Chewing gum to treat postoperative nausea and vomiting in female patients: a multicenter randomized trial.

BACKGROUND: Postoperative nausea and vomiting (PONV) is common after general anesthesia, with consequences for patient outcomes, satisfaction with care and healthcare costs. Our aim was to compare a new treatment, chewing gum, with a widely-used intravenous agent, ondansetron, to treat PONV in female patients in the post anesthesia care unit (PACU). METHODS: We conducted a multicenter, randomized, controlled non-inferiority trial in 17 hospitals in Australia and New Zealand. Female patients aged ≥12 years undergoing volatile anesthetic-based general anesthesia for laparoscopic or breast surgery were enrolled. Protocolized anti-emetic prophylaxis was administered. Patients who developed PONV in the PACU were randomized to either 15 min of chewing gum or 4 mg of intravenous ondansetron. The primary outcome was cessation of nausea, retching or vomiting, with no recurrence nor rescue medication for 2 h after administration of the randomized intervention (i.e., complete response). RESULTS: Of 865 enrolled patients, 218 were randomized. In a per-protocol analysis, 50 of 105 (47.6%) ondansetron-treated patients compared with 31 of 103 (30.1%) chewing gum-treated patients achieved the primary outcome (absolute risk difference [95% confidence interval (CI)] -17.3 [-30.4 to -4.3] %), not reaching our prespecified non-inferiority limit. Time to complete response was longer for patients randomized to chewing gum (hazard ratio [95% CI] 0.53 [0.34, 0.83]), and they were more likely to receive antiemetics in the 24 h after surgery (absolute risk difference [95% CI] 14.07 [1.65, 26.49]). CONCLUSIONS: Chewing gum cannot be recommended as an alternative to ondansetron for treatment of PONV in female patients administered antiemetic prophylaxis.

Agitation during anaesthetic emergence: An observational study of adult cardiac surgery patients in two Australian intensive care units.

BACKGROUND: Anaesthetic emergence agitation among adult patients being recovered after open cardiac and/or thoracic aorta surgery has not been described. OBJECTIVES: The objective of this study was to characterise emergence agitation in terms of incidence, clinical features, and consequences in a cohort of cardiac surgery patients being recovered in the intensive care unit (ICU). METHODS: A prospective, observational pilot study was implemented. Over a 5-week period, the study was conducted in two metropolitan hospitals in Victoria, Australia. The cohort comprised all patients admitted to the ICUs aged ≥18 years, who had undergone cardiac surgery via an open sternotomy with general anaesthetic, and whose emergence was directly observed. Emergence agitation was defined as a Richmond Agitation and Sedation Scale score of ≥+2. RESULTS: Fifty patients were observed. Emergence agitation occurred in 24/50 (48%) of patients. Patients with emergence agitation experienced more clinical consequences than patients with calm emergence, including a significantly greater number of episodes of airway compromise (12/24, 50%, p < 0.001); ventilator dyssynchrony (23/24, 96%, p = 0.004); and hypertension (13/24, 54%, p = 0.004). Significant treatment interference (potentially dangerous patient movements such as pulling tubes) occurred with 23/24 patients (96%, p < 0.0001). Patients who underwent emergence agitation required significantly more interventions during anaesthetic emergence than patients who underwent a calm emergence. Interventions included extra nursing measures (16/24, 67%, p = 0.001) administration of sedative and/or opioid intravenous boluses (22/24, 92%, p = 0.001) and vasoactive agents (15/24, 63%, p = 0.05). CONCLUSIONS: In patients recovering from cardiac surgery in the ICU, emergence agitation was clinically important. Immediate interventions were required to prevent and manage complications.

Interrater reliability of the Clinical Frailty Scale in the anesthesia preadmission clinic.

