Risk factors for mortality in hospitalized patients with COVID-19 from three hospitals in Peru: a retrospective cohort study

Laboratory biomarkers associated with COVID-19 mortality among inpatients in a Peruvian referral hospital

Aim

To evaluate the biochemical and hematological markers associated with the risk of death due to COVID-19 in a clinical cohort with a severe clinical profile.

Methods

A retrospective study was conducted among 215 anonymized inpatient records from the Hospital Nacional Almanzor Aguinaga Asenjo, Peru, between April and June 2020. The association between biomarkers and death due to COVID-19 was assessed using Cox regression, with a multivariable modeling of 1) biochemical and 2) hematological markers. Kaplan-Meier analyses and time-dependent receiver operating characteristic curves were calculated for each associated biomarker (p < 0.05).

Results

Data analysis of 215 inpatient records revealed an overall mortality rate of 51.30% (95% CI 44.70-58.50), a mean age of 63.90 ± 14.10 years, and a median oxygen saturation of 88% (interquartile range 82-92%). The best-fitted biochemical model included higher levels of C-reactive protein (CRP), D-dimer, fibrinogen, urea, and lactate dehydrogenase. Similarly, the best-fitted hematological model included higher absolute neutrophil and prothrombin time, and lower absolute platelet counts. The best area under the curve values in both models were found to be CRP and D-dimer values (>0.74) and the absolute neutrophil count (0.63).

Conclusions

Some specific biochemical markers outperformed hematological markers. Evaluated hematological counts analyzed in multivariable models proved to be better markers and could be useful to discriminate COVID-19 patients at high risk of death.

Assessing medication use patterns by clinical outcomes severity among inpatients with COVID-19: A retrospective drug utilization study

PURPOSE

This study assessed medication patterns for inpatients at a central hospital in Portugal and explored their relationships with clinical outcomes in COVID-19 cases.

METHODS

A retrospective study analyzed inpatient medication data, coded using the Anatomical Therapeutic Chemical classification system, from electronic patient records. It investigated the association between medications and clinical severity outcomes such as ICU admissions, respiratory/circulatory support needs, and hospital discharge status, including mortality (identified by ICD-10-CM/PCS codes). Multivariate analyses incorporating demographic data and comorbidities were used to adjust for potential confounders and understand the impact of medication patterns on disease progression and outcomes.

RESULTS

The analysis of 2688 hospitalized COVID-19 patients (55.3% male, average age 62.8 years) revealed a significant correlation between medication types and intensity and disease severity. Cases requiring ICU admission or ECMO support often involved blood and blood-forming organ drugs. Increased use of nervous system and genitourinary hormones was observed in nonsurvivors. Corticosteroids, like dexamethasone, were common in critically ill patients, while tocilizumab was used in ECMO cases. Medications for the alimentary tract, metabolism, and cardiovascular system, although widely prescribed, were linked to more severe cases. Invasive mechanical ventilation correlated with higher usage of systemic anti-infectives and musculoskeletal medications. Trends in co-prescribing blood-forming drugs with those for acid-related disorders, analgesics, and antibacterials were associated with intensive interventions and worse outcomes.

CONCLUSIONS

The study highlights complex medication regimens in managing severe COVID-19, underscoring specific drug patterns associated with critical health outcomes. Further research is needed to explore these patterns.

Predictors of hospital length of stay and mortality among COVID-19 inpatients during 2020-2021 in Hormozgan Province of Iran: A retrospective cohort study

Background and Aims

About one-fifth of patients with COVID-19 need to be hospitalized. Predicting factors affecting the hospital length of stay (LOS) can be effective in prioritizing patients, planning for services, and preventing the increase in LOS and death of patients. The present study aimed to identify the factors that predict LOS and mortality in COVID-19 patients in a retrospective cohort study.

