Comparison of the healthcare-associated infections in intensive care units in Turkey before and during COVID-19.

Background: Secondary bacterial infections are an important cause of mortality in patients with coronavirus disease 2019 (COVID-19). All healthcare providers acted with utmost care with the reflex of protecting themselves during the COVID-19 period. We aimed to compare the rates of ventilator-associated pneumonia (VAP) and bloodstream infections (BSIs) in our intensive care units (ICUs) before and during the COVID-19 outbreak surges. Methods: This multicenter, retrospective, cross-sectional study was performed in six centers in Turkey. We collected the patient demographic characteristics, comorbidities, reasons for ICU admission, mortality and morbidity scores at ICU admission, and laboratory test data. Results: A total of 558 patients who required intensive care from six centers were included in the study. Four hundred twenty-two of these patients (males (62%), whose mean age was 70 [IQR, 58-79] years) were followed up in the COVID period, and 136 (males (57%), whose mean age was 73 [IQR, 61-82] years) were followed up in the pre-COVID period. BSI and VAP rates were 20.7 (19 events in 916 patient days) and 17 (74 events in 4361 patient days) with a -3.8 difference (P = 0.463), and 33.7 (31 events in 919 patient days) and 34.6 (93 events in 2685 patient days) with a 0.9 difference (P = 0.897), respectively. The mortality rates were 71 (52%) in pre-COVID and 291 (69%) in COVID periods. Conclusion: Protective measures that prioritize healthcare workers rather than patients and exceed standard measures made no difference in terms of reducing mortality.

Plasminogen activator inhibitor-1 levels as an indicator of severity and mortality for COVID-19

OBJECTIVE Coronavirus disease-19 (COVID-19) is a multisystemic disease that can cause severe illness and mortality by exacerbating symptoms such as thrombosis, fibrinolysis, and inflammation. Plasminogen activator inhibitor-1 (PAI-1) plays an important role in regulating fibrinolysis and may cause thrombotic events to develop. The goal of this study is to examine the relationship between PAI-1 levels and disease severity and mortality in relation to COVID-19. METHODS A total of 71 hospitalized patients were diagnosed with COVID-19 using real time-polymerase chain reaction tests. Each patient underwent chest computerized tomography (CT). Data from an additional 20 volunteers without COVID-19 were included in this single-center study. Each patient's PAI-1 data were collected at admission, and the CT severity score (CT-SS) was then calculated for each patient. RESULTS The patients were categorized into the control group (n=20), the survivor group (n=47), and the non-survivor group (n=24). In the non-survivor group, the mean age was 75.3±13.8, which is higher than in the survivor group (61.7±16.9) and in the control group (59.5±11.2), (p=0.001). When the PAI-1 levels were compared between each group, the non-survivor group showed the highest levels, followed by the survivor group and then the control group (p<0.001). Logistic regression analysis revealed that age, PAI-1, and disease severity independently predicted COVID-19 mortality rates. In this study, it was observed that PAI-1 levels with >10.2 ng/mL had 83% sensitivity and an 83% specificity rate when used to predict mortality after COVID-19. Then, patients were divided into severe (n=33) and non-severe (n=38) groups according to disease severity levels. The PAI-1 levels found were higher in the severe group (p<0.001) than in the non-severe group. In the regression analysis that followed, high sensitive troponin I and PAI-1 were found to indicate disease severity levels. The CT-SS was estimated as significantly higher in the non-survivor group compared to the survivor group (p<0.001). When comparing CT-SS between the severe group and the non-severe group, this was significantly higher in the severe group (p<0.001). In addition, a strong statistically significant positive correlation was found between CT-SS and PAI-1 levels (r: 0.838, p<0.001). CONCLUSION Anticipating poor clinical outcomes in relation to COVID-19 is crucial. This study showed that PAI-1 levels could independently predict disease severity and mortality rates for patients with COVID-19.

Safety of Surgery Among Asymptomatic SARS-CoV-2 PCR-Positive Patients: A Single-Center Retrospective Cohort Study.

BACKGROUND: Screening with SARS-CoV-2 PCR tests is recommended for all patients undergoing surgery under general anesthesia, and elective surgery is deferred for positive patients. This study evaluated the outcomes of asymptomatic PCR-positive patients who underwent general anesthesia and surgery. METHODS: Patient data were collected from the hospital records of patients who underwent surgery between January 2021 and May 2022. Asymptomatic patients with a positive PCR test between 7 days before and 5 days after surgery were compared with controls. The cases were propensity score-matched with a 1:2 ratio to the controls. All-cause in-hospital mortality was the primary outcome of the study. RESULTS: A total of 217 asymptomatic PCR-positive patients were matched to 434 controls. In multivariate analysis, PCR-positive test results were not associated with mortality (log(OR) (95%CIs), p; 0.86 (- 0.13, 1.9), 0.09). Age and ASA score (>3) were the most significant risk factors associated with mortality. CONCLUSION: This study found that surgery among asymptomatic PCR-positive patients was not associated with increased mortality.

Comparison of Initial CT Findings and CO-RADS Stage in COVID-19 Patients with PCR, Inflammation and Coagulation Parameters in Diagnostic and Prognostic Perspectives.

