The usefulness of a combination of age, body mass index, and blood urea nitrogen as prognostic factors in predicting oxygen requirements in patients with coronavirus disease 2019

Clinical and epidemiological risk factors associated with hospitalization and mortality rate of COVID-19 patients in Banja Luka County: A retrospective observational cohort study on 40,000 patients

Context

Since beginning of the coronavirus disease (COVID-19) it became clear that severe forms of this infection have primarily affected patients with chronic conditions.

Aims

The aim of the study was to explore clinical and epidemiological characteristics associated with COVID 19 outcomes.

Settings and Design

The retrospective observational study included 40,692 citizens of Banja Luka County, Bosnia and Herzegovina, who were confirmed as reverse transcriptase polymerase chain reaction (RT-PCR) positive on COVID-19 at a primary healthcare centre from March 2020 to September 2022.

Methods and Materials

Epidemiological data were obtained from Web-Medic medical records of patients. The COVID-19 data were obtained from COVID-19 data sheets comprised of patients' RT-PCR testing forms, surveillance forms for severe acute respiratory syndrome coronavirus-2 status, and a map of their positive and isolated contacts.

Statistical Analysis Used

Differences regarding the distributions of patients between groups were analysed using the Pearson chi-square test and Mantel-Haenszel chi-square test for trends, while differences in mean values were compared using an independent sample t-test.

Results

The average age of hospitalised patients was significantly higher compared to the age of non-hospitalised patients (P < 0.001). The average age of patients with lethal outcomes was nearly twice as high in comparison to patients with non-lethal outcomes (P < 0.001). Male patients had a higher hospitalization and mortality rate (P < 0.001). The highest hospitalization rate was in patients with chronic renal failure (CRF), diabetes and cardiovascular diseases (CVDs), while the death rate was the highest among patients with CRF and hearth comorbidities. Patients with fatigue and appetite loss had a higher percentage of lethal outcomes. Vaccinated patients had a significantly lower rate of lethal outcome.

Conclusions

Clinical symptoms, signs and outcomes, are posing as predictive parameters for further management of COVID-19. Vaccination has an important role in the clinical outcomes of COVID-19.

Serum lipid mediator profiles in COVID-19 patients and lung disease severity: a pilot study

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 infection is highly heterogeneous, ranging from asymptomatic to severe and fatal cases. COVID-19 has been characterized by an increase of serum pro-inflammatory cytokine levels which seems to be associated with fatal cases. By contrast, the role of pro-resolving lipid mediators (SPMs), involved in the attenuation of inflammatory responses, has been scarcely investigated, so further studies are needed to understand SPMs metabolism in COVID-19 and other infectious diseases. Our aim was to analyse the lipid mediator metabolome, quantifying pro- and anti-inflammatory serum bioactive lipids by LC-MS/MS in 7 non-infected subjects and 24 COVID-19 patients divided into mild, moderate, and severe groups according to the pulmonary involvement, to better understand the disease outcome and the severity of the pulmonary manifestations. Statistical analysis was performed with the R programming language (R Foundation for Statistical Computing, Vienna, Austria). All COVID-19 patients had increased levels of Prostaglandin E₂. Severe patients showed a significant increase versus controls, mild- and moderate-affected patients, expressed as median (interquartile range), in resolvin E1 [112.6 (502.7) vs 0.0 (0.0) pg/ml in the other groups], as well as in maresin 2 [14.5 (7.0) vs 8.1 (4.2), 5.5 (4.3), and 3.0 (4.0) pg/ml, respectively]. Moreover, 14-hydroxy docosahexaenoic acid (14-HDHA) levels were also increased in severe vs control and mild-affected patients [24.7 (38.2) vs 2.4 (2.2) and 3.7 (6.4) ng/mL, respectively]. Resolvin D5 was also significantly elevated in both moderate [15.0 (22.4) pg/ml] and severe patients [24.0 (24.1) pg/ml] versus controls [0.0 (0.0) pg/ml]. These results were confirmed by sparse partial least squares discriminant analysis which highlighted the contribution of these mediators to the separation between each of the groups. In conclusion, the potent inflammatory response to SARS-CoV-2 infection involves not only pro- but also anti-inflammatory lipid mediators that can be quantified in easily accessible serum samples, suggesting the need to perform future research on their generation pathways that will help us to discover new therapeutic targets.

Development and Validation of a Predictive Nomogram with Age and Laboratory Findings for Severe COVID-19 in Hunan Province, China

Purpose

To identify more objectively predictive factors of severe outcome among patients hospitalized for coronavirus disease 2019 (COVID-19).

Patients and Methods

A retrospective cohort of 479 hospitalized patients diagnosed with COVID-19 in Hunan Province was selected. The prognostic effects of factors such as age and laboratory indicators were analyzed using the Kaplan–Meier method and Cox proportional hazards model. A prognostic nomogram model was established to predict the progression of patients with COVID-19.

Results

A total of 524 patients in Hunan province with COVID-19 from December 2019 to October 2020 were retrospectively recruited. Among them, 479 eligible patients were randomly assigned into the training cohort (n = 383) and validation cohort (n = 96), at a ratio of 8:2. Sixty-eight (17.8%) and 15 (15.6%) patients developed severe COVID-19 after admission in the training cohort and validation cohort, respectively. The differences in baseline characteristics were not statistically significant between the two cohorts with regard to age, sex, and comorbidities (P > 0.05). Multivariable analyses included age, C-reactive protein, fibrinogen, lactic dehydrogenase, neutrophil-to-lymphocyte ratio, urea, albumin-to-globulin ratio, and eosinophil count as predictive factors for patients with progression to severe COVID-19. A nomogram was constructed with sufficient discriminatory power (C index = 0.81), and proper consistency between the prediction and observation, with an area under the ROC curve of 0.81 and 0.86 in the training and validation cohort, respectively.

Conclusion

We proposed a simple nomogram for early detection of patients with non-severe COVID-19 but at high risk of progression to severe COVID-19, which could help optimize clinical care and personalized decision-making therapies.