Methods

A total of 27,859 patients were admitted to 22 hospitals from February 20, 2020 to June 21, 2021. The data collected from 12,454 patients were screened according to the inclusion and exclusion criteria. The data were captured from the MCMC (Medical Care Monitoring Center) database. The study tracked patients until their hospital discharge or death. Hospital LOS and mortality were assessed as the study outcomes.

Results

As the results revealed, 50.8% of patients were male and 49.2% were female. The mean hospital LOS of the discharged patients was 4.94. Yet, 9.1% of the patients (n = 1133) died. Among the predictors of mortality and long hospital LOS were the age above 60, admission to the ICU, coughs, respiratory distress, intubation, oxygen level less than 93%, cigarette and drug abuse, and a history of chronic diseases. Masculinity, gastrointestinal symptoms, and cancer were the effective variables in mortality, and positive CT was a factor significantly affecting the hospital LOS.

Conclusion

Paying special attention to high-risk patients and modifiable risk factors such as heart disease, liver disease, and other chronic diseases can diminish the complications and mortality rate of COVID-19. Providing training, especially for those who care for patients experiencing respiratory distress such as nurses and operating room personnel can improve the qualifications and skills of medical staff. Also, ensuring the availability of sufficient supply of medical equipment is strongly recommended.

Depression and anxiety in peruvian military personnel during the pandemic context: a cross-sectional study

BACKGROUND

During the COVID-19 pandemic, increased workload and stress could have increased mental health problems (anxiety and depression) in military personnel. However, the number of studies in military members is scarce, especially in regard to mental health. The objective of this study was determine the prevalence and factors associated with depression and anxiety in Peruvian military personnel.

METHODS

We undertook an analytical cross-sectional study. The survey was distributed face to face between November 02 and 09, 2021, during the second wave of the COVID-19 pandemic among the military personnel. We used some instruments to measure depression (Patient Health Questionnaire, PHQ-9), anxiety (Generalized Anxiety Disorder, GAD-7), insomnia (Insomnia Severity Index, ISI), food insecurity (Household Food Insecurity Access Scale, HFIAS), physical activity (International Physical Activity Questionnaires, IPAQ-S), resilience (abbreviated CD-RISC), and fear of COVID-19 scale. The exclusion criteria included those who did not completely fill out the evaluation instruments.

RESULTS

We analyzed the data of 615 military personnel that participated in the survey. Of them, 93.7% were male and the median age was 22 years old. There was a prevalence of 29.9% and 22.0% in regard to depression and anxiety symptoms, respectively. In addition, it was found that being married (PR: 0.63; 95% IC: 0.42-0.94), having a relative with mental health problems (PR: 2.16), having experienced food insecurity (PR: 1.48), insomnia (PR: 2.71), fear of COVID-19 (PR: 1.48), and a high level of resilience (PR: 0.65) were factors associated with depression. In regard to anxiety, the factors associated were working for more than 18 months since the beginning of the COVID-19 pandemic (PR: 0.52), a high level of resilience (PR: 0.50; 95% IC: 0.33-0.77), insomnia (PR: 3.32), fear of COVID-19 (PR: 2.43).

CONCLUSION

We found a prevalence of symptoms of depression and anxiety of 29.9% and 22.0%, respectively. In regard to the factors that attenuate depression, we can mention being married and having resilience; and among the aggravating factors, having a relative with mental health problems, food insecurity, insomnia, and fear of COVID-19. Finally, anxiety increased through working time, insomnia, and fear of COVID-19.

Comorbidities associated with COVID-19 mortality in adults in Lima, Peru: a retrospective cohort study

OBJECTIVES.

Motivation for the study. During the COVID-19 pandemic, the mortality rate from this disease was higher in adults and the elderly. Therefore, it is important to identify the factors that were associated with mortality from COVID-19 in adults, by age group. Main findings. Chronic neurological disease, kidney disease, liver disease, and cancer increased the risk of dying from COVID-19 in the three age groups we analyzed, which were made up of hospitalized patients from Lima and Callao. The risk of mortality associated with comorbidities was higher in patients aged 18 to 29. Implications. This study helps to identify the groups of patients with the highest risk of death from COVID-19, according to age group and type of comorbidity. . To evaluate comorbidities associated with mortality in adult patients hospitalized due to COVID-19 in hospitals in Lima and Callao.

