Evaluation and Comparison of the Predictive Value of 4C Mortality Score, NEWS, and CURB-65 in Poor Outcomes in COVID-19 Patients: A Retrospective Study from a Single Center in Romania

High-Flow Nasal Cannula oxygen therapy in COVID-19: retrospective analysis of clinical outcomes - single center experience

Background

High-Flow Nasal Cannula (HFNC) oxygen therapy emerged as the therapy of choice in COVID-19-related pneumonia and moderate to severe acute hypoxemic respiratory failure (AHRF). HFNC oxygen therapy in COVID-19 has been recommended based its use to treat AHRF of other etiologies, and studies on assessing outcomes in COVID-19 patients are highly needed. This study aimed to examine outcomes in COVID-19 patients with pneumonia and severe AHRF treated with HFNC.

Materials and methods

The study included 235 COVID-19 patients with pneumonia treated with HFNC. Data extracted from medical records included demographic characteristics, comorbidities, laboratory parameters, clinical and oxygenation status, clinical complications, as well as the length of hospital stay. Patients were segregated into two groups based on their oxygen therapy needs: HDU group, those who exclusively required HFNC and ICU group, those whose oxygen therapy needed to be escalated at some point of hospital stay. The primary outcome was the need for respiratory support escalation (noninvasive or invasive mechanical ventilation) and the secondary outcome was the in-hospital all-cause mortality.

Results

The primary outcome was met in 113 (48%) of patients. The overall mortality was 70%, significantly higher in the ICU group [102 (90.2%) vs. 62 (50.1%), p < 0.001]. The rate of intrahospital infections was significantly higher in the ICU group while there were no significant differences in the length of hospital stay between the groups. The ICU group exhibited significant increases in D-dimer, NLR, and NEWS values, accompanied by a significant decrease in the SaO2/FiO2 ratio. The multivariable COX proportional regression analysis identified malignancy, higher levels of 4C Mortality Score and NEWS2 as significant predictors of mortality.

Conclusion

High-Flow Nasal Cannula oxygen therapy is a safe type of respiratory support in patients with COVID-19 pneumonia and acute hypoxemic respiratory failure with significantly less possibility for emergence of intrahospital infections. In 52% of patients, HFNC was successful in treating AHRF in COVID-19 patients. Overall, mortality in COVID-19 pneumonia with AHRF is still very high, especially in patients treated with noninvasive/invasive mechanical ventilation.

A specific combination of laboratory data is associated with overweight lungs in patients with COVID-19 pneumonia at hospital admission: secondary cross-sectional analysis of a randomized clinical trial

Background

Lung weight may be measured with quantitative chest computed tomography (CT) in patients with COVID-19 to characterize the severity of pulmonary edema and assess prognosis. However, this quantitative analysis is often not accessible, which led to the hypothesis that specific laboratory data may help identify overweight lungs.

Methods

This cross-sectional study was a secondary analysis of data from SARITA2, a randomized clinical trial comparing nitazoxanide and placebo in patients with COVID-19 pneumonia. Adult patients (≥18 years) requiring supplemental oxygen due to COVID-19 pneumonia were enrolled between April 20 and October 15, 2020, in 19 hospitals in Brazil. The weight of the lungs as well as laboratory data [hemoglobin, leukocytes, neutrophils, lymphocytes, C-reactive protein, D-dimer, lactate dehydrogenase (LDH), and ferritin] and 47 additional specific blood biomarkers were assessed.

Results

Ninety-three patients were included in the study: 46 patients presented with underweight lungs (defined by ≤0% of excess lung weight) and 47 patients presented with overweight lungs (>0% of excess lung weight). Leukocytes, neutrophils, D-dimer, and LDH were higher in patients with overweight lungs. Among the 47 blood biomarkers investigated, interferon alpha 2 protein was higher and leukocyte inhibitory factor was lower in patients with overweight lungs. According to CombiROC analysis, the combinations of D-dimer/LDH/leukocytes, D-dimer/LDH/neutrophils, and D-dimer/LDH/leukocytes/neutrophils achieved the highest area under the curve with the best accuracy to detect overweight lungs.

Conclusion

The combinations of these specific laboratory data: D-dimer/LDH/leukocytes or D-dimer/LDH/neutrophils or D-dimer/LDH/leukocytes/neutrophils were the best predictors of overweight lungs in patients with COVID-19 pneumonia at hospital admission.

