Anticoagulants in COVID-19:Is there a role for a D-dimerdriven dosing ?

Introduction: The optimal anticoagulant treatment regimen in hospitalized COVID-19 patients is debated amid studies investigating the effectiveness of different dosing strategies. Aims and Objectives: The aim of this study was to compare the rates of disease progression and mortality in patients treated with LMWH according to a protocol based on baseline D-dimer levels (prophylactic dose when level is below 1000 ng/mL, intermediate dose between 1000 and 3000 ng/mL, therapeutic dose when levels exceed 3000 ng/mL)(on-protocol) and those treated with a fixed-dose regimen (off-protocol). Method(s): This was a retrospective analysis of all patients admitted to a university hospital for COVID-19 pneumonia during a one-year period. Out of a total of 384 patients (mean age 61.5+/-15.9y, 216 male), 294 patients with complete data composed the study group. Result(s): 174 patients were treated on-protocol and 120 patients were off-protocol. The on-protocol group had higher CRP, ferritin, LDH and D-dimer levels and lower SpO2/FiO2 levels at admission. Disease progression developed in 44 out of 174 on-protocol patients (25.3%) vs 53 of 120 off-protocol patients (44.2%) during the follow-up (p=0.001) and 29 (16.7%) vs 32 (26.7%), respectively, died in hospital (p=0.041). Logistic regression analysis was performed and included age, presence of comorbidities, LMWH regimen, baseline SpO2/FiO2, CRP and LDH levels as independent variables. The presence of cardiac comorbidity, age and LDH levels, but not LMWH treatment regimen, were associated with both disease progression and mortality. Conclusion(s): A d-dimer-driven LMWH treatment protocol is not associated with better clinical outcomes in hospitalized COVID-19 patients.

Can Some Viral Respiratory Infections Observed Before the Pandemic Announcement Be Related to SARS-CoV-2?

OBJECTIVE: There have been doubts that SARS-CoV-2 has been circulating before the first case was announced. The aim of this study was to evaluate the possibility of COVID-19 in some cases diagnosed to be viral respiratory tract infection in the pre-pandemic period in our center. MATERIAL AND METHODS: Patients who were admitted to our hospital's pulmonary diseases, infectious diseases, and intensive care clinics with the diagnosis of viral respiratory system infection within a 6-month period between October 2019 and March 12, 2020, were screened. Around 248 archived respiratory samples from these patients were analyzed for SARS-CoV-2 ribonucleic acid by real-time-quantitative polymerase chain reaction. The clinical, laboratory, and radiological data of the patients were evaluated. RESULT(S): The mean age of the study group was 47.5 (18-89 years);103 (41.5%) were female and 145 (58.4%) were male. The most common presenting symptoms were cough in 51.6% (n = 128), fever in 42.7% (n = 106), and sputum in 27.0% (n = 67). Sixty-nine percent (n = 172) of the patients were pre-diagnosed to have upper respiratory tract infection and 22.0% (n = 55) had pneumonia, one-third of the patients (n = 84, 33.8%) were followed in the service. Respiratory viruses other than SARS-CoV-2 were detected in 123 (49.6%) patients. Influenza virus (31.9%), rhinovirus (10.5%), and human metapneumovirus (6.5%) were the most common pathogens, while none of the samples were positive for SARS-CoV-2 RNA. Findings that could be significant for COVID-19 pneumonia were detected in the thorax computed tomography of 7 cases. CONCLUSION(S): The negative SARS-CoV-2 real-time-quantitative polymerase chain reaction results in the respiratory samples of the cases followed up in our hospital for viral pneumonia during the pre-pandemic period support that there was no COVID-19 among our cases during the period in question. However, if clinical suspicion arises, both SARS and non-SARS respiratory viral pathogens should be considered for differential diagnosis.Copyright © Author(s).

Epidemiology and Acute Respiratory Distress Syndrome Propensity of Viral Respiratory Infections in Pediatric Intensive Care Units Prior to the Coronavirus Disease 2019 Pandemic

This study aimed to determine the epidemiology and acute respiratory distress syndrome (ARDS) propensity of common respiratory viruses in a tertiary pediatric intensive care unit (PICU) among hospitalized children who were tested for respiratory viruses by polymerase chain reaction (PCR) prior to the coronavirus disease 2019 (COVID-19) pandemic. Respiratory tract samples were collected from patients who were followed up in the Dokuz Eylul University Hospital pediatric intensive care unit between March 2015 and March 2020 and tested for viral pathogens. The results of 269 patients between 1 month and 18 years of age were evaluated retrospectively. In the 5 years preceding the COVID-19 pandemic, 269 patients with a lower respiratory infection were admitted to the PICU. A positive viral PCR result was detected in 160 patients (59.5%). Human rhinovirus was the most common virus (40%), followed by respiratory syncytial virus (26.3%), human bocavirus (10%), and seasonal coronaviruses (10%). Five (33.3%) of the fifteen children who developed ARDS were infected with influenza A/B, while four (26.7%) were infected with human metapneumovirus (hMPV). Although rhinovirus was the most common viral agent in critically ill children, the incidence of ARDS was higher in children aged over 1 year who had influenza or hMPV infection.

