Characteristics of SARS-CoV-2, COVID-19, and laboratory diagnosis / Características del SARS-CoV-2, COVID-19 y su diagnóstico en el laboratorio

La enfermedad COVID­19 es causada por el virus SARS-CoV-2, descrito por primera vez en diciembre del 2019 en Wuhan, China, y declarada en marzo del 2020 como una pandemia mundial. Actualmente existen diversos métodos diagnósticos para COVID-19, siendo el estándar de oro la detección del material genético mediante la reacción en cadena de la polimerasa (PCR), en su variante, la RT-PCR, que detecta el material genético de tipo ARN presente en el virus. Sin embargo, es necesario disponer de pruebas rápidas con alta sensibilidad y precisión para realizarlas a gran escala y brindar un diagnóstico oportuno. Adicionalmente, se debe disponer de otras herramientas que, si bien no van a establecer un diagnóstico, le van a permitir al profesional brindar un mejor manejo clínico y epidemiológico que ayuden a predecir el agravamiento del paciente y su posible ingreso a UCI, destacando entre estas los niveles de dímero D, linfocitos, ferritina, urea y creatinina, entre otras. En esta revisión se evalúa la utilidad y limitaciones de los diferentes métodos diagnósticos para COVID-19, al igual que las características, fisiopatología y respuesta inmune al SARS-CoV-2, así como algunos aspectos preanalíticos de importancia que ayudan a minimizar errores en el diagnóstico como consecuencia de procedimientos incorrectos en la toma, transporte y conservación de la muestra, y que permiten al profesional emitir resultados veraces y confiables. Lo anterior se realizó basado en artículos originales, revisiones y guías clínicas

COVID­19 is caused by the SARS-CoV-2 virus, first described in December 2019 in Wuhan, China, and declared a global pandemic in March 2020. Currently there are various diagnostic methods for COVID-19, the gold standard is the detection of genetic material through polymerase chain reaction (PCR) in its variant, RT-PCR, which detects RNA-type genetic material present in the virus. However, it is necessary to have rapid tests with high sensitivity and precision to be performed on a large scale and provide timely diagnosis. Furthermore, other tools must be available, and although they will not establish the diagnosis, will allow the professional to provide better clinical and epidemiological management that will help predict the worsening of the patient and possible admission to the ICU. Among these, levels of D-dimer, lymphocytes, ferritin, urea and creatinine. In this review, the usefulness and limitations of the different diagnostic methods for COVID-19 are evaluated, as well as the characteristics, pathophysiology and immune response to SARS-CoV-2, and some important preanalytical aspects that allow minimizing diagnostic errors as a consequence of incorrect procedures in the collection, transport and conservation of the sample, that allow the professional to yield accurate and reliable results. This article was completed based on original articles, reviews and clinical guidelines

Interleukin-6 (IL-6) as a Predictor of Clinical Outcomes in Patients with COVID-19.

BACKGROUND: Interleukin-6 (IL-6) has been known to be involved in immune regulation, inflammatory response, and metabolism. It is also recognized as the major cause to underscore the pathology of severe COVID-19 patients. However, it remains to be seen if IL-6 is superior to other inflammatory biomarkers in ascertaining clinical severity and mortality rate for COVID-19. This study aimed to determine the value of IL-6 as a predictor of severity and mortality in COVID-19 patients and compare it with other pro-inflammatory biomarkers in the South Asian region. METHODS: An observational study was conducted, including all adult SARS-CoV-2 patients who had undergone IL-6 testing from December 2020 to June 2021. The patients' medical records were reviewed to collect demographic, clinical, and biochemical data. Other pro-inflammatory biomarkers apart from IL-6 included Neutrophils to Lymphocyte Ratio (NLR), D-dimer, C-reactive protein (CRP), ferritin, lactate dehydrogenase (LDH), and procal-citonin for analysis. SPSS version 22.0 was utilized. RESULTS: Out of the 393 patients who underwent IL-6 testing, 203 were included in the final analysis with a mean (SD) age of 61.9 years (12.9) and 70.9% (n = 144) were male. Fifty-six percent (n = 115) subjects had critical disease. IL-6 levels were elevated (> 7 pg/mL) in 160 (78.8%) patients. Levels of IL-6 significantly correlated with age, NLR, D-dimer, CRP, ferritin, LDH, length of stay, clinical severity, and mortality. All the inflammatory markers were significantly increased in critically ill and expired patients (p < 0.05). The receiver operator curve showed that IL-6 had the best area under the curve (0.898) compared to other pro-inflammatory biomarkers for mortality with comparable results for clinical severity. CONCLUSIONS: Study findings show that though IL-6 is an effective marker of inflammation and can be helpful for clinicians in recognizing patients with severe COVID-19. However, we still need further studies with larger sample size.