MATERIALS AND METHODS.

In this retrospective cohort study, we analyzed data from adult patients hospitalized due to COVID-19 reported to the National Epidemiological Surveillance System of the Peruvian Ministry of Health from March to October 2020. We estimated relative risks with 95% confidence intervals using Poisson regression models with robust variance to assess comorbidities associated with mortality by age group: young adults (18-29 years), adults (30-59 years) and older adults (≥60 years).

RESULTS.

We included 2366 young adults, 23,781 adults and 25,356 older adults. Older adults had the highest mortality (63.7%) compared to adults (27.1%) and young adults (8.5%). Regardless of age group, the presence of neurological disease, renal disease, liver disease, and cancer was associated with an increased risk of mortality. Additionally, cardiovascular disease was also a risk factor in young adults; obesity, diabetes, cardiovascular disease, chronic lung disease, and immunodeficiency in adults; and obesity and chronic lung disease in the elderly.

CONCLUSIONS.

Regardless of age groups, individuals with chronic neurologic disease, renal disease, liver disease, and cancer were at high risk of death from COVID-19.

Factors Associated with COVID-19 Death in a High-Altitude Peruvian Setting during the First 14 Months of the Pandemic: A Retrospective Multicenter Cohort Study in Hospitalized Patients

Risk factors for COVID-19 death in high-altitude populations have been scarcely described. This study aimed to describe risk factors for COVID-19 death in three referral hospitals located at 3399 m in Cusco, Peru, during the first 14 months of the pandemic. A retrospective multicenter cohort study was conducted. A random sample of ~50% (1225/2674) of adult hospitalized patients who died between 1 March 2020 and 30 June 2021 was identified. Of those, 977 individuals met the definition of death by COVID-19. Demographic characteristics, intensive care unit (ICU) admission, invasive respiratory support (IRS), disease severity, comorbidities, and clinical manifestation at hospital admission were assessed as risk factors using Cox proportional-hazard models. In multivariable models adjusted by age, sex, and pandemic periods, critical disease (vs. moderate) was associated with a greater risk of death (aHR: 1.27; 95%CI: 1.14–1.142), whereas ICU admission (aHR: 0.39; 95%CI: 0.27–0.56), IRS (aHR: 0.37; 95%CI: 0.26–0.54), the ratio of oxygen saturation (ROX) index ≥ 5.3 (aHR: 0.87; 95%CI: 0.80–0.94), and the ratio of SatO2/FiO2 ≥ 122.6 (aHR: 0.96; 95%CI: 0.93–0.98) were associated with a lower risk of death. The risk factors described here may be useful in assisting decision making and resource allocation.

Prevalence and Factors Associated with Eating Disorders in Military First Line of Defense against COVID-19: A Cross-Sectional Study during the Second Epidemic Wave in Peru

Few studies have evaluated eating disorders in military personnel engaged in defense activities during the COVID-19 pandemic. We aimed to determine the prevalence and factors associated with eating disorders in military personnel from Lambayeque, Peru. A secondary data analysis was performed among 510 military personnel during the second epidemic wave of COVID-19 in Peru. We used the Eating Attitudes Test (EAT-26) to assess eating disorders. We explored associations with insomnia, food insecurity, physical activity, resilience, fear to COVID-19, burnout syndrome, anxiety, depression, post-traumatic stress and selected sociodemographic variables. Eating disorders were experienced by 10.2% of participants. A higher prevalence of eating disorders was associated with having 7 to 12 months (PR: 2.97; 95% CI: 1.24-7.11) and 19 months or more (PR: 2.62; 95% CI: 1.11-6.17) working in the first line of defense against COVID-19, fear of COVID-19 (PR: 2.20; 95% CI: 1.26-3.85), burnout syndrome (PR: 3.73; 95% CI: 1.90-7.33) and post-traumatic stress (PR: 2.97; 95% CI: 1.13-7.83). A low prevalence of eating disorders was found in the military personnel. However, prevention of this problem should be focused on at-risk groups that experience mental health burdens.