PURPOSE: As many as 30% of patients with frailty die, are discharged to a nursing home, or have a new disability after surgery. The 2010 United Kingdom National Confidential Enquiry into Patient Outcome and Death recommended that frailty assessment be developed and included in the routine risk assessment of older surgical patients. The Clinical Frailty Scale (CFS) is a simple, clinically-assessed frailty measure; however, few studies have investigated interrater reliability of the CFS in the surgical setting. The objective of this study was to determine the interrater reliability of frailty classification between anesthesiologists and perioperative nurses. METHODS: We conducted a cohort study assessing interrater reliability of the CFS between perioperative nurses and anesthesiologists for elective surgical patients aged ≥ 65 yr, admitted to a large regional university-affiliated hospital in Australia between July 2020 and February 2021. Agreement was measured via Cohen's kappa. RESULTS: Frailty assessment was conducted on 238 patients with a median [interquartile range] age of 74 [70-80] yr. Agreement was perfect between nursing and medical staff for CFS scores in 112 (47%) patients, with a further 99 (42%) differing by only one point. Interrater kappa was 0.70 (95% confidence interval, 0.63 to 0.77; P < 0.001), suggesting good agreement between anesthesiologists and perioperative nurses. CONCLUSION: This study suggests that CFS assessment by either anesthesiologists or nursing staff is reliable across a population of patients from a range of surgical specialities, with an acceptable degree of agreement. The CFS measurement should be included in the normal preanesthesia clinic workflow.

RéSUMé: OBJECTIF: Jusqu'à 30 % de la patientèle fragilisée meurt, est envoyée dans un centre d'hébergement et de soins de longue durée, ou souffre d'une nouvelle invalidité après la chirurgie. L'enquête nationale confidentielle de 2010 du Royaume-Uni sur les Devenirs et les décès des patient·es (National Confidential Enquiry into Patient Outcome and Death) a recommandé que l'évaluation de la fragilité soit élaborée et incluse dans l'évaluation systématique du risque pour la patientèle chirurgicale âgée. L'échelle de fragilité clinique (EFC) est une mesure de la fragilité simple et évaluée cliniquement; cependant, peu d'études ont examiné la fiabilité interévaluateur·trice de cette échelle en milieu chirurgical. L'objectif de cette étude était de déterminer la fiabilité interévaluateur·trice de la classification de la fragilité entre les anesthésiologistes et le personnel infirmier périopératoire. MéTHODE: Nous avons mené une étude de cohorte évaluant la fiabilité interévaluateur·trice de l'EFC entre le personnel infirmier périopératoire et les anesthésiologistes pour la patientèle de chirurgie non urgente âgée de ≥ 65 ans et admise dans un grand hôpital universitaire régional affilié en Australie entre juillet 2020 et février 2021. La concordance a été mesurée via le coefficient Kappa de Cohen. RéSULTATS: Une évaluation de la fragilité a été réalisée pour 238 patient·es dont l'âge médian [écart interquartile] était de 74 ans [70-80]. La concordance dans les scores sur l'EFC était parfaite entre le personnel infirmier et médical pour 112 (47 %) patient·es, et ne différait que d'un point chez 99 autres (42 %) personnes. Le coefficient Kappa était de 0,70 (intervalle de confiance à 95 %, 0,63 à 0,77; P < 0,001), suggérant une bonne concordance entre les anesthésiologistes et le personnel infirmier périopératoire. CONCLUSION: Cette étude suggère que l'évaluation via l'EFC par des anesthésiologistes ou du personnel infirmier est fiable pour une population de patient·es pris·es en charge par diverses spécialités chirurgicales, avec un degré acceptable de concordance. Cette échelle de mesure devrait être incluse dans le flux de travail normal de la clinique de préanesthésie.

Anaesthetist prediction of postoperative opioid use: a multicentre prospective cohort study.