Predictors of COVID-19 severity among pregnant patients.

Coronavirus disease 2019 (COVID-19) was declared a pandemic and has spread around the globe, unsparingly affecting vulnerable populations. Effective prevention measures for pregnant women, who are particularly affected, include early identification of those patients at risk of developing in-hospital complications, and the continuous improvement of maternal-fetal treatment strategies to ensure the efficient use of health resources. The objective of our retrospective study was to determine which patient biomarkers on hospital admission correlate with disease severity as measured by disease course classification, the need for oxygen supplementation and higher demand for oxygen, the need for mechanical ventilation, intensive care unit admission, and length of hospital stay. Analysis of 52 PCR SARS-CoV-2 positive pregnant women revealed that the median date of hospital admission was the 30th gestational week, with dyspnoea, cough, and fever as the leading symptoms. The presence of diabetes and hypertension predisposed pregnant women to the severe course of illness. Lung involvement shown by CT scans on admission correlated with the greater clinical severity. The main laboratory predictors of disease progression were lymphocytopenia, hypocalcemia, low total cholesterol, low total protein levels, and high serum levels of C-reactive protein, ferritin, interleukin-6, glucose, lactate dehydrogenase, procalcitonin, and troponin I. Further research with a larger cohort of pregnant women is needed to determine the utility of these results for everyday practice.

Predictors of New-Onset Diabetes in Hospitalized Patients with SARS-CoV-2 Infection.

The pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is one of the world's most disruptive health crises. The presence of diabetes plays an important role in the severity of the infection, and a rise in newly diagnosed diabetes cases has been identified. The aim of this retrospective study was to determine the incidence of new-onset diabetes (NOD) and predictive factors with their cut-off values for patients hospitalized with COVID-19. All patients (n = 219) hospitalized for COVID-19 during three consecutive months were included. NOD was diagnosed in 26.48% of patients. The severity of the infection, hospital admission values for fasting plasma glucose, lactate dehydrogenase (LDH), PaO2/FiO2 ratio, the peak values for leucocytes, neutrophils, C-reactive protein, triglycerides, and the need for care in the intensive care unit were predictors for the occurrence of NOD in univariate analysis, while only LDH level remained a significant predictor in the multivariable analysis. In conclusion, the results of the study showed a high incidence of NOD in patients hospitalized with COVID-19 and identified LDH levels at hospital admission as a significant predictor of NOD during SARS-CoV-2 infection. However, the persistence of NOD after the COVID-19 infection is not known, therefore, the results must be interpreted with caution.

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.

National early warning score on admission as risk factor for invasive mechanical ventilation in COVID-19 patients: A STROBE-compliant study.

ABSTRACT: The coronavirus disease (COVID-19) has become a global pandemic. Invasive mechanical ventilation is recommended for the management of patients with COVID-19 who have severe respiratory symptoms. However, various complications can develop after its use. The efficient and appropriate management of patients requires the identification of factors associated with an aggravation of COVID-19 respiratory symptoms to a degree where invasive mechanical ventilation becomes necessary, thereby enabling clinicians to prevent such ventilation. This retrospective study included 138 inpatients with COVID-19 at a tertiary hospital. We evaluated the differences in the demographic and clinical data between 27 patients who required invasive mechanical ventilation and 111 patients who did not. Multivariate logistic regression analysis indicated that the duration of fever, national early warning score (NEWS), and lactate dehydrogenase (LDH) levels on admission were significantly associated with invasive mechanical ventilation in this cohort. The optimal cut-off values were: fever duration ≥1 day (sensitivity 100.0%, specificity 54.95%), NEWS ≥7 (sensitivity 72.73%, specificity 92.52%), and LDH >810 mg/dL (sensitivity 56.0%, specificity 90.29%). These findings can assist in the early identification of patients who will require invasive mechanical ventilation. Further studies in larger patient populations are recommended to validate our findings.