Clinical trial registration

Brazilian Registry of Clinical Trials (REBEC) number RBR-88bs9x and ClinicalTrials.gov number NCT04561219.

Circulating mid-regional proadrenomedullin is a predictor of mortality in patients with COVID-19: a systematic review and meta-analysis

BACKGROUND

Although there is increasing understanding of the changes in the laboratory parameters of Coronavirus disease 2019 (COVID-19), the correlation between circulating Mid-regional Proadrenomedullin (MR-proADM) and mortality of patients with COVID-19 is not fully understood. In this study, we conducted a systematic review and meta-analysis to evaluate the prognostic value of MR-proADM in patients with COVID-19.

METHODS

The PubMed, Embase, Web of Science, Cochrane Library, Wanfang, SinoMed and Chinese National Knowledge Infrastructure (CNKI) databases were searched from 1 January 2020 to 20 March 2022 for relevant literature. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was used to assess quality bias, STATA was employed to pool the effect size by a random effects model, and potential publication bias and sensitivity analyses were performed.

RESULTS

14 studies comprising 1822 patients with COVID-19 met the inclusion criteria, there were 1145 (62.8%) males and 677 (31.2%) females, and the mean age was 63.8 ± 16.1 years. The concentration of MR-proADM was compared between the survivors and non-survivors in 9 studies and the difference was significant (P < 0.01), I² = 46%. The combined sensitivity was 0.86 [0.73-0.92], and the combined specificity was 0.78 [0.68-0.86]. We drew the summary receiver operating characteristic (SROC) curve and calculated the area under curve (AUC) = 0.90 [0.87-0.92]. An increase of 1 nmol/L of MR-proADM was independently associated with a more than threefold increase in mortality (odds ratio (OR) 3.03, 95% confidence interval (CI) 2.26-4.06, I² = 0.0%, P = 0.633). The predictive value of MR-proADM for mortality was better than many other biomarkers.

CONCLUSION

MR-proADM had a very good predictive value for the poor prognosis of COVID-19 patients. Increased levels of MR-proADM were independently associated with mortality in COVID-19 patients and may allow a better risk stratification.

Prognostic models in COVID-19 infection that predict severity: a systematic review

Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.

A Retrospective Analysis of the Challenges of Urothelial Cancer Management during the COVID-19 Pandemic at a Single Academic Center in Romania

The COVID-19 pandemic caused major changes in the healthcare sector due to adaptations required to hospitalize and treat an impressive number of patients. This retrospective study intended to collect reliable information on urothelial cancer patients in Romania. The primary objective was to compare the pre-pandemic and pandemic periods to observe the differences that occurred in the management of patients with urothelial carcinoma. The secondary objective was to determine the risk factors for urothelial cancer progression in the study cohort correlated with the COVID-19 pandemic. All patients that were diagnosed and treated at our clinic with a diagnosis of urothelial carcinoma (transitional cell carcinoma) during 2019-2021 were included in the current study. A total of 1122 eligible unique cases were identified during the study period. The number of patients who underwent intervention in the pre-pandemic year was 421, followed by a 22.6% decrease in 2020 to 326 cases and a 13.1% increase in 2021 to 375 cases. The proportion of muscle-invasive bladder cancer (MIBC) cases was significantly higher during the pandemic years, from 30.5% MIBC cases in 2019 to 37.4% in 2020 and 39.4% in 2021, suggesting a delay in presentations during the pandemic. Stage III and IV (TNM) cases were significantly more frequent, even though approximately 40% of all patients were operated on in stage I. The number of cystectomies increased significantly, from 5.2% in 2019 and 4.3% in 2020 to 10.1% in 2021, while the number of elective surgeries decreased, although no significant difference was observed regarding the in-hospital mortality and disease progression at six months. Patients with stage III and IV at presentation had the highest likelihood of disease progression at six months (HR = 5.61). Distant invasion was the second highest risk factor (HR = 5.13), followed by MIBC type (HR = 2.49). Nevertheless, the duration of hospitalization and year of diagnosis during the COVID-19 pandemic were not significant risk factors for cancer progression at six months. It can be concluded that there was a significant delay in patient presentations in 2020, and we advocate for increased public health awareness for urothelial cancer and increased attention toward the screening and management of these patients in the following years.

