Mortality risk factors in elderly patients in intensive care without limitation of therapeutic effort

Do not resuscitate orders and limitation of therapeutic effort: Ethical challenges in healthcare teams in Chile

The purpose of this paper is to delve into the ethical aspects experienced by the healthcare team when they receive the directive to limit therapeutic effort or a do-not-resuscitate order. From an interpretative, qualitative paradigm with a content analysis approach, a process based on three phases was conducted: pre-analysis in which categories were identified, the projection of the analysis, and inductive analysis. During 2023, interviews were conducted in the clinical setting of a high-complexity hospital in Chile with 56 members of the healthcare teams from critical and emergency units, from which four categories emerged: a) the risk of violating patients' rights by using do-not-resuscitate orders and limiting therapeutic effort; b) the gap in the interpretation of the legal framework addressing the care and attention of patients at the end of life or with terminal illnesses by the healthcare team; c) ethical conflicts in end-of-life care; and d) efficient care versus holistic care in patients with terminal illness. There are significant gaps in bioethics training and aspects of a good death in healthcare teams facing the directive to limit therapeutic effort and not resuscitate. It is suggested to train personnel and work on a consensus guide to address the ethical aspects of a good death.

Palliative Emergency General Surgery

Acute care surgeons encounter patients experiencing surgical emergencies related to advanced malignancy, catastrophic vascular events, or associated with multisystem organ failure. The acute nature is a factor in establishing a relationship between surgeon, patient, and family. Surgeons must use effective communication skills, empathy, and a knowledge of legal and ethical foundations. Training in palliative care principles is limited in many medical school and residency curricula. We offer examples of clinical situations facing acute care surgeons and discuss evidence-based recommendations to facilitate successful treatment and outcomes.

Improved performance of an intensive care unit after changing the admission triage model

The aim of this study is to analyze the effect of implementing a prioritization triage model for admission to an intensive care unit on the outcome of critically ill patients. Retrospective longitudinal study of adult patients admitted to the Intensive Care Unit (ICU) carried out from January 2013 to December 2017. The primary outcome considered was vital status at hospital discharge. Patients were divided into period 1 (chronological triage) during the years 2013 and 2014 and period 2 (prioritization triage) during the years 2015-2017. A total of 1227 patients in period 1 and 2056 in period 2 were analyzed. Patients admitted in period 2 were older (59.8 years) compared to period 1 (57.3 years; p < 0.001) with less chronic diseases (13.6% vs. 19.2%; p = 0.001), and higher median APACHE II score (21.0 vs. 18.0; p < 0.001)) and TISS 28 score (28.0 vs. 27.0; p < 0.001). In period 2, patients tended to stay in the ICU for a shorter time (8.5 ± 11.8 days) compared to period 1 (9.6 ± 16.0 days; p = 0.060) and had lower mortality at ICU (32.8% vs. 36.9%; p = 0.016) and hospital discharge (44.2% vs. 47.8%; p = 0.041). The change in the triage model from a chronological model to a prioritization model resulted in improvement in the performance of the ICU and reduction in the hospital mortality rate.

[Mortality in patients with dementia admitted in critical care units]

OBJECTIVE

To determine the mortality and comorbidities associated of patients with dementia admitted to the Intensive Care Unit (ICU) on the hospitalization and at one year of follow-up.

MATERIALS AND METHODS

A retrospective observational cohort study was carried out between 2012 and 2017 at the Hospital Italiano de San Justo, of patients who were admitted to the ICU, these were observed up to hospitalary death, out hospital death one year of hospitalization, the disenrollment from the institution's health plan or the end of the follow-up.

RESULTS

A total of 163 patients were included for analysis. We recorded those 79 patients (48.47%) died one year after the hospitalization, of them 25 (15.34%) in ICU and 8 (4.91%) in general room. The most frequent causes of death were respiratory. The factors most associated with mortality were: orotracheal intubation (HR=2.01; 95% CI: 1.11-3.65; P=.02), history of leukemia (HR=8.55; 95% CI: 1.82-40.05; P≤.05), elevated Charlson (HR=1.16, 95% CI: 1.04-1.41; P=.05), and elevated APACHE II at admission (HR=1.07; 95% CI: 1.03-1.11; P≤.05).

CONCLUSIONS

The present study expresses the prognosis of patients with a diagnosis of dementia admitted to the ICU and that depends not only on their baseline neurological status but also on the severity at admission and comorbidities.

[Analysis of the factors involved in the evolution of patients over 80 years of age admitted to the intensive care unit: Should we change our procedure?]

BACKGROUND AND OBJECTIVES

The care of older patients in intensive care units (ICU) is becoming more frequent. To describe characteristics of elderly patients admitted to the ICU and to analyze the factors associated with mortality.