Increased lactate dehydrogenase reflects the progression of COVID-19 pneumonia on chest computed tomography and predicts subsequent severe disease.

Chest computed tomography (CT) is effective for assessing the severity of coronavirus disease 2019 (COVID-19). However, the clinical factors reflecting the disease progression of COVID-19 pneumonia on chest CT and predicting a subsequent exacerbation remain controversial. We conducted a retrospective cohort study of 450 COVID-19 patients. We used an automated image processing tool to quantify the COVID-19 pneumonia lesion extent on chest CT at admission. The factors associated with the lesion extent were estimated by a multiple regression analysis. After adjusting for background factors by propensity score matching, we conducted a multivariate Cox proportional hazards analysis to identify factors associated with severe disease after admission. The multiple regression analysis identified, body-mass index (BMI), lactate dehydrogenase (LDH), C-reactive protein (CRP), and albumin as continuous variables associated with the lesion extent on chest CT. The standardized partial regression coefficients for them were 1.76, 2.42, 1.54, and 0.71. The multivariate Cox proportional hazards analysis identified LDH (hazard ratio, 1.003; 95% confidence interval, 1.001-1.005) as a factor independently associated with the development of severe COVID-19 pneumonia. Increased serum LDH at admission may be useful in real-world clinical practice for the simple screening of COVID-19 patients at high risk of developing subsequent severe disease.

Lactate dehydrogenase and PaO2/FiO2 ratio at admission helps to predict CT score in patients with COVID-19: An observational study.

INTRODUCTION: Since the beginning of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pandemic an important tool for patients with Coronavirus Disease 2019 (COVID-19) has been the computed tomography (CT) scan, but not always available in some settings The aim was to find a cut-off that can predict worsening in patients with COVID-19 assessed with a computed tomography (CT) scan and to find laboratory, clinical or demographic parameters that may correlate with a higher CT score. METHODS: We performed a multi-center, observational, retrospective study involving seventeen COVID-19 Units in southern Italy, including all 321 adult patients hospitalized with a diagnosis of COVID-19 who underwent at admission a CT evaluated using Pan score. RESULTS: Considering the clinical outcome and Pan score, the best cut-off point to discriminate a severe outcome was 12.5. High lactate dehydrogenase (LDH) serum value and low PaO2/FiO2 ratio (P/F) resulted independently associated with a high CT score. The Area Under Curve (AUC) analysis showed that the best cut-off point for LDH was 367.5 U/L and for P/F 164.5. Moreover, the patients with LDH> 367.5 U/L and P/F < 164.5 showed more frequently a severe CT score than those with LDH< 367.5 U/L and P/F> 164.5, 83.4%, vs 20%, respectively. CONCLUSIONS: A direct correlation was observed between CT score value and outcome of COVID-19, such as CT score and high LDH levels and low P/F ratio at admission. Clinical or laboratory tools that predict the outcome at admission to hospital are useful to avoiding the overload of hospital facilities.

Reducing unnecessary routine laboratory testing for noncritically ill patients with COVID-19.