A Systematic Review of Lung Autopsy Findings in Elderly Patients after SARS-CoV-2 Infection

Although COVID-19 may cause various and multiorgan diseases, few research studies have examined the postmortem pathological findings of SARS-CoV-2-infected individuals who died. Active autopsy results may be crucial for understanding how COVID-19 infection operates and preventing severe effects. In contrast to younger persons, however, the patient's age, lifestyle, and concomitant comorbidities might alter the morpho-pathological aspects of the damaged lungs. Through a systematic analysis of the available literature until December 2022, we aimed to provide a thorough picture of the histopathological characteristics of the lungs in patients older than 70 years who died of COVID-19. A thorough search was conducted on three electronic databases (PubMed, Scopus, and Web of Science), including 18 studies and a total of 478 autopsies performed. It was observed that the average age of patients was 75.6 years, of which 65.4% were men. COPD was identified in an average of 16.7% of all patients. Autopsy findings indicated significantly heavier lungs, with an average weight of the right lung of 1103 g, while the left lung mass had an average weight of 848 g. Diffuse alveolar damage was a main finding in 67.2% of all autopsies, while pulmonary edema had a prevalence of between 50% and 70%. Thrombosis was also a significant finding, while some studies described focal and extensive pulmonary infarctions in 72.7% of elderly patients. Pneumonia and bronchopneumonia were observed, with a prevalence ranging from 47.6% to 89.5%. Other important findings described in less detail comprise hyaline membranes, the proliferation of pneumocytes and fibroblasts, extensive suppurative bronchopneumonic infiltrates, intra-alveolar edema, thickened alveolar septa, desquamation of pneumocytes, alveolar infiltrates, multinucleated giant cells, and intranuclear inclusion bodies. These findings should be corroborated with children's and adults' autopsies. Postmortem examination as a technique for studying the microscopic and macroscopic features of the lungs might lead to a better knowledge of COVID-19 pathogenesis, diagnosis, and treatment, hence enhancing elderly patient care.

The Assessment of Multiplex PCR in Identifying Bacterial Infections in Patients Hospitalized with SARS-CoV-2 Infection: A Systematic Review

Bacterial infection can occur in patients hospitalized with SARS-CoV-2 in various conditions, resulting in poorer outcomes, such as a higher death rate. This current systematic review was conducted in order to assess the efficiency of multiplex PCR in detecting bacterial infections in hospitalized COVID-19 patients, as well as to analyze the most common bacterial pathogens and other factors that interfere with this diagnosis. The research was conducted using four electronic databases (PubMed, Taylor&Francis, Web of Science, and Wiley Online Library). Out of 290 studies, nine were included in the systematic review. The results supported the use of multiplex PCR in detecting bacteria, considering its high sensitivity and specificity rates. The most common bacterial pathogens found were Klebsiella pneumoniae, Staphylococcus aureus, Pseudomonas aeruginosa, Streptococcus pneumoniae, and Haemophilus influenzae. The median age at admission was 61.5 years, and the majority of patients were men (70.3%), out of a total of 1553 patients. The proportion of ICU admission was very high, with a pooled proportion of 52.6% over the analyzed studies, and an average duration of hospitalization of 13 days. The mortality rate was proportionally high, as was the rate of ICU admission, with a pooled mortality of 24.9%. It was discovered that 65.2% of all patients used antibiotics before admission, with or without medical prescription. Antibiotic treatment should be considered consciously, considering the high risks of developing antibiotic resistance.

Assessing the Outcomes of Patients with Severe SARS-CoV-2 Infection after Therapeutic Plasma Exchange by Number of TPE Sessions

