Clinical outcome, risk assessment, and seasonal variation in hospitalized COVID-19 patients-Results from the CORONA Germany study

COVID-19 fatality rates in hospitalized patients: A new systematic review and meta-analysis

BACKGROUND

SARS-COV2 or COVID-19 disease is an infectious illness that emerged for the first time at the end of 2019, in Wuhan, China and rapidly turned out to be an international pandemic with deleterious effects all over the world. In March 2021, A. Macedo et al., has published the first meta-analysis of hospital mortality, so the authors decided to update those data at a time of emergence of new therapies and increasing vaccination rates.

METHODS

As the outcome of interest was the mortality in hospitalized general patients, the authors looked for articles evaluating the clinical characteristics of those patients, consulting PUBMED (The US National Library of Medicine) and EMBASE (Medical database) in an independent selection using predefined terms of search. A meta-analysis random-effect model was estimated using Mantel-Haenszel method. Heterogeneity among studies was tested using Tau2 statistics and Chi2 statistics.

RESULTS

In a first instance 25 articles were included for final analysis with a total of 103,840 patients, but as the goal was to update the anterior data, these studies were analysed together with the 21 studies of the previous meta-analysis, with a total of 114609 patients. The mortality rate of COVID-19 general patients admitted to the hospital was 16% (95% CI 12; 21, I2 =100%).

CONCLUSION

Global hospital mortality of COVID-19 of general patients was 16%, with quite different rates according to the different geographic areas analysed.

Higher in-hospital mortality in SARS-CoV-2 omicron variant infection compared to influenza infection-Insights from the CORONA Germany study

BACKGROUND

With the emergence of new subvariants, the disease severity of Severe Acute Respiratory Syndrome Coronavirus-2 has attenuated. This study aimed to compare the disease severity in patients hospitalized with omicron variant infection to those with influenza infection.

METHODS

We compared data from the multicenter observational, prospective, epidemiological "CORONA Germany" (Clinical Outcome and Risk in hospitalized COVID-19 patients) study on patients infected with Severe Acute Respiratory Syndrome Coronavirus-2 to retrospective data on influenza infection cases from November 2016 to August 2022. Severe Acute Respiratory Syndrome Coronavirus-2 cases were classified as wild-type/delta variant before January 2022, or omicron variant from January 2022 onward. The primary outcome was in-hospital mortality, adjusted for age, gender, and comorbidities.

RESULTS

The study included 35,806 patients from 53 hospitals in Germany, including 4,916 patients (13.7%) with influenza infection, 16,654 patients (46.5%) with wild-type/delta variant infection, and 14,236 patients (39.8%) with omicron variant infection. In-hospital mortality was highest in patients with wild-type/delta variant infection (16.8%), followed by patients with omicron variant infection (8.4%) and patients with influenza infection (4.7%). In the adjusted analysis, higher age was the strongest predictor for in-hospital mortality (age 80 years vs. age 50 years: OR 4.25, 95% CI 3.10-5.83). Both, patients with wild-type/delta variant infection (OR 3.54, 95% CI 3.02-4.15) and patients with omicron variant infection (OR 1.56, 95% CI 1.32-1.84) had a higher risk for in-hospital mortality than patients with influenza infection.

CONCLUSION

After adjusting for age, gender and comorbidities, patients with wild-type/delta variant infection had the highest risk for in-hospital mortality compared to patients with influenza infection. Even for patients with omicron variant infection, the adjusted risk for in-hospital mortality was higher than for patients with influenza infection. The adjusted risk for in-hospital mortality showed a strong age dependency across all virus types and variants.

TRIAL REGISTRATION NUMBER

NCT04659187.

Temporal trends in hospitalizations and 30-day mortality in older patients during the COVID pandemic from March 2020 to July 2021

BACKGROUND

A reduction in mortality risk of COVID-19 throughout the first wave of the pandemic has been reported, but less is known about later waves. This study aimed to describe changes in hospitalizations and mortality of patients receiving inpatient geriatric care for COVID-19 or other causes during the pandemic.