Clinical Characteristics and Outcomes of COVID-19 Patients in Mazandaran Province, Iran

Background

The problem issue of coronaviruses is one of the most serious problems in the world. The present study aimed to investigate and describe the clinical characteristics, risk factors of fatality rate, and length of hospital stay in patients with COVID-19 in Mazandaran province.

Materials and Methods

In this epidemiological study, data from COVID-19 patients admitted to hospitals in Mazandaran province from July 22 to August 21, 2020, were reported. Multivariate logistic regression methods and the Cox proportional hazards model were used to determine the risk factors of fatality.

Results

Out of the 6759 hospitalized patients, 3111(46.03%) patients had comorbidity; 19.77% of them had diabetes, 19.97% had hypertension, and 15.28% had heart failure. Cox regression model on COVID-19 patient data showed that risk factors for fatality including having age over 60 years (HR: 1.93; P< 0.001), intubation (HR: 4.22; P<0.001), SpO2≤ 93% (HR: 2.57; P=0.006), comorbidities of cancer (HR: 1.87; P=0.006), chronic blood diseases (HR: 1.83; P=0.049), heart failure (HR: 1.63; P<0.001), and chronic kidney disease (HR: 1.98; P<0.001).

Conclusion

Paying much attention to risk factors for fatality can help identify patients with a poor prognosis in the early stages. More assessments should also be performed to examine the underlying mechanisms of these risk factors. Highlighting death-relate d risk factors is crucial to increase preparedness through appropriate medical care and prevention regulations.

Clinical-epidemiologic variation in patients treated in the first and second wave of COVID-19 in Lambayeque, Peru: A cluster analysis

OBJECTIVES

To identify differences in the clinical and epidemiologic characteristics of patients during the first and second waves of the COVID-19 pandemic at the EsSalud Lambayeque health care network, Peru.

METHODS

An analytical cross-sectional study of 53,912 patients enrolled during the first and second waves of COVID-19 was conducted. Cluster analysis based on clustering large applications (CLARA) was applied to clinical-epidemiologic data presented at the time of care. The two pandemic waves were compared using clinical-epidemiologic data from epidemiologic surveillance.

RESULTS

Cluster analysis identified four COVID-19 groups with a characteristic pattern. Cluster 1 included the largest number of participants in both waves, and the participants were predominantly female. Cluster 2 included patients with gastrointestinal, respiratory, and systemic symptoms. Cluster 3 was the "severe" cluster, characterized by older adults and patients with dyspnea or comorbidities (cardiovascular, diabetes, obesity). Cluster 4 included asymptomatic, pregnant, and less severe patients. We found differences in all clinical-epidemiologic characteristics according to the cluster to which they belonged.

CONCLUSION

Using cluster analysis, we identified characteristic patterns in each group. Respiratory, gastrointestinal, dyspnea, anosmia, and ageusia symptoms were higher in the second COVID-19 wave than the first COVID-19 wave.

A systematic review and meta-analysis of the association between the neutrophil, lymphocyte, and platelet count, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio and COVID-19 progression and mortality

BACKGROUND AND AIMS

Severe manifestations of coronavirus disease 2019 (COVID-19) are associated with alterations in blood cells that regulate immunity, inflammation, and hemostasis. We conducted an updated systematic review and meta-analysis of the association between the neutrophil, lymphocyte, and platelet count, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), and COVID-19 progression and mortality.

METHODS

A systematic literature search was conducted in PubMed, Web of Science, and Scopus for studies published between January 2020 and June 2022.