The high mortality risk in severe SARS-CoV-2 infections is tightly correlated to the extreme elevation of inflammatory markers. This acute accumulation of inflammatory proteins can be cleared using plasma exchange (TPE), commonly known as plasmapheresis, although the available data on performing TPE in COVID-19 patients is limited regarding the optimal treatment protocol. The purpose for this study was to examine the efficacy and outcomes of TPE based on different treatment methods. A thorough database search was performed to identify patients from the Intensive Care Unit (ICU) of the Clinical Hospital of Infectious Diseases and Pneumology between March 2020 and March 2022 with severe COVID-19 that underwent at least one session of TPE. A total of 65 patients satisfied the inclusion criteria and were eligible for TPE as a last resort therapy. Of these, 41 patients received 1 TPE session, 13 received 2 TPE sessions, and the remaining 11 received more than 2 TPE sessions. It was observed that IL-6, CRP, and ESR decreased significantly after all sessions were performed in all three groups, with the highest decrease of IL-6 in those who received >2 TPE sessions (from 305.5 pg/mL to 156.0 pg/mL). Interestingly, there was a significant increase in leucocyte levels after TPE, but there was no significant difference in MAP changes, SOFA score, APACHE 2 score, or the PaO2/FiO2 ratio. The ROX index was significantly higher among the patients who underwent more than two TPE sessions, with an average of 11.4, compared to 6.5 in group 1 and 7.4 in group 2, which increased significantly after TPE. Nevertheless, the mortality rate was very high (72.3%), and the Kaplan-Meier analysis identified no significant difference in survival according to the number of TPE sessions. TPE can be used as last resort salvage therapy that can be regarded as an alternative treatment method when the standard management of these patients fails. It significantly decreases the inflammatory status measured via IL-6, CRP, and WBC, as well as demonstrating an improvement of the clinical status measured via PaO2/FiO2, and duration of hospitalization. However, the survival rate does not seem to change with the number of TPE sessions. Based on the survival analysis, one session of TPE as last resort treatment in patients with severe COVID-19 proved to have the same effect as repeated TPE sessions of 2 or more.

Mechanical ventilation and death in pregnant patients admitted for COVID-19: a prognostic analysis from the Brazilian COVID-19 registry score

BACKGROUND

The assessment of clinical prognosis of pregnant COVID-19 patients at hospital presentation is challenging, due to physiological adaptations during pregnancy. Our aim was to assess the performance of the ABC2-SPH score to predict in-hospital mortality and mechanical ventilation support in pregnant patients with COVID-19, to assess the frequency of adverse pregnancy outcomes, and characteristics of pregnant women who died.

METHODS

This multicenter cohort included consecutive pregnant patients with COVID-19 admitted to the participating hospitals, from April/2020 to March/2022. Primary outcomes were in-hospital mortality and the composite outcome of mechanical ventilation support and in-hospital mortality. Secondary endpoints were pregnancy outcomes. The overall discrimination of the model was presented as the area under the receiver operating characteristic curve (AUROC). Overall performance was assessed using the Brier score.

RESULTS

From 350 pregnant patients (median age 30 [interquartile range (25.2, 35.0)] years-old]), 11.1% had hypertensive disorders, 19.7% required mechanical ventilation support and 6.0% died. The AUROC for in-hospital mortality and for the composite outcome were 0.809 (95% IC: 0.641-0.944) and 0.704 (95% IC: 0.617-0.792), respectively, with good overall performance (Brier = 0.0384 and 0.1610, respectively). Calibration was good for the prediction of in-hospital mortality, but poor for the composite outcome. Women who died had a median age 4 years-old higher, higher frequency of hypertensive disorders (38.1% vs. 9.4%, p < 0.001) and obesity (28.6% vs. 10.6%, p = 0.025) than those who were discharged alive, and their newborns had lower birth weight (2000 vs. 2813, p = 0.001) and five-minute Apgar score (3.0 vs. 8.0, p < 0.001).

CONCLUSIONS

The ABC2-SPH score had good overall performance for in-hospital mortality and the composite outcome mechanical ventilation and in-hospital mortality. Calibration was good for the prediction of in-hospital mortality, but it was poor for the composite outcome. Therefore, the score may be useful to predict in-hospital mortality in pregnant patients with COVID-19, in addition to clinical judgment. Newborns from women who died had lower birth weight and Apgar score than those who were discharged alive.

Assessment of the disease severity in patients hospitalized for COVID-19 based on the National Early Warning Score (NEWS) using statistical and machine learning methods: An electronic health records database analysis

BACKGROUND

The coronavirus disease 2019 (COVID-19) was a cause of concern in the healthcare system and increased the need for disease severity indicators. However, they still vary in use to evaluate in-hospital outcomes and severity. The National Early Warning Score (NEWS) is routinely used to evaluate patient health status at the hospital. Further research is needed to ensure if NEWS can be a good instrument for an overall health status assessment with or without additional information like laboratory tests, intensive care needs, and history of chronic diseases.

OBJECTIVE

To evaluate if NEWS can be an indicator to measure COVID-19 patient status in-hospital.