METHODS

Patients 70 years and older hospitalized in geriatric hospitals in Stockholm for COVID-19 or other causes between March 2020-July 2021 were included. Data on the incidence of COVID-positive cases and 30-day mortality of the total ≥ 70-year-old population, in relation to weekly hospitalizations and mortality after hospital admissions were analyzed. Findings The total number of hospitalizations was 5,320 for COVID-19 and 32,243 for non-COVID-cases. In COVID-patients, the 30-day mortality rate was highest at the beginning of the first wave (29% in March-April 2020), reached 17% at the second wave peak (November-December) followed by 11-13% in the third wave (March-July 2021). The mortality in non-COVID geriatric patients showed a similar trend, but of lower magnitude (5-10%). During the incidence peaks, COVID-19 hospitalizations displaced non-COVID geriatric patients.

INTERPRETATION

Hospital admissions and 30-day mortality after hospitalizations for COVID-19 increased in periods of high community transmission, albeit with decreasing mortality rates from wave 1 to 3, with a probable vaccination effect in wave 3. Thus, the healthcare system could not compensate for the high community spread of COVID-19 during the pandemic peaks, which also led to displacing care for non-COVID geriatric patients.

Pulmonary Hypertension in Interstitial Lung Disease: Management Options to Move Beyond Supportive Care

Purpose of Review

This review delineates current diagnostic and management strategies for pulmonary hypertension due to interstitial lung disease (PH-ILD).

Recent Findings

The INCREASE trial, a phase III multicenter, randomized, placebo-controlled trial demonstrated both improved 6-min walk distance and decreased disease progression with inhaled treprostinil. This pivotal trial led to inhaled treprostinil becoming the first FDA approved medication for treatment of PH-ILD. The availability of this treatment has generated subsequent recommendations for the screening for PH in patients with ILD. As a result, it is becoming increasingly important for clinicians to gain awareness and familiarity with the evolving management options for PH-ILD.

Summary

The management of PH-ILD has its roots in goal-directed treatment of the underlying lung disease. However, recent medication advances and ongoing clinical studies are opening opportunities for more disease-specific treatment.

Trends in management and outcomes of COVID patients admitted to a Swiss tertiary care hospital

Two successive COVID-19 flares occurred in Switzerland in spring and autumn 2020. During these periods, therapeutic strategies have been constantly adapted based on emerging evidence. We aimed to describe these adaptations and evaluate their association with patient outcomes in a cohort of COVID-19 patients admitted to the hospital. Consecutive patients admitted to the Geneva Hospitals during two successive COVID-19 flares were included. Characteristics of patients admitted during these two periods were compared as well as therapeutic management including medications, respiratory support strategies and admission to the ICU and intermediate care unit (IMCU). A mutivariable model was computed to compare outcomes across the two successive waves adjusted for demographic characteristics, co-morbidities and severity at baseline. The main outcome was in-hospital mortality. Secondary outcomes included ICU admission, Intermediate care (IMCU) admission, and length of hospital stay. A total of 2'983 patients were included. Of these, 165 patients (16.3%, n = 1014) died during the first wave and 314 (16.0%, n = 1969) during the second (p = 0.819). The proportion of patients admitted to the ICU was lower in second wave compared to first (7.4 vs. 13.9%, p < 0.001) but their mortality was increased (33.6% vs. 25.5%, p < 0.001). Conversely, a greater proportion of patients was admitted to the IMCU in second wave compared to first (26.6% vs. 22.3%, p = 0.011). A third of patients received lopinavir (30.7%) or hydroxychloroquine (33.1%) during the first wave and none during second wave, while corticosteroids were mainly prescribed during second wave (58.1% vs. 9.1%, p < 0.001). In the multivariable analysis, a 25% reduction of mortality was observed during the second wave (HR 0.75; 95% confidence interval 0.59 to 0.96). Among deceased patients, 82.3% (78.2% during first wave and 84.4% during second wave) died without beeing admitted to the ICU. The proportion of patients with therapeutic limitations regarding ICU admission increased during the second wave (48.6% vs. 38.7%, p < 0.001). Adaptation of therapeutic strategies including corticosteroids therapy and higher admission to the IMCU to receive non-invasive respiratory support was associated with a reduction of hospital mortality in multivariable analysis, ICU admission and LOS during the second wave of COVID-19 despite an increased number of admitted patients. More patients had medical decisions restraining ICU admission during the second wave which may reflect better patient selection or implicit triaging.