Background: The Apfel simplified risk score includes four risk factors: female sex, non-smoking status, postoperative nausea and vomiting or motion sickness history, and postoperative opioid use. The score is calculated preoperatively, so postoperative opioid use must be predicted. We aimed to determine whether anaesthetists can predict patients' postoperative opioid use and dose. Methods: Specialist anaesthetists from eight hospitals preoperatively predicted opioid use and dose in the post-anaesthesia care unit (PACU) and for the first 24 h postoperatively, which was compared with actual opioid use and dose. Opioid doses were converted to oral morphine equivalents (MEQ). Correlations between predicted and actual opioid use and dose were analysed with Spearman's rho and linear regression. Results: A total of 487 anaesthetist-patient pairs were included. Anaesthetists overpredicted opioid use (398 [82%] predicted vs 251 [52%] actual patients requiring opioids in the PACU; 396 [81%] predicted vs 291 [60%] actual in the first 24 h) (Spearman's rho [95% confidence interval] 0.24 [0.16-0.33], P<0.001 in the PACU; 0.36 [0.28-0.44], P<0.001 in the first 24 h). Anaesthetists also overpredicted opioid dose (median [inter-quartile range] 12 [8-20] mg predicted MEQ vs 4 [0-18] mg actual MEQ in the PACU; 32 [18-60] mg vs 24 [0-65] mg MEQ in the first 24 h) (Spearman's rho 0.21 [0.13-0.29], P<0.001 in the PACU; 0.53 [0.40-0.60], P<0.001 in the first 24 h). Conclusions: Specialist anaesthetists cannot accurately predict opioid use or dose in the PACU or the first 24 postoperative hours. The Apfel risk criterion for postoperative opioid use may be inaccurate in clinical practice.

A protocol for an international, multicentre pharmacokinetic study for Screening Antifungal Exposure in Intensive Care Units: The SAFE-ICU study.

Objective: To describe whether contemporary dosing of antifungal drugs achieves therapeutic exposures in critically ill patients that are associated with optimal outcomes. Adequate antifungal therapy is a key determinant of survival of critically ill patients with fungal infections. Critical illness can alter an antifungal agents' pharmacokinetics, increasing the risk of inappropriate antifungal exposure that may lead to treatment failure and/or toxicity. Design setting and participants: This international, multicentre, observational pharmacokinetic study will comprise adult critically ill patients prescribed antifungal agents including fluconazole, voriconazole, posaconazole, isavuconazole, caspofungin, micafungin, anidulafungin, and amphotericin B for the treatment or prophylaxis of invasive fungal disease. A minimum of 12 patients are targeted for enrolment for each antifungal agent, across 12 countries and 30 intensive care units to perform descriptive pharmacokinetics. Pharmacokinetic sampling will occur during two dosing intervals (occasions): firstly, between days 1 and 3, and secondly, between days 4 and 7 of the antifungal course, collecting three samples per occasion. Patients' demographic and clinical data will be collected. Main outcome measures: The primary endpoint of the study is attainment of pharmacokinetic/pharmacodynamic target exposures that are associated with optimal efficacy. Thirty-day mortality will also be measured. Results and conclusions: This study will describe whether contemporary antifungal drug dosing achieves drug exposures associated with optimal outcomes. Data will also be used for the development of antifungal dosing algorithms for critically ill patients. Optimised drug dosing should be considered a priority for improving clinical outcomes for critically ill patients with fungal infections.

Vasopressors to treat postoperative hypotension after adult noncardiac, non-obstetric surgery: a systematic review.

BACKGROUND: Postoperative hypotension is common after major surgery and is associated with patient harm. Vasopressors are commonly used to treat hypotension without clear evidence of benefit. We conducted a systematic review to better understand the use, impact, and rationale for vasopressor administration after noncardiac, non-obstetric surgery in adults. METHODS: We conducted a prospectively registered systematic review. Cochrane CENTRAL, EMBASE, MEDBASE, and MEDLINE were searched for RCTs and cohort studies of adult patients receiving vasopressors after noncardiac, non-obstetric surgery. Study quality was critically appraised by two investigators. Findings from the review were synthesised, but formal meta-analysis was not performed because of significant variability in study populations and outcomes. RESULTS: A total of 3201 articles were screened, of which seven RCTs, two prospective cohort studies, and 15 retrospective cohort studies were included in the analysis (24 in total). One study was graded as high quality, two as moderate quality, and the remaining 21 as low quality. Sixteen studies relied on clinical assessment alone to decide on therapeutic interventions. Vasodilation was the most common suggested physiological disturbance. The median proportion of patients receiving vasopressors was 42% (interquartile range: 11.5-74.7%). Norepinephrine was the most common vasopressor used. CONCLUSIONS: The evidence supporting the use of vasopressors to treat postoperative hypotension is limited. Future research should focus on whether vasodilatation or other physiological disturbance is driving postoperative hypotension to allow rational decision-making.

