The Effectiveness of the Intermediate and Therapeutic Doses of Enoxaparin in COVID-19 Patients: A Comparative Study of Factor Xa Inhibition.

BACKGROUND: Management of anticoagulant therapy in COVID-19 patients is critical. Low-molecular-weight heparin (LMWH) thromboprophylaxis is already recommended, and anti-Factor Xa (anti-FXa) monitoring has been used to titrate LMWH doses. METHODS: Through a cross-sectional study, we evaluated anti-FXa activity in patients admitted to the ICU, receiving intermediate dose (30, 40, 50 mg, subcutaneously [SC], twice daily) or therapeutic dose (1 mg/kg, SC, Q12h) of enoxaparin to find whether the patients in these two groups achieved anti-FXa levels in the accepted thromboprophylaxis range. RESULTS: The occurrence of deep vein thrombosis was 26% in the therapeutic-dose group and 17% in the intermediate-dose group. D-dimer values were nearly 3.5-fold higher in those who received a therapeutic dose of anticoagulants than in those who received intermediate-dose thromboprophylaxis. Patients in the therapeutic-dose group had significantly higher IL-6 levels (p ≤ 0.001). More than one-third of the patients in the therapeutic-dose group (n = 8; 42.18%) and approximately half of the patients in the intermediate-dose group (n = 12; 52.2%) achieved the target range level of anti-FXa. Patients who received therapeutic doses were more likely to have anti-FXa levels above the expected range (47.4 vs 13% in the intermediate-dose group; p < 0.05). CONCLUSION: Therapeutic dose of enoxaparin in critically ill COVID-19-infected patients did not reduce the incidence of thromboembolic events and, on the other hand, may predispose these patients to increased risk of bleeding by increasing anti-FXa activity above the desired level. Administration of intermediate-dose thromboprophylaxis is suggested to achieve anti-FXa levels in the accepted thromboprophylaxis range.

Unintended impact of COVID-19 pandemic on the rate of catheter related nosocomial infections and incidence of multiple drug resistance pathogens in three intensive care units not allocated to COVID-19 patients in a large teaching hospital.

BACKGROUND: The prevalence of resistant hospital infections in the intensive care unit (ICU) increases mortality and antibiotic resistance. COVID-19 pandemic may have unintended impact on nosocomial infections (NI) and the prevalence of resistant microorganism. METHODOLOGY: The present non-interventional study was performed by a pre and a post survey each lasting 8 months before (March-October 2019) and after (March-October 2020) the onset of COVID-19 pandemic in three ICU's, not allocated to COVID-19 patients, in Nemazee Hospital, Shiraz, Iran. The rates of the following nosocomial infections were compared at pre- and post-pandemic period: ventilator associated pneumonia (VAP), central line associated blood stream infection (CLABSI), catheter-associated urinary tract infections (CAUTI) and incidence of multiple drug resistance (MDR) pathogens. RESULTS: Pre-pandemic and pandemic incidence of VAP was 23.5 and 17.2 cases per 1000 device-days, respectively; an absolute decrease of 27%. The main reason for the decrease in the rate of VAP during the pandemic was a significant decrease in the rate of VAP caused by Acinetobacter baumannii; from 39 to 17% in total VAP episodes. The rate of VAP associated with other microorganisms remained relatively unchanged from 14.2 cases in pre-pandemic period to 14.3 cases per 1000 MV-days during the pandemic (P = 0.801). Pre-pandemic incidence of CLABSI was 7.3 cases and, in pandemic period, was 6.5 cases per 1000 device-days (IRR = 0.88, 95% CI 0.43-1.73, P = 0.703). Pre-pandemic incidence of CAUTI was 2 and in pandemic period, was 1.4 cases per 1000 device-days (IRR = 0.70, 95% CI 0.22-1.98, P = 0.469). CONCLUSION: The results of the present study showed a decrease in the incidence of VAP in critically ill non-COVID-19 patients during the pandemic compared to before the pandemic, especially regarding Acinetobacter baumannii.

Trauma and COVID-19: Clinical and Paraclinical similarities between Trauma Patients with Positive and Negative PCR Tests.

