Timely goals of care documentation in patients with frailty in the COVID-19 era: a retrospective multi-site study

Frailty as a trigger for goals-of-care discussions in rapid response calls: A single-centre retrospective cohort study

BACKGROUND

Timely goals-of-care (GOC) discussions are essential for end-of-life planning, particularly during acute hospital admissions, where ambiguity often persists. Frailty, prevalent in the ageing population and linked to adverse outcomes, underscores the need to align treatment strategies with quality of life. Recognising frailty as a trigger for GOC discussions during rapid response calls (RRCs) is critical for efficient resource management and improving patient outcomes.

METHODS

This single-centre retrospective cohort study included all hospitalised patients aged ≥65 years admitted between September 2021 and June 2023 who experienced an RRC. Frailty was assessed using the Clinical Frailty Scale (CFS) during the RRC. The primary outcome was to investigate whether frailty, specifically assessed by the CFS as screened during an RRC, could be a suitable clinical trigger for initiating GOC discussions. We also aimed to identify the proportion of patients with frailty (CFS score: ≥5) and predictors at the time of RRC, resulting in recommendations for GOC discussions.

RESULTS

Among 4954 patients, 1685 (34.0%) were classified as frail (CFS score: ≥5). Recommendations increased with frailty levels (nonfrail [CFS score: 1-4]: 6.6%, mildly frail [CFS score: 5]: 19.3%, moderate-to-severely frail [CFS score: 6-9]: 32.2%; p < 0.001). Frailty independently increased the probability of GOC recommendations during an RRC (area under the receiver operating characteristic curve = 0.71). The CFS cut-off point for GOC recommendations was ≥5. The presence of frailty was associated with higher odds of receiving GOC recommendations for mildly frail (CFS score: 5; odds ratio [OR] = 2.53; 95% confidence interval: 1.96-3.27) and moderate-to-severely frail (CFS score: 6-9; OR = 4.69; 95% confidence interval: 3.81-5.78) compared to nonfrail patients.

CONCLUSION

Frailty, identified during an RRC, served as a robust trigger for GOC recommendations, highlighting the importance of tailored proactive discussions before episodes of deterioration. Higher levels of frailty (CFS score: ≥5) demonstrate practical markers for aiding clinicians with proactive GOC discussions.

Persistent Critical Illness and Long-Term Outcomes in Patients With COVID-19: A Multicenter Retrospective Cohort Study

OBJECTIVES

A nontrivial number of patients in ICUs experience persistent critical illness (PerCI), a phenomenon in which features of the ICU course more consistently predict mortality than the initial indication for admission. We aimed to describe PerCI among patients with critical illness caused by COVID-19, and these patients' short- and long-term outcomes.

DESIGN

Multicenter retrospective cohort study.

SETTING

Australian and New Zealand Intensive Care Society Adult Patient Database of 114 Australian ICUs between January 1, 2020, and March 31, 2022.

PATIENTS

Patients 16 years old or older with COVID-19, and a documented ICU length of stay.

EXPOSURE

The presence of PerCI, defined as an ICU length of stay greater than or equal to 10 days.

MEASUREMENTS

We compared the survival time up to 2 years from ICU admission using time-varying robust-variance estimated Cox proportional hazards models. We further investigated the impact of PerCI in subgroups of patients, stratifying based on whether they survived their initial hospitalization.

MAIN RESULTS

We included 4961 patients in the final analysis, and 882 patients (17.8%) had PerCI. ICU mortality was 23.4% in patients with PerCI and 6.5% in those without PerCI. Patients with PerCI had lower 2-year (70.9% [95% CI, 67.9-73.9%] vs. 86.1% [95% CI, 85.0-87.1%]; p < 0.001) survival rates compared with patients without PerCI. Patients with PerCI had higher mortality (adjusted hazards ratio: 1.734; 95% CI, 1.388-2.168); this was consistent across several sensitivity analyses. When analyzed as a nonlinear predictor, the hazards of mortality were inconsistent up until 10 days, before plateauing.

