Evaluating the factors affecting clinical outcomes in critically ill COVID-19 unvaccinated patients admitted to the intensive care unit in a lower-middle-income country

Background

COVID-19, the most destructive pandemic of this century, caused the highest mortality rate among ICU patients. The evaluation of these patients is insufficient in lower-middle-income countries with limited resources during pandemics. As a result, our primary goal was to examine the characteristics of patients at baseline as well as their survival outcomes, and propose mortality predictors for identifying and managing the most vulnerable patients more effectively and quickly.

Methods

A prospective analysis of COVID-19 ICU-admitted patients was conducted in our healthcare centre in Iran, from 1 April until 20 May 2020. Ninety-three patients were included in the study, and all were unvaccinated. A multi-variate logistic regression was conducted to evaluate mortality-associated factors.

Results

There were 53 non-survivors among our ICU-admitted patients. The mean duration from symptoms' onset to hospitalization was 6.92 ± 4.27 days, and from hospitalization to ICU admission was 2.52 ± 3.61 days. The average hospital stay for patients was 13.23 ± 10.43 days, with 8.84 ± 7.53 days in the ICU. Non-survivors were significantly older, had significantly lower haemoglobin levels and higher creatine phosphokinase levels compared to survivors. They had marginally lower SpO2 levels at admission, higher vasopressor administrations, and were intubated more significantly during their ICU stay. The use of immunosuppressive drugs was also significantly higher in non-survivors. Logistic regression revealed that a one-point increase in APACHE II score at ICU admission increased mortality by 6%, and the presence of underlying diseases increased mortality by 4.27 times.

Conclusion

The authors presented clinical mortality prediction factors for critically ill patients infected with COVID-19. Additional studies are necessary to identify more generalized mortality indicators for these patients in lower-middle-income countries.

Predictors of shorter- and longer-term mortality after COVID-19 presentation among dialysis patients: parallel use of machine learning models in Latin and North American countries

Background

We developed machine learning models to understand the predictors of shorter-, intermediate-, and longer-term mortality among hemodialysis (HD) patients affected by COVID-19 in four countries in the Americas.

Methods

We used data from adult HD patients treated at regional institutions of a global provider in Latin America (LatAm) and North America who contracted COVID-19 in 2020 before SARS-CoV-2 vaccines were available. Using 93 commonly captured variables, we developed machine learning models that predicted the likelihood of death overall, as well as during 0–14, 15–30, > 30 days after COVID-19 presentation and identified the importance of predictors. XGBoost models were built in parallel using the same programming with a 60%:20%:20% random split for training, validation, & testing data for the datasets from LatAm (Argentina, Columbia, Ecuador) and North America (United States) countries.

Results

Among HD patients with COVID-19, 28.8% (1,001/3,473) died in LatAm and 20.5% (4,426/21,624) died in North America. Mortality occurred earlier in LatAm versus North America; 15.0% and 7.3% of patients died within 0–14 days, 7.9% and 4.6% of patients died within 15–30 days, and 5.9% and 8.6% of patients died > 30 days after COVID-19 presentation, respectively. Area under curve ranged from 0.73 to 0.83 across prediction models in both regions. Top predictors of death after COVID-19 consistently included older age, longer vintage, markers of poor nutrition and more inflammation in both regions at all timepoints. Unique patient attributes (higher BMI, male sex) were top predictors of mortality during 0–14 and 15–30 days after COVID-19, yet not mortality > 30 days after presentation.

Conclusions

Findings showed distinct profiles of mortality in COVID-19 in LatAm and North America throughout 2020. Mortality rate was higher within 0–14 and 15–30 days after COVID-19 in LatAm, while mortality rate was higher in North America > 30 days after presentation. Nonetheless, a remarkable proportion of HD patients died > 30 days after COVID-19 presentation in both regions. We were able to develop a series of suitable prognostic prediction models and establish the top predictors of death in COVID-19 during shorter-, intermediate-, and longer-term follow up periods.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-022-02961-x.

Mortality Attributable to Long-Term Exposure to Ambient Fine Particulate Matter: Insights from the Epidemiologic Evidence for Understudied Locations

Epidemiologic cohort studies have consistently demonstrated that long-term exposure to ambient fine particles (PM_2.5) is associated with mortality. Nevertheless, extrapolating results to understudied locations may involve considerable uncertainty. To explore this issue, this review discusses the evidence for (i) the associated risk of mortality, (ii) the shape of the concentration-response function, (iii) a causal interpretation, and (iv) how the source mix/composition of PM_2.5 and population characteristics may alter the effect. The accumulated evidence suggests the following: (i) In the United States, the change in all-cause mortality risk per μg/m³ is about 0.8%. (ii) The concentration-response function appears nonlinear. (iii) Causation is overwhelmingly supported. (iv) Fossil fuel combustion-related sources are likely more toxic than others, and age, race, and income may modify the effect. To illustrate the use of our findings in support of a risk assessment in an understudied setting, we consider Kuwait. However, given the complexity of this relationship and the heterogeneity in reported effects, it is unreasonable to think that, in such circumstances, point estimates can be meaningful. Consequently, quantitative probabilistic estimates, which cannot be derived objectively, become essential. Formally elicited expert judgment can provide such estimates, and this review provides the evidence to support an elicitation.

The Correlation of Comorbidities on the Mortality in Patients with COVID-19: an Observational Study Based on the Korean National Health Insurance Big Data

BACKGROUND

Mortality of coronavirus disease 2019 (COVID-19) is a major concern for quarantine departments in all countries. This is because the mortality of infectious diseases determines the basic policy stance of measures to prevent infectious diseases. Early screening of high-risk groups and taking action are the basics of disease management. This study examined the correlation of comorbidities on the mortality of patients with COVID-19.

