COVID-19-mediated patient delay caused increased total ischaemic time in ST-segment elevation myocardial infarction.

BACKGROUND: The current study aimed to evaluate changes in treatment delay and outcome for ST-segment elevation myocardial infarction (STEMI) in the Netherlands during the first coronavirus disease 2019 (COVID-19) outbreak, thereby comparing regions with a high and low COVID-19 hospitalisation rate. METHODS: Clinical characteristics, STEMI timing variables, 30-day all-cause mortality and cardiovascular complications of all consecutive patients admitted for STEMI from 1 January to 30 June in 2020 and 2019 to six hospitals performing a high volume of percutaneous coronary interventions were collected retrospectively using data from the Netherlands Heart Registry, hospital records and ambulance report forms. Patient delay, pre-hospital delay and door-to-balloon time before and after the outbreak of COVID-19 were compared to the equivalent periods in 2019. RESULTS: A total of 2169 patients were included. During the outbreak median total treatment delay significantly increased (2 h 51 min vs 2 h 32 min; p = 0.043) due to an increased patient delay (1 h 20 min vs 1 h; p = 0.030) with more late presentations > 24 h (1.1% vs 0.3%) in 2020. This increase was particularly evident during the peak phase of COVID-19 in regions with a high COVID-19 hospitalisation rate. During the peak phase door-to-balloon time was shorter (38 min vs 43 min; p = 0.042) than in 2019. All-cause 30-day mortality was comparable in both time frames (7.8% vs 7.3%; p = 0.797). CONCLUSIONS: During the outbreak of COVID-19 patient delay caused an increase in total ischaemic time for STEMI, with a more pronounced delay in high-endemic regions, stressing the importance of good patient education during comparable crisis situations.

Comparison of the efficacy of PSI, CURB-65, CALL and BCRSS in predicting prognosis and mortality in COVID-19 patients

This study aimed to determine whether the PSI, CURB-65, CALL and BCRSS had any superiority over each other as a prognostic determinant in patients with COVID-19. This prospective cohort study included patients over 18 years of age that presented to the emergency department between May 12 and August 12, 2020 and had a positive COVID-19 polymerase chain reaction (PCR) test. The PSI, CURB-65, CALL and BCRS scores were calculated. SPSS version 22 was used for all statistical analyses. A total of 213 patients with a positive COVID-19 PCR result were included in the study. The total 30-day mortality rate was determined as 14.08%. PSI, CURB-65, CALL and BCRSS had a statistically significant relationship with mortality (p<0.001). The best parameter in predicting mortality was determined as PSI (area under the curve: 0.900;95% CI: 0.972-0.828). A positive correlation was found between each scoring system, both with the length of hospital stay (PSI, CURB-65, CALL and BCRSS: r=0.696, p=0;r=0.621, p=0;r=0.75, p=0;and r=0.666, p=0, respectively). Scoring systems, which include comorbidity, vital signs as well as laboratory, imaging findings, will be more effective than other scoring systems in determining the mortality in patients with covid-19.

Analysis of laboratory parameters in patients with COVID-19: Experiences from a pandemic hospital Laboratory parameters of COVID-19

Aim: This study aimed to determine the analysis of the laboratory parameters in patients infected with SARS-CoV-2 during the early pandemic period in Turkey. Material and Methods : This retrospective descriptive study was conducted at a pandemic hospital. All hospitalized patients and outpatients with a positive RT-PCR assay for SARS-CoV-2 were included In the study. Demographics, clinical characteristics, vital parameters on admission, laboratory findings, and drugs used for SARS-CoV-2 infection were obtained from the computer-based patient data system of the hospital and analyzed. The primary outcome of the study was the laboratory parameters of patients with COVID-19. The secondary outcome was 30-day all-cause mortality following emergency department admission. Results: A total of 2,012 patients were included in study. The rates of hospitalization and 30-day mortality were 24% and 2%, respectively. The most common symptom was cough, and the most common comorbidity was hypertension. The neutrophil count, neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio values were elevated in the non-survivor group compared to the survivor group (P = 0.001, P < 0.001, and P = 0.020, respectively). The lymphocyte and platelet counts were elevated in the survivor group compared to the non-survivor group (P = 0.001 and P < 0.001, respectively). As predictors of mortality, the cut-off value for the neutrophil, lymphocyte and platelet counts, and the neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios were 5.68, 1.42, 195, 3.09, and 141.8, respectively, and the AUC was determined as 0.704, 0.714, 0.727, 0.745, and 0.610, respectively (P < 0.001, P < 0.001, P < 0.001, P < 0.001, and P = 0.023, respectively). Discussion: The results of the study demonstrated that the neutrophil count, lymphocyte count, platelet count, neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio are useful in determining prognosis in SARS-CoV-2 Infection.

The effect of the Coronavirus 2019 pandemic on the mental health of healthcare workers

Aim: The riskiest working group in pandemics is healthcare workers. This study sought to determine the effect of the coronavirus 2019 pandemic on the mental health of healthcare workers. Material and Methods: The study, designed as a case-control, clinical observation study, was conducted on healthcare workers working in pandemic clinics during the pandemic period. One hundred fifty-three healthcare workers included. The study form included demographic data, marital status, working hours, job, Insomnia Severity Index, Patient Health Questionnaire-9 and Beck's Depression Inventory, and clinical questions. Turkish-adapted versions of all scales were applied. Results: In our clinical observation study, 26.2% of healthcare professionals working in pandemic clinics during the pandemic period were depressed (according to Beck's Depression Inventory), 39.8% had moderate and severe depression (according to the Patient Health Questionnaire-9), and 58.6% had insomnia (according to the Insomnia Severity Index). However, there was no significant difference between the subgroups of health workers in terms of depression and insomnia. Discussion: All medical and non-medical healthcare workers working in COVID 19 clinics during the pandemic have been widely adversely affected by the process.

