Long-term survival and quality of life after intensive care for patients 80 years of age or older

Background: Comparison of survival and quality of life in a mixed ICU population of patients 80 years of age or older with a matched segment of the general population. Methods: We retrospectively analyzed survival of ICU patients ≥80 years admitted to the Haukeland University Hospital in 2000–2012. We prospectively used the EuroQol-5D to compare the health-related quality of life (HRQOL) between survivors at follow-up and an age- and gender-matched general population. Follow-up was 1–13.8 years. Results: The included 395 patients (mean age 83.8 years, 61.0 % males) showed an overall survival of 75.9 (ICU), 59.5 (hospital), and 42.0 % 1 year after the ICU. High ICU mortality was predicted by age, mechanical ventilator support, SAPS II, maximum SOFA, and multitrauma with head injury. High hospital mortality was predicted by an unplanned surgical admission. One-year mortality was predicted by respiratory failure and isolated head injury. We found no differences in HRQOL at follow-up between survivors (n = 58) and control subjects (n = 179) or between admission categories. Of the ICU non-survivors, 63.2 % died within 2 days after ICU admission (n = 60), and 68.3 % of these had life-sustaining treatment (LST) limitations. LST limitations were applied for 71.3 % (n = 114) of the hospital non-survivors (ICU 70.5 % (n = 67); post-ICU 72.3 % (n = 47)). Conclusions: Overall 1-year survival was 42.0 %. Survival rates beyond that were comparable to those of the general octogenarian population. Among survivors at follow-up, HRQOL was comparable to that of the age- and sex-matched general population. Patients admitted for planned surgery had better short- and long-term survival rates than those admitted for medical reasons or unplanned surgery for 3 years after ICU admittance. The majority of the ICU non-survivors died within 2 days, and most of these had LST limitation decisions

The good, the bad and the ugly: pandemic priority decisions and triage.

In this analysis we discuss the change in criteria for triage of patients during three different phases of a pandemic like COVID-19, seen from the critical care point of view. Availability of critical care beds has become a hot topic, and in many countries, we have seen a huge increase in the provision of temporary intensive care bed capacity. However, there is a limit where the hospitals may run out of resources to provide critical care, which is heavily dependent on trained staff, just-in-time supply chains for clinical consumables and drugs and advanced equipment. In the first (good) phase, we can still do clinical prioritisation and decision-making as usual, based on the need for intensive care and prognostication: what are the odds for a good result with regard to survival and quality of life. In the next (bad phase), the resources are mostly available, but the system is stressed by many patients arriving over a short time period and auxiliary beds in different places in the hospital being used. We may have to abandon admittance of patients with doubtful prognosis. In the last (ugly) phase, usual medical triage and priority setting may not be sufficient to decrease inflow and there may not be enough intensive care unit beds available. In this phase different criteria must be applied using a utilitarian approach for triage. We argue that this is an important transition where society, and not physicians, must provide guidance to support triage that is no longer based on medical priorities alone

Profit and loss analysis for an intensive care unit (ICU) in Japan: a tool for strategic management

BACKGROUND: Accurate cost estimate and a profit and loss analysis are necessary for health care practice. We performed an actual financial analysis for an intensive care unit (ICU) of a university hospital in Japan, and tried to discuss the health care policy and resource allocation decisions that have an impact on critical intensive care. METHODS: The costs were estimated by a department level activity based costing method, and the profit and loss analysis was based on a break-even point analysis. The data used included the monthly number of patients, the revenue, and the direct and indirect costs of the ICU in 2003. RESULTS: The results of this analysis showed that the total costs of US$2,678,052 of the ICU were mainly incurred due to direct costs of 88.8$ 2,295,044. However, it was determined that the ICU required at least 1,986 patient days within one fiscal year based on a break-even point analysis. As a result, an annual deficit of US$ 383,008 has occurred in the ICU. CONCLUSION: These methods are useful for determining the profits or losses for the ICU practice, and how to evaluate and to improve it. In this study, the results indicate that most ICUs in Japanese hospitals may not be profitable at the present time. As a result, in order to increase the income to make up for this deficit, an increase of 437 patient days in the ICU in one fiscal year is needed, and the number of patients admitted to the ICU should thus be increased without increasing the number of beds or staff members. Increasing the number of patients referred from cooperating hospitals and clinics therefore appears to be the best strategy for achieving these goals

Noninvasive ventilation in COVID-19 patients aged ≥ 70 years-a prospective multicentre cohort study.

