Association of Interleukin-32 and Interleukin-34 with Cardiovascular Disease and Short-Term Mortality in COVID-19.

BACKGROUND: Excess cardiovascular (CV) morbidity and mortality has been observed in patients with COVID-19. Both interleukin-32 (IL-32) and interleukin-34 (IL-34) have been hypothesized to contribute to CV involvement in COVID-19. METHODS: This prospective, observational study of patients with laboratory-confirmed COVID-19 infection was conducted from 6 June to 22 December 2020 in a tertiary care hospital in Vienna, Austria. IL-32 and IL-34 levels on admission were collected and tested for their association with CV disease and short-term mortality in patients with COVID-19. CV disease was defined by the presence of coronary artery disease, heart failure, stroke or atrial fibrillation and patients were stratified by CV disease burden. RESULTS: A total of 245 eligible patients with COVID-19 were included, of whom 37 (15.1%) reached the primary endpoint of 28-day mortality. Of the total sample, 161 had no CV disease (65.7%), 69 had one or two CV diseases (28.2%) and 15 patients had ≥three CV diseases (6.1%). Median levels of IL-32 and IL-34 at admission were comparable across the three groups of CV disease burden. IL-32 and IL-34 failed to predict mortality upon both univariable and multivariable Cox regression analysis. The two CV disease groups, however, had a significantly higher risk of mortality within 28 days (one or two CV diseases: crude HR 4.085 (95% CI, 1.913-8.725), p < 0.001 and ≥three CV diseases: crude HR 13.173 (95% CI, 5.425-31.985), p < 0.001). This association persisted for those with ≥three CV diseases after adjustment for age, gender and CV risk factors (adjusted HR 3.942 (95% CI, 1.288-12.068), p = 0.016). CONCLUSION: In our study population of hospitalized patients with COVID-19, IL-32 and IL-34 did not show any associations with CV disease or 28-day mortality in the context of COVID-19. Patients with multiple CV diseases, however, had a significantly increased risk of short-term mortality.

The Value of Early and Follow-Up Elevated Scores Based on Peripheral Complete Blood Cell Count for Predicting Adverse Outcomes in COVID-19 Patients.

Background: The ongoing COVID-19 pandemic has put a constant strain on hospital resources, so there is a dire need for investigation methods that are widely available and that can predict mortality and the need for critical care. Hematological indices, which can be easily calculated from a complete blood count (CBC), are useful in determining a patient's inflammatory response to infectious diseases. Aim: This was a prospective cohort study that aimed to assess the prognostic value of scores based on CBCs in hospitalized patients with mild or moderate COVID-19 and medical comorbidities regarding the need for intensive care unit (ICU) therapy and short-term mortality. Methods: We included 607 patients with confirmed COVID-19, followed up for the need for ICU admission (15.5%) and 30 day mortality post-discharge (21.7%). CBC-derived scores were tested upon emergency department (ED) admission and after a median of 8 days. Results: In a multivariate model, elevated followed-up neutrophil-to-lymphocyte ratio (NLR) predicted increased odds for ICU admission (OR: 1.14 [95%CI: 1.06−1.22], p < 0.001) and short-term mortality (OR: 1.30 [95%CI: 1.09−1.57], p = 0.005). Monocyte-to-lymphocyte ratio (MLR) predicted 2.5-fold increased odds for ICU admission and 2.2-fold increased odds for mortality. Conclusion: NLR and MLR followed up 8 days post-admission are predictive for adverse outcomes in mild or moderate COVID-19 patients.

The Effect of COVID-19 on 30-Day Mortality Rates Amongst Fragility Hip Fracture Patients.

Aim Fragility hip fracture patients have always been vulnerable to high rates of short term mortality, an issue that may have been exacerbated by the ongoing COVID-19 pandemic. To date, published data regarding Irish hip fracture patients in the era of COVID-19 is limited. This study aims to assess the effect of COVID-19 on 30-day mortality rates amongst a group of Irish hip fracture patients. Additionally, patient demographics, length of stay, admission haematological parameters, fracture type and surgical procedure will be assessed. Methods A multicentre, observational, retrospective study of hip fracture patients (n = 1,017) admitted to six Dublin teaching hospitals during the COVID-19 pandemic (4th February to 9th July 2020) was performed. For comparative purposes, equivalent data was retrospectively collected relating to hip fracture patients admitted to the same six teaching hospitals during the same time period in 2019. Results 481 patients were admitted during the specified timeframe in 2020, compared with 536 in 2019. The mean patient age was 77.6 years and 65.9% of patients were female. There was no statistically significant overall difference in 30-day mortality rates between the study and control groups, at 5.4% in 2020 and 4.3% in 2019 (p=0.338). There was an insignificant decrease in mean length of stay (17.85 days in 2020 vs. 18.82 days in 2019; p=0.106). Advancing age (p=0.021), male gender (p=0.019), low admission haemoglobin (p=0.024) and high admission white cell count (p=0.019) were all associated with increased 30-day mortality. Conclusion We found no significant difference in 30-day mortality rates amongst our cohort of hip fracture patients at the height of the COVID-19 pandemic in Ireland. Advancing age, male gender, anaemia at admission and leucocytosis at admission were associated with increased 30-day mortality. The continuation of COVID-19 related safety protocols in the treatment of hip fracture patients is essential in maintaining a safe hip fracture service.