The predictors of long-COVID in the cohort of Turkish Thoracic Society-TURCOVID multicenter registry: One year follow-up results

Objective: To evaluate long-term effects of COVID-19, and to determine the risk factors in long-COVID in a cohort of the Turkish Thoracic Society (TTS)-TURCOVID multicenter registry. Method(s): Thirteen centers participated with 831 patients;504 patients were enrolled after exclusions. The study was designed in three-steps: (1) Phone questionnaire;(2) retrospective evaluation of the medical records;(3) face-to-face visit. Result(s): In the first step, 93.5% of the patients were hospitalized;61.7% had a history of pneumonia at the time of diagnosis. A total of 27.1% reported clinical symptoms at the end of the first year. Dyspnea (17.00%), fatigue (6.30%), and weakness (5.00%) were the most prevalent long-term symptoms. The incidence of long-term symptoms was increased by 2.91 fold (95% CI 1.04-8.13, P=0.041) in the presence of chronic obstructive pulmonary disease and by 1.84 fold (95% CI 1.10-3.10, P=0.021) in the presence of pneumonia at initial diagnosis, 3.92 fold (95% Cl 2.29-6.72, P=0.001) of dyspnea and 1.69 fold (95% Cl 1.02-2.80, P=0.040) fatigue persists in the early-post-treatment period and 2.88 fold (95% Cl 1.52-5.46, P=0.001) in the presence of emergency service admission in the post COVID period. In step 2, retrospective analysis of 231 patients revealed that 1.4% of the chest X-rays had not significantly improved at the end of the first year, while computed tomography (CT) scan detected fibrosis in 3.4%. In step 3, 138 (27.4%) patients admitted to face-to-face visit at the end of first year;at least one symptom persisted in 49.27% patients. The most common symptoms were dyspnea (27.60%), psychiatric symptoms (18.10%), and fatigue (17.40%). Thorax CT revealed fibrosis in 2.4% patients. Conclusion(s): COVID-19 symptoms can last for extended lengths of time, and severity of the disease as well as the presence of comorbidities might contribute to increased risk. Long-term clinical issues should be regularly evaluated after COVID-19. Copyright © 2022 Asian Pacific Journal of Tropical Medicine Produced by Wolters Kluwer Medknow.

Tracking SARS-CoV-2, Ízmir, Turkey

Objective: With the rapid spread of SARS-CoV-2, a new coronavirus, around the world, a pandemic was declared by World Health Organization on March 2020. The first cases were reported in March 2020 from Turkey. In our hospital, the first pediatric case was detected on April 2, 2020. However, there is no data on whether this virus had been present in our region or not before this date. The aim of our study was to de-termine the first entry of SARS-CoV-2 virus to our region for pediatric patients. Material and Methods: SARS-CoV-2 positivity was investigated retro-spectively with the RT-qPCR method in the pediatric respiratory tract specimens taken between the October 1, 2019 and March 31, 2020. In the specimens, SARS-CoV-2 RNA was studied using real-time PCR based “COVID-19 RT-qPCR Detection Kit”. Results: 886 samples were included in the study. Of the respiratory tract specimens, 97.1% were nasopharyngeal swabs, 2.8% were bronchoal-veolar lavage. Most frequently, rhinovirus (28.6%), influenza A subtype H1N1 (pandemic H1N1) (18.5%) and influenza B (16%) were detected. Rhinovirus and enterovirus were the most frequent double agents seen together. No SARS-CoV-2 positivity was detected in the respiratory tract specimens studied. Conclusion: SARS-CoV-2 PCR test was conducted in a limited number of centers at the beginning of the pandemics may have affected the detection of the first case in Turkey. Multicenter studies of archived samples would enable more realistic results in tracking SARS-CoV-2 in our country.

