Factors associated with admission to the intensive care unit and mortality in patients with COVID-19, Colombia

Lived Experiences Among Critically Ill and Near-Death Survivors Relating to the COVID-19 Infection: A Phenomenological Study

INTRODUCTION

The COVID-19 pandemic has resulted in severe illnesses worldwide. Around 655.5 million cases were having been confirmed, including 6.6 million deaths. The extreme cases experienced near death in the intensive care unit (ICU). This study explored the survivors' experience of being near death while critically ill with the infection.

METHODOLOGY

A descriptive phenomenological study was employed. Data were collected through in-depth interviews with 14 participants from Northeastern Thailand. Content analysis was applied by using Creswell's strategy.

RESULTS

Four themes emerged: (a) anxiety and fear of dying alone, (b) environmental chaos, (c) using Thai Buddhist teaching in coping, and (d) returning from the brink of death. Moreover, the patients felt great gratitude and were grateful to the health care team.

DISCUSSION

Traumas experienced by patients in the ICU included physical and psychological distress, coping strategies, and an understanding of cultural awareness.

CONCLUSION

Psychological and culturally congruent care should be implemented for patients in the ICU.

Cytokine expression and mortality risk among COVID-19 hospitalized patients over 60 years of age in a referral hospital in Cartagena, Colombia

Background

Cytokine dysregulation in COVID-19 patients aged over 60 has been associated to adverse outcomes. While serum levels have been studied, cellular expression, particularly in Afro-Colombians, remains understudied. This research aims to describe cytokine expression in peripheral blood leukocytes and its association with adverse outcomes in COVID-19 patients aged over 60 at Cartagena's referral hospital.

Methods

A cohort study was conducted, encompassing severe and critical cases of COVID-19 between November 2021 and February 2022. At baseline, the cellular expression level of cytokines IL-2, IL-4, IL-6, IL-10, TNF-α and IFN-γ was assessed using flow cytometry. Additionally, various biochemical, hematological, and coagulation markers were evaluated. The main outcome was time to death.

Results

Among the 50 enrolled participants, the median age was 76.5 years, 60% were male, 60% were admitted to the ICU, and 42% died. Lactate dehydrogenase and hemoglobin were the only markers that differed between fatal and surviving cases. Regarding cytokines, the level of IL-6 expression was associated with an increased risk of death. Specifically, a one percent increase in the expression was associated with a 7.3% increase in the risk of death. Stratifying the analysis by death and ICU admission, the median expression level remained high in fatal cases who were admitted to the ICU.

Conclusions

Our findings revealed a significant association between high cellular expression levels of IL-6 and an increased risk of mortality. These results provide valuable scientific insights that could inform the prioritization of case management, providing especially advantageous for the vulnerable Afro-Colombian group.

General Hospitalization and Intensive Care Unit-Related Factors of COVID-19 Patients in Northeastern Colombia: Baseline Characteristics of a Cohort Study

Objective This study aims to describe demographic and clinical characteristics and the factors associated with the risk of COVID-19 general hospitalization and intensive care unit (ICU) care of patients who consulted in a third-level hospital in Santander, Colombia. Methods We used baseline data from an ambidirectional cohort study. We included all patients with positive real-time polymerase chain reaction (PCR) tests for COVID-19 who came to the emergency room (ER) for respiratory symptoms related to COVID-19. Information regarding patients' baseline characteristics and symptoms was collected through telephone interviews and review of medical records. Vital signs were extracted from medical records as well. Results We enrolled 3,030 patients, predominantly men, with a median age of 60 (interquartile range (IQR): 44-73). Symptoms of the acute phase varied between men and women. Men presented with more respiratory symptoms, and women had general symptoms. Hypertension, obesity, and diabetes were common risk factors for hospital admission. Antibiotic consumption may also play a role in hospital admission.  Conclusions Male sex, older age, hypertension, obesity, prior thrombotic events, and self-medicated antibiotics were associated with general hospitalization. Hypertension, obesity, diabetes, and cancer were associated with ICU admission. The Charlson comorbidity index (CCI) is a powerful tool for evaluate the impact of pre-existing health conditions on COVID-19 hospital admission. We highlight the importance of these findings as possible predictors in our region.