METHODS

We used the fully anonymized Electronic Health Records (EHR) characterizing patients admitted to the hospital with COVID-19. Data was obtained from Vilnius University Hospital Santaros Klinikos EHR system (SANTA-HIS) from 01-03-2020 to 31-12-2022. The study sample included 3875 patients. We created several statistical and machine learning models for discrimination between in-hospital death/discharge for evaluation NEWS as a disease severity measure for COVID-19 patients. In these models, two variable sets were considered: median NEWS and its combination with clinical parameters and medians of laboratory test results. Assessment of models' performance was based on the scoring metrics: accuracy, sensitivity, specificity, area under the ROC curve (AUC), and F1-score.

RESULTS

Our analysis revealed that NEWS predictive ability for describing patient health status during the stay in the hospital can be increased by adding the patient's age at hospitalization, gender, clinical and laboratory variables (0.853 sensitivity, 0.992 specificity and F1-score - 0.859) in comparison with single NEWS (0.603, 0.995, 0.719, respectively). A comparison of different models showed that stepwise logistic regression was the best method for in-hospital mortality classification. Our findings suggest employing models like ours for advisory routine usage.

CONCLUSION

Our model demonstrated incremental value for COVID-19 patient's status evaluation.

Temporal Improvements in COVID-19 Outcomes for Hospitalized Adults: A Post Hoc Observational Study of Remdesivir Group Participants in the Adaptive COVID-19 Treatment Trial

BACKGROUND

The COVID-19 standard of care (SOC) evolved rapidly during 2020 and 2021, but its cumulative effect over time is unclear.

OBJECTIVE

To evaluate whether recovery and mortality improved as SOC evolved, using data from ACTT (Adaptive COVID-19 Treatment Trial).

DESIGN

ACTT is a series of phase 3, randomized, double-blind, placebo-controlled trials that evaluated COVID-19 therapeutics from February 2020 through May 2021. ACTT-1 compared remdesivir plus SOC to placebo plus SOC, and in ACTT-2 and ACTT-3, remdesivir plus SOC was the control group. This post hoc analysis compared recovery and mortality between these comparable sequential cohorts of patients who received remdesivir plus SOC, adjusting for baseline characteristics with propensity score weighting. The analysis was repeated for participants in ACTT-3 and ACTT-4 who received remdesivir plus dexamethasone plus SOC. Trends in SOC that could explain outcome improvements were analyzed. (ClinicalTrials.gov: NCT04280705 [ACTT-1], NCT04401579 [ACTT-2], NCT04492475 [ACTT-3], and NCT04640168 [ACTT-4]).

SETTING

94 hospitals in 10 countries (86% U.S. participants).

PARTICIPANTS

Adults hospitalized with COVID-19.

INTERVENTION

SOC.

MEASUREMENTS

28-day mortality and recovery.

RESULTS

Although outcomes were better in ACTT-2 than in ACTT-1, adjusted hazard ratios (HRs) were close to 1 (HR for recovery, 1.04 [95% CI, 0.92 to 1.17]; HR for mortality, 0.90 [CI, 0.56 to 1.40]). Comparable patients were less likely to be intubated in ACTT-2 than in ACTT-1 (odds ratio, 0.75 [CI, 0.53 to 0.97]), and hydroxychloroquine use decreased. Outcomes improved from ACTT-2 to ACTT-3 (HR for recovery, 1.43 [CI, 1.24 to 1.64]; HR for mortality, 0.45 [CI, 0.21 to 0.97]). Potential explanatory factors (SOC trends, case surges, and variant trends) were similar between ACTT-2 and ACTT-3, except for increased dexamethasone use (11% to 77%). Outcomes were similar in ACTT-3 and ACTT-4. Antibiotic use decreased gradually across all stages.

LIMITATION

Unmeasured confounding.

CONCLUSION

Changes in patient composition explained improved outcomes from ACTT-1 to ACTT-2 but not from ACTT-2 to ACTT-3, suggesting improved SOC. These results support excluding nonconcurrent controls from analysis of platform trials in rapidly changing therapeutic areas.

PRIMARY FUNDING SOURCE

National Institute of Allergy and Infectious Diseases.