RESULTS

In 71 studies reporting the investigated parameters within 48 hours of admission, higher NLR (HR 1.21, 95% CI 1.16 to 1.27, p < 0.0001), relative neutrophilia (HR 1.62, 95% CI 1.46 to 1.80, p < 0.0001), relative lymphopenia (HR 1.62, 95% CI 1.27 to 2.08, p < 0.001), and relative thrombocytopenia (HR 1.74, 95% CI 1.36 to 2.22, p < 0.001), but not PLR (p = 0.11), were significantly associated with disease progression and mortality. Between-study heterogeneity was large-to-extreme. The magnitude and direction of the effect size were not modified in sensitivity analysis.

CONCLUSIONS

NLR and neutrophil, lymphocyte, and platelet count significantly discriminate COVID-19 patients with different progression and survival outcomes. (PROSPERO registration number: CRD42021267875).

The Neutrophil-to-Lymphocyte Ratio and the Platelet-to-Lymphocyte Ratio as Predictors of Mortality in Older Adults Hospitalized with COVID-19 in Peru

Background

The prognostic value of the neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) in patients with COVID-19 is rarely described in older adults. We aimed to estimate the prognostic value of NLR and PLR, determining the mortality of adults over 60 years of age hospitalized for COVID-19 in three hospitals in Peru from March to May 2020.

Methods

We performed a secondary analysis of data from a retrospective cohort carried out in Lambayeque, Peru, from March 18 to May 13, 2020. Older adults hospitalized for COVID-19 were included. The outcome variable was in-hospital mortality by all causes, while the exposure variable was the NLR and PLR (categorized in tertiles and numerically, performing a logarithmic transformation). We included sociodemographic variables, comorbidities, vital functions, laboratory markers, and treatment received during hospital stay. We evaluated the association between NLR and PLR using the hazard ratio (HR) in a Cox regression model. We estimated HR with their respective 95% confidence intervals (95% CI). We estimated cumulative/dynamic time-dependent ROC curves and reported area under the curve ROC (AUC-ROC) for 15-, 30-, and 60-day mortality with their respective simultaneous confidence intervals (confidence bands (CB)). Also, we estimated an optimal cut-off point based on the maximally selected rank statistics.

Results

A total of 262 hospitalized older adults were analyzed, 71.8% (n = 188) of whom were male with a median age of 70 years (interquartile range: 65-78). The mean NLR and PLR were 16.8 (95% CI: 14.9-18.7; SD: 15.5) and 50.3 (95% CI: 44.6-55.9; SD: 46.3), respectively. The mortality rate was 68.7% (95% CI: 62.7-74.3). The adjusted Cox regression analysis showed that the high NLR (adjusted HR (aHR) = 2.12; 95% CI: 1.43-3.14) and PLR (aHR = 1.90; 95% CI: 1.30-2.79) tertiles were associated with a higher risk of mortality. The maximum AUC-ROC values at 60 days of follow-up for NLR and PLR were 0.713 (95%CB: 0.627-0.800) and 0.697 (95%CB: 0.583-0.754), respectively.

Conclusions

The NLR and PLR are predictors of higher risk of mortality, and these results suggest that both could be reliable and practical markers for the identification of older adults at high risk of mortality by COVID-19. NLR and PLR have prognostic value, with an AUC greater than 0.5; however, by themselves, they are weak prognostic markers. It is important to carry out future studies incorporating these two markers into preexisting models or designing new ones considering them.

Developing a Comprehensive Multidimensional Wellbeing Index Based on What People Value: An Application to a Middle-Income Country

We introduce a comprehensive policy-relevant measure of multidimensional wellbeing conceptually rooted in Amartya Sen's capability approach and applied to a middle-income country: the Multidimensional Wellbeing Index for Peru (MWI-P). We design and collect a specialized survey in Peru in late 2018, which included data on wellbeing achievements across 12 dimensions, on the value that respondents place upon each of these dimensions, and on self-perceived freedom. Then, we utilize this information to set the weighting structure and select a wellbeing sufficiency threshold for the MWI-P, which we estimate using the capability-inspired Alkire-Foster method. Our results show that only 45.9% of the sample population live above the wellbeing threshold, which involves achieving sufficiency in at least seven out of the 12 weighted dimensions of the MWI-P. Subgroup analyses reveal that rural populations, women, and older adults are at a disadvantage compared with urban populations, men, and younger adults, respectively. These subgroups' disparities hold valid if we introduce changes in the weighting structure or in the wellbeing sufficiency threshold. We argue that the MWI-P can inspire other low- and middle-income countries to reorient post-pandemic recovery policies from a focus on economic growth to a human flourishing approach based on what people value.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11482-022-10064-w.

