Figure - available via license: CC BY
Content may be subject to copyright.
Fraction of new prognostic information from including frailty in the model

Fraction of new prognostic information from including frailty in the model

Source publication
Article
Full-text available
Background: The Clinical Frailty Scale (CFS) is frequently used to measure frailty in critically ill adults. There is wide variation in the approach to analysing the relationship between the CFS score and mortality after admission to the ICU. This study aimed to evaluate the influence of modelling approach on the association between the CFS score...

Context in source publication

Context 1
... fraction of new information from the categorical CFS score over and above data on patient's age, sex, reason for admission to the ICU, and the SOFA score across different modelling strategies is shown in Table 2. ...

Similar publications

Article
Full-text available
Background Corticosteroids are part of the treatment guidelines for COVID-19 and have been shown to improve mortality. However, the impact corticosteroids have on the development of secondary infection in COVID-19 is unknown. We sought to define the rate of secondary infection in critically ill patients with COVID-19 and determine the effect of cor...

Citations

... Due to multimorbidity and frailty, critically ill elderly patients have a particularly poor prognosis [13]. Similar analyses among patients with COVID-19 confirmed that increasing age and degree of frailty are related to worse outcomes in this population [14]. ...
Article
Full-text available
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 .
... Respiratory disorders caused by bronchial and pulmonary lesions in patients with respiratory diseases may lead to hypoxia during transport, resulting in the decrease of SpO 2 in patients. In addition, some patients can maintain their normal blood oxygen saturation during rest, but hypoxemia often occurs during walking, sleeping, or exercise [11]. Changes in position during transfer and movement may lead to changes in breathing patterns and psychological changes, resulting in dizziness, palpitations, shortness of breath, and other symptoms [12]. ...
Article
Full-text available
Objective: Multivariate logistic analysis was employed to explore the risk factors of safety risks in the transport of critically ill patients with ICU and the improvement of nursing strategies. Methods: Two hundred critical transport patients with ICU treated in our hospital from January 2019 to April 2021 were enrolled. According to the occurrence of unsafe events in transit, the patients were assigned to the control group (165 cases without unsafe events, n = 165) and the study group (35 cases with safety incidents, n = 35). Multivariate logistic analysis was employed to explore the risk factors of safety risks in the transport of critically ill patients with ICU and to enhance nursing strategies. Results: (1) General data of the subjects: among the 200 critically ill patients with ICU who needed in-hospital transport, the age ranged from 18 to 85 years with an average age of 52.48 ± 3.31, including 89 males and 111 females. There were 35 cases of gastrointestinal bleeding, 16 cases of respiratory failure, 23 cases of heart failure, 43 cases of myocardial infarction, 26 cases of cerebrovascular accident, 14 cases of ectopic pregnancy, 25 cases of severe injury, and 18 cases of mechanical ventilation. There were 35 cases in the study group with accidents and 45 cases in group B without accidents. (2) Among the 200 patients, 35 patients had complications during the transit process in the intermediate people's court, with an incidence rate of 17.5%. It included blood pressure fluctuation (n = 6), artificial airway obstruction (n = 6), decrease in blood oxygen saturation (n = 10), dyspnea (n = 5), fall pain (n = 3), elevated intracranial pressure (n = 2), and other factors (n = 3). There exhibited no significant difference in blood oxygen saturation at each time point during transport (P > 0.05). There exhibited no significant difference in SpO2 before transport. The comparison of 5 min and 10 min blood oxygen saturation during transit in the study group was lower compared to the control group (P < 0.05). (3) In a univariate analysis of safety risks for critically ill ICU patients, home escorts did not show significant differences in hospital transport for critically ill ICU patients (P > 0.05). There were significant differences in terms of age, patient's condition, transport escort, auxiliary ventilation, means of transport, uncarried drugs and goods, and carrying pipeline (P < 0.05). The results of multivariate logistic regression analysis indicated that age, patient's condition, transport escort, auxiliary ventilation, means of transport, uncarried drugs and goods, and carrying pipeline were the risk factors affecting the safe transport of critically ill patients (P < 0.05). Conclusion: Age, patient's condition, transport escort, auxiliary ventilation, means of transport, uncarried drugs and goods, and carrying pipeline are the independent risk factors that affect the safe transport of emergency or ICU critically ill patients. Therefore, in order to reduce the risk of transshipment, we must enhance the safety awareness of escorts, strengthen the management and training of escorts, promote rules and regulations, and formulate dangerous plans, so as to eliminate the occurrence of unsafe factors.