Clinical outcome of pcr-negative covid-19 patients: A retrospective study

OBJECTIVE: To evaluate the clinical features and outcomes of patients who were admitted with a diagnosis of coronavirus disease 2019 (COVID-19) but who were not confirmed with polymerase chain reaction (PCR) positivity. MATERIAL AND METHODS: This is a retrospective analysis of all patients admitted to two tertiary care centers between March 15 and May 15, 2020, with a diagnosis of COVID-19. From a common database prepared for COVID-19, we retrieved the relevant data and compared the clinical findings and outcomes of PCR-positive patients with those of PCR-negative cases who had been diagnosed on the basis of typical clinical and radiographic findings. RESULTS: A total of 349 patients were included in the analysis, of which 126 (36.1%) were PCR-negative. PCR-negative patients were younger (54.6 ± 20.8 vs. 60.8 ± 18.9 years, P = .009) but were similar to PCR-positive patients in terms of demographics, comorbidities, and presenting symptoms. They had higher lymphocyte counts (1519 ± 868 vs. 1331 ± 737/mm3, P = .02) and less frequently presented with bilateral radiographic findings (68.3% vs. 79.4%, P = .046) than PCR-positive patients. Besides, they had less severe disease and better clinical outcomes regarding admission to the intensive care unit (9.6% vs. 20.6%, P = .023), oxygen therapy (21.4% vs. 43.5%, P < .001), ventilatory support (3.2% vs. 11.2%, P = .03) and length of hospital stay (5.0 ± 5.0 vs. 9.7 ± 5.9 days, P < .001). CONCLUSION: This study confirms that about one-third of the COVID-19 patients are PCR-negative and diagnosed based on clinicaand radiographic findings. These patients have a more favorable clinical course, shorter hospital stays, and are less frequently admitteto the intensive care unit.

Pneumonia severity indices predict prognosis in coronavirus disease-2019.

BACKGROUND: Early recognition of the severe illness is critical in coronavirus disease-19 (COVID-19) to provide best care and optimize the use of limited resources. OBJECTIVES: We aimed to determine the predictive properties of common community-acquired pneumonia (CAP) severity scores and COVID-19 specific indices. METHODS: In this retrospective cohort, COVID-19 patients hospitalized in a teaching hospital between 18 March-20 May 2020 were included. Demographic, clinical, and laboratory characteristics related to severity and mortality were measured and CURB-65, PSI, A-DROP, CALL, and COVID-GRAM scores were calculated as defined previously in the literature. Progression to severe disease and in-hospital/overall mortality during the follow-up of the patients were determined from electronic records. Kaplan-Meier, log-rank test, and Cox proportional hazard regression model was used. The discrimination capability of pneumonia severity indices was evaluated by receiver-operating-characteristic (ROC) analysis. RESULTS: Two hundred ninety-eight patients were included in the study. Sixty-two patients (20.8%) presented with severe COVID-19 while thirty-one (10.4%) developed severe COVID-19 at any time from the admission. In-hospital mortality was 39 (13.1%) while the overall mortality was 44 (14.8%). The mortality in low-risk groups that were identified to manage outside the hospital was 0 in CALL Class A, 1.67% in PSI low risk, and 2.68% in CURB-65 low-risk. However, the AUCs for the mortality prediction in COVID-19 were 0.875, 0.873, 0.859, 0.855, and 0.828 for A-DROP, PSI, CURB-65, COVID-GRAM, and CALL scores respectively. The AUCs for the prediction of progression to severe disease was 0.739, 0.711, 0,697, 0.673, and 0.668 for CURB-65, CALL, PSI, COVID-GRAM, A-DROP respectively. The hazard ratios (HR) for the tested pneumonia severity indices demonstrated that A-DROP and CURB-65 scores had the strongest association with mortality, and PSI, and COVID-GRAM scores predicted mortality independent from age and comorbidity. CONCLUSION: Community-acquired pneumonia (CAP) scores can predict in COVID-19. The indices proposed specifically to COVID-19 work less than nonspecific scoring systems surprisingly. The CALL score may be used to decide outpatient management in COVID-19.

The Follow-Up of Biomarkers Better Predicts the Poor Outcome in COVID-19 Patients

Objective. To investigate the course of biomarkers on admission and follow-up in order to identify early predictors for poor outcome in COVID-19 patients. Methods. In this study, 132 COVID-19 patients were classified as good outcome (n=62) and poor outcome (n=70) groups. Laboratory parameters were evaluated on admission and within 5-7 days after hospitalization. Results. Baseline levels of neutrophil-lymphocyte ratio, CRP, procalcitonin, ferritin, D-dimer and LDH were higher (p<0.01);lymphocyte count was lower in the poor outcome patients. During follow-up there was a larger decrease in lymphocyte count and more prominent increases in other biomarkers (p<0.001). In ROC analysis, the AUCs strongly indicated the poor outcome on days 5-7 of the hospitalization. Conclusions. This study suggests that the follow-up measurements of the biomarkers better predict the poor outcome in COVID-19 pneumonia.