Analysis of Excess All-Cause Mortality and COVID-19 Mortality in Peru: Observational Study

During the COVID-19 pandemic, an excess of all-cause mortality has been recorded in several countries, including Peru. Most excess deaths were likely attributable to COVID-19. In this study, we compared the excess all-cause mortality and COVID-19 mortality in 25 Peruvian regions to determine whether most of the excess deaths in 2020 were attributable to COVID-19. Excess deaths were calculated as the difference between the number of observed deaths from all causes during the COVID-19 pandemic (in 2020) and the number of expected deaths in 2020 based on a historical from recent years (2017–2019). Death data were retrieved from the Sistema Informatico Nacional de Defunciones (SINADEF) at the Ministry of Health of Peru from January 2017 to December 2020. Population counts were obtained from projections from Peru’s Instituto Nacional de Estadística e Informática (INEI). All-cause excess mortality and COVID-19 mortality were calculated by region per 100,000 population. Spearman’s test and linear and multiple regression models were used to estimate the correlation between excess all-cause mortality and COVID-19 mortality per 100,000 population. Excess all-cause death rates varied widely among regions (range: 115.1 to 519.8 per 100,000 population), and COVID-19 mortality ranged between 83.8 and 464.6 per 100,000 population. There was a correlation between the all-cause excess mortality and COVID-19 mortality (r = 0.90; p = 0.00001; y = 0.8729x + 90.808; R² = 0.84). Adjusted for confounding factors (mean age in the region, gender balance, and number of intensive care unit (ICU) beds), the all-cause excess mortality rate was correlated with COVID-19 mortality rate (β = 0.921; p = 0.0001). These findings suggest that most of the excess deaths in Peru are related to COVID-19. Therefore, these findings can help decision-makers to understand the high COVID-19 mortality rates in Peru.

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.

Mortality and associated risk factors in patients hospitalized due to COVID-19 in a Peruvian reference hospital

OBJECTIVES

To determine the risk factors for in-hospital mortality in patients with COVID-19 from a Peruvian national hospital.

METHODS

Retrospective cohort study of medical records of patients with COVID-19 hospitalized at Hospital Nacional Hipólito Unanue (HNHU) during the months of April to August 2020. The dependent variable was in-hospital mortality. Independent variables included sociodemographic and clinical characteristics, physical examination findings, oxygen saturation (SaO2) at admission, treatment received during hospitalization and laboratory results at admission. A Cox regression model was used to evaluate the crude and adjusted hazard ratios for associated factors.

RESULTS

We included 1418 patients. Median age was 58 years (IQR 47-68 years) and 944 (66.6%) were male. The median length of hospitalization was 7 (4-13) days, and the mortality rate was 46%. The most frequent comorbidities were type 2 diabetes mellitus, hypertension, and obesity. In the adjusted analysis, mortality was associated with age (HR 1.02; 95%CI 1.02-1.03), history of surgery (HR 1.89; 95%CI 1.31-2.74), lower oxygen saturation at admission (HR 4.08; CI95% 2.72-8.05 for SaO2<70% compared to SaO2>94%), the presence of poor general condition (HR 1.81; 95% CI 1.29-2.53), altered state of consciousness (HR 1.58; 95%CI 1.18-2.11) and leukocyte levels (HR 1.01; 95%CI 1.00-1. 02). Treatment with ivermectin (HR 1.44; 95%CI 1.18-1.76) and azithromycin (HR 1.25; 95%CI 1.03-1.52) were associated with higher mortality. Treatment with corticosteroids at low to moderate doses was associated with lower mortality (HR 0.56 95%CI 0. 37-0. 86) in comparison to no steroid use.