Comparison of geriatric nutritional risk index and creatinine index in short-term mortality prediction in maintenance hemodialysis patients.

BACKGROUND: The aim of this study is to analyze and compare the predictive values of the Geriatric Nutritional Risk Index (GNRI) and Creatinine Index (CI) in the short-term mortality of maintenance hemodialysis patients and to determine their best cut-offs. METHODS: A total of 169 adult hemodialysis patients were included in this retrospective, cross-sectional, and single-center study. The demographic, clinical, and laboratory data of the month in which the patients were included in the study were obtained from their medical files and computer records. All-cause death was the primary outcome of the study during a 12-month follow-up after baseline GNRI and CI calculations. RESULTS: The mean age of the study population was 57 ± 16 years (49.7% were women, 15% were diabetic). During the one-year observation period, 19 (11.24%) of the cases died (8 CV deaths). The optimal cut-off value for GNRI was determined as 104.2 by ROC analysis [AUC = 0.682 ± 0.06, (95% CI, 0.549-0.815), p = 0.01]. The low GNRI group had a higher risk for all-cause and CV mortality compared to the higher GNRI group (p = 0.02 for both in log-rank test). The optimal sex-specific cut-off was 12.18 mg/kg/day for men [AUC = 0.723 ± 0.07, (95% CI, 0.574-0.875), p = 0.03] and was 12.08 mg/kg/day for females [AUC = 0.649 ± 0.13, (95% CI, 0.384- 0.914), p = 0.01]. Patients with lower sex-specific CI values had higher all-cause and CV mortality (p = 0.001 and p = 0.009 in log-rank test, respectively). In multivariate cox models, both GNRI [HR = 4.904 (% 95 CI, 1.77-13.56), p = 0.002] and sex-specific CI [HR = 5.1 (95% CI, 1.38-18.9), p = 0.01] predicted all-cause mortality. The association of GNRI with CV was lost [HR = 2.6 (CI 95%, 0.54-13.455), p = 0.22], but low CI had a very strong association with CV mortality [HR = 11.48 (CI 95%, 1.25 -104), p = 0.03]. DISCUSSION: In hemodialysis patients, GNRI and CI have similar powers in predicting all-cause short-term mortality. The association of CI with all-cause death depends on gender. On the other hand, sex-specific CI predicts CV mortality better than GNRI.

Myocardial Injury Predicts Risk of Short-Term All-Cause Mortality in Patients With COVID-19: A Dose-Response Meta-Analysis.

Objective: Predictive value of myocardial injury as defined by elevated cardiac tropnins (cTns) in patients with COVID-19 has not been fully investigated. We performed a meta-analysis to evaluate the dose-response relationship between myocardial injury and short-term all-cause mortality. Methods: Pubmed, Embase, and the Cochrane Library database were searched for all the studies which evaluated the relationship between cTns and the risk of short-term all-cause mortality in patients with COVID-19. Results: Compared with patients without myocardial injury, the group with elevated cTns was associated with increased short-term mortality (11 studies, 29,128 subjects, OR 3.17, 95% CI 2.19-4.59, P = 0.000, I 2 = 92.4%, P for heterogeneity 0.00). For the dose-response analysis, the elevation of cTns 1 × 99th percentile upper reference limit (URL) was associated with increased short-term mortality (OR 1.99, 95% CI 1.53-2.58, P = 0.000). The pooled OR of short-term mortality for each 1 × URL increment of cTns was 1.25 (95% CI 1.22-1.28, P = 0.000). Conclusion: We found a positive dose-response relationship between myocardial injury and the risk of short-term all-cause mortality, and propose elevation of cTns > 1 × 99th percentile URL was associated with the increased short-term risk of mortality.

What should be the baseline when calculating excess mortality? New approaches suggest that we have underestimated the impact of the COVID-19 pandemic and previous winter peaks.

