Comparison of four different threshold values of shock index in predicting mortality of COVID-19 patients.

OBJECTIVE: The object of this study was to examine the accuracy in pre-hospital shock index (SI) for predicting intensive care unit (ICU) requirement and 30-day mortality among from COVID-19 patients transported to the hospital by ambulance. METHOD: All consecutive patients who were the age ≥18 years, transported to the emergency department (ED) by ambulance with a suspected or confirmed COVID-19 in the pre-hospital frame were included in the study. Four different cut-off points were compared (0.7, 0.8, 0.9, and 1.0) to examine the predictive performance of both the mortality and ICU requirement of the SI. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) was employed to evaluate each cut-off value discriminatory for predicting 30-day mortality and ICU admission. RESULTS: The total of 364 patients was included in this study. The median age in the study population was 69 (55-80), of which 196 were men and 168 were women. AUC values for 30-day mortality outcome were calculated as 0.672, 0.674, 0.755, and 0.626, respectively, for threshold values of 0.7, 0.8, 0.9 and 1.0. ICU admission was more likely for the patients with pre-hospital SI> 0.9. Similarly, the mortality rate was higher in patients with pre-hospital SI> 0.9. CONCLUSION: Early triage of COVID-19 patients will ensure efficient use of healthcare resources. The SI could be a helpful, fast and powerful tool for predicting mortality status and ICU requirements of adult COVID-19 patients. It was concluded that the most useful threshold value for the shock index in predicting the prognosis of COVID-19 patients is 0.9.

Hesitancy Regarding Medical Advice on COVID-19: An Emergency Department Perspective.

OBJECTIVE: The rejection of or non-compliance with treatment arises for different reasons by patients who receive treatment recommendations for various diseases. These states are described by various concepts, such as discharge against medical advice (DAMA) and medication nonadherence (MNA). The basis of the study is to determine how these states have arisen during the coronavirus disease (COVID-19) pandemic. METHOD: The data of this study were collected through standardized interviews with 103 volunteer participants who were diagnosed with COVID-19 at different times and who did not use their prescribed medicine during the pandemic in Turkey. The data obtained in the research were analyzed through the MAXQDA qualitative analysis program. RESULTS: As a result of the analysis of the data, 4 main themes and sub-codes have been reached: (1) prescribed medicine, (2) an information source for the COVID-19 period/treatment, (3) the reason for medication nonadherence, and (4) treatment of choice. When the approach toward treatment of patients who were diagnosed with COVID-19 and had started treatment by a physician was evaluated, it was revealed that the nonadherence state emerged as a cycle. In the initial period, nonadherence due to the medication itself was observed. The second period is when the patients recognize their disease and collect information from their environment. Although this period begins before the disease, the search for informative sources intensifies, especially once the diagnosis has been received. In the third period, with their diagnosis and the information they had obtained, patients consider the reasons to use the medication and then decide whether or not to use it. In the fourth period, the patients who will not use antivirals consider other medications, such as anti-flu, anticoagulant, supplements, and nutrition. CONCLUSION: Since a specific treatment protocol has not yet been revealed for COVID-19, a new conceptual framework is required. In the current condition, the state of "hesitation for medical advice" arises for non-hospitalized patients.

Comparison of C-reactive protein and C-reactive protein-to-albumin ratio in predicting mortality among geriatric coronavirus disease 2019 patients.

OBJECTIVE: The aim of this study was to evaluate and compare C-reactive protein and C-reactive protein-to-albumin ratio performances in predicting mortality of geriatric patients who visited the emergency department. METHODS: The data of patients with COVID-19 and aged 65 years and above, who visited emergency department during the study period, were retrospectively analyzed. The data were obtained from an electronic-based hospital information system. The area under the receiver operating characteristic curve and the area under the curve were used to assess each cutoff value discriminatory for predicting mortality. RESULTS: The mean age of the population included in this study was 76 (71-82) years, while 52.7% were males. The sensitivity, specificity, and area under the curve values for C-reactive protein in terms of mortality were calculated as 71.01, 52.34, and 0.635%, respectively, while the sensitivity, specificity, and area under the curve values for C-reactive protein-to-albumin ratio were calculated as 75.74, 47.66, and 0.645%, respectively (p<0.001). In the pairwise comparison for the receiver operating characteristic curves of C-reactive protein and C-reactive protein-to-albumin ratio, no statistically significant difference was found. CONCLUSIONS: Geriatric patients are the "most vulnerable" patient group against the COVID-19. In this study, both C-reactive protein and C-reactive protein-to-albumin ratio were found to be successful in predicting mortality for geriatric COVID-19 patients.

Vaccine Hesitancy of Health-Care Workers: Another Challenge in the Fight Against COVID-19 in Istanbul.