Anaesthetic emergence agitation after cardiac surgery: An intensive care staff survey.

BACKGROUND: Anecdotal reports suggest that during emergence from anaesthesia, some post-cardiac surgery patients exhibit signs of agitation with concerning clinical features, including hypoxaemia, ventilation dysynchrony, and haemodynamic instability. This clinical phenomenon has not been described in the published literature. OBJECTIVE: We aimed to investigate the perceptions and practice of intensive care unit staff members who have managed adult patients after cardiac surgery regarding emergence agitation, its clinical features, and treatment. METHODS: A descriptive survey was conducted from December 2020 to January 2021 in two metropolitan hospitals. Items included Likert scale, multiple-item selection, and free-text responses. RESULTS: There were 144 respondents (response rate: 55%). Post-cardiac surgery emergence agitation was witnessed by 143 respondents (99%). Fifty-seven (40%) reported encountering this clinical problem often. Clinical concerns included instabilities with airway or ventilation (347 items selected), cardiovascular system (189 items selected), and patient treatment interference, such as pulling tubes (229 items selected). Overall, 143 (99%) respondents re-sedated patients with emergence agitation, 138 (96%) added a narcotic bolus, and 121 respondents reported use of mechanical restraints (84%). Twenty-four respondents (2%) recalled receiving any formal anaesthetic emergence education, including after cardiac surgery. CONCLUSION: Anaesthetic emergence agitation following cardiac surgery is a concerning clinical problem. Clinical management of emergence agitation was influenced more by clinical experience than research evidence. Further observational research is required to investigate clinical characteristics and inform evidence-based management practices and education.

Triggers for medical emergency team activation after non-cardiac surgery.

Deterioration after major surgery is common, with many patients experiencing a medical emergency team (MET) activation. Understanding the triggers for MET calls may help design interventions to prevent deterioration. We aimed to identify triggers for MET activation in non-cardiac surgical patients. A retrospective cohort study of adult patients who experienced a postoperative MET call at a single tertiary hospital was undertaken. The trigger and timing of each MET call and patient characteristics were collected.Four hundred and one MET calls occurred after 23,258 surgical procedures, a rate of 1.7% of all non-cardiac surgical procedures, accounting for 11.7% of all MET calls over the study period. Hypotension (41.4%) was the most common trigger, followed by tachycardia (18.5%), altered conscious state (11.0%), hypoxia (10.0%), tachypnoea (5.7%), 'other' (5.7%), clinical concern (4.0%), increased work of breathing (1.5%) and bradypnoea (0.7%). Cardiac and/or respiratory arrest triggered 1.2% of MET activations. Eighty-six percent of patients had a single MET call, 10.2% had two, 1.8% had three and one patient (0.3%) had four. The median interval between post-anaesthetic care unit (PACU) discharge and MET call was 14.7 h (95% confidence interval 4.2 to 28.9 h). MET calls resulted in intensive care unit (ICU) admission in 40 patients (10%), while 82% remained on the ward, 4% had a MET call shortly after ICU discharge and returned there, 2% returned to theatre, and 2% went to a high dependency unit.Hypotension was the most common trigger for MET calls after non-cardiac surgery. Deterioration frequently occurred within 24 h of PACU discharge. Future research should focus on prevention of hypotension and tachycardia after surgery.

Characteristics and Outcomes of Very Elderly Patients Admitted to Intensive Care: A Retrospective Multicenter Cohort Analysis.