BACKGROUND: Reducing unnecessary routine laboratory testing is a Choosing Wisely® recommendation, and new areas of overuse were noted during the COVID-19 pandemic. OBJECTIVE: To reduce unnecessary repetitive routine laboratory testing for patients with COVID-19 during the pandemic across a large safety net health system. DESIGNS, SETTINGS AND PARTICIPANTS: This quality improvement initiative was initiated by the System High-Value Care Council at New York City Health + Hospitals (H + H), the largest public healthcare system in the United States consisting of 11 acute care hospitals. INTERVENTION: four overused laboratory tests in noncritically ill hospitalized patients with COVID-19 were identified: C-reactive protein (CRP), ferritin, lactate dehydrogenase (LDH), and procalcitonin. A two-pronged electronic health record intervention was implemented consisting of (1) nonintrusive, informational nudge statements placed on selected order sets, and (2) a forcing function of one consecutive day limit on ordering. MAIN OUTCOME AND MEASURES: The average of excess tests per encounter days (ETPED) for each of four target laboratory testing only in patients with COVID-19. OBJECTIVE: Interdisciplinary System High-Value Care Council identified four overused laboratory tests (inflammatory markers) in noncritically ill hospitalized patients with COVID-19: C-reactive protein (CRP), ferritin, lactate dehydrogenase (LDH), and procalcitonin. Within an 11-hospital safety net health system, a two-pronged electronic health record intervention was implemented consisting of (1) nonintrusive, informational nudge statements placed on selected order sets, and (2) a forcing function of one consecutive day limit on ordering. The preintervention period (March 16, 2020 to January 24, 2021) was compared to the postintervention period (January 25, 2021 to March 22, 2022). RESULTS: Time series linear regression showed decreases in CRP (-17.9%, p < .05), ferritin (-37.6%, p < .001), and LDH (-30.1%, p < .001). Slope differences were significant (CRP, ferritin, and LDH p < 0.001; procalcitonin p < 0.05). Decreases were observed across weekly averages: CRP (-19%, p < .01), ferritin (-37.9%, p < .001), LDH (-28.7%, p < .001), and procalcitonin (-18.4%, p < .05). CONCLUSION: This intervention was associated with reduced routine inflammatory marker testing in non-intensive care unit COVID-19 hospitalized patients across 11 hospitals. Variation was high among individual hospitals.

Abnormal myocardial enzymes in the prediction of mortality and hypertension in COVID-19 patients: a retrospective study.

This study aims to determine the differences in myocardial enzymes in COVID-19 patients with and without hypertension. A total of 130 patients with COVID-19 in Yunmeng County People's Hospital were analyzed. The clinical manifestations and laboratory indicators were collected and analyzed. We found that COVID-19 patients with hypertension had higher mortality rate, greater age, and higher rates of basic disease such as diabetes than patients without hypertension. The γ-glutamyl transpeptidase (GGT), blood urea nitrogen (BUN), albumin/globulin (A/G), Ca, Mg, lactate dehydrogenase (LDH), and α-hydroxybutyric-dehydrogenase (α-HBD) levels in COVID-19 patients with hypertension were higher than in COVID-19 patients without hypertension. We found that the predictive effect of the creatine kinase isoenzyme (CK-MB), LDH-L, and α-HBD levels in the COVID-19 patients without hypertension were higher than in COVID-19 patients with hypertension. We used the ROC curve model to predict whether patients would have hypertension, and we found that CK-MB, LDH-L and HBD parameters could distinguish the COVID-19 patients with hypertension and non-hypertension, and could predict the mortality of COVID-19 patients.

Predicting the risk of chest radiograph abnormality 12-weeks post hospitalisation with SARS CoV-2 PCR confirmed COVID-19.

