Cardiovascular disease in an intensive care unit: patterns of an often fatal omen

Background

Care for the critically ill patient with Cardiovascular Disease (CVD) requires a unique management approach, as the theoretical critical threshold for decompensation is lower and inherent adaptive mechanisms may be compromised. We aimed to characterize the prognostic impact of CVD in patients admitted to an Intensive Care Unit (ICU).

Methods

We performed a cohort study of consecutive patients admitted to an ICU from January to December 2019. Patients were stratified as follows: (1) established CVD – presence of either atrial fibrillation, heart failure, coronary artery disease and/or peripheral artery disease; (2) at higher risk of CVD – known arterial hypertension, dyslipidemia, diabetes mellitus and/or current smoking, in the absence of established CVD; and (3) at lower risk of CVD – i.e. none of the above. The co-primary endpoints were all-cause death in ICU and death during index hospitalization.

Results

During 2019, there were 334 admissions in ICU, comprising a total of 296 patients (mean age 67±15 years, 58.1% male). Overall, 69 (23.3%) and 108 (36.5%) died in ICU and during index hospitalization, respectively. Compared to patients at lower risk of CVD, those at higher CVD risk or with established CVD had markers of more severe disease, as noted by higher risk scores (e.g., SAPS-II 35.0±20.0 vs. 43.5±22.3 vs. 52.6±20.0; p<0.001), higher rates of mechanical ventilation (41.5 vs. 57.3 vs. 63.9%; p=0.020), shock during ICU stay (34.0 vs. 52.7 vs. 66.9%; p<0.001) and acute kidney injury (26.4 vs. 35.5 vs. 57.9%; p<0.001), respectively, as well as higher death rates in ICU (5.7 vs. 21.8 vs. 31.6%; p=0.001) and index hospitalization (9.4 vs. 37.3 vs. 46.6%; p<0.001). In multivariate analysis, adjusted for age and cause of admission, established CVD independently predicted the risk of all-cause death in ICU (HR: 2.084; 95% CI: 1.136–3.823; p=0.018) and during index hospitalization (HR 1.712; CI: 1.009–2.889; p=0.046). The analysis for the group of patients at higher risk of CVD yielded similar results to the abovementioned.

Conclusion

Roughly 4 in every 5 patients admitted in ICU were at risk of or had established CVD. The presence of either of the above independently predicted a two- to three-fold higher risk of death during hospitalization. Our findings emphasize the considerable burden of CVD in ICU and underscore the importance of comprehensive management of the complex critically ill patient.

Funding Acknowledgement

Type of funding sources: None.

Chronic heart failure in intensive care unit: can we accurately predict the risk?

Background

Severity of disease scoring systems, namely the Simplified Acute Physiology Score (SAPS) and Acute Physiology and Chronic Health Evaluation (APACHE), are widely used to predict mortality in Intensive Care Units (ICU). Yet, neither score includes chronic HF in their model. We aimed to evaluate whether these scores perform well in risk prediction of death of patients previously diagnosed with heart failure (HF).

Methodology

This is a single-center retrospective cohort of patients admitted to an ICU in 2019. Those whose admission lasted <24 hours were excluded from analysis. The SAPS II and APACHE II scores were calculated using data from the first 24 hours of ICU admission, imputing the worst variable obtained within this timeframe. HF was defined according to the ESC recommendations. In order to assess the performance of the scores, Receiver Operating Characteristic (ROC) Curves were used to predict the risk of death in ICU in HF compared to the non-HF population.

Results

A total of 267 patients were hospitalized in ICU for a period over 24 hours in 2019 (mean age 67±16 years; 58.8% males; 21.7% with chronic HF; 33.7% admitted for sepsis). Compared to patients without HF, those with chronic HF were older (74±13 vs. 65±16 years; p<0.001) and had higher risk scores (mean SAPS II: 43.2±21.7 vs. 56.5±20.7; p<0.001; mean APACHE II: 19.8±10.0 vs. 25.1±10.0; p<0.001). Moreover, these patients were at higher risk of meaningful events during hospitalization (e.g. acute kidney injury: 38.0 vs. 66.1%; p<0.001; shock at any time: 52.4 vs. 67.8%; p=0.036). Furthermore, patients with HF had a trend towards higher mortality rates in ICU (17.3 vs. 28.8%; p=0.051) and a significantly higher death in overall hospitalization (30.8 vs. 45.8%; p=0.032). ROC curves performed well in predicting the risk of ICU death regardless of HF (SAPS II – AUC 0.78 vs. 0.81; p=0.36; APACHE II – AUC 0.75 vs. 0.78; p=0.37).