OBJECTIVES: To characterize and compare trends in ICU admission, hospital outcomes, and resource utilization for critically ill very elderly patients (≥ 80 yr old) compared with the younger cohort (16-79 yr old). DESIGN: A retrospective multicenter cohort study. SETTING: One-hundred ninety-four ICUs contributing data to the Australian and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation Adult Patient Database between January 2006 and December 2018. PATIENTS: Adult (≥ 16 yr) patients admitted to Australian and New Zealand ICUs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Very elderly patients with a mean ± sd age of 84.8 ± 3.7 years accounted for 14.8% (232,582/1,568,959) of all adult ICU admissions. They had higher comorbid disease burden and illness severity scores compared with the younger cohort. Hospital (15.4% vs 7.8%, p < 0.001) and ICU mortality (8.5% vs 5.2%, p < 0.001) were higher in the very elderly. They stayed fewer days in ICU, but longer in hospital and had more ICU readmissions. Among survivors, a lower proportion of very elderly was discharged home (65.2% vs 82.4%, p < 0.001), and a higher proportion was discharged to chronic care/nursing home facilities (20.1% vs 7.8%, p < 0.001). Although there was no change in the proportion of very elderly ICU admissions over the study period, they showed a greater decline in risk-adjusted mortality (6.3% [95% CI, 5.9%-6.7%] vs 4.0% [95% CI, 3.7%-4.2%] relative reduction per year, p < 0.001) compared with the younger cohort. The mortality of very elderly unplanned ICU admissions improved faster than the younger cohort ( p < 0.001), whereas improvements in mortality among elective surgical ICU admissions were similar in both groups ( p = 0.45). CONCLUSIONS: The proportion of ICU admissions greater than or equal to 80 years old did not change over the 13-year study period. Although their mortality was higher, they showed improved survivorship over time, especially in the unplanned ICU admission subgroup. A higher proportion of survivors were discharged to chronic care facilities.

The Clinical Frailty Scale for mortality prediction of old acutely admitted intensive care patients: a meta-analysis of individual patient-level data.

BACKGROUND: This large-scale analysis pools individual data about the Clinical Frailty Scale (CFS) to predict outcome in the intensive care unit (ICU). METHODS: A systematic search identified all clinical trials that used the CFS in the ICU (PubMed searched until 24th June 2020). All patients who were electively admitted were excluded. The primary outcome was ICU mortality. Regression models were estimated on the complete data set, and for missing data, multiple imputations were utilised. Cox models were adjusted for age, sex, and illness acuity score (SOFA, SAPS II or APACHE II). RESULTS: 12 studies from 30 countries with anonymised individualised patient data were included (n = 23,989 patients). In the univariate analysis for all patients, being frail (CFS ≥ 5) was associated with an increased risk of ICU mortality, but not after adjustment. In older patients (≥ 65 years) there was an independent association with ICU mortality both in the complete case analysis (HR 1.34 (95% CI 1.25-1.44), p < 0.0001) and in the multiple imputation analysis (HR 1.35 (95% CI 1.26-1.45), p < 0.0001, adjusted for SOFA). In older patients, being vulnerable (CFS 4) alone did not significantly differ from being frail. After adjustment, a CFS of 4-5, 6, and ≥ 7 was associated with a significantly worse outcome compared to CFS of 1-3. CONCLUSIONS: Being frail is associated with a significantly increased risk for ICU mortality in older patients, while being vulnerable alone did not significantly differ. New Frailty categories might reflect its "continuum" better and predict ICU outcome more accurately. TRIAL REGISTRATION: Open Science Framework (OSF: https://osf.io/8buwk/ ).

Sex differences in long-term survival after intensive care unit treatment for sepsis: A cohort study.