Analysis of laboratory parameters in patients with covid-19: Experiences from a pandemic hospital

Aim: This study aimed to determine the analysis of the laboratory parameters in patients infected with SARS-CoV-2 during the early pandemic period in Turkey. Material and Methods: This retrospective descriptive study was conducted at a pandemic hospital. All hospitalized patients and outpatients with a positive RT-PCR assay for SARS-CoV-2 were included in the study. Demographics, clinical characteristics, vital parameters on admission, laboratory findings, and drugs used for SARS-CoV-2 infection were obtained from the computer-based patient data system of the hospital and analyzed. The primary outcome of the study was the laboratory parameters of patients with COVID-19. The secondary outcome was 30-day all-cause mortality following emergency department admis-sion. Results: A total of 2,012 patients were included in study. The rates of hospitalization and 30-day mortality were 24% and 2%, respectively. The most common symptom was cough, and the most common comorbidity was hypertension. The neutrophil count, neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio values were elevated in the non-survivor group compared to the survivor group (P = 0.001, P < 0.001, and P = 0.020, respectively). The lymphocyte and platelet counts were elevated in the survivor group compared to the non-survivor group (P = 0.001 and P < 0.001, respectively). As predictors of mortality, the cut-off value for the neutrophil, lymphocyte and platelet counts, and the neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios were 5.68, 1.42, 195, 3.09, and 141.8, respectively, and the AUC was determined as 0.704, 0.714, 0.727, 0.745, and 0.610, respectively (P < 0.001, P < 0.001, P < 0.001, P < 0.001, and P = 0.023, respectively). Discussion: The results of the study demonstrated that the neutrophil count, lymphocyte count, platelet count, neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio are useful in determining prognosis in SARS-CoV-2 infection.

Effectiveness of the rapid emergency medicine score and the rapid acute physiology score in prognosticating mortality in patients presenting to the emergency department with COVID-19 symptoms

Objective: We investigated the effectiveness of the Rapid Emergency Medicine Score and the Rapid Acute Physiology Score in identifying critical patients among those presenting to the emergency department with COVID-19 symptoms. Material and methods: This prospective, observational, cohort study included patients with COVID-19 symptoms presenting to the emergency department over a two-month period. Demographics, clinical characteristics, and the data of all-cause mortality within 30 days after admission were noted, and the Rapid Emergency Medicine Score and the Rapid Acute Physiology Score were calculated by the researchers. The receiver operating characteristic curve analysis was performed to determine the discriminative ability of the scores. Results: A total of 555 patients with a mean of age of 49.4 +/- 16.8 years were included in the study. The rate of 30-day mortality was 3.9% for the whole study cohort, 7.2% for the patients with a positive rt-PCR test result for SARS-CoV-2, and 1.2% for those with a negative rt-PCR test result for SARS-CoV-2. In the group of patients with COVID-19 symptoms, according to the best Youden's index, the cut-off value for the Rapid Emergency Medicine Score was determined as 3.5 (sensitivity: 81.82%, specificity: 73.08%), and the area under curve (AUC) value was 0.840 (95% confidence interval 0.768-0.913). In the same group, according to the best Youden's index, the cut-off value for the Rapid Acute Physiology Score was 2.5 (sensitivity: 90.9%, specificity: 97.38%), and the AUC value was 0.519 (95% confidence interval 0.393-0.646). Conclusion: REMS is able to predict patients with COVID-19-like symptoms without positive rt-PCR for SARS-CoV-2 that are at a high-risk of 30-day mortality. Prospective multicenter cohort studies are needed to provide best scoring system for triage in pandemic clinics. (C) 2021 Elsevier Inc. All rights reserved.

Comparison of laboratory results and chest ct findings in covid-19 patients

Aim: COVID-19 has emerged in China and quickly spread around the world. Efficient screening of patients for the disease is crucial in the diagnosis and determination of the severity of the disease. However, the diagnostic methods performed are not optimal when applied alone. In this study, we aimed to investigate whether CT together with laboratory test results can provide insight for the prognosis of COVID-19 for patients admitted to the emergency room (ER) and investigate possible factors affecting the mortality. Material and Methods: This retrospective study was conducted on 313 patients older than 18 years who had COVID-19 presentations and admitted to the ER. Patients’ demographic data (age, gender, and comorbidities), complete blood counts, biochemistry parameters (d-dimer, ferritin, CRP, troponin, and lactate), chest CT and qRT-PCR-based SARS-CoV-2 test results were evaluated. Results: The mean age of the patients was 58.7 ± 16.2 years (male = 58.7%). One hundred eighty-one patients had comorbidities and the most common comorbidity was hypertension (HT), followed by coronary artery disease (CAD). Ferritin and CRP levels were significantly higher in patients with severe CT findings compared to the patients with mild and moderate CT findings (p < 0.05). Interestingly, patients with severe CT findings were significantly younger than patients in other groups (p < 0.05). The number of patients with HT and CAD was significantly higher among patients with severe CT findings than among patients with mild and moderate CT findings (p < 0.05). Patients with moderate and severe findings had a higher mortality rate compared to patients with mild CT findings (p < 0.05). Discussion: Despite inconsistencies between clinical findings, radiological features, and blood biochemistry results among COVID-19 patients, CRP and ferritin levels, together with HT and CAD, may be prognostic for disease severity, suggesting that the integration of CT assessments and laboratory results may be essential for predicting disease severity.