BACKGROUND: Routine follow-up of patients hospitalised with COVID-19 is recommended, however due to the ongoing high number of infections this is not without significant health resource and economic burden. In a previous study we investigated the prevalence of, and risk factors for, persistent chest radiograph (CXR) abnormalities post-hospitalisation with COVID-19 and identified a 5-point composite score that strongly predicted risk of persistent CXR abnormality at 12-weeks. Here we sought to validate and refine our findings in an independent cohort of patients. METHODOLOGY: A single-centre prospective study of consecutive patients attending a virtual post-hospitalisation COVID-19 clinic and CXR as part of their standard clinical care between 2nd March - 22nd June 2021. Inpatient and follow-up CXRs were scored by the assessing clinician for extent of pulmonary infiltrates (0-4 in each lung) with complete resolution defined as a follow-up score of zero. RESULTS: 182 consecutive patients were identified of which 31% had persistent CXR abnormality at 12-weeks. Patients with persistent CXR abnormality were significantly older (p < 0.001), had a longer hospital length of stay (p = 0.005), and had a higher incidence of both level 2 or 3 facility admission (level 2/3 care) (p = 0.003) and ever-smoking history (p = 0.038). Testing our composite score in the present cohort we found it predicted persistent CXR abnormality with reasonable accuracy (area under the receiver operator curve [AUROC 0.64]). Refining this score replacing obesity with Age ≥ 50 years, we identify the SHADE-750 score (1-point each for; Smoking history, Higher-level care (level 2/3 admission), Age ≥ 50 years, Duration of admission ≥ 15 days and Enzyme-lactate dehydrogenase (LDH ≥ 750U/L), that accurately predicted risk of persistent CXR abnormality, both in the present cohort (AUROC 0.73) and when retrospectively applied to our 1st cohort (AUROC 0.79). Applied to both cohorts combined (n = 213) it again performed strongly (AUROC 0.75) with all patients with a score of zero (n = 18) having complete CXR resolution at 12-weeks. CONCLUSIONS: In two independent cohorts of patients hospitalised with COVID-19, we identify a 5-point score which accurately predicts patients at risk of persistent CXR abnormality at 12-weeks. This tool could be used by clinicians to identify patients in which radiological follow-up may not be required.

Evaluating the Factors Affecting COVID-19 Patients' Mortality in Arak in 2020.

Background: The coronavirus disease 2019 (COVID-19) pandemic has been a leading cause of death in the world in the last few years. This study has investigated various causes and risk factors that may lead to death due to this disease. Methods: From June to October 2020, 98 expired and 196 recovered patients were studied for risk factors, underlying diseases, and laboratory findings that could lead to disease progression and mortality. Results: There was a significant relationship in terms of blood pressure, age, oxygen saturation, tachycardia, tachypnea, the interval between the onset of symptoms and hospitalization, diabetes mellitus, lung disease, cardiovascular disease, history of opium abuse, C-reactive protein, white blood cell, lymphocytes, hemoglobin, creatinine elevation, elevated liver enzyme, creatine phosphokinase, lactate dehydrogenase, ferritin, D-dimer, troponin, prothrombin time, international normalized ratio, intensive care unit admission days, arrhythmia, sepsis, acute respiratory distress syndrome, acute kidney injury (AKI), and the type of antiviral and antibiotic therapy between the two groups of patients. Conclusions: Mortality due to COVID-19 is affected by various causes such as age, underlying diseases, and complications that may occur in the course of the disease (e.g., arrhythmia, myocardial infarction, and AKI). By accurately identifying these causes and risk factors, we can prevent these complications and the mortality from COVID-19.

Lactate dehydrogenase/albumin ratio as a prognostic factor in severe acute respiratory distress syndrome cases associated with COVID-19.

BACKGROUND: Patients with severe acute respiratory distress syndrome (ARDS) have high mortality rates; therefore, new biomarkers are necessary to predict the prognosis in the early stages. Serum lactate dehydrogenase (LDH) level is a specific marker of lung damage, but it is not sensitive because it is affected by several factors. This study aimed to determine whether the LDH/albumin ratio could be used as a prognostic biomarker in patients with severe ARDS due to COVID 19. METHODS: Tertiary intensive care unit (ICU) patients with severe ARDS and confirmed COVID-19 diagnosis between August 1, 2020, and October 31, 2021, were included. The demographic and clinical characteristics of the patients were recorded from the hospital databases, together with laboratory results on the day of admission to the ICU and the length of stay in the ICU and hospital. LDH/albumin, lactate/albumin, C-reactive protein (CRP)/albumin, and BUN/albumin ratios were calculated. Logistic regression analysis was performed to determine independent risk factors affecting mortality. RESULTS: Nine hundred and five patients hospitalized in a tertiary ICU were evaluated. Three hundred fifty-one patients with severe ARDS were included in this study. The mortality rate of the included patients was 61.8% (of 217/351). LDH/albumin, lactate/albumin, and BUN/albumin ratios were higher in the nonsurvivor group (P < .001). The area under the curve (AUC) from the receiver operating characteristic analysis that predicted in-hospital mortality was 0.627 (95% confidence intervals (CI): 0.574-0.678, P < .001) for the LDH/albumin ratio, 0.605 (95% CI: 0.551-0.656, P < .001) for lactate/albumin, and 0.638 (95% CI: 0.585-0.688, P < .001) for BUN/albumin. However, LDH/albumin ratio was independently associated with mortality in multivariate logistic regression analysis. CONCLUSION: LDH/albumin ratio can be used as an independent prognostic factor for mortality in patients with severe ARDS caused by COVID-19.