OBJECTIVE: To determine the effect of sex on sepsis-related ICU admission and survival for up to 3-years. METHODS: Retrospective cohort study of adults admitted to Australian ICUs between 2018 and 2020. Men and women with a primary diagnosis of sepsis were included. The primary outcome of time to death for up to 3-years was examined using Kaplan Meier plots. Secondary outcomes included the duration of ICU and hospital stay. RESULTS: Of 523,576 admissions, there were 63,039 (12·0%) sepsis-related ICU admissions. Of these, there were 50,956 patients (43·4% women) with 3-year survival data. Men were older (mean age 66·5 vs 63·6 years), more commonly received mechanical ventilation (27·4% vs 24·7%) and renal replacement therapy (8·2% vs 6·8%) and had worse survival (Hazard Ratio [HR] 1·11; 95% Confidence Interval [CI] 1·07 to 1·14, P<0·001) compared to women. The duration of hospital and ICU stay was longer for men, compared to women (median hospital stay, 9.8 vs 9.4 days; p<0.001 and ICU stay, 2.7 vs 2.6 days; p<0.001). CONCLUSION: Men are more likely to be admitted to ICU with sepsis and have worse survival for up to 3-years. Understanding causal mechanisms of sex differences may facilitate the development of targeted sepsis strategies.

Comparing the Clinical Frailty Scale and an International Classification of Diseases-10 Modified Frailty Index in Predicting Long-Term Survival in Critically Ill Patients.

The Clinical Frailty Scale (CFS) is the most used frailty measure in intensive care unit (ICU) patients. Recently, the modified frailty index (mFI), derived from 11 comorbidities has also been used. It is unclear to what degree the mFI is a true measure of frailty rather than comorbidity. Furthermore, the mFI cannot be freely obtained outside of specific proprietary databases. OBJECTIVE: To compare the performance of CFS and a recently developed International Classification of Diseases-10 (ICD-10) mFI (ICD-10mFI) as frailty-based predictors of long-term survival for up to 1 year. DESIGN: A retrospective multicentric observational study. SETTING AND PARTICIPANTS: All adult (≥16 yr) critically ill patients with documented CFS scores admitted to sixteen Australian ICUs in the state of Victoria between April 1, 2017 to June 30, 2018 were included. We used probabilistic methods to match de-identified ICU admission episodes listed in the Australia and New Zealand Intensive Care Society Adult Patient Database with the Victorian Admission Episode Dataset and the Victorian Death Index via the Victorian Data Linkage Centre. MAIN OUTCOMES AND MEASURES: The primary outcome was the longest available survival following ICU admission. We compared CFS and ICD-10mFI as primary outcome predictors, after adjusting for key confounders. RESULTS: The CFS and ICD-10mFI were compared in 7,001 ICU patients. The proportion of patients categorized as frail was greater with the CFS than with the ICD-10mFI (18.9% [n = 1,323] vs. 8.8% [n = 616]; p < 0.001). The median (IQR) follow-up time was 165 (82-276) days. The CFS predicted long-term survival up to 6 months after adjusting for confounders (hazard ratio [HR] = 1.26, 95% CI, 1.21-1.31), whereas ICD-10mFI did not (HR = 1.04, 95% CI, 0.98-1.10). The ICD-10mFI weakly correlated with the CFS (Spearman's rho = 0.22) but had a poor agreement (kappa = 0.06). The ICD-10mFI more strongly correlated with the Charlson comorbidity index (Spearman's rho 0.30) than CFS (Spearman's rho = 0.25) (p < 0.001). CONCLUSIONS: CFS, but not ICD-10mFI, predicted long-term survival in ICU patients. ICD-10mFI correlated with co-morbidities more than CFS. These findings suggest that CFS and ICD-10mFI are not equivalent. RELEVANCE: CFS and ICD-10mFI are not equivalent in screening for frailty in critically ill patients and therefore ICD-10mFI in its current form should not be used.

Defining ICD-10 surrogate variables to estimate the modified frailty index: a Delphi-based approach.

