptomatology and overall evolution of the patients.

Prognostic value of fasting hyperglycemia in patients with COVID-19 - Diagnostic test accuracy meta-analysis

Aims

This meta-analysis aimed to assess the prognostic value of fasting hyperglycemia in patients with COVID-19.

Methods

A systematic literature search on PubMed, Embase, and Scopus were performed up until February 18, 2021. Fasting hyperglycemia was defined as fasting plasma glucose level above the reference value. The outcome of interest was poor outcome, which was a composite of mortality and severe COVID-19. The effect estimate was in odds ratio (OR).

Results

There were 9045 patients from 12 studies included in this systematic review and meta-analysis. The prevalence of fasting hyperglycemia was 29%. The incidence of poor outcome was 15%. Fasting hyperglycemia was associated with poor outcome in COVID-19 (OR 4.72 [3.32, 6.72], p < 0.001; I²: 69.8%, p < 0.001). Subgroup analysis in patients without prior history of diabetes showed that fasting hyperglycemia was associated with poor outcome in COVID-19 (OR 3.387 [2.433, 4.714], p < 0.001; I²: 0, p = 0.90). Fasting hyperglycemia has a sensitivity of 0.57 [0.45, 0.68], specificity of 0.78 [0.70, 0.84], PLR of 2.6 [2.0, 3.3], NLR of 0.55 [0.44, 0.69], DOR of 5 [3, 7], and AUC of 0.74 [0.70, 0.78] for predicting poor outcome. In this pooled analysis, fasting hyperglycemia has a 32% post-test probability for poor outcome, and absence of fasting hyperglycemia confers to a 9% post-test probability. Meta-regression and subgroup analysis showed that the sensitivity and specificity varies by chronic kidney disease but not by age, male (gender), hypertension, and chronic kidney disease.

Conclusion

Fasting hyperglycemia was associated with mortality in COVID-19 patients, with or without diabetes.

Prospero

CRD42021237997.