Objective: To compare clinical and paraclinical similarities between trauma patients with positive RT-PCR tests (PCR+ve) and the RT-PCR negative ones (PCR -ve). Methods: This a case-control study, where cases had a PCR+ve and controls had a negative result. Two groups were compared regarding (para) clinical values. Multivariable binary logistic regression analysis investigated the variables predicting COVID-19 and the mortality rate. Results: Both groups were similar regarding the clinical findings and comorbidities (p>0.05). PCR+ve group had lower lymphocyte count (1.41 [1.45] vs. 1.66 [1.61], p=0.030), CPK level (411 [928.75] vs. 778 [1946.5]. p=0.006) and CRP level (17 [42.5] vs. 24 [50.75], p=0.004). However, none of these findings were significant in the multivariable analysis. Finally, PCR+ve group had increased odds of death (OR=2.88; 95% CI=1.22-7.41). Conclusion: Unlike our primary hypothesis, the study failed to mark any significant (para) clinical features guiding us to detect COVID-19 earlier in trauma patients. Moreover, the PCR+ve group is at increased mortality risk. A larger, multicentric prospective study should be designed to address this issue.

Predictors of Intensive Care Unit Admission in Patients with Confirmed Coronavirus Disease 2019: A Cross-Sectional Study.

Background: The coronavirus disease 2019 (COVID-19) has become the leading source of pneumonia outbreaks in the world. The present study aimed to compare the condition of intensive care unit (ICU) and non-ICU COVID-19 patients in terms of epidemiological and clinical features, laboratory findings, and outcomes in three cities across Iran. Methods: In a cross-sectional study, 195 COVID-19 patients admitted to five hospitals across Iran during March-April 2020 were recruited. Collected information included demographic data, laboratory findings, symptoms, medical history, and outcomes. Data were analyzed using SPSS software with t test or Mann-Whitney U test (continuous data) and Chi square test or Fisher's exact test (categorical variables). P<0.05 was considered statistically significant. Results: Of the 195 patients, 57.4% were men, and 67.7% had at least one comorbidity. The prevalence of stroke, chronic obstructive pulmonary disease, and autoimmune diseases was higher in ICU than in non-ICU patients (P=0.042, P=0.020, and P=0.002, respectively). Compared with non-ICU, ICU patients had significantly higher white blood cell (WBC) count (P=0.008), cardiac troponin concentrations (P=0.040), lactate dehydrogenase levels (P=0.027), erythrocyte sedimentation rates (P=0.008), and blood urea nitrogen (BUN) (P=0.029), but lower hematocrit levels (P=0.001). The mortality rate in ICU and non-ICU patients was 48.1% and 6.1%, respectively. The risk factors for mortality included age>40 years, body mass index<18 Kg/m2, hypertension, coronary artery disease, fever, cough, dyspnea, ST-segment changes, pericardial effusion, and a surge in WBC and C-reactive protein, aspartate aminotransferase, and BUN. Conclusion: A high index of suspicion for ICU admission should be maintained in patients with positive clinical and laboratory predictive factors.

Prediction of Patients with COVID-19 Requiring Intensive Care: A Cross-sectional Study Based on Machine-learning Approach from Iran.

Background: Prioritizing the patients requiring intensive care may decrease the fatality of coronavirus disease-2019 (COVID-19). Aims and objectives: To develop, validate, and compare two models based on machine-learning methods for predicting patients with COVID-19 requiring intensive care. Materials and methods: In 2021, 506 suspected COVID-19 patients, with clinical presentations along with radiographic findings, were laboratory confirmed and included in the study. The primary end-point was patients with COVID-19 requiring intensive care, defined as actual admission to the intensive care unit (ICU). The data were randomly partitioned into training and testing sets (70% and 30%, respectively) without overlapping. A decision-tree algorithm and multivariate logistic regression were performed to develop the models for predicting the cases based on their first 24 hours data. The predictive performance of the models was compared based on the area under the receiver operating characteristic curve (AUC), sensitivity, and accuracy of the models. Results: A 10-fold cross-validation decision-tree model predicted cases requiring intensive care with the AUC, accuracy, and sensitivity of 97%, 98%, and 94.74%, respectively. The same values in the machine-learning logistic regression model were 75%, 85.62%, and 55.26%, respectively. Creatinine, smoking, neutrophil/lymphocyte ratio, temperature, respiratory rate, partial thromboplastin time, white blood cell, Glasgow Coma Scale (GCS), dizziness, international normalized ratio, O2 saturation, C-reactive protein, diastolic blood pressure (DBP), and dry cough were the most important predictors. Conclusion: In an Iranian population, our decision-based machine-learning method offered an advantage over logistic regression for predicting patients requiring intensive care. This method can support clinicians in decision-making, using patients' early data, particularly in low- and middle-income countries where their resources are as limited as Iran. How to cite this article: Sabetian G, Azimi A, Kazemi A, Hoseini B, Asmarian N, Khaloo V, et al. Prediction of Patients with COVID-19 Requiring Intensive Care: A Cross-sectional Study based on Machine-learning Approach from Iran. Indian J Crit Care Med 2022;26(6):688-695. Ethics approval: This study was approved by the Ethical Committee of Shiraz University of Medical Sciences (IR.SUMS.REC.1399.018).

