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Background: The aim was clinical evaluation of immune response against SARS-CoV-2, analyzing serum levels of IgG antibodies against the SARS-CoV-2 protein S in infected and vaccinated patients, as well as in subjects with and without frequent comorbidities (arterial hypertension, diabetes mellitus, heart disease, and chronic respiratory disease)., Methods: Patients infected by SARS-CoV-2 confirmed by RT-PCR and subjects vaccinated with vaccines based on the mRNA encoding the SARS-CoV-2 protein S were studied. SARS-CoV-2 anti-S IgG serum levels were quantified by chemiluminescent microparticle immunoassay., Results: There were 79 infected patients with a median age of 53.0 years; 35 women and 44 men; 42 patients with any comorbidities and 37 without comorbidities. The median of SARS-CoV-2 anti-S IgG serum level was 203.4 BAU/mL (11.6 - 5,620.6). The median antibody level in the infected patients with any comorbidities was higher than those without comorbidities. The group of vaccinated subjects included 96 subjects with a median age of 49.5 years; 77 women and 19 men; 31 subjects with any comorbidities and 65 without comorbidities. The median of SARS-CoV-2 anti-S IgG serum levels was 1,145.6 BAU/mL (138.3 - 4,828.1). No significant differences were found in terms of specific or global comorbidities in the vaccinated subjects., Conclusions: SARS-CoV-2 anti-S IgG serum levels were 5.6 times higher in vaccinated subjects than infected patients. The vaccination produces higher serum antibody levels than SARS-CoV-2 infection. This reinforces the indication for the vaccine in infected patients. These antibodies did not decrease significantly in patients with frequent comorbidities such as hypertension, diabetes, heart disease or chronic respiratory disease.

Background: Real-time reverse transcription polymerase chain reaction assay (RT-PCR) is the gold standard for diagnosis of coronavirus disease 2019 (COVID-19); however, it is not universally available and may have limitations in response times. The aim was to evaluate the routine blood tests for diagnosis of COVID-19, determining the diagnostic accuracy of blood biomarkers to differentiate between patients with and without COVID-19., Methods: Clinical charts, nursing records, laboratory findings, and chest x-rays from adult patients with clinical suspicion of COVID-19 (fever, cough and/or dyspnea) at hospital admission were reviewed. Patients were classified into two groups according to RT-PCR COVID-19: positive (COVID-19) or negative (NON-COVID-19). Diagnostic accuracy was determined by analyzing receiver operating characteristic (ROC) curve, calculating the area under the ROC curve (AUC) and the cutoff value. In order to reduce the number of false positives, the cutoff value with a specificity of 80% was considered., Results: Two hundred three patients (101 females, 102 males) with ages between 18 and 96 years (mean = 61.3) were studied. Ninety-four were COVID-19 and 109 were NON-COVID-19. Plasma ferritin level was the most accurate biomarker (AUC = 0.847 and 0.804 in women and men, respectively). The following diagnostic criteria for suspected COVID-19 were established with biomarker cutoff values to differentiate between COVID-19 and NON-COVID-19 patients: lymphocytes ≤ 1.0 x 109/L; eosinophils ≤ 0.02 x 109/L; ferritin > 125% of upper reference limit (URL); LDH > 125% of URL; hsCRP > 80 mg/L; and D-dimer > 1.2 mg/L. Sensitivity was 66%, 64% 62%, 46%, 43%, and 33% for ferritin, eosinophils, LDH, hsCRP, lymphocytes, and D-dimer, respectively. Of those determined to be COVID-19 patients, 91% met one or more of the diagnostic criteria with these blood biomarkers, and of the NON-COVID-19 patients, 47% did not met any diagnostic criteria., Conclusions: Blood counts of lymphocytes and eosinophils, and plasma levels of D-dimer, LDH, hsCRP, and ferritin can be used to differentiate patients with and without COVID-19 and as a tool for diagnosis of suspected COVID-19 in adult patients at hospital admission.

Background: The aim was to measure the accuracy of pleural fluid lactate concentration for diagnosis of parapneumonic pleural effusion (PPE) and to discriminate between uncomplicated (UPPE) and complicated PPE (CPPE)., Methods: Pleural fluid lactate was measured in patients with pleural effusion. Patients were classified into two groups according to the etiology of pleural effusion: PPE and NOT PPE., Results: We studied 173 patients. Thirty patients were PPE (10 UPPE and 20 CPPE) and 143 were NOT PPE. The AUC value was 0.831 (p < 0.0001) and the optimal cutoff value was 5.6 mmol/L exhibiting 70% sensitivity and 90.9% specificity for diagnosis of PPE. Also, pleural fluid lactate could be used to discriminate between UPPE and CPPE, the AUC value was 0.740 (p = 0.0089) and the optimal cutoff value was 10.2 mmol/L, exhibiting 45% sensitivity and 90% specificity., Conclusions: Pleural fluid lactate has a high accuracy for diagnosis and management of PPE.

Background: Evaluate the utility of serum lactate dehydrogenase (LDH) in combination with free-to-total serum prostate specific antigen ratio (%fPSA), for diagnosis of prostate cancer (PC) with serum total prostate specific antigen (PSA) levels in the intermediate range of 4 to 10 ng/mL., Methods: The following variables were analysed: PSA, %fPSA, and LDH. Two categories of patients were included in the analysis: NOT PC and PC., Results: We studied 134 patients, 112 had NOT PC and 22 had PC. We defined the following multivariable score (S): S = A + B, where A and B are coefficients of LDH and %fPSA, respectively. AUC values were 0.719 (p = 0.0036), 0.749 (p = 0.0082), and 0.816 (p = 0.0001) for %fPSA, LDH, and S, respectively. Using the proposed S increases by 18% specificity compared to only using the %fPSA parameter., Conclusions: LDH in combination with %fPSA improves diagnostic performance for detection of PC compared to using only %fPSA.

Background: A study to analyse tumor markers (CEA, CA125, CA15.3, CA19.9, CYFRA 21-1, and NSE) for metastasis detection in lung cancer patients., Methods: Serum tumor markers from 73 lung cancer patients were measured before they were diagnosed. After lung cancer diagnosis, tumor markers were analyzed for the detection of distant metastases., Results: In NSCLC patients CYFRA 21-1 and NSE showed differences between stage IV and any of the other stages, p < 0.05. The accuracy for metastasis detection was AUC = 81.5 % for CYFRA 21-1 and AUC = 78.6 % for < 0.05) were independent predictors for metastasis presence. No tumor marker showed significant differences according to stages in SCLC patients., Conclusions: CYFRA 21-1 could be used as a screening tool for metastasis detection in lung cancer patients without symptoms of metastasis as well as CYFRA 21-1 and NSE in NSCLC patients.