CONCLUSIONS

In this multicenter retrospective observational study patients with PerCI tended to have poorer short-term and long-term outcomes. However, the hazards of mortality plateaued beyond the first 10 days of ICU stay. Further studies should investigate predictors of developing PerCI, to better prognosticate long-term outcomes.

Discovering common pathogenic processes between COVID-19 and HFRS by integrating RNA-seq differential expression analysis with machine learning

Zoonotic virus spillover in human hosts including outbreaks of Hantavirus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) imposes a serious impact on the quality of life of patients. Recent studies provide a shred of evidence that patients with Hantavirus-caused hemorrhagic fever with renal syndrome (HFRS) are at risk of contracting SARS-CoV-2. Both RNA viruses shared a higher degree of clinical features similarity including dry cough, high fever, shortness of breath, and certain reported cases with multiple organ failure. However, there is currently no validated treatment option to tackle this global concern. This study is attributed to the identification of common genes and perturbed pathways by combining differential expression analysis with bioinformatics and machine learning approaches. Initially, the transcriptomic data of hantavirus-infected peripheral blood mononuclear cells (PBMCs) and SARS-CoV-2 infected PBMCs were analyzed through differential gene expression analysis for identification of common differentially expressed genes (DEGs). The functional annotation by enrichment analysis of common genes demonstrated immune and inflammatory response biological processes enriched by DEGs. The protein-protein interaction (PPI) network of DEGs was then constructed and six genes named RAD51, ALDH1A1, UBA52, CUL3, GADD45B, and CDKN1A were identified as the commonly dysregulated hub genes among HFRS and COVID-19. Later, the classification performance of these hub genes were evaluated using Random Forest (RF), Poisson Linear Discriminant Analysis (PLDA), Voom-based Nearest Shrunken Centroids (voomNSC), and Support Vector Machine (SVM) classifiers which demonstrated accuracy >70%, suggesting the biomarker potential of the hub genes. To our knowledge, this is the first study that unveiled biological processes and pathways commonly dysregulated in HFRS and COVID-19, which could be in the next future used for the design of personalized treatment to prevent the linked attacks of COVID-19 and HFRS.

Treatment limitations and clinical outcomes in critically ill frail patients with and without COVID-19 pneumonitis

BACKGROUND

The presence of treatment limitations in patients with frailty at intensive care unit (ICU) admission is unknown. We aimed to evaluate the presence and predictors of treatment limitations in patients with and without COVID-19 pneumonitis in those admitted to Australian and New Zealand ICUs.

METHODS

This registry-based multicenter, retrospective cohort study included all frail adults (≥16 years) with documented clinical frailty scale (CFS) scores, admitted to ICUs with admission diagnostic codes for viral pneumonia or acute respiratory distress syndrome (ARDS) over 2 years between January 01, 2020 and December 31, 2021. Frail patients (CFS ≥5) coded as having viral pneumonitis or ARDS due to COVID-19 were compared to those with other causes of viral pneumonitis or ARDS for documented treatment limitations.

RESULTS

884 frail patients were included in the final analysis from 129 public and private ICUs. 369 patients (41.7%) had confirmed COVID-19. There were more male patients in COVID-19 (55.3% vs 47.0%; p = 0.015). There were no differences in age or APACHE-III scores between the two groups. Overall, 36.0% (318/884) had treatment limitations, but similar between the two groups (35.8% [132/369] vs 36.1% [186/515]; p = 0.92). After adjusting for confounders, increasing frailty (OR = 1.72; 95%-CI 1.39-2.14), age (OR = 1.05; 95%-CI 1.04-1.06), and presence of chronic respiratory condition (OR = 1.58; 95%-CI 1.10-2.27) increased the likelihood of instituting treatment limitations. However, the presence of COVID-19 by itself did not influence treatment limitations (odds ratio [OR] = 1.39; 95%-CI 0.98-1.96).

CONCLUSIONS

The proportion of treatment limitations was similar in patients with frailty with or without COVID-19 pneumonitis at ICU admission.