Risk factors for persistent tomographic abnormalities at 6 months of follow-up in a cohort of hospitalized patients with moderate and severe COVID-19 living at high altitude

Introduction

After COVID-19, functional and tomographic lung alterations may occur, but there are no studies at high altitude where, due to lower barometric pressure, there are lower levels of arterial oxygen pressure and saturation in both normal subjects and patients with respiratory disease. In this study, we evaluated the computed tomographic (CT), clinical, and functional involvement at 3 and 6 months post-hospitalization in survivors with moderate-severe COVID-19, as well the risk factors associated with abnormal lung computed tomography (ALCT) at 6 months of follow-up.

Materials and methods

Prospective cohort, after hospitalization for COVID-19, of patients older than 18 years residing at high altitude. Follow-up at 3 and 6 months with lung CT, spirometry, diffusing capacity of the lung for carbon monoxide (DLCO), six-minute walk test (6MWT), and oxygen saturation (SpO₂). Comparisons between ALCT and normal lung computed tomography (NLCT) groups with X² and Mann-Whitney U test, and paired test for changes between 3 and 6 months. A multivariate analysis was performed to evaluate the variables associated with ALCT at 6-month follow-up.

Results

We included 158 patients, 22.2% hospitalized in intensive care unit (ICU), 92.4% with typical COVID CT scan (peripheral, bilateral, or multifocal ground glass, with or without consolidation or findings of organizing pneumonia), and median hospitalization of 7 days. At 6 months, 53 patients (33.5%) had ALCT. There were no differences between ALCT and NLCT groups in symptoms or comorbidities on admission. ALCT patients were older and more frequently men, smokers and hospitalized in ICU. At 3 months, ALCT patients had more frequently a reduced forced vital capacity (< 80%), and lower meters walked (6MWT) and SpO₂. At 6 months, all patients improved lung function with no differences between groups, but there were more dyspnea and lower exercise SpO₂ in ALCT group. The variables associated with ALCT at 6 months were age, sex, ICU stay, and typical CT scan.

Conclusion

At 6-month follow-up, 33.5% of patients with moderate and severe COVID had ALCT. These patients had more dyspnea and lower SpO₂ in exercise. Regardless of the persistence of tomographic abnormalities, lung function and 6MWT improved. We identified the variables associated with ALCT.

Use of Systemic Antibiotics in Patients with COVID-19 in Colombia: A Cross-Sectional Study

Antibiotics are frequently prescribed to patients with COVID-19. The aim was to determine the pattern of use of systemic antibiotics in a group of patients diagnosed with COVID-19 in Colombia between 2020-2022. This was a descriptive cross-sectional study designed to identify antibiotics prescription patterns for patients diagnosed with COVID-19 treated in eight clinics in Colombia. The AWaRe tool of the World Health Organization (WHO) was used to classify the antibiotics. A total of 10,916 patients were included. The median age was 57 years, and 56.4% were male. A total of 57.5% received antibiotics, especially ampicillin/sulbactam (58.8%) and clarithromycin (47.9%). Most of the antibiotics were classified as Watch (65.1%), followed by Access (32.6%) and Reserve (2.4%). Men (OR: 1.29; 95%CI: 1.17-1.43), older adults (OR: 1.67; 95%CI: 1.48-1.88), patients with dyspnea (OR: 1.26; 95%CI: 1.13-1.41), rheumatoid arthritis (OR: 1.94; 95%CI: 1.17-3.20), and high blood pressure at admission (OR: 1.45; 95%CI: 1.29-1.63), patients treated in-hospital (OR: 5.15; 95%CI: 4.59-5.77), patients admitted to the ICU (OR: 10.48; 95%CI: 8.82-12.45), patients treated with systemic glucocorticoids (OR: 3.60; 95%CI: 3.21-4.03) and vasopressors (OR: 2.10; 95%CI: 1.60-2.75), and patients who received invasive mechanical ventilation (OR: 2.37; 95%CI: 1.82-3.09) were more likely to receive a systemic antibiotic. Most of the patients diagnosed with COVID-19 received antibiotics, despite evidence showing that bacterial coinfection is rare. Antibiotics from the Watch group predominated, a practice that goes against WHO recommendations.