The Predictive Role of Maternal Biological Markers and Inflammatory Scores NLR, PLR, MLR, SII, and SIRI for the Risk of Preterm Delivery

In many countries, preterm birth, defined as birth before 37 completed weeks of gestation, is the primary cause of infant death and morbidity. An increasing body of research suggests that inflammation (both clinical and subclinical) plays a significant role in inducing preterm labor or developing pregnancy problems that lead to premature birth. Consequently, the purpose of this research was to determine the predictive value of the Neutrophil-Lymphocyte Ratio (NLR), derived Neutrophil-Lymphocyte Ratio (dNLR), Monocytes-to-Lymphocyte Ratio (MLR), Platelets-to-Lymphocyte Ratio (PLR), Systemic immune-inflammation index (SII), and systemic inflammatory response index (SIRI), for premature delivery. A retrospective study analyzed a total of 243 eligible pregnancies that resulted in a preterm birth during 2020 and 2021. A control group without a history of preterm birth was matched by age and trimester of laboratory analysis at a 1:1 ratio. Although the number of comorbidities was similar among study groups, the body-mass index estimated for the week of gestation was significantly higher among the patients from the prematurity group, as well as the prevalence of urinary tract infections and smoking. Laboratory data showed that patients with a preterm birth had significantly higher white blood cell count and monocytes, but significantly lower lymphocytes, platelets, and hemoglobin. The NLR, dNLR, PLR, and MLR scores showed to be significantly higher among patients from the prematurity group, but SII and SIRI were not significantly different between the study groups. It was observed that the AUC values of NLR, dNLR, PLR, and MLR were higher than 0.600, respectively NLR had the highest value among the tested scores (AUC = 0.694) and the highest sensitivity in this study (71%). The highest sensibility was achieved by dNLR, with 70%, and an AUC value of 0.655 (p-value = 0.022). PLR had the second-highest AUC value (0.682) and the best score in terms of sensitivity (70%) and sensibility (69%) (p-value = 0.015). Lastly, MLR had the lowest significant AUC score (0.607) and lowest sensitivity/sensibility. The significant cut-off values for the inflammatory scores were 9.0 for NLR, 9.8 for dNLR, 250 for PLR, and 4.07 for MLR. After evaluating the importance of these inflammatory scores, further clinical applications should be conducted to confirm the results and improve therapy and care to reduce the burden of premature deliveries.

Physiologic Scoring Systems in Predicting the COVID-19 Patients' one-month Mortality; a Prognostic Accuracy Study

Introduction : It is critical to quickly and easily identify severe coronavirus disease 2019 (COVID-19) patients and predict their mortality. This study aimed to determine the accuracy of the physiologic scoring systems in predicting the mortality of COVID-19 patients. Methods: This prospective cross-sectional study was performed on COVID-19 patients admitted to the emergency department (ED). The clinical characteristics of the participants were collected by the emergency physicians and the accuracy of the Quick Sequential Failure Assessment (qSOFA), Coronavirus Clinical Characterization Consortium (4C) Mortality, National Early Warning Score-2 (NEWS2), and Pandemic Respiratory Infection Emergency System Triage (PRIEST) scores for mortality prediction was evaluated. Results: Nine hundred and twenty-one subjects were included. Of whom, 745 (80.9%) patients survived after 30 days of admission. The mean age of patients was 59.13 ± 17.52 years, and 550 (61.6%) subjects were male. Non-Survived patients were significantly older (66.02 ± 17.80 vs. 57.45 ± 17.07, P< 0.001) and had more comorbidities (diabetes mellitus, respiratory, cardiovascular, and cerebrovascular disease) in comparison with survived patients. For COVID-19 mortality prediction, the AUROCs of PRIEST, qSOFA, NEWS2, and 4C Mortality score were 0.846 (95% CI [0.821-0.868]), 0.788 (95% CI [0.760-0.814]), 0.843 (95% CI [0.818-0.866]), and 0.804 (95% CI [0.776-0.829]), respectively. All scores were good predictors of COVID-19 mortality. Conclusion: All studied physiologic scores were good predictors of COVID-19 mortality and could be a useful screening tool for identifying high-risk patients. The NEWS2 and PRIEST scores predicted mortality in COVID-19 patients significantly better than qSOFA.