Is Dementia Associated with COVID-19 Mortality? A Multicenter Retrospective Cohort Study Conducted in 50 Hospitals in Germany

BACKGROUND

Dementia has been identified as a major predictor of mortality associated with COVID-19.

OBJECTIVE

The objective of this study was to investigate the association between dementia and mortality in COVID-19 inpatients in Germany across a longer interval during the pandemic.

METHODS

This retrospective study was based on anonymized data from 50 hospitals in Germany and included patients with a confirmed COVID-19 diagnosis hospitalized between March 11, 2020 and July, 20, 2022. The main outcome of the study was the association of mortality during inpatient stays with dementia diagnosis, which was studied using multivariable logistic regression adjusted for age, sex, and comorbidities as well as univariate logistic regression for matched pairs.

RESULTS

Of 28,311 patients diagnosed with COVID-19, 11.3% had a diagnosis of dementia. Prior to matching, 26.5% of dementia patients and 11.5% of non-dementia patients died; the difference decreased to 26.5% of dementia versus 21.7% of non-dementia patients within the matched pairs (n = 3,317). This corresponded to an increase in the risk of death associated with dementia (OR = 1.33; 95% CI: 1.16-1.46) in the univariate regression conducted for matched pairs.

CONCLUSION

Although dementia was associated with COVID-19 mortality, the association was weaker than in previously published studies. Further studies are needed to better understand whether and how pre-existing neuropsychiatric conditions such as dementia may impact the course and outcome of COVID-19.

Is there an association between depression, anxiety disorders and COVID-19 severity and mortality? A multicenter retrospective cohort study conducted in 50 hospitals in Germany

BACKGROUND

The aim of this retrospective cohort study was to investigate associations between depression and anxiety disorder and the risk of COVID-19 severity and mortality in patients treated in large hospitals in Germany.

METHODS

This retrospective study was based on anonymized electronic medical data from 50 public healthcare service hospitals across Germany. Multivariable logistic regression models were used to study associations between depression, anxiety and mechanical ventilation and mortality due to COVID adjusted for age, sex, time of COVID-19 diagnosis, and pre-defined co-diagnoses.

RESULTS

Of 28,311 patients diagnosed with COVID-19, 1970 (6.9%) had a diagnosis of depression and 369 (1.3%) had a diagnosis of anxiety disorder prior to contracting COVID-19. While multivariable logistic regression models did not indicate any association between depression diagnosis and the risk of mechanical ventilation, depression was associated with a decreased risk of mortality (OR: 0.71; 95% CI: 0.53-0.94). There was no association between anxiety disorders and risk of mortality, but there was a strong positive association between anxiety disorders and the risk of mechanical ventilation (OR: 2.04; 95% CI: 1.35-3.10).

CONCLUSION

In the present study, depression and anxiety disorder diagnoses were not associated with increased COVID-19 mortality. Anxiety disorder was strongly associated with an increased risk of mechanical ventilation. Further studies are needed to clarify how depression and anxiety disorders may influence COVID-19 severity and mortality.

Comparison of machine learning methods with logistic regression analysis in creating predictive models for risk of critical in-hospital events in COVID-19 patients on hospital admission

BACKGROUND

Machine learning (ML) algorithms have been trained to early predict critical in-hospital events from COVID-19 using patient data at admission, but little is known on how their performance compares with each other and/or with statistical logistic regression (LR). This prospective multicentre cohort study compares the performance of a LR and five ML models on the contribution of influencing predictors and predictor-to-event relationships on prediction model´s performance.

METHODS

We used 25 baseline variables of 490 COVID-19 patients admitted to 8 hospitals in Germany (March-November 2020) to develop and validate (75/25 random-split) 3 linear (L1 and L2 penalty, elastic net [EN]) and 2 non-linear (support vector machine [SVM] with radial kernel, random forest [RF]) ML approaches for predicting critical events defined by intensive care unit transfer, invasive ventilation and/or death (composite end-point: 181 patients). Models were compared for performance (area-under-the-receiver-operating characteristic-curve [AUC], Brier score) and predictor importance (performance-loss metrics, partial-dependence profiles).