Excess mortality has been used to measure the impact of COVID-19 over time and across countries. But what baseline should be chosen? We propose two novel approaches: an alternative retrospective baseline derived from the lowest weekly death rates achieved in previous years and a within-year baseline based on the average of the 13 lowest weekly death rates within the same year. These baselines express normative levels of the lowest feasible target death rates. The excess death rates calculated from these baselines are not distorted by past mortality peaks and do not treat non-pandemic winter mortality excesses as inevitable. We obtained weekly series for 35 industrialized countries from the Human Mortality Database for 2000-2020. Observed, baseline and excess mortalities were measured by age-standardized death rates. We assessed weekly and annual excess death rates driven by the COVID-19 pandemic in 2020 and those related to seasonal respiratory infections in earlier years. There was a distinct geographic pattern with high excess death rates in Eastern Europe followed by parts of the UK, and countries of Southern and Western Europe. Some Asia-Pacific and Scandinavian countries experienced lower excess mortality. In 2020 and earlier years, the alternative retrospective and the within-year excess mortality figures were higher than estimates based on conventional metrics. While the latter were typically negative or close to zero in years without extraordinary epidemics, the alternative estimates were substantial. Cumulation of this "usual" excess over 2-3 years results in human losses comparable to those caused by COVID-19. Challenging the view that non-pandemic seasonal winter mortality is inevitable would focus attention on reducing premature mortality in many countries. As SARS-CoV-2 is unlikely to be the last respiratory pathogen with the potential to cause a pandemic, such measures would also strengthen global resilience in the face of similar threats in the future.

Red Cell Distribution Width Upon Hospital Admission Predicts Short-Term Mortality in Hospitalized Patients With COVID-19: A Single-Center Experience.

Background: Coronavirus disease (COVID-19) was first described at the end of 2019 in China and has since spread across the globe. Red cell distribution width (RDW) is a potent prognostic marker in several medical conditions and has recently been suggested to be of prognostic value in COVID-19. Methods: This retrospective, observational study of consecutive patients with COVID-19 was conducted from March 12, 2020 to December 4, 2020 in the Wilhelminenhospital, Vienna, Austria. RDWlevels on admission were collected and tested for their predictive value of 28-day mortality. Results: A total of 423 eligible patients with COVID-19 were included in the final analyses and 15.4% died within 28 days (n = 65). Median levels of RDWwere significantly higher in non-survivors compared to survivors [14.6% (IQR, 13.7-16.3) vs. 13.4% (IQR, 12.7- 14.4), P < 0.001]. Increased RDW was a significant predictor of 28-day mortality [crude odds ratio (OR) 1.717, 95% confidence interval (CI) 1.462-2.017; P = < 0.001], independent of clinical confounders, comorbidities and established prognostic markers of COVID-19 (adjusted OR of the final model 1.368, 95% CI 1.126-1.662; P = 0.002). This association remained consistent upon sub-group analysis. Our study data also demonstrate that RDW levels upon admission for COVID-19 were similar to previously recorded, non-COVID-19 associated RDW levels [14.2% (IQR, 13.3-15.7) vs. 14.0% [IQR, 13.2-15.1]; P = 0.187]. Conclusions: In this population, RDWwas a significant, independent prognostic marker of short-term mortality in patients with COVID-19.

Development and validation of a laboratory risk score for the early prediction of COVID-19 severity and in-hospital mortality.

BACKGROUND AND AIMS: Coronavirus Disease 2019 is characterized by a spectrum of clinical severity. This study aimed to develop a laboratory score system to identify high-risk individuals, to validate this score in a separate cohort, and to test its accuracy in the prediction of in-hospital mortality. METHODS: In this cohort study, biological data from 330 SARS-CoV-2 infected patients were used to develop a risk score to predict progression toward severity. In a second stage, data from 240 additional COVID-19 patients were used to validate this score. Accuracy of the score was measured by the area under the receiver operating characteristic curve (AUC). RESULTS: In the development cohort, a step-wise decrease in the average survival duration was noted with the increment of the risk score (pANOVA < 0.0001). A similar trend was confirmed when analyzing this association in the validation cohort (p < 0.0001). The AUC was 0.74 [0.66-0.82] and 0.90 [0.87-0.94], p < 0.0001, respectively for severity and mortality prediction. CONCLUSION: This study provides a useful risk score based on biological routine parameters assessed at the time of admission, which has proven its effectiveness in predicting both severity and short-term mortality of COVID-19. Improved predictive scores may be generated by including other clinical and radiological features.