Evaluation of FIB-4, NFS, APRI and Liver Function Tests as Predictors for SARS-CoV-2 Infection in the Elderly Population: A Matched Case-Control Analysis

Several investigations have revealed that COVID-19 causes a significant death rate due to acute respiratory distress syndrome, alterations in the quantity of ACE2 receptor expression, or the intensity of cytokine storm. Similarly, patients with hepatic impairment that are co-infected with SARS-CoV-2 are more likely to display upregulations of ACE2 receptors and cytokine storm overload, which exacerbates hepatic impairment, potentially increasing the death rate. Moreover, it is expected that the aging population develops a higher degree of hepatic fibrosis in association with other comorbid conditions that are likely to influence the course of COVID-19. Therefore, this research was developed to describe the differences in liver test parameters in elderly individuals with COVID-19 in relation to other inflammatory markers and outcomes. This current observational single-center research followed a case-control design of elderly patients hospitalized for SARS-CoV-2 infection. The research was conducted at a tertiary emergency hospital in western Romania during a two-year period. There were 632 patients included in the analysis that were split into two equal groups matched 1:1 based on gender and body mass index. Three hundred sixteen patients made the group of cases with COVID-19 patients older than 65 years, while the other half were the 316 patient controls with COVID-19 that were younger than 65 years old. Disease outcomes showed a higher prevalence of ICU admissions (22.8% vs. 12.7%, p-value < 0.001) and in-hospital mortality (17.1% vs. 8.9%, p-value = 0.002) in the group of cases. Specific and non-specific liver biomarkers were identified as risk factors for mortality in the elderly, such as ALP (OR = 1.26), LDH (OR = 1.68), AST (OR = 1.98), and ALT (OR = 2.34). Similarly, patients with APRI and NFS scores higher than 1.5 were, respectively, 2.69 times and, 3.05 times more likely to die from COVID-19, and patients with FIB-4 scores higher than 3.25 were 3.13 times more likely to die during hospitalization for SARS-CoV-2 infection. Our research indicates that abnormally increased liver biomarkers and high liver fibrosis scores are related to a worse prognosis in SARS-CoV-2 infected individuals.

The Impact of SARS-CoV-2 Pandemic on Patients Undergoing Radiation Therapy for Advanced Cervical Cancer at a Romanian Academic Center: A Four-Year Retrospective Analysis

Background and Objectives: Throughout the COVID-19 pandemic, health systems worldwide adapted to support COVID-19 patients while continuing to provide assistance to patients with other potentially fatal illnesses. While patients with cancer may be at an elevated risk of severe COVID-19-related complications, their oncologic therapies generally cannot be postponed indefinitely without a negative effect on outcomes. Taking this into account, a thorough examination of the therapy management of various cancers is necessary, such as cervical cancer. Therefore, we aimed to develop a retrospective cohort study to measure the impact of the COVID-19 pandemic on the delivery of cancer care services for women diagnosed with cervical cancer staged IB2-IVA, necessitating chemo- and radiotherapy in Romania, as well as determine the difference in cervical cancer staging between the pandemic and pre-pandemic period. Materials and Methods: Using a multicentric hospital database, we designed a retrospective study to compare the last 24 months of the pre-pandemic period to the first 24 months of the SARS-CoV-2 pandemic to evaluate the variation in the proportion of women diagnosed with cervical cancer and the percentage of inoperable cases requiring chemotherapy and radiotherapy, as well as to detail their clinical presentation and other findings. Results: We observed that the likelihood of cervical cancer patients requiring radiation therapy at a later stage than before the pandemic increased by about 20% during the COVID-19 pandemic. Patients at an advanced FIGO stage of cervical cancer had a 3.39 higher likelihood of disease progression after radiotherapy (CI [2.06−4.21], p-value < 0.001), followed by tumor size at diagnosis with a hazard ratio (HR) of 3.12 (CI [2.24−4.00], p-value < 0.001). The factors related to the COVID-19 pandemic, postponed treatment and missed appointments, were also identified as significant risk factors for cervical cancer progression (HR = 2.51 and HR = 2.24, respectively). Conclusions We predict that there will be a considerable rise in cervical cancer cases over the next several years based on existing data and that expanding screening and treatment capacity will attenuate this with a minimal increase in morbidity and fatality.