Objectives: This study aims to determine whether COVID-19 patients with different initial reverse transcriptase-polymerase chain reaction (RT-PCR), computed tomography (CT) and laboratory findings have different clinical outcomes. Materials and Methods: In this multi-center retrospective cohort study, 895 hospitalized patients with the diagnosis of COVID-19 were included. According to the RT-PCR positivity and presence of CT findings, the patients were divided into four groups. These groups were compared in terms of mortality and need for intensive care unit (ICU). According to the COVID-19 Reporting and Data System (CO-RADS), all patients' CT images were staged. Multivariate binary logistic regression analysis was used to examine the relationship between CO-RADS and predictive inflammation and coagulation parameters. Results: RT-PCR test positivity was 51.5%, the CT finding was 70.7%, and 49.7% of the patients were in the CO-RADS 5 stage. The need for ICU and mortality rates was higher in the group with only CT findings compared to the group with only RT-PCR positivity, (14.9% vs. 4.0%, p < 0.001; 9.3% vs. 3.3%, p > 0.05; respectively). Mortality was 3.27 times higher in patients with CO-RADS 4 compared to those with CO-RADS 1-2. Being in the CO-RADS 4 stage and LDH were discovered to be the most efficient parameters in determining mortality risk. Conclusion: Performing only the RT-PCR test in the initial evaluation of patients in SARS-CoV-2 infection may lead to overlooking groups that are more at risk for severe disease. The use of a chest CT to perform CO-RADS staging would be beneficial in terms of providing both diagnostic and prognostic information.

Carbapenem-resistant Klebsiella pneumoniae outbreak in a COVID-19 intensive care unit; a case-control study.

We analysed a carbapenem-resistant Klebsiella pneumoniae (CRKP) outbreak in the coronavirus disease (COVID) ICU. We retrospectively collected data from ICU records. We identified 25 cases between 12 November 2020 and 19 December 2020, and compared them to 42 controls present in the ICU during the same period. The presence of a femoral haemodialysis catheter was strongly associated with invasive CRKP infections (cases, 9 [36%]; controls, 0 [0%]; odds ratio [OR] 95% confidence intervals [CIs], 21 (5; 89)). We found a significant association between old age and CRKP infection with adverse outcomes. Sequence analysis revealed three distinct carbapenemase genes: blaNDM-1, blaOXA-48 and blaKPC-2. We launched rectal swab sampling upon admission to the ICU, cohorted colonized patients and cases and conducted an intensive training programme for newly employed staff. This study revealed that the emergence and dissemination of CRKP in COVID ICUs were associated with increased adverse outcomes. The presence of a femoral haemodialysis catheter was a significant risk factor for CRKP infections.

Is vaccination necessary for COVID-19 patients? A retrospective cohort study investigating reinfection rates and symptomatology in a tertiary hospital.

BACKGROUND: Durability of immune response by the COVID-19 natural infection and the necessity of vaccines in recovered patients are important inquiries for the healthcare provider. RESEARCH DESIGN AND METHODS: Here, we investigated the characteristics and the rate of cases with reinfection that have been admitted to our tertiary hospital. RESULTS: A total of 119985 patients were applied between March 2020 and May 2021. Of these patients, 32607 (27%, 32,607/119985) tested positive. A total of 27 (0.08%, 27/32607) patients were found to be reinfected beyond 90 days. Only one of these reinfected patients (0.003, 1/32607) had novel COVID-19 pneumonia and was hospitalized for the second time. Other 26 reinfected patients were followed up as outpatients. CONCLUSIONS: COVID-19 reinfection is extremely rare. However, the reinfection may be severe in patients with immune deficiency. Healthcare providers may prioritize uninfected and immune-compromised patients for vaccination.

Tocilizumab treatment in severe COVID-19: a multicenter retrospective study with matched controls.

Coronavirus disease-2019 (COVID-19) associated pneumonia may progress into acute respiratory distress syndrome (ARDS). Some patients develop features of macrophage activation syndrome (MAS). Elevated levels of IL-6 were reported to be associated with severe disease, and anti-IL-6R tocilizumab has been shown to be effective in some patients. This retrospective multicenter case-control study aimed to evaluate the efficacy of tocilizumab in hospitalized COVID-19 patients, who received standard of care with or without tocilizumab. Primary outcome was the progression to intubation or death. PSMATCH (SAS) procedure was used to achieve exact propensity score (PS) matching. Data from 1289 patients were collected, and study population was reduced to 1073 based on inclusion-exclusion criteria. The composite outcome was observed more frequently in tocilizumab-users, but there was a significant imbalance between arms in all critical parameters. Primary analyses were carried out in 348 patients (174 in each arm) after exact PS matching according to gender, ferritin, and procalcitonin. Logistic regression models revealed that tocilizumab significantly reduced the intubation or death (OR 0.40, p = 0.0017). When intubation is considered alone, tocilizumab-users had > 60% reduction in odds of intubation. Multiple imputation approach, which increased the size of the matched patients up to 506, provided no significant difference between arms despite a similar trend for intubation alone group. Analysis of this retrospective cohort showed more frequent intubation or death in tocilizumab-users, but PS-matched analyses revealed significant results for supporting tocilizumab use overall in a subset of patients matched according to gender, ferritin and procalcitonin levels.