METHODS

We constructed epidemiologic characteristics and medical history database based on the Korean National Health Insurance Service Big Data and linked COVID-19 registry data of Korea Centers for Disease Control & Prevention (KCDC) for this emergent observational cohort study. A total of 9,148 patients with confirmed COVID-19 were included. Mortalities by sex, age, district, income level and all range of comorbidities classified by International Classification of Diseases-10 based 298 categories were estimated.

RESULTS

There were 3,556 male confirmed cases, 67 deaths, and crude death rate (CDR) of 1.88%. There were 5,592 females, 63 deaths, and CDR of 1.13%. The most confirmed cases were 1,352 patients between the ages of 20 to 24, followed by 25 to 29. As a result of multivariate logistic regression analysis that adjusted epidemiologic factors to view the risk of death, the odds ratio of death would be hemorrhagic conditions and other diseases of blood and blood-forming organs 3.88-fold (95% confidence interval [CI], 1.52-9.88), heart failure 3.17-fold (95% CI, 1.88-5.34), renal failure 3.07-fold (95% CI, 1.43-6.61), prostate malignant neoplasm 2.88-fold (95% CI, 1.01-8.22), acute myocardial infarction 2.38-fold (95% CI, 1.03-5.49), diabetes was 1.82-fold (95% CI, 1.25-2.67), and other ischemic heart disease 1.71-fold (95% CI, 1.09-2.66).

CONCLUSION

We hope that this study could provide information on high risk groups for preemptive interventions. In the future, if a vaccine for COVID-19 is developed, it is expected that this study will be the basic data for recommending immunization by selecting those with chronic disease that had high risk of death, as recommended target diseases for vaccination.

The Influence of Negative Mental Health on the Health Behavior and the Mortality Risk: Analysis of Korean Longitudinal Study of Aging from 2006 to 2014

Background

Several studies have shown that negative mental health increases risky health behavior and mortality risk. We investigated the relationship between mental health and health behavior, and the causal association between mental health and mortality risk.

Methods

We used data from the 8-year (2006–2014) Korean Longitudinal Study of Aging with a cohort of 10,247 individuals (whom we divided into a younger group aged <65 years and an older group aged ≥65 years). Mental health was assessed with the following factors: depression, social engagement, and satisfaction of life. Health behavior was assessed with smoking, alcohol use, and regular exercise. Mortality risk was calculated using survival status and survival months as of 2014. Multiple logistic regression and Cox proportional hazard analysis were performed.

Results

Negative mental health was associated with current smoking and sedentary life style, but not with alcohol consumption. In addition, it was associated with an increase in all-cause mortality risk. The increase in mortality risk in the highest quartile (vs. lowest) was 1.71 times (hazard ratio [HR], 1.71; 95% confidence interval [CI], 1.12– 2.62) and 2.07 times (HR, 2.07; 95% CI, 1.60–2.67) for the younger and older group, respectively.

Conclusion

Our results show that mental health affects health behavior and mortality risk. A key inference from this study is that improving mental health can lead to positive changes in health behavior and reduce the risk of mortality.

Increased Mortality After Prosthetic Joint Infection in Primary THA

BACKGROUND

Revision for prosthetic joint infection (PJI) has a major effect on patients' health but it remains unclear if early PJI after primary THA is associated with a high mortality.

QUESTIONS/PURPOSES

(1) Do patients with a revision for PJI within 1 year of primary THA have increased mortality compared with patients who do not undergo revision for any reason within 1 year of primary THA? (2) Do patients who undergo a revision for PJI within 1 year of primary THA have an increased mortality risk compared with patients who undergo an aseptic revision? (3) Are there particular bacteria among patients with PJI that are associated with an increased risk of death?

METHODS

This population-based cohort study was based on the longitudinally maintained Danish Hip Arthroplasty Register on primary THA performed in Denmark from 2005 to 2014. Data from the Danish Hip Arthroplasty Register were linked to microbiology databases, the National Register of Patients, and the Civil Registration System to obtain data on microbiology, comorbidity, and vital status on all patients. Because reporting to the register is compulsory for all public and private hospitals in Denmark, the completeness of registration is 98% for primary THA and 92% for revisions (2016 annual report). The mortality risk for the patients who underwent revision for PJI within 1 year from implantation of primary THA was compared with (1) the mortality risk for patients who did not undergo revision for any reason within 1 year of primary THA; and (2) the mortality risk for patients who underwent an aseptic revision. A total of 68,504 primary THAs in 59,954 patients were identified, of those 445 primary THAs underwent revision for PJI, 1350 primary THAs underwent revision for other causes and the remaining 66,709 primary THAs did not undergo revision. Patients were followed from implantation of primary THA until death or 1 year of followup, or, in case of a revision, 1 year from the date of revision.

RESULTS

Within 1 year of primary THA, 8% (95% CI, 6%-11%) of patients who underwent revision for PJI died. The adjusted relative mortality risk for patients with revision for PJI was 2.18 (95% CI, 1.54-3.08) compared with the patients who did not undergo revision for any cause (p < 0.001). The adjusted relative mortality risk for patients with revisions for PJI compared with patients with aseptic revision was 1.87 (95% CI, 1.11-3.15; p = 0.019). Patients with enterococci-infected THA had a 3.10 (95% CI, 1.66-5.81) higher mortality risk than patients infected with other bacteria (p < 0.001).

CONCLUSIONS

Revision for PJI within 1 year after primary THA induces an increased mortality risk during the first year after the revision surgery. This study should incentivize further studies on prevention of PJI and on risk to patients with the perspective to reduce mortality in patients who have had THA in general and for patients with PJI specifically.

LEVEL OF EVIDENCE

Level III, therapeutic study.