A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received

Vaccines have allowed for a significant decrease in COVID-19 risk, and new antiviral medications can prevent disease progression if given early in the course of the disease. The rapid and accurate estimation of the risk of severe disease in new patients is needed to prioritize the treatment of high-risk patients and maximize lives saved. We used electronic health records from 101,039 individuals infected with SARS-CoV-2, since the beginning of the pandemic and until 30 November 2021, in a national healthcare organization in Israel to build logistic models estimating the probability of subsequent hospitalization and death of newly infected patients based on a few major risk factors (age, sex, body mass index, hemoglobin A1C, kidney function, and the presence of hypertension, pulmonary disease, and malignancy) and the number of BNT162b2 mRNA vaccine doses received. The model’s performance was assessed by 10-fold cross-validation: the area under the curve was 0.889 for predicting hospitalization and 0.967 for predicting mortality. A total of 50%, 80%, and 90% of death events could be predicted with respective specificities of 98.6%, 95.2%, and 91.2%. These models enable the rapid identification of individuals at high risk for hospitalization and death when infected, and they can be used to prioritize patients to receive scarce medications or booster vaccination. The calculator is available online.

Prescription Patterns of Drugs Given to Hospitalized COVID-19 Patients: A Cross-Sectional Study in Colombia

The impact of COVID-19 prompted a race to find a treatment that would reduce its mortality. Most studies have not shown favorable results for many of these drugs, but they are still used. The aim as to determine the differences and similarities in the hospital pharmacological management of patients with COVID-19 according to sex, age group, and geographical region of Colombia, 2020–2021. Descriptive cross-sectional study was conducted on the prescription patterns of the medications given to patients diagnosed with COVID-19 treated in eight clinics in Colombia between 6 March 2020 and 31 May 2021. We performed a descriptive analysis of the sociodemographic, clinical, and pharmacological variables of the patients. A total of 8596 patients from 170 cities were identified, with a median age of 53.0 years and 53.3% of them men. A total of 24.3% required care in the intensive care unit, and 18.7% required invasive mechanical ventilation. The most commonly used drugs for the treatment of COVID-19 were systemic corticosteroids (63.6%), followed by colchicine (12.8%), azithromycin (8.9%), and ivermectin (6.4%). Corticosteroids, anticoagulants, colchicine, azithromycin, ivermectin, and hydroxychloroquine were prescribed more frequently in men, and their overall use increased with age. There were differences in prescriptions between geographic regions. The majority of patients were managed with medications included in the management guidelines. There were differences between sexes, age groups, and geographical regions.

Predicting COVID-19 severity using major risk factors and received vaccines

BACKGROUND

Vaccines are highly effective in preventing severe disease and death from COVID-19, and new medications that can reduce severity of disease have been approved. However, many countries are facing limited supply of vaccine doses and medications. A model estimating the probabilities for hospitalization and mortality according to individual risk factors and vaccine doses received could help prioritize vaccination and yet scarce medications to maximize lives saved and reduce the burden on hospitalization facilities.

METHODS

Electronic health records from 101,039 individuals infected with SARS-CoV-2, since the beginning of the pandemic and until November 30, 2021 were extracted from a national healthcare organization in Israel. Logistic regression models were built to estimate the risk for subsequent hospitalization and death based on the number of BNT162b2 mRNA vaccine doses received and few major risk factors (age, sex, body mass index, hemoglobin A1C, kidney function, and presence of hypertension, pulmonary disease and malignancy).

RESULTS

The models built predict the outcome of newly infected individuals with remarkable accuracy: area under the curve was 0.889 for predicting hospitalization, and 0.967 for predicting mortality. Even when a breakthrough infection occurs, having received three vaccination doses significantly reduces the risk of hospitalization by 66% (OR=0.339) and of death by 78% (OR=0.223).

CONCLUSIONS

The models enable rapid identification of individuals at high risk for hospitalization and death when infected. These patients can be prioritized to receive booster vaccination and the yet scarce medications. A calculator based on these models is made publicly available on http://covidest.web.app.