Evaluation of Chest CT Scan as a Screening and Diagnostic Tool in Trauma Patients with Coronavirus Disease 2019 (COVID-19): A Cross-Sectional Study.

BACKGROUND: The lack of enough medical evidence about COVID-19 regarding optimal prevention, diagnosis, and treatment contributes negatively to the rapid increase in the number of cases globally. A chest computerized tomography (CT) scan has been introduced as the most sensitive diagnostic method. Therefore, this research aimed to examine and evaluate the chest CT scan as a screening measure of COVID-19 in trauma patients. METHODS: This cross-sectional study was conducted in Rajaee Hospital in Shiraz from February to May 2020. All patients underwent unenhanced CT with a 16-slice CT scanner. The CT scans were evaluated in a blinded manner, and the main CT scan features were described and classified into four groups according to RSNA recommendation. Subsequently, the first two Radiological Society of North America (RSNA) categories with the highest probability of COVID-19 pneumonia (i.e., typical and indeterminate) were merged into the "positive CT scan group" and those with radiologic features with the least probability of COVID-19 pneumonia into "negative CT scan group." RESULTS: Chest CT scan had a sensitivity of 68%, specificity of 56%, positive predictive value of 34.8%, negative predictive value of 83.7%, and accuracy of 59.3% in detecting COVID-19 among trauma patients. Moreover, for the diagnosis of COVID-19 by CT scan in asymptomatic individuals, a sensitivity of 100%, specificity of 66.7%, and negative predictive value of 100% were obtained (p value: 0.05). CONCLUSION: Findings of the study indicated that the CT scan's sensitivity and specificity is less effective in diagnosing trauma patients with COVID-19 compared with nontraumatic people.

Establishment of a novel triage system for SARS-CoV-2 among trauma victims in trauma centers with limited facilities.

OBJECTIVES: The triage of trauma patients with potential COVID-19 remains a major challenge given that a significant number of patients may be asymptomatic or pre-symptomatic. This study aimed to compare the specificity and sensitivity of available triage systems for COVID-19 among trauma patients. Furthermore, it aimed to develop a novel triage system for SARS-CoV-2 detection among trauma patients in centers with limited resources. METHODS: All patients referred to our center from February to May 2020 were enrolled in this prospective study. We evaluated the SARS-CoV-2 triage protocols from the WHO, the Iranian Ministry of Health and Medical Education (MOHME), and the European Centre for Disease Control and Prevention (ECDC) for their effectiveness in finding COVID-19 infected individuals among trauma patients. We then used these data to design a stepwise triage protocol to detect COVID-19 positive patients among trauma patients. RESULTS: According to our findings, the WHO protocol showed 100% specificity and 13.3% sensitivity. The MOHME protocol had 99% specificity and 23.3% sensitivity. While the ECDC protocol showed 93.3% sensitivity and 89.5% specificity, it did not prioritize patients based on traumatic injuries and unstable conditions. Our stepwise triage protocol, which prioritizes traumatic injuries, had 93.3% sensitivity and 90.3% specificity. CONCLUSION: Our study shows that the triage protocols from the WHO, MOHME and ECDC are not best equipped to diagnose SARS-CoV-2 infected individuals among trauma patients. In our proposed stepwise triage system, patients are triaged according to their hemodynamic conditions, COVID-19 related clinical states, and COVID-19 related laboratory findings. Our triage model can lead to more accurate and resource-effective management of trauma patients with potential COVID-19 infection. LEVEL OF EVIDENCE: Level Ⅲ.

