Epidemiological and Demographic Data From 150 Patients Diagnosed With Coronavirus Disease 2019 Pneumonia in Intensive Care Unit- a Retrospective, Observational Study in Istanbul, Turkey
Conditions: Corona Virus Infection, Pneumonia, Acute Respiratory Failure
Sponsor: Sisli Hamidiye Etfal Training and Research Hospital

Epidemiological and demographic data from 150 patients 
diagnosed with covid-19 pneumonia in intensive care unit- 
a retrospective, observational study in Istanbul, Turkey. 
06.06.2020 
 
 

 
Study Protocol 
Permission was obtained from Sisli Hamidiye Etfal Training and Research Hospital local Ethics 
Committee. The study was planned retrospectively, cross-sectionally and observationally with 
193 patients hospitalized between 16 March 2020 and 15 May 2020 in five different covid-19 
intensive care units in Sisli and Sariyer campuses of our hospital. While the covid-19 diagnosis 
of the patients was made by the Polymerase Chain Reaction (PCR) test, the disease was pre-
diagnosed based on the criteria published by WHO on 12 January 2020 and the PCR results 
were concluded within 24 hours. Health workers, patients hospitalized less than 24 hours, 
patients with negative PCR tests, and patients who returned to intensive care unit after discharge 
were excluded from the study. The PCR samples were obtained from nasopharyngeal swab 
samples in non-intubated patients and endotracheal aspiration samples in intubated patients and 
examined in public health centers established in Ankara and Istanbul and then in the 
laboratories of our hospital respectively. The patients with intensive care requirements were 
admitted from emergency department and covid-19 wards to our units. The criteria for intensive 
care requirement was identified as SpO2<90%, PaO2<70 mmHg, respiratory rate> 30/min or 
PaO2/FiO2 <300 despite conventional oxygen treatment of 5lt/min. Primary objective was the 
effect of defined data on 28-day mortality, and secondary objective was the impact of 
lymphocyte count, LDH, ferritin, D-dimer and procalcitonin levels, and SOFA score on 
prognosis, which are among the risk factors determined by previous studies. All data were 
evaluated and recorded using the standardized International Severe Acute Respiratory and 
Emerging Infection Consortium (ISARIC) case report forms, complemented by electronic 
records of the hospital, nurse observation records, and missing information was completed by 
telephone interviews with patients’ relatives. Patients' age, gender, BMI, medical history, 
symptoms at admission (e.g., cough, fever, myalgia, gastrointestinal symptoms, headache), 

concomitant diseases (e.g., diabetes mellitus, hypertension, chronic lung disease, 
cerebrovascular disease, kidney disease, heart disease, cancer, smoking) were recorded. The 
sequential organ failure assessment (SOFA) and acute physiology and chronic health evaluation 
score II (APACHE II) were worked out during their intensive care unit stays. Data from arterial 
blood gas and biochemistry laboratory test results on the first day and the days 7-14-21-28 of 
hospitalization; antiviral/antibiotic treatments and supportive treatments; all respiratory support 
methods and complications developed during hospitalization (e.g., acute coronary syndrome, 
acute renal failure) were recorded. Acute respiratory distress syndrome due to covid-19 
infection was defined by 2012 Berlin criteria, acute coronary syndrome by > 99th percentile of 
troponin I concentration or the presence of dynamic changes in ECG, and the renal failure 
according to KDIGO criteria. The duration of pre-intensive care hospitalization, intensive care 
stay and the outcome (discharge or death) were recorded. Statistical data was expressed as 
standard deviation (SD) for continuously changing data and as percentile (%) for median and 
categorical variables. Wilcoxon rank-sum test or t-test were used based on parametric or non-
parametric data for continuous variables to compare the differences between survivors and non-
survivors. The survival rate was shown with the Kaplan-Meier estimator curve. Univariate and 
multivariate logistic regression models were used to investigate risk factors associated with 
death in intensive care.