BACKGROUND Noninvasive ventilation (NIV) is a promising alternative to invasive mechanical ventilation (IMV) with a particular importance amidst the shortage of intensive care unit (ICU) beds during the COVID-19 pandemic. We aimed to evaluate the use of NIV in Europe and factors associated with outcomes of patients treated with NIV. METHODS This is a substudy of COVIP study-an international prospective observational study enrolling patients aged ≥ 70 years with confirmed COVID-19 treated in ICU. We enrolled patients in 156 ICUs across 15 European countries between March 2020 and April 2021.The primary endpoint was 30-day mortality. RESULTS Cohort included 3074 patients, most of whom were male (2197/3074, 71.4%) at the mean age of 75.7 years (SD 4.6). NIV frequency was 25.7% and varied from 1.1 to 62.0% between participating countries. Primary NIV failure, defined as need for endotracheal intubation or death within 30 days since ICU admission, occurred in 470/629 (74.7%) of patients. Factors associated with increased NIV failure risk were higher Sequential Organ Failure Assessment (SOFA) score (OR 3.73, 95% CI 2.36-5.90) and Clinical Frailty Scale (CFS) on admission (OR 1.46, 95% CI 1.06-2.00). Patients initially treated with NIV (n = 630) lived for 1.36 fewer days (95% CI - 2.27 to - 0.46 days) compared to primary IMV group (n = 1876). CONCLUSIONS Frequency of NIV use varies across European countries. Higher severity of illness and more severe frailty were associated with a risk of NIV failure among critically ill older adults with COVID-19. Primary IMV was associated with better outcomes than primary NIV. Clinical Trial Registration NCT04321265 , registered 19 March 2020, https://clinicaltrials.gov

Reporting of unintended events in an intensive care unit: comparison between staff and observer

BACKGROUND: In order to identify relevant targets for change, it is essential to know the reliability of incident staff reporting. The aim of this study is to compare the incidence and type of unintended events (UE) reported by facilitated Intensive Care Unit (ICU) staff with those recorded concurrently by an observer. METHODS: The study is a prospective data collection performed in two 4-bed multidisciplinary ICUs of a teaching hospital. The format of the UE reporting system was voluntary, facilitated and not necessarily anonymous, and used a structured form with a predetermined list of items. UEs were reported by ICU staff over a period of 4 weeks. The reporting incidence during the first fourteen days was compared with that during the second fourteen. During morning shifts in the second fourteen days, one observer in each ICU recorded any UE seen. The staff was not aware of the observers' study. The incidence of UEs reported by staff was compared with that recorded by the observers. RESULTS: The staff reported 36 UEs in the first fourteen days and 31 in the second.. The incidence of UE detection during morning shifts was significantly higher than during afternoon or night shifts (p < 0.001). Considering only working day morning shifts, the rate of UE reporting by the staff per 100 patient days was 26.9 (CI 95% 16.9–37.0) in the first fourteen day period and 20.3 (CI 95% 10.3–30.4) in the second. The rate of UE detection by the observers was 53.1 per 100 patient days (CI 95% 40.6–65.6), significantly higher (p < 0.001) than that reported concurrently by the staff. There was excellent agreement between staff and observers about the severity of the UEs recorded (Intraclass Correlation Coefficient 0.869). The observers recorded mainly UEs involving Airway/mechanical ventilation and Patient management, and the staff Catheter/Drain/Probe and Medication errors (p = 0.025). CONCLUSION: UE incidence is strongly underreported by staff in comparison with observers. Also the types of UEs reported are different. Invaluable information about incidents in ICU can be obtained in a few days by observer monitoring

Consensus on circulatory shock and hemodynamic monitoring. Task force of the European Society of Intensive Care Medicine.