Predictive performance of CT for adverse outcomes among COVID-19 suspected patients: a two-center retrospective study.

The aim of the study was to compare the performance of various computed tomography (CT) reporting tools, including zonal CT visual score (ZCVS), the number of involved lobes, and Radiological Society of North America (RSNA) categorization in predicting adverse outcomes among patients hospitalized due to the lower respiratory symptoms during the coronavirus disease 2019 (COVID-19) pandemic. A total of 405 patients admitted with severe respiratory symptoms who underwent a chest CT were enrolled. The primary adverse outcome was intensive care unit (ICU) admission of patients. Predictive performances of reporting tools were compared using the area under the receiver operating characteristic curves (AUC ROC). Among the 405 patients, 39 (9.63%) required ICU support during their hospital stay. At least two or more observers reported a typical and indeterminate COVID-19 pneumonia CT pattern according to RSNA categorization in 70% (285/405) of patients. Among these, 63% (179/285) had a positive polymerase chain reaction (PCR test for the SARS-CoV-2 virus. The median number of lobes involved according to CT was higher in patients who required ICU support (median interquartile range [IQR], 5[3; 5] vs. 3[0; 5]). The median ZCVS score was higher among the patients that subsequently required ICU support (median [IQR], 4[0; 12] vs. 13[5.75; 24]). The bootstrap comparisons of AUC ROC showed significant differences between reporting tools, and the ZCVS was found to be superior (AUC ROC, 71-75%). The ZCVS score at the first admission showed a linear and significant association with adverse outcomes among patients with the lower respiratory tract symptoms during the COVID-19 pandemic.

A novel approach to managing COVID-19 patients; results of lopinavir plus doxycycline cohort.

This manuscript aims to present a treatment algorithm we applied to manage COVID-19 patients admitted to our hospital. During the study period, 2043 patients with suspected COVID-19 were admitted to the emergency department. Molecular tests indicated that 475 of these patients tested positive for COVID-19. We administered hydroxychloroquine plus doxycycline to mild cases (isolated at home) for 3 days and lopinavir plus doxycycline to moderate and severe cases (hospitalized) for 5 days. The overall case fatality rate was 4.2% (20/475).

Prognostic significance of cardiac injury in COVID-19 patients with and without coronary artery disease.

OBJECTIVE: COVID-19 is a disease with high mortality, and risk factors for worse clinical outcome have not been well-defined yet. The aim of this study is to delineate the prognostic importance of presence of concomitant cardiac injury on admission in patients with COVID-19. METHODS: For this multi-center retrospective study, data of consecutive patients who were treated for COVID-19 between 20 March and 20 April 2020 were collected. Clinical characteristics, laboratory findings and outcomes data were obtained from electronic medical records. In-hospital clinical outcome was compared between patients with and without cardiac injury. RESULTS: A total of 607 hospitalized patients with COVID-19 were included in the study; the median age was 62.5 ± 14.3 years, and 334 (55%) were male. Cardiac injury was detected in 150 (24.7%) of patients included in the study. Mortality rate was higher in patients with cardiac injury (42% vs. 8%; P < 0.01). The frequency of patients who required ICU (72% vs. 19%), who developed acute kidney injury (14% vs. 1%) and acute respiratory distress syndrome (71%vs. 18%) were also higher in patients with cardiac injury. In multivariate analysis, age, coronary artery disease (CAD), elevated CRP levels, and presence of cardiac injury [odds ratio (OR) 10.58, 95% confidence interval (CI) 2.42-46.27; P < 0.001) were found to be independent predictors of mortality. In subgroup analysis, including patients free of history of CAD, presence of cardiac injury on admission also predicted mortality (OR 2.52, 95% CI 1.17-5.45; P = 0.018). CONCLUSION: Cardiac injury on admission is associated with worse clinical outcome and higher mortality risk in COVID-19 patients including patients free of previous CAD diagnosis.

A Statistical Modeling of the Course of COVID-19 (SARS-CoV-2) Outbreak: A Comparative Analysis.

This study aims to provide both a model by using cumulative cases and cumulative death toll for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) outbreak in four countries, China, Italy, South Korea, and Turkey, starting from the first diagnosis and to compare associated indicators. The most successful estimation was obtained from the cubic model with natural logarithm for China, Italy, South Korea, and Turkey. The success of the models was around 99%. However, differences began to emerge in China, Italy, and South Korea after the second week. Although the highest number of new cases per 1 million people in China was 9.8 on February 28, 2020; it was 108.4 on March 21, 2020, in Italy; and this was 16.6 on March 5, 2020, in South Korea. On the other hand, the number of new cases was 24.6 per 1 million people on March 27, 2020, in Turkey. The log-cubic model proposed in this study has been set forth to obtain successful results for aforementioned countries, as well as to estimate the course of the COVID-19 outbreak. Other factors such as climacteric factors and genetic differences, which may have an impact on viral spreading and transmission, would also have strengthened the model prediction capacity.