Conclusion

Approximately 1 in every 4 patients admitted to the ICU had chronic HF. Traditional risk scoring systems (SAPS II and APACHE II) performed well regardless of HF. While these results are reassuring as far as risk stratification accuracy is concerned, HF patients remained at a higher risk for worse outcomes. Therefore, prognostic tools with a therapeutic clinical applicability are urgently needed to improve the outcome of this population.

Funding Acknowledgement

Type of funding sources: None.

The Reality of Critical Cancer Patients in a Polyvalent Intensive Care Unit

Background and objective With the increasing incidence of cancer and the rise in the survival rates of cancer patients, more and more oncological candidates are being considered for admission to intensive care units (ICU). Several studies have demonstrated no difference in the outcomes of cancer patients compared to non-cancer patients. Our study aimed to describe and analyze the outcomes related to cancer patients in a polyvalent ICU. Methods We conducted a retrospective study of consecutive oncological patients admitted to a polyvalent ICU (2013-2017). Cox model and receiver operating characteristic (ROC) curve analysis were performed to analyze the results. Results A total of 236 patients were included in the study; the mean age of the patients was 53.5 ± 15.3 years, and 65% of them were male. The main cancer types were those related to the central nervous system (CNS; 31%), as well as gastrointestinal (18%), genitourinary (17%), and hematological (15%). Curative/diagnostic surgeries (49%) and sepsis/septic shock (17%) were the main reasons for admission. The Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) scores in hematological patients vs. solid tumors were as follows: 30 vs. 20 and 63 vs. 38, respectively (p<0.005). Vasopressors, invasive mechanical ventilation (IMV), and renal replacement therapy (RRT) were used more widely in hematological patients compared to solid-tumor patients. Length of stay was longer in hematological patients vs. solid-tumor patients (12.8 vs. 7 days, p=0.002). The median overall survival in hematological patients was one month and that in solid-tumor patients was 5.8 months (p<0.005). The survival rate at six months was better than described in the existing literature (48 vs. 32.4%). Conclusion Both SAPS II and APACHE II scores were reasonably accurate in predicting mortality, demonstrating their value in cancer patients.

A Estratégia de Combate à COVID-19

O Grupo de Coordenação Local – Programa de Prevenção e Controlo de Infeções e de Resistência aos Antimicrobianos (GCL-PPCIRA) do Hospital CUF Infante Santo foi criado em novembro de 2019 e tem por missão implementar uma abordagem estruturada multidisciplinar e multiprofissional de prevenção e controlo de infeção associada a cuidados de saúde, nomeadamente da infeção adquirida durante o internamento hospitalar, e de utilização criteriosa de antimicrobianos, promovendo a sua eficácia clínica e limitando a sua toxicidade e a emergência de resistências microbianas. E o primeiro grande teste da comissão recém-formada foi enfrentar uma pandemia global COVID-19 causado pelo vírus SARS-CoV-2 com início em Wuhan, na China em dezembro de 2019.

Global Ultrasound Check for the Critically lll (GUCCI)-a new systematized protocol unifying point-of-care ultrasound in critically ill patients based on clinical presentation

Ultrasound technology is an essential tool in the management of critically ill patients. Point-of-care ultrasonography (POCUS) enables data collection from different anatomic areas to achieve the most probable diagnosis and administer the right therapy at the right time. Despite the increasing utilization of POCUS, there is still a lack of standards to establish how to use different bedside ultrasound protocols, and it is imperative to develop a unifying protocol. Thus, the aim of this paper is to establish a new systematized approach that can be adopted by all physicians to implement POCUS for critically ill patient management. To achieve this, we propose a new systematized approach—Global Ultrasound Check for the Critically Ill (GUCCI)—that integrates multiple protocols. This protocol is organized based on three syndromes (acute respiratory failure, shock, and cardiac arrest) and includes ultrasound-guided procedures.