RESULTS

Models performed close with a small benefit for LR (utilizing restricted cubic splines for non-linearity) and RF (AUC means: 0.763-0.731 [RF-L1]); Brier scores: 0.184-0.197 [LR-L1]). Top ranked predictor variables (consistently highest importance: C-reactive protein) were largely identical across models, except creatinine, which exhibited marginal (L1, L2, EN, SVM) or high/non-linear effects (LR, RF) on events.

CONCLUSIONS

Although the LR and ML models analysed showed no strong differences in performance and the most influencing predictors for COVID-19-related event prediction, our results indicate a predictive benefit from taking account for non-linear predictor-to-event relationships and effects. Future efforts should focus on leveraging data-driven ML technologies from static towards dynamic modelling solutions that continuously learn and adapt to changes in data environments during the evolving pandemic.

TRIAL REGISTRATION NUMBER

NCT04659187.

Rapid systematic review of respiratory rate as a vital sign of clinical deterioration in COVID-19

OBJECTIVES

This meta-analysis aimed to establish a clinical evidence base for respiratory rate (RR) as a single predictor of early-onset COVID-19. The review also looked to determine the practical implementation of mobile respiratory rate measuring devices where information was available.

METHODS

We focused on domestic settings with older adults. Relevant studies were identified through MEDLINE, Embase, and CENTRAL databases. A snowballing method was also used. Articles published from the beginning of the COVID-19 pandemic (2019) until Feb 2022 were selected. Databases were searched for terms related to COVID-19 and respiratory rate measurements in domestic patients.

RESULTS

A total of 2,889 articles were screened for relevant content, of which 60 full-text publications were included. We compared the Odds Ratios and statistically significant results of both vital signs.

CONCLUSION

Multinational studies across dozens of countries have shown respiratory rate to have predictive accuracy in detecting COVID-19 deterioration. However, considerable variability is present in the data, making it harder to be sure about the effects. There is no meaningful difference in data quality in terms of variability (95% CI intervals) between vital signs as predictors of decline in COVID-19 patients. Contextual and economic factors will likely determine the choice of measurement used.

Severity and prognostic factors of SARS-CoV-2-induced pneumonia: The value of clinical and laboratory biomarkers and the A-DROP score

Introduction

Numerous clinical and laboratory scores that include C-reactive protein (CRP), D-dimer, ferritin, lactate dehydrogenase (LDH), interleukin 6 (IL-6), procalcitonin (PCT), blood urea nitrogen (BUN), creatinine levels and oxygenation (PaO₂ and SaO₂) have been used for the prognosis of COVID-19. In addition, composite scores have been developed for the assessment of general state and risk in community-acquired pneumonia (CAP) that may be applied for COVID-19 as well. In this study, we assessed severity and potential prognostic risk factors for unfavorable outcome among hospitalized COVID-19 patients. We also applied the A-DROP general scoring system used in CAP to COVID-19.

Patients and methods

Altogether 233 patients admitted to our center with COVID-19 were included in the study. Clinical status, several laboratory biomarkers described above, indicators of oxygenation were determined at hospital admission. We also applied the A-DROP composite scoring system that includes Age (≥ 70 years in males and ≥ 75 years in females), Dehydration (BUN ≥ 7.5 mmol/l), Respiratory failure (SaO₂ ≤ 90% or PaO₂ ≤ 60 mmHg), Orientation disturbance (confusion) and low blood Pressure (systolic BP ≤ 90 mmHg) to COVID-19.

Results

At the time of admission, most patients had elevated CRP, LDH, ferritin, D-dimer, and IL-6 levels indicating multisystemic inflammatory syndrome (MIS). Altogether 49 patients (21.2%) required admission to ICU, 46 (19.7%) needed ventilation and 40 patients (17.2%) died. In the binary analysis, admission to ICU, the need for ventilation and death were all significantly associated with the duration of hospitalization, history of hypertension or obesity, confusion/dizziness, as well as higher absolute leukocyte and neutrophil and lower lymphocyte counts, elevated CRP, PCT, LDH, ferritin, IL-6, BUN, and creatinine levels, low PaO₂ and SaO₂ and higher A-DROP score at the time of admission (p < 0.05).