CONCLUSION

A high mortality was found in our cohort. Low oxygen saturation at admission, age, and the presence of hematological and biochemical alterations were associated with higher mortality. The use of hydroxychloroquine, ivermectin or azithromycin was not useful and was probably associated with unfavorable outcomes. The use of corticosteroids at moderate doses was associated with lower mortality.

Predictors of Mortality Among Hospitalized COVID-19 Patients at a Tertiary Care Hospital in Ethiopia

BACKGROUND

The very unprecedented virus causing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued causing catastrophes in economy and loss of human lives. Despite countries' urgent and resilient public health actions against the COVID-19 pandemic, the disease is causing a large number of deaths. However, predictors of mortality among hospitalized COVID-19 patients have not been well investigated in Ethiopia. Therefore, this study aimed to identify the predictors of mortality among hospitalized COVID-19 patients at a tertiary care hospital in Ethiopia.

METHODS

A hospital-based retrospective cohort design study was implemented among hospitalized COVID-19 patients at a tertiary care hospital in Harar, Ethiopia from March 20 to August 20, 2021. Data of 531 admitted patients were entered using Epi-data 3.1 and exported to STATA 14.2 for analysis. Binary logistic regression was used to identify significant predictors of outcome variables with an adjusted odds ratio (AOR) with a 95% confidence interval.

RESULTS

Of the total 531 study participants, 101 deaths occurred. The mortality rate was 16.2 per 1000 person-days of observation with median survival time of 44 days with IQR [28, 74]. Smoking history [AOR=2.55, 95% CI (1.15, 5.65)], alcohol history [AOR=2.3, 95% CI (1.06, 4.97)], comorbidities [AOR=2.95, 95% CI (1.26, 6.91)], and increasing oxygen saturation [AOR=0.92, 95% CI (0.89, 0.95)], and lymphocyte count [AOR=0.90, 95% CI (0.88, 0.97)] were independent significant predictors of death from Covid-19.

CONCLUSION

The incidence of mortality among hospitalized COVID-19 patients was found to be high. Devising individual, tailored management for patients with "risk" behaviors, comorbid conditions, and poor prognostic markers such as lymphopenia and low oxygen saturation, may reduce the incidence of death among hospitalized COVID-19 patients.

Antibiotic Use and Fatal Outcomes among Critically Ill Patients with COVID-19 in Tacna, Peru

Overuse of antibiotics during the Coronavirus Disease 2019 (COVID-19) pandemic could increase the selection of extensively resistant bacteria (XDR). However, it is unknown what impact they could have on the evolution of patients, particularly critically ill patients. This study aimed to evaluate the characteristics and impact of ICU-acquired infections in patients with COVID-19. A retrospective cohort study was conducted, evaluating all patients with critical COVID-19 admitted to the intensive care unit (ICU) of a hospital in Southern Peru from 28 March 2020 to 1 March 2021. Of the 124 patients evaluated, 50 (40.32%) developed a healthcare-associated infection (HAI), which occurred at a median of 8 days (IQR 6-17) after ICU admission. The proportion of patients with HAI that required ceftriaxone was significantly higher; the same was true for the use of dexamethasone. Forty bacteria isolations (80%) were classified as XDR to antibiotics, with the most common organisms being Acinetobacter baumannii (54%) and Pseudomonas aeruginosa (22%); 33% (41/124) died at the ICU during the follow-up. In the adjusted analysis, healthcare-associated infection was associated with an increased risk of mortality (aHR= 2.7; 95% CI: 1.33-5.60) and of developing acute renal failure (aRR = 3.1; 95% CI: 1.42-6.72). The incidence of healthcare infection mainly by XDR pathogens is high in critically ill patients with COVID-19 and is associated with an increased risk of complications or death.