Predictive monitoring and therapeutic immune biomarkers in the management of clinical complications of COVID-19.

The coronavirus disease-2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), appears with a wide spectrum of mild-to-critical clinical complications. Many clinical and experimental findings suggest the role of inflammatory mechanisms in the immunopathology of COVID-19. Hence, cellular and molecular mediators of the immune system can be potential targets for predicting, monitoring, and treating the progressive complications of COVID-19. In this review, we assess the latest cellular and molecular data on the immunopathology of COVID-19 according to the pathological evidence (e.g., mucus and surfactants), dysregulations of pro- and anti-inflammatory mediators (e.g., cytokines and chemokines), and impairments of innate and acquired immune system functions (e.g., mononuclear cells, neutrophils and antibodies). Furthermore, we determine the significance of immune biomarkers for predicting, monitoring, and treating the progressive complications of COVID-19. We also discuss the clinical importance of recent immune biomarkers in COVID-19, and at the end of each section, recent clinical trials in immune biomarkers for COVID-19 are mentioned.

COVID-19 infection among healthcare workers: a cross-sectional study in southwest Iran.

OBJECTIVE: With the novel coronavirus pandemic, the impact on the healthcare system and workers cannot be overlooked. However, studies on the infection status of medical personnel are still lacking. It is imperative to ensure the safety of health-care workers (HCWs) not only to safeguard continuous patient care but also to ensure they do not transmit the virus, therefore evaluation of infection rates in these groups are indicated. METHODS: Demographic and clinical data regarding infected cases among HCWs of Fars, Iran with positive SARS-CoV-2 PCR tests were obtained from 10th March to 17th May 2020. RESULTS: Our data demonstrated a rate of 5.62% (273 out of 4854 cases) infection among HCW, with a mean age of 35 years and a dominance of female cases (146 cases: 53.5%). The majority of infected cases were among nurses (51.3%), while the most case infection rate (CIR) was among physicians (27 positive cases out of 842 performed test (3.2%)). Also, the highest rate of infection was in the emergency rooms (30.6%). Also, 35.5% of the patients were asymptomatic and the most frequent clinical features among symptomatic patients were myalgia (46%) and cough (45.5%). Although 5.5% were admitted to hospitals, there were no reports of ICU admission. Furthermore, 10.3% of the cases reported transmitting the infection to family and friends. Regarding safety precautions, 1.6% didn't wear masks and 18.7% didn't use gloves in work environments. CONCLUSION: HCWs are among the highest groups at risk of infection during the COVID-19 pandemic; therefore, evaluating infection rates and associated features is necessary to improve and adjust protective measures of these vulnerable, yet highly essential group.

Challenges of diagnosis of COVID-19 in trauma patients: A case series

BackgroundDiagnosis of COVID-19 can be challenging in trauma patients, especially those with chest trauma and lung contusion.MethodsWe present a case series of patients from February and March 2020 who were admitted to our trauma center at Rajaee Hospital Trauma Center, in Shiraz, Iran and had positive SARS-CoV-2 PCR test or chest CT scan suggestive of COVID-19 and were admitted to the specific ICU for COVID-19.ResultsEight COVID-19 patients (6 male) with mean age of 40 (SD?=?16.3) years old, were presented. All patients were cases of trauma injuries, with multiple injuries including chest trauma and lung contusion, admitted to our trauma center for management of their injuries, but they were diagnosed with COVID-19 as well. Two of them had coinfection of influenza type-B and SARS-CoV-2. All patients were treated for COVID-19 and three of them died;the rest were discharged from hospital.ConclusionSince PCR for SARS-CoV-2 is not always sensitive enough to confirm the cause of pneumonia, chest CT manifestations can be helpful, though, they are not always differentiable from lung contusion. Therefore, both the CT scan and the clinical and paraclinical presentation and course of improvement can be beneficial in diagnosing COVID-19 in the trauma setting.