... The frailty level prior to the acute illness and hospital admission was assessed using the CFS version 1.0 [15,16]. The CFS defines nine classes from very fit to terminally ill (1-9). ...
Article
Full-text available
Purpose: The number of patients ≥ 80 years admitted into critical care is increasing. Coronavirus disease 2019 (COVID-19) added another challenge for clinical decisions for both admission and limitation of life-sustaining treatments (LLST). We aimed to compare the characteristics and mortality of very old critically ill patients with or without COVID-19 with a focus on LLST. Methods: Patients 80 years or older with acute respiratory failure were recruited from the VIP2 and COVIP studies. Baseline patient characteristics, interventions in intensive care unit (ICU) and outcomes (30-day survival) were recorded. COVID patients were matched to non-COVID patients based on the following factors: age (± 2 years), Sequential Organ Failure Assessment (SOFA) score (± 2 points), clinical frailty scale (± 1 point), gender and region on a 1:2 ratio. Specific ICU procedures and LLST were compared between the cohorts by means of cumulative incidence curves taking into account the competing risk of discharge and death. Results: 693 COVID patients were compared to 1393 non-COVID patients. COVID patients were younger, less frail, less severely ill with lower SOFA score, but were treated more often with invasive mechanical ventilation (MV) and had a lower 30-day survival. 404 COVID patients could be matched to 666 non-COVID patients. For COVID patients, withholding and withdrawing of LST were more frequent than for non-COVID and the 30-day survival was almost half compared to non-COVID patients. Conclusion: Very old COVID patients have a different trajectory than non-COVID patients. Whether this finding is due to a decision policy with more active treatment limitation or to an inherent higher risk of death due to COVID-19 is unclear.
... However, no simple index usable in an emergency department has been validated to date, except the frailness score CSH [23]. However, more than 60% of patients aged 85 and above are classified as "frail" [11,24]. Therefore, these indices are not particularly discriminating for this age group. ...
Article
Elderly patients (over age 85) are increasingly treated in Intensive Care Units (ICU), despite doctors' reluctance to accept these frail patients. There are only few studies describing the relevance of treatments for this group of patients in ICU. One of these studies defined an age of 85 or over as the essential admittance criterion. Exclusion criteriwere low autonomy before admittance or an inability to answer the phone. Epidemiological data, history, lifestyle, and autonomy (ADL score of six items) were recorded during admission to the ICU and by phone interviews six months later. Eight French ICUs included 239 patients aged over 85. The most common diagnostics were non-cardiogenic lung disease (36%), severe sepsis/septic shock (29%), and acute pulmonary oedem (28%). Twenty-three percent of patients were dependent at the time of their admission. Seventy-one percent of patients were still alive when released from ICU, and 52% were still alive after 6 months. Among the patients which were non-dependent before hospitalization, 17% became dependent. The only prognostic criterifound were the SAPS II score on admission and the place of residence before admission (nursing home or family environment had poor prognosis). Although the prognosis of these elderly patients was good after hospitalization in ICU, it should be noted that the population was carefully selected as having few comorbidities or dependence. No triage critericould be suggested.
Chapter
To discuss the major challenges hospitals and ICUs are faced with during prolonged periods of increased morbidity and demand.To discuss the importance of flexibility in resource allocation during increasing and decreasing demand.To understand the importance of prioritization at a national, regional, and institutional level.To discuss options for increasing availability of personnel and equipmentTo understand the importance of staff safety, protection, and reducing burnoutTo increase pre and post ICU capabilitiesTo improve triage decisions in the elderly populationTo plan for future events based on past experience To discuss the major challenges hospitals and ICUs are faced with during prolonged periods of increased morbidity and demand. To discuss the importance of flexibility in resource allocation during increasing and decreasing demand. To understand the importance of prioritization at a national, regional, and institutional level. To discuss options for increasing availability of personnel and equipment To understand the importance of staff safety, protection, and reducing burnout To increase pre and post ICU capabilities To improve triage decisions in the elderly population To plan for future events based on past experience