Conclusion

Numerous laboratory biomarkers in addition to obesity, dizziness at the time of admission and the history of hypertension may predict the need for ICU admission and ventilation, as well as mortality in COVID-19. Moreover, A-DROP may be a suitable scoring system for the assessment of general health and disease outcome in COVID-19.

Palliative care in COVID-19

PURPOSE OF REVIEW

The purpose of this paper is (1) to provide insight in the palliative care needs of patients with COVID-19; (2) to highlight the challenges of COVID-19 for palliative care; and (3) to highlight developments in COVID-19 palliative care.

RECENT FINDINGS

Patients with serious COVID-19 have palliative care needs in all domains: physical, psychological, social and spiritual. COVID-19 palliative care is confronted with many challenges, including: the uncertain prognosis, resource limitations, challenges regarding advance care planning, lack of guidance, limited multidisciplinary collaboration, need for remote communication, restrictions in family visits, and burden for clinicians. Palliative care responded with many developments: development of services; integration of palliative care with other services; tools to support advance care planning, (remote) communication with patients and families, or spiritual care; and care for team members.

SUMMARY

Palliative care has an important role in this pandemic. Palliative care rapidly developed services and opportunities were found to support patients, families and clinicians. Further developments are warranted to face future demands of a pandemic, including integrated palliative care and education in palliative care skills across all specialties. Intervention studies are needed to enable evidence-based recommendations for palliative care in COVID-19.

Prognostic Impact of Acute Cardiovascular Events in COVID-19 Hospitalized Patients-Results from the CORONA Germany Study

BACKGROUND

Acute myocardial injury (AMJ), assessed by elevated levels of cardiac troponin, is associated with fatal outcome in coronavirus disease 2019 (COVID-19). However, the role of acute cardiovascular (CV) events defined by clinical manifestation rather than sole elevations of biomarkers is unclear in hospitalized COVID-19 patients.

OBJECTIVE

The aim of this study was to investigate acute clinically manifest CV events in hospitalized COVID-19 patients.

METHODS

From 1 March 2020 to 5 January 2021, we conducted a multicenter, prospective, epidemiological cohort study at six hospitals from Hamburg, Germany (a portion of the state-wide 45-center CORONA Germany cohort study) enrolling all hospitalized COVID-19 patients. Primary endpoint was occurrence of a clinically manifest CV-event.

RESULTS

In total, 132 CV-events occurred in 92 of 414 (22.2%) patients in the Hamburg-cohort: cardiogenic shock in 10 (2.4%), cardiopulmonary resuscitation in 12 (2.9%), acute coronary syndrome in 11 (2.7%), de-novo arrhythmia in 31 (7.5%), acute heart-failure in 43 (10.3%), myocarditis in 2 (0.5%), pulmonary-embolism in 11 (2.7%), thrombosis in 9 (2.2%) and stroke in 3 (0.7%). In the Hamburg-cohort, mortality was 46% (42/92) for patients with a CV-event and 33% (27/83) for patients with only AMJ without CV-event (OR 1.7, CI: (0.94-3.2), p = 0.077). Mortality was higher in patients with CV-events (Odds ratio(OR): 4.8, 95%-confidence-interval(CI): [2.9-8]). Age (OR 1.1, CI: (0.66-1.86)), atrial fibrillation (AF) on baseline-ECG (OR 3.4, CI: (1.74-6.8)), systolic blood-pressure (OR 0.7, CI: (0.53-0.96)), potassium (OR 1.3, CI: (0.99-1.73)) and C-reactive-protein (1.4, CI (1.04-1.76)) were associated with CV-events.

CONCLUSION

Hospitalized COVID-19 patients with clinical manifestation of acute cardiovascular events show an almost five-fold increased mortality. In this regard, the emergence of arrhythmias is a major determinant.