OBJECTIVE: Health-care workers (HCWs) are often seen as the most reliable source of vaccine-related information for their patients; nevertheless, various studies show that HCWs experience vaccine hesitation. In this study, the aim was to determine the reasons for vaccine hesitation among HCWs working in a large public hospital and its affiliated units in Istanbul. METHODS: A descriptive method for collecting qualitative data was designed for this study. The data of the HCWs were analyzed in line with the vaccine hesitancy factors put forward by the World Health Organization (WHO). RESULTS: The most important vaccine hesitancy theme that emerged was the fear and lack of confidence in the vaccines, which was expressed at a higher rate than any other theme in all HCWs. The most cited reason for fear/lack of confidence in the vaccine was the fear of its side effects. It was observed that the HCWs who reported hesitation about vaccination due to pregnancy and breastfeeding consisted of women. The second most common theme for vaccine hesitation was reported as an inconvenience in accessing the vaccines. Although HCWs have priority, they stated that their reason for vaccine hesitancy was due to heavy personal issues or workloads. The final theme was about complacency, or thinking they do not need the vaccine. CONCLUSIONS: Vaccine hesitation is a challenge that can be overcome with detailed monitoring and policy-making. Although the vaccine seems to be more significant, we do not want to see vaccine hesitancy grow more than the vaccine itself.

Performance of the CURB-65, ISARIC-4C and COVID-GRAM scores in terms of severity for COVID-19 patients.

BACKGROUND: In the COVID-19 pandemic, difficulties have been experienced in the provision of healthcare services because of excessive patient admissions to hospitals and emergency departments. It has become important to use clear and objective criteria for the early diagnosis of patients with high-risk classification and clinical worsening risk. OBJECTIVE: The aim of this study was to assess the prognostic accuracy of CURB-65, ISARIC-4C and COVID-GRAM scores in patients hospitalised for COVID-19 and to compare the scoring systems in terms of predicting in-hospital mortality and intensive care unit requirement. METHODS: The files of all COVID-19 patients over the age of 18 who were admitted to the emergency department and hospitalised between September 1, 2020 and December 1, 2020 were retrospectively scanned. The area under the receiver operating characteristic curve and Youden J Index were used to compare scoring systems for predicting in-hospital mortality and intensive care requirement. RESULTS: There were 481 patients included in this study. The median age of the patients was 67 (52-79). In terms of in-hospital mortality, the AUC of CURB-65, ISARIC-4C and COVID-GRAM were 0.846, 0.784 and 0.701 respectively. In terms of intensive care requirement, the AUC of CURB-65, ISARIC-4C and COVID-GRAM were 0.898, 0.797 and 0.684 respectively. In our study, Youden's J indexes of CURB-65, ISARIC-4C and COVID-GRAM scores were found to be 0.59, 0.27 and 0.01 respectively, for mortality prediction of COVID-19 patients. Whereas Youden's J indexes were found to be 0.63, 0.26 and 0.01 respectively for determining intensive care requirement. CONCLUSIONS: Among the scoring systems assessed, CURB-65 score had better performance in predicting in-hospital mortality and ICU requirement in COVID-19 patients. ISARIC-4C has been found successful in identifying low-risk patients and the use of the ISARIC-4C score with CURB-65 increases the accuracy of risk assessment.

Usefulness of the neutrophil-to-lymphocyte ratio in predicting the severity of COVID-19 patients: a retrospective cohort study.

BACKGROUND: Quick and accurate identification of critically ill patients ensures appropriate and correct use of medical resources. In situations that threaten public health, like pandemics, rapid and effective methods are needed for early disease detection among critically ill patients. OBJECTIVE: To determine the relationship between the neutrophil-to-lymphocyte ratio (NLR) of coronavirus disease-19 (COVID-19) patients upon admission to the emergency department (ED) and these patients' prognosis. DESIGN AND SETTING: Retrospective cohort study among COVID-19 patients in the ED of a tertiary-level hospital. METHODS: Data on patients' age, gender, vital signs, chronic diseases, laboratory tests and clinical outcomes were collected from electronic medical records. Receiver operating characteristic (ROC) curve analysis was performed. The area under the curve (AUC) was used to assess the accuracy of NLR for predicting in-hospital mortality risk and intensive care unit (ICU) requirement. The Youden J index (YJI) was used to determine optimal threshold values. RESULTS: 1,175 patients were included. Their median age was 63 years (IQR, 48-75). With an NLR cutoff value of 5.14, the sensitivity, specificity, PPV, AUC and YJI for ICU requirement were calculated as 77.87%, 74.08%, 92.4%, 0.811 and 0.5194, respectively. With the same cutoff value, the sensitivity, specificity, AUC and YJI for in-hospital mortality were 77.27%, 75.82%, 0.815 and 0.5309, respectively. In addition, advanced age, leukocytosis, anemia and lymphopenia were found to be associated with poor prognosis. CONCLUSION: The NLR, which is a widely available simple parameter, can provide rapid insights regarding early recognition of critical illness and prognosis among COVID-19 patients.