OBJECTIVE: Circulatory shock is a life-threatening syndrome resulting in multiorgan failure and a high mortality rate. The aim of this consensus is to provide support to the bedside clinician regarding the diagnosis, management and monitoring of shock. METHODS: The European Society of Intensive Care Medicine invited 12 experts to form a Task Force to update a previous consensus (Antonelli et al.: Intensive Care Med 33:575-590, 2007). The same five questions addressed in the earlier consensus were used as the outline for the literature search and review, with the aim of the Task Force to produce statements based on the available literature and evidence. These questions were: (1) What are the epidemiologic and pathophysiologic features of shock in the intensive care unit ? (2) Should we monitor preload and fluid responsiveness in shock ? (3) How and when should we monitor stroke volume or cardiac output in shock ? (4) What markers of the regional and microcirculation can be monitored, and how can cellular function be assessed in shock ? (5) What is the evidence for using hemodynamic monitoring to direct therapy in shock ? Four types of statements were used: definition, recommendation, best practice and statement of fact. RESULTS: Forty-four statements were made. The main new statements include: (1) statements on individualizing blood pressure targets; (2) statements on the assessment and prediction of fluid responsiveness; (3) statements on the use of echocardiography and hemodynamic monitoring. CONCLUSIONS: This consensus provides 44 statements that can be used at the bedside to diagnose, treat and monitor patients with shock

Differences in mortality in critically ill elderly patients during the second COVID-19 surge in Europe

The primary aim of this study was to assess the outcome of elderly intensive care unit (ICU) patients treated during the spring and autumn COVID-19 surges in Europe. This was a prospective European observational study (the COVIP study) in ICU patients aged 70 years and older admitted with COVID-19 disease from March to December 2020 to 159 ICUs in 14 European countries. An electronic database was used to register a number of parameters including: SOFA score, Clinical Frailty Scale, co-morbidities, usual ICU procedures and survival at 90 days. The study was registered at ClinicalTrials.gov (NCT04321265). In total, 2625 patients were included, 1327 from the first and 1298 from the second surge. Median age was 74 and 75 years in surge 1 and 2, respectively. SOFA score was higher in the first surge (median 6 versus 5, p < 0.0001). The PaO/FiO ratio at admission was higher during surge 1, and more patients received invasive mechanical ventilation (78% versus 68%, p < 0.0001). During the first 15 days of treatment, survival was similar during the first and the second surge. Survival was lower in the second surge after day 15 and differed after 30 days (57% vs 50%) as well as after 90 days (51% vs 40%). An unexpected, but significant, decrease in 30-day and 90-day survival was observed during the second surge in our cohort of elderly ICU patients. The reason for this is unclear. Our main concern is whether the widespread changes in practice and treatment of COVID-19 between the two surges have contributed to this increased mortality in elderly patients. Further studies are urgently warranted to provide more evidence for current practice in elderly patients. , registered March 19th, 2020. The online version contains supplementary material available at 10.1186/s13054-021-03739-7

Variations in end-of-life care practices in older critically ill patients with COVID-19 in Europe

BACKGROUND: Previous studies reported regional differences in end-of-life care (EoLC) for critically ill patients in Europe. OBJECTIVES: The purpose of this post-hoc analysis of the prospective multi-centre COVIP study was to investigate variations in EoLC practices among older patients in intensive care units during the coronavirus disease 2019 pandemic. METHODS: A total of 3105 critically ill patients aged 70 years and older were enrolled in this study (Central Europe: n = 1573; Northern Europe: n = 821; Southern Europe: n = 711). Generalised estimation equations were used to calculate adjusted odds ratios (aOR) to population averages. Data were adjusted for patient-specific variables (demographic, disease-specific) and health economic data (GDP, health expenditure per capita). The primary outcome was any treatment limitation, and 90-day-mortality was a secondary outcome. RESULTS: The frequency of the primary endpoint (treatment limitation) was highest in Northern Europe (48%), intermediate in Central Europe (39%), and lowest in Southern Europe (24%). The likelihood for treatment limitations was lower in Southern than in Central Europe (aOR 0.39; 95%CI 0.21-0.73; p = 0.004), even after multivariable adjustment, whereas no statistically significant differences were observed between Northern and Central Europe (aOR 0.57; 95%CI 0.27-1.22; p = 0.15). After multivariable adjustment, no statistically relevant mortality differences were found between Northern and Central Europe (aOR 1.29; 95%CI 0.80-2.09; p = 0.30) or between Southern and Central Europe (aOR 1.07; 95%CI 0.66-1.73; p = 0.78). CONCLUSION: This study shows a north-to-south gradient in rates of treatment limitation in Europe, highlighting the heterogeneity of EoLC practices across countries. However, mortality rates were not affected by these results. This article is protected by copyright. All rights reserved.publishersversionepub_ahead_of_prin