PATIENTS AND METHODS

Retrospective cross-sectional study, with patients ≥80 years, admitted to the ICU of the Rey Juan Carlos University Hospital, from March 2012 to December 2018. Demographic variables, comorbidities and mortality in the ICU, in hospital and at one year were collected, analyzed by univariate analysis and binary logistic regression.

RESULTS

Six hundred twenty patients, mean age 83.6 years (SD: 3.25), 31% required invasive mechanical ventilation (IMV), 25% vasopressors and 29% renal replacement therapy (RRT) due to acute renal failure (ARF). The 60% were admissions of medical origin. In-hospital mortality was 156 patients (25%), 91 died in the ICU and 65 on the ward, with shorter ICU stays for the survivors (2.72; SD: 0.22) compared to the deceased (3.74; SD: 0.38), with statistically significant differences. 63% remained alive one year after ICU discharge. An explanatory model of ICU mortality was obtained by logistic regression that included the following factors: IMV (OR: 5.78, 95% CI 2.73-12.22), vasopressors (OR: 2.54, 95% CI 1.24-5.19), AKI/TRS (OR: 2.69, 95% CI 1.35-5.35), medical admission (OR: 2.88, 95% CI 1.40-5.92), urgent admission (OR: 2.33, 95% CI 1.30-4.18) and limitation of life support (LTSV) (OR: 47.35, 95% CI 22.96-97.68). The days in the ICU (OR: 0.93, 95% CI 0.87-0.99) would be inversely related to mortality.

CONCLUSIONS

In older patients, there is no increase in mortality, with a 1-year survival >63%. The need for IMV, the use of vasopressor drugs and ARF/RTS were factors associated with mortality in the multivariate analysis.

The association of the Activities of Daily Living and the outcome of old intensive care patients suffering from COVID-19

Purpose

Critically ill old intensive care unit (ICU) patients suffering from Sars-CoV-2 disease (COVID-19) are at increased risk for adverse outcomes. This post hoc analysis investigates the association of the Activities of Daily Living (ADL) with the outcome in this vulnerable patient group.

Methods

The COVIP study is a prospective international observational study that recruited ICU patients ≥ 70 years admitted with COVID-19 (NCT04321265). Several parameters including ADL (ADL; 0 = disability, 6 = no disability), Clinical Frailty Scale (CFS), SOFA score, intensive care treatment, ICU- and 3-month survival were recorded. A mixed-effects Weibull proportional hazard regression analyses for 3-month mortality adjusted for multiple confounders.

Results

This pre-specified analysis included 2359 patients with a documented ADL and CFS. Most patients evidenced independence in their daily living before hospital admission (80% with ADL = 6). Patients with no frailty and no disability showed the lowest, patients with frailty (CFS ≥ 5) and disability (ADL < 6) the highest 3-month mortality (52 vs. 78%, p < 0.001). ADL was independently associated with 3-month mortality (ADL as a continuous variable: aHR 0.88 (95% CI 0.82–0.94, p < 0.001). Being “disable” resulted in a significant increased risk for 3-month mortality (aHR 1.53 (95% CI 1.19–1.97, p 0.001) even after adjustment for multiple confounders.

Conclusion

Baseline Activities of Daily Living (ADL) on admission provides additional information for outcome prediction, although most critically ill old intensive care patients suffering from COVID-19 had no restriction in their ADL prior to ICU admission. Combining frailty and disability identifies a subgroup with particularly high mortality.

Trial registration number: NCT04321265.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-022-00996-9.

Comparison of Clinical Characteristics and Outcomes of Younger and Elderly Patients with Severe COVID-19 in Korea: A Retrospective Multicenter Study

Old age is associated with disease severity and poor prognosis among coronavirus disease 2019 (COVID-19) cases; however, characteristics of elderly patients with severe COVID-19 are limited. We aimed to assess the clinical characteristics and outcomes of patients hospitalized with severe COVID-19 at tertiary care centers in South Korea. This retrospective multicenter study included patients with severe COVID-19 who were admitted at seven hospitals in South Korea from 2 February 2020 to 28 February 2021. The Cox regression analyses were performed to assess factors associated with the in-hospital mortality. Of 488 patients with severe COVID-19, 318 (65.2%) were elderly (≥65 years). The older patient group had more underlying diseases and a higher severity score than the younger patient group. The older patient group had a higher in-hospital mortality rate than the younger patient group (25.5% versus 4.7%, p-value < 0.001). The in-hospital mortality risk factors among patients with severe COVID-19 included age, acute physiology and chronic health evaluation II score, presence of diabetes and chronic obstructive lung disease, high white blood cell count, low neutrophil-lymphocyte ratio and platelet count, do-not-resuscitate order, and treatment with invasive mechanical ventilation. In addition to old age, disease severity and examination results must be considered in treatment decision-making.