Predictive Value of SOFA and qSOFA for In-Hospital Mortality in COVID-19 Patients: A Single-Center Study in Romania

Two years after the outbreak of the COVID-19 pandemic, the disease continues to claim victims worldwide. Assessing the disease’s severity on admission may be useful in reducing mortality among patients with COVID-19. The present study was designed to assess the prognostic value of SOFA and qSOFA scoring systems for in-hospital mortality among patients with COVID-19. The study included 133 patients with COVID-19 proven by reverse transcriptase polymerase chain reaction (RT-PCR) admitted to the Municipal Emergency Clinical Hospital of Timisoara, Romania between 1 October 2020 and 15 March 2021. Data on clinical features and laboratory findings on admission were collected from electronic medical records and used to compute SOFA and qSOFA. Mean SOFA and qSOFA values were higher in the non-survivor group compared to survivors (3.5 vs. 1 for SOFA and 2 vs. 1 for qSOFA, respectively). Receiver operating characteristic (ROC) and area under the curve (AUC) analyses were performed to determine the discrimination accuracy, both risk scores being excellent predictors of in-hospital mortality, with ROC–AUC values of 0.800 for SOFA and 0.794 for qSOFA. The regression analysis showed that for every one-point increase in SOFA score, mortality risk increased by 1.82 and for every one-point increase in qSOFA score, mortality risk increased by 5.23. In addition, patients with SOFA and qSOFA above the cut-off values have an increased risk of mortality with ORs of 7.46 and 11.3, respectively. In conclusion, SOFA and qSOFA are excellent predictors of in-hospital mortality among COVID-19 patients. These scores determined at admission could help physicians identify those patients at high risk of severe COVID-19.

Predictive Value of Blood Coagulation Parameters in Poor Outcomes in COVID-19 Patients: A Retrospective Observational Study in Romania

SARS-CoV-2 infection produces alterations in blood clotting, especially in severe cases of COVID-19. Abnormal coagulation parameters in patients with COVID-19 are important prognostic factors of disease severity. The objective of this study was to evaluate the predictive value of aPTT, D-dimer, INR and PT in the mortality of patients with COVID-19. A retrospective, single-center, observational study was conducted on COVID-19 patients admitted to the Municipal Emergency Clinical Hospital in Timisoara, Romania, between August and October 2021. Patients were confirmed as COVID-19 positive by reverse transcription-polymerase chain reaction (RT-PCR) assay. After applying the inclusion/exclusion criteria, a total of 82 patients were included in the analysis. Receiver operating characteristic (ROC) curves of D-Dimer, INR, PT and aPTT were generated to assess whether the baseline of each of these biomarkers was accurately predictive for mortality in patients with COVID-19. Mortality among patients enrolled in this study was 20.7%, associated with older age and presence of heart disease. The areas under the ROC curve (AUC-ROC) of D-Dimer, INR, PT, and aPTT were 0.751, 0.724, 0.706 and 0.753. Differences in survival for patients with coagulation biomarker levels above cut-off values compared to patients below these values were statistically significant. All evaluated parameters had significant differences and good performance in predicting mortality of COVID-19 patients, except fibrinogen, which had no significant difference. Moreover, aPTT and D-dimer were the best performing parameters in predicting mortality in patients with SARS-CoV-2 infection.

External Validation of the Modified 4C Deterioration Model and 4C Mortality Score for COVID-19 Patients in a Swiss Tertiary Hospital

Prognostic models to predict the deterioration and mortality risk in COVID-19 patients are utterly needed to assist in informed decision making. Most of these models, however, are at high risk of bias, model overfitting, and unclear reporting. Here, we aimed to externally validate the modified (urea was omitted) 4C Deterioration Model and 4C Mortality Score in a cohort of Swiss COVID-19 patients and, second, to evaluate whether the inclusion of the neutrophil-to-lymphocyte ratio (NLR) improves the predictive performance of the models. We conducted a retrospective single-centre study with adult patients hospitalized with COVID-19. Both prediction models were updated by including the NLR. Model performance was assessed via the models' discriminatory performance (area under the curve, AUC), calibration (intercept and slope), and their performance overall (Brier score). For the validation of the 4C Deterioration Model and Mortality Score, 546 and 527 patients were included, respectively. In total, 133 (24.4%) patients met the definition of in-hospital deterioration. Discrimination of the 4C Deterioration Model was AUC = 0.78 (95% CI 0.73-0.82). A total of 55 (10.44%) patients died in hospital. Discrimination of the 4C Mortality Score was AUC = 0.85 (95% CI 0.79-0.89). There was no evidence for an incremental value of the NLR. Our data confirm the role of the modified 4C Deterioration Model and Mortality Score as reliable prediction tools for the risk of deterioration and mortality. There was no evidence that the inclusion of NLR improved model performance.