Serum creatinine to absolute lymphocyte count ratio effectively risk stratifies patients who require intensive care in hospitalized patients with coronavirus disease 2019.

Patients with preexisting kidney disease or acute kidney injury had poorer outcomes in coronavirus disease 2019 (COVID-19) illness. Lymphopenia was associated with more severe illness. Risk stratification with simple laboratory tests may help appropriate site patients in a cost-effective manner and ease the burden on healthcare systems. We examined a ratio of serum creatinine level to absolute lymphocyte count at presentation (creatinine-lymphocyte ratio, CLR) in predicting outcomes in hospitalized patients with COVID-19. We analyzed 553 consecutive polymerase chain reaction-positive SARS-COV-2 hospitalized patients. Patients with end-stage kidney disease were excluded. Serum creatinine and full blood count (FBC) examination were obtained within the first day of admission. We examined the utility of CLR in predicting adverse clinical outcomes (requiring intensive care, mechanical ventilation, acute kidney injury requiring renal replacement therapy or death). An optimized cutoff of CLR > 77 was derived for predicting adverse outcomes (72.2% sensitivity, and 83.9% specificity). Ninety-seven patients (17.5%) fell within this cut off. These patients were older and more likely to have chronic medical conditions. A higher proportion of these patients had adverse outcomes (13.4% vs 1.1%, P < .001). On receiver operating curve analyses, CLR predicted patients who had adverse outcomes well (area under curve [AUC] = 0.82, 95%CI 0.72-0.92), which was comparable to other laboratory tests like serum ferritin, C-reactive protein and lactate dehydrogenase. Elevated CLR on admission, which may be determined by relatively simple laboratory tests, was able to reasonably discriminate patients who had experienced adverse outcomes during their hospital stay. This may be a simple and cost-effective means of risk stratification and triage.

Identification of Predictive Markers of Response to Immunomodulators in the Treatment of COVID-19 Patients.

BACKGROUND: Proper identification of patients at risk of developing serious disease in the context of SARS-CoV-2 infection, as well as the initiation of early treatment, is one of the fundamental elements for successful management of COVID-19. The main objective of this study was to evaluate the usefulness of serum biomarkers (neutrophils, lymphocytes, C-reactive protein, lactate dehydrogenase, D-dimer, ferritin, and interleukin-6) to predict the early response to immunosuppressant therapy in COVID-19 patients. METHODS: This is a case-control study nested in a retrospective cohort, which included hospitalized patients with interstitial pneumonia and with elevation of some proinflammatory parameters. Each of the individuals who died during the 28-day follow-up was defined as a case. For each case, 4 controls were selected, matched by age, gender, and comorbidities. RESULTS: The initial cohort included 856 patients. The incidence of therapeutic failure in the cohort was 14%, thus we identified a total of 120 cases. After the application of a Cox regression model, high serum concentrations of LDH (> 451 IU/L), ferritin (> 1,014 ng/mL) and D-Dimer (> 1,300 ng/mL) were identified as predictors of poor response to treatment. Highly-specific cut-off points could not be established for any of these biomarkers. CONCLUSIONS: Some inflammatory biomarkers, such as LDH, ferritin, and D-dimer, may be helpful in identifying patients for whom an early immunomodulatory therapeutic intervention should be considered in the treatment of COVID-19 patients with pneumonia.