Comparison of 2 Risk Prediction Models Specific for COVID-19: The Brescia-COVID Respiratory Severity Scale Versus the Quick COVID-19 Severity Index.

OBJECTIVE: This study compared the prognostic performances of the Brescia-COVID Respiratory Severity Scale (BCRSS) and the Quick COVID-19 Severity Index (qCSI) scores in hospitalized patients diagnosed with COVID-19. METHODS: The data of all adult patients (over 18 y of age) who were admitted into a state hospital with confirmed COVID-19 between May 1, 2020, and October 31, 2020, were retrospectively examined. The area under the receiver operating characteristic (ROC) curve, known as the area under the curve (AUC), was used to assess the BCRSS prediction rule and the qCSI score to assess the discriminatory power in predicting in-hospital mortality and intensive care unit (ICU) admission. RESULTS: There were 341 patients included in this study. The mean age of the patients was 58.2 ± 17.2, of which 165 were men and 176 were women, and 61.3% of patients had at least 1 comorbidity. The most common comorbidity was hypertension. The predictive power scores of BCRSS and qCSI were found as very good in terms of in-hospital mortality (AUC 0.804 and 0.847, respectively) and likewise in terms of ICU admission (AUC 0.842 and 0.851, respectively). CONCLUSIONS: Both BCRSS and qCSI scoring systems were found to be successful in predicting in-hospital mortality and ICU admission in our patient population.

Recurrence of COVID-19 Documented with RT-PCR.

We present a case of coronavirus disease 2019 (COVID-19) re-infection where the time interval between two COVID-positive episodes is the longest in the literature. A 40-year male patient was admitted to the Emergency Department with  complaints of sore throat, cough and diarrhea; and was re-diagnosed as COVID-19 positive after a virus-free period. He did not have a chronic disease in his anamnesis and used no medication. After COVID-19 infection and a long recovery period, he became COVID-19 positive again. In this case, the time to second COVID-19 infection was 94 days from the first positive PCR test and 86 days from the complete resolution of symptoms. This is one of the longest COVID-19-free period between two episodes of infection in the literature. Key Words: COVID-19, Recurrence, Re-infection, Recovery.

Recurrence of COVID-19 Documented with RT-PCR.

We present a case of coronavirus disease 2019 (COVID-19) re-infection where the time interval between two COVID-positive episodes is the longest in the literature. A 40-year male patient was admitted to the Emergency Department with complaints of sore throat, cough and diarrhea; and was re-diagnosed as COVID-19 positive after a virus-free period. He did not have a chronic disease in his anamnesis and used no medication. After COVID-19 infection and a long recovery period, he became COVID-19 positive again. In this case, the time to second COVID-19 infection was 94 days from the first positive PCR test and 86 days from the complete resolution of symptoms. This is one of the longest COVID-19-free period between two episodes of infection in the literature. Key Words: COVID-19, Recurrence, Re-infection, Recovery.

Investigation of QT Prolongation with Hydroxychloroquine and Azithromycin for the Treatment of COVID-19.

OBJECTIVE: To assess and identify the risk of prolonged QT about hydroxychloroquine (HQ) and azithromycin (AZ) used in the treatment of patients with COVID-19. STUDY DESIGN: Cohort study. PLACE AND DURATION OF STUDY: Kartal Dr. Lütfi Kirdar City Hospital, Istanbul, Turkey, from March to May 2020. METHODOLOGY: One hundred and forty-four patients with the diagnosis of COVID-19, confirmed by Rt-PCR (reverse transcription-polymerase chain reaction), were restrospectively reviewed. Patients who were hospitalised, received HQ or HQ plus AZ treatment, had a baseline electrocardiogram (ECG), and had at least one ECG after treatment were included in the study. Patients with missing data were excluded. RESULTS: Fifty-one (35.4%) patients were given hydroxychloroquine monoterapy (HQ), 93 (64.6%) were given hydroxychloroquine plus azithromycin (HA), and 70 (48.6%) were women. Pre-treatment mean QTc measurements were calculated as 410.61 ± 29.44 milliseconds (ms) for HQ group and 412.02 ± 25.37 ms for HA group, while the mean values of post-treatment QTc measurements were calculated as 432.31 ± 33.97 ms for HQ group and 432.03 ± 27.0 ms for the HA group. Post-treatment QTc measurements of both HA group and HQ group were prolonged compared to pre-treatment measurements. Ventricular arrhythmia was not observed in any patient. CONCLUSION: For COVID-19, no globally accepted definite treatment has yet been found. Both of hydroxychloroquine monotherapy and hydroxychloroquine plus azithromycin treatment regimens cause QTc measurement to increase at a statistically significant level. We concluded that this increase in QTc did not cause ventricular arrhythmia. Key Words: COVID-19, QTc interval, Hydroxychloroquine, Azithromycin.