BACKGROUND: There are currently no validated globally and freely available tools to estimate the modified frailty index (mFI). The widely available and non-proprietary International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) coding could be used as a surrogate for the mFI. We aimed to establish an appropriate set of the ICD-10 codes for comorbidities to be used to estimate the eleven-variable mFI. METHODS: A three-stage, web-based, Delphi consensus-building process among a panel of intensivists and geriatricians using iterative rounds of an online survey, was conducted between March and July 2021. The consensus was set a priori at 75% overall agreement. Additionally, we assessed if survey responses differed between intensivists and geriatricians. Finally, we ascertained the level of agreement. RESULTS: A total of 21 clinicians participated in all 3 Delphi surveys. Most (86%, 18/21) had more than 5-years' experience as specialists. The agreement proportionately increased with every Delphi survey. After the third survey, the panel had reached 75% consensus in 87.5% (112/128) of ICD-10 codes. The initially included 128 ICD-10 variables were narrowed down to 54 at the end of the 3 surveys. The inter-rater agreements between intensivists and geriatricians were moderate for surveys 1 and 3 (κ = 0.728, κ = 0.780) respectively, and strong for survey 2 (κ = 0.811). CONCLUSIONS: This quantitative Delphi survey of a panel of experienced intensivists and geriatricians achieved consensus for appropriate ICD-10 codes to estimate the mFI. Future studies should focus on validating the mFI estimated from these ICD-10 codes. TRIAL REGISTRATION: Not applicable.

Impact of frailty on persistent critical illness: a population-based cohort study.

PURPOSE: Acute illness severity predicts mortality in intensive care unit (ICU) patients, however, its predictive value decreases over time in ICU. Typically after 10 days, pre-ICU (antecedent) characteristics become more predictive of mortality, defining the onset of persistent critical illness (PerCI). How patient frailty affects development and death from PerCI is unknown. METHODS: We conducted a secondary analysis of data from a prospective binational cohort study including 269,785 critically ill adults from 168 ICUs in Australia and New Zealand, investigating whether frailty measured with the Clinical Frailty Scale (CFS) changes the timing of onset and risk of developing PerCI and of subsequent in-hospital mortality. We assessed associations between frailty (CFS ≥ 5) and mortality prediction using logistic regression and area under the receiver operating characteristics (AUROC) curves. RESULTS: 2190 of 50,814 (4.3%) patients with frailty (CFS ≥ 5) versus 6624 of 218,971 (3%) patients without frailty (CFS ≤ 4) developed PerCI (P < 0.001). Among patients with PerCI, 669 of 2190 (30.5%) with frailty and 1194 of 6624 without frailty (18%) died in hospital (P < 0.001). The time point defining PerCI onset did not vary with frailty degree; however, with increasing length of ICU stay, inclusion of frailty progressively improved mortality discrimination (0.1% AUROC improvement on ICU day one versus 3.6% on ICU day 17). CONCLUSION: Compared to patients without frailty, those with frailty have a higher chance of developing and dying from PerCI. Moreover the importance of frailty as a predictor of mortality increases with ICU length of stay. Future work should explore incorporation of frailty in prognostic models, particularly for long-staying patients.

The Relationship between Frailty and Mechanical Ventilation: A Population-based Cohort Study.

Rationale: Frailty in critically ill patients is associated with higher mortality and prolonged length of stay; however, little is known about the impact on the duration of mechanical ventilation. Objectives: To identify the relationship between frailty and total duration of mechanical ventilation and the interaction with patients' age. Methods: This retrospective population-based cohort study was performed using data submitted to the Australian and New Zealand Intensive Care Society Adult Patient Database between 2017 and 2020. We analyzed adult critically ill patients who received invasive mechanical ventilation within the first 24 hours of intensive care unit admission. Results: Of 59,319 available patients receiving invasive mechanical ventilation, 8,331 (14%) were classified as frail. Patients with frailty had longer duration of mechanical ventilation compared with patients without frailty. Duration of mechanical ventilation increased with higher frailty score. Patients with frailty had longer intensive care unit and hospital stay with higher mortality than patients without frailty. After adjustment for relevant covariates in multivariate analyses, frailty was significantly associated with a reduced probability of cessation of invasive mechanical ventilation (adjusted hazard ratio, 0.57 [95% confidence interval, 0.51-0.64]; P < 0.001). Sensitivity and subgroup analyses suggested that frailty could prolong mechanical ventilation in survivors, and the relationship was especially strong in younger patients. Conclusions: Frailty score was independently associated with longer duration of mechanical ventilation and contributed to identifying patients who were less likely to be liberated from mechanical ventilation. The impact of frailty on ventilation time varied with age and was most apparent for younger patients.