Diagnostic Value of Natural Killer Cells, CD56+ CD16+ Natural Killer Cells, NLRP3, and Lactate Dehydrogenase in Severe/Critical COVID-19: A Prospective Longitudinal Study According to the Severe/Critical COVID-19 Definitions.

Innate immunity, as the first line of defense of our immune system, plays a crucial role in defending against SARS-CoV-2 infection and also its immunopathogenesis. We aim to investigate the immune status of natural killer (NK) cells, natural killer T (NKT) cells, and NLRP3 gene expression in COVID-19 patient blood samples. The immunophenotype of NK cell subsets and NKT cells was detected by flow cytometry and the expression of NLRP3 gene assessed by reverse transcriptase real-time polymerase chain reaction in 44 COVID-19 patients and 20 healthy individuals. The percentage of most of NK cell subpopulation and NKT cells was significantly decreased in COVID-19 patients. The percentage of CD56dim CD16- NK cell subsets, and NLRP3 gene expression increased. The percentage of total NK cells, CD56+ CD16+ NK cells, and NLRP3 gene expression had acceptable sensitivity and specificity for assisting diagnosis of severe/critical COVID-19. O2 saturation% and lactate dehydrogenase levels showed valuable diagnostic value to identify critical cases. The declined NK and NKT cells in COVID-19 patients and enhanced NLRP3 gene expression were associated with disease severity. Total NK cells, CD56+ CD16+ NK cells, and NLRP3 gene expression might be used as meaningful indicators for assisting diagnosis of severe/critical COVID-19.

The role of electrolyte imbalances in predicting the severity of COVID-19 in the hospitalized patients: a cross-sectional study.

Coronavirus disease 2019 (COVID-19) can be fatal in severe cases. Accordingly, predicting the severity and prognosis of the disease is valuable. This study examined the role of electrolyte imbalances in predicting the severity of COVID-19. In this cross-sectional study, 169 hospitalized patients with COVID-19 were included and categorized into three groups based on the severity of the disease (moderate, severe, and critical). Serum levels of electrolytes (calcium [Ca], phosphorus [P], sodium [Na], potassium [k], and magnesium [Mg]), inflammatory markers (D-dimer, C-reactive protein [CRP], ferritin, and lactate dehydrogenase [LDH]), and 25OHVitamin D were measured. The mean age of patients was 53 years, and 54% were male. They had moderate, severe, and critical illnesses in 22%, 47%, and 31%, respectively. CRP, D-dimer, and ferritin increased with the severity of the disease. The lower median values of Mg, Na, 25OHVitamin D, Ca, LDH, and higher median lymphocyte counts were observed in the moderate vs. the severe group (P < 0.05). These parameters have acceptable sensitivity and specificity at the suggested cut-off level to discriminate the moderate and critical cases. Serum parameters introduced in this study are appropriate for differentiating between critical and moderate cases. The electrolyte imbalance can predict critical patients.

Clinical Characteristics Predicting Mortality Risk in Hospitalized Geriatric Patients with COVID-19 Pneumonia: a Retrospective Study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Geriatric patients with COVID-19 are more likely to progress to severe disease, and they are at increased risk of hospitalization and mortality. In this study we aimed to investigate the risk factors for predicting mortality in geriatric patients with COVID 19 by reviewing the clinical data of survivors and non-survivors. METHODS: This was a retrospective study of 189 geriatric patients with COVID- 19 pneumonia who were hospitalized in pulmonology clinic, in Duzce University, Medical Faculty Hospital between March 2020 and January 2021 in Turkey. RESULTS: In the study, 60.3% (n = 114) of the patients were male and the median age was 75. 80.4% (n = 152) of the patients were discharged. The presence of cardiovascular disease, chronic renal failure, malignancy, increased number of comorbidities, complaints of anorexia, no fever, decreased oxygen saturation value, increased pulse rate, high values of maximum (max) D-dimer, aspartate aminotransferase, urea, creatinine, troponin, lactate dehydrogenase (LDH), max LDH, ferritin and max ferritin, C-reactive protein (CRP), max CRP, procalcitonin, max procalcitonin, potassium values and low albumin values, complications as bacterial infection, cardiac disease, acute respiratory distress syndrome, liver function tests failure, arrhythmia and shock, the need for corticosteroid and pulse corticosteroid therapy increased the mortality. According to multiple logistic regression model, the de-velopment of cardiac disease, acute respiratory distress syndrome, bacterial infection, the need for pulse steroids, and the max ferritin value increased the risk of mortality by between 1.001 and 28.715 times. CONCLUSIONS: Both clinical and laboratory parameters predicting mortality in geriatric patients with COVID-19 pneumonia should be monitored very carefully. Complications that develop should be evaluated and multidisciplinary and necessary treatments should be initiated without delay.