Factors and Outcomes of Intensive Care Unit Readmission in Elderly Patients

INTRODUCTION

An increase in age has been observed among patients admitted to the intensive care unit (ICU). Age is a well-known risk factor for ICU readmission and mortality. However, clinical characteristics and risk factors of ICU readmission of elderly patients (≥65 years) have not been studied.

METHODS

This retrospective single-center cohort study was conducted in a total of 122-bed ICU of a tertiary care hospital in Seoul, Korea. A total of 85,413 patients were enrolled in this hospital between January 1, 2007, and December 31, 2017. The odds ratio of readmission and in-hospital mortality was calculated by logistic regression analysis.

RESULTS

Totally, 29,503 patients were included in the study group, of which 2,711 (9.2%) had ICU readmissions. Of the 2,711 readmitted patients, 472 patients were readmitted more than once (readmitted 2 or more times to the ICU, 17.4%). In the readmitted patient group, there were more males, higher sequential organ failure assessment (SOFA) scores, and hospitalized for medical reasons. Length of stay (LOS) in ICU and in-hospital were longer, and 28-day and in-hospital mortality was higher in readmitted patients than in nonreadmitted patients. Risk factors of ICU readmission included the ICU admission due to medical reason, SOFA score, presence of chronic heart disease, diabetes mellitus, chronic kidney disease, transplantation, use of mechanical ventilation, and initial ICU LOS. ICU readmission and age (over 85 years) were independent predictors of in-hospital mortality on multivariable analysis. The delayed ICU readmission group (>72 h) had higher in-hospital mortality than the early readmission group (≤72 h) (20.6 vs. 16.2%, p = 0.005).

CONCLUSIONS

ICU readmissions occurred in 9.2% of elderly patients and were associated with poor prognosis and higher mortality.

SARC-F Predicts Mortality Risk of Older Adults during Hospitalization

OBJECTIVES

To determine the association between SARC-F scores and the in-hospital mortality risk among older patients admitted to acute care hospitals.

DESIGN

Single-center retrospective study.

SETTING

A university hospital.

PARTICIPANTS

All consecutive patients aged older than 65 were admitted and discharged from the study hospital between July 2019 and September 2019.

MEASUREMENTS

Relevant patient data included age, sex, body mass index, nutritional status, fat-free mass, disease, activities of daily living (ADL), duration of hospital stay, SARC-F, and occurrence of death within 30 days of hospitalization. The diseases that caused hospitalization and comorbidities (Charlson Comorbidity Index; CCI) were obtained from medical records. The Eastern Cooperative Oncology Group-performance status (PS) was used to determine ADL, and the in-hospital mortality rate within 30 days of hospitalization as the outcome.

RESULTS

We analyzed 2,424 patients. The mean age was 75.9±6.9 and 55.5% were male. Fifty-three in-hospital mortalities occurred among the participants within the first 30 days of hospitalization. Patients who died in-hospital were older, had poorer nutritional status and severer PS scores, and more comorbidities than those who did not. A SARC-F score of ≥4 predicted a higher mortality risk within those 30 days with the following precision: sensitivity 0.792 and specificity 0.805. There were significantly more deaths in Kaplan-Meier curves regarding a score of SARC-F≥4 than a score of SARC-F<4 (p<0.001). Cox proportional hazard analysis was used to identify the clinical indicators most associated with in-hospital mortality. SARC-F≥4 (Hazard Ratio: HR 5.65, p<0.001), CCI scores (HR1.11, p=0.004), and infectious and parasitic diseases (HR3.13, p=0.031) were associated with in-hospital mortality. The SARC-F items with significant in-hospital mortality effects were assistance with walking (HR 2.55, p<0.001) and climbing stairs (HR 2.46, p=0.002).

CONCLUSION

The SARC-F questionnaire is a useful prognostic indicator for older adults because a SARC-F ≥4 score during admission to an acute care hospital predicts in-hospital mortality within 30 days of hospitalization.

[ISAR Score (Identification of Seniors At Risk) predicts mortality in patients older than 75 years admitted in Intensive Care]

BACKGROUND AND OBJECTIVES

Currently, the patient's baseline situation is a more important prognostic factor than age. The purpose of this study is to estimate the prognostic value of the ISAR score (Identification of Senior at Risk) in patients ≥75 years admitted to intensive care (ICU).