Baseline laboratory parameters for preliminary diagnosis of COVID-19 among children: a cross-sectional study.

BACKGROUND: Clinical judgment of initial baseline laboratory tests plays an important role in triage and preliminary diagnosis among coronavirus disease 2019 (COVID-19) patients. OBJECTIVES: To determine the differences in laboratory parameters between COVID-19 and COVID-like patients, and between COVID-19 and healthy children. Additionally, to ascertain whether healthy children or patients with COVID-like symptoms would form a better control group. DESIGN AND SETTING: Cross-sectional study at the Institute for Child and Youth Health Care of Vojvodina, Novi Sad, Serbia. METHODS: A retrospective study was conducted on 42 pediatric patients of both sexes with COVID-19. Hematological parameters (white blood cell count, absolute lymphocyte count and platelet count) and biochemical parameters (natremia, kalemia, chloremia, aspartate aminotransferase [AST], alanine aminotransferase [ALT], lactate dehydrogenase [LDH] and C-reactive protein [CRP]) were collected. The first control group was formed by 80 healthy children and the second control group was formed by 55 pediatric patients with COVID-like symptoms. RESULTS: Leukocytosis, lymphopenia, thrombocytosis, elevated systemic inflammatory index and neutrophil-lymphocyte ratio, hyponatremia, hypochloremia and elevated levels of AST, ALT, LDH and CRP were present in COVID patients, in comparison with healthy controls, while in comparison with COVID-like controls only lymphopenia was determined. CONCLUSIONS: The presence of leukocytosis, lymphopenia, thrombocytosis, elevated systemic inflammatory index and neutrophil-lymphocyte ratio, hyponatremia, hypochloremia and elevated levels of AST, ALT, LDH and CRP may help healthcare providers in early identification of COVID-19 patients. Healthy controls were superior to COVID-like controls since they provided better insight into the laboratory characteristics of children with novel betacoronavirus (SARS-CoV-2) infection.

The Lactate and the Lactate Dehydrogenase in Inflammatory Diseases and Major Risk Factors in COVID-19 Patients.

Lactate dehydrogenase (LDH) is a terminating enzyme in the metabolic pathway of anaerobic glycolysis with end product of lactate from glucose. The lactate formation is crucial in the metabolism of glucose when oxygen is in inadequate supply. Lactate can also be formed and utilised by different cell types under fully aerobic conditions. Blood LDH is the marker enzyme, which predicts mortality in many conditions such as ARDS, serious COVID-19 and cancer patients. Lactate plays a critical role in normal physiology of humans including an energy source, a signaling molecule and a pH regulator. Depending on the pH, lactate exists as the protonated acidic form (lactic acid) at low pH or as sodium salt (sodium lactate) at basic pH. Lactate can affect the immune system and act as a signaling molecule, which can provide a "danger" signal for life. Several reports provide evidence that the serum lactate represents a chemical marker of severity of disease similar to LDH under inflammatory conditions. Since the mortality rate is much higher among COVID-19 patients, associated with high serum LDH, this article is aimed to review the LDH as a therapeutic target and lactate as potential marker for monitoring treatment response of inflammatory diseases. Finally, the review summarises various LDH inhibitors, which offer potential applications as therapeutic agents for inflammatory diseases, associated with high blood LDH. Both blood LDH and blood lactate are suggested as risk factors for the mortality of patients in serious inflammatory diseases.