PATIENTS AND METHODS

Prospective multicenter study including patients ≥75 years admitted to the ICU > 24hours. On admission, 28 days and 6 months after discharge from the ICU, mortality and baseline were evaluated using the ISAR score, the Lawton and Brody scale (LB) and the Barthel index (BI), the Frail fragility scale. scale (FS), the Charlson comorbidity index (ICC), Dementia rating score (DRC).

RESULTS

38 of 94 patients (40%) were high risk (ISAR ≥ 3) and were characterized by BI 90 (65-100), LB 4 (3-5), and CDR 1 (0-2), ICC 7.5 (6-10). 58% had FS ≥ 3. In the long term, they were in a situation of dependency [BI 50 (2.5-77.5), LB 3 (0-4), CDR 1 (0-1.5)]. The ICU mortality at 28 days and 6 months was 18.4%, 25.7% and 35.3%, respectively, being statistically significant. The area under the ISAR score ROC curve was 0.749 to 0.797, in all the mortality periods studied, although the difference with other predictive variables was not significant, but the p value was the lowest.

CONCLUSIONS

The ISAR score predicts mortality in critically elderly patients with a discriminative capacity comparable to other predictive variables.

Mortality Predictors and Associated Factors in Patients in the Intensive Care Unit: A Cross-Sectional Study

BACKGROUND

Mortality in the intensive care unit (ICU) has been associated to an array of risk factors. Identification of risk factors potentially contribute to predict and reduce mortality rates in the ICU. The objectives of the study were to determine the prevalence and the factors associated with the mortality and to analyze the survival.

METHOD

A cross-sectional study conducted in two clinical and surgical ICU in the state of Sergipe, northeastern Brazil. We enrolled 316 patients with at least 48 h of hospitalization, minimum age of 18 years old, sedated or weaned, with RASS ≥ -3, between July 2017 and April 2018. We categorized data in (1) age and gender, (2) clinical condition, and (3) prevalence of delirium. Data from enrolled patients were collected from enrollment until death or ICU discharge. Patients' outcomes were categorized in (1) death and (2) nondeath (discharge).

RESULTS

Twenty-one percent of participants died. Age (53 ± 17 years vs. 45 ± 18 years, p < 0.01), electrolyte disturbance (30.3% vs 18.1%, p=0.029), glycemic index (33.3% vs 18.2%, p=0.008), tube feeding (83.3% vs 67.1%, p=0.01), mechanical ventilation (50% vs 35.7%, p=0.035), sedation with fentanyl (24.2 vs 13.6, p=0.035), use of insulin (33.8% vs 21.7%, p=0.042), and higher Charlson score (2.61 vs 2.17, p=0.041) were significantly associated with death on the adjusted model. However, the regression model indicated that patients admitted from the emergency (HR = 0.40, p=0.006) and glycemic index alterations (HR = 1.68, p=0.047) were associated with mortality. There was no statistically significant difference (p=0.540) in survival between patients with and without delirium, based on the survival analysis and length of hospitalization.

CONCLUSION

The prevalence of death was 21%, and age, electrolyte disturbance, glycemic index, tube feeding, mechanical ventilation, sedation with fentanyl, use of insulin, and higher Charlson score were associated with mortality.

A Review of the Development and Application of Generic Preference-Based Instruments with the Older Population

Older people (aged 65 years and over) are the fastest growing age cohort in the majority of developed countries, and the proportion of individuals defined as the oldest old (aged 80 years and over) living with physical frailty and cognitive impairment is rising. These population changes put increasing pressure on health and aged care services, thus it is important to assess the cost effectiveness of interventions targeted for older people across health and aged care sectors to identify interventions with the strongest capacity to enhance older peoples' quality of life and provide value for money. Cost-utility analysis (CUA) is a form of economic evaluation that typically uses preference-based instruments to measure and value health-related quality of life for the calculation of quality-adjusted life-years (QALYS) to enable comparisons of the cost effectiveness of different interventions. A variety of generic preference-based instruments have been used to measure older people's quality of life, including the Adult Social Care Outcomes Toolkit (ASCOT); Health Utility Index Mark 2 (HUI2); Health Utility Index Mark 3 (HUI3); Short-Form-6 Dimensions (SF-6D); Assessment of Quality of Life-6 dimensions (AQoL-6D); Assessment of Quality of Life-8 dimensions (AQoL-8D); Quality of Wellbeing Scale-Self-Administered (QWB-SA); 15 Dimensions (15D); EuroQol-5 dimensions (EQ-5D); and an older person specific preference-based instrument-the Investigating Choice Experiments Capability Measure for older people (ICECAP-O). This article reviews the development and application of these instruments within the older population and discusses the issues surrounding their use with this population. Areas for further research relating to the development and application of generic preference-based instruments with populations of older people are also highlighted.