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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 [greater than or equal to] 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 [greater than or equal to] 5) versus 6624 of 218,971 (3%) patients without frailty (CFS [less than or equal to] 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., Author(s): Jai N. Darvall [sup.1] [sup.2], Rinaldo Bellomo [sup.1] [sup.2] [sup.3] [sup.4], Michael Bailey [sup.3], Paul J. Young [sup.2] [sup.3] [sup.5] [sup.6], Kenneth Rockwood [sup.7], David Pilcher [sup.3] [sup.8] [sup.9] [...]

BackgroundObesity in pregnancy is a growing problem worldwide, with excessive gestational weight gain (GWG) occurring in the majority of pregnancies. This significantly increases risks to both mother and child. A major contributor to both prepregnancy obesity and excessive GWG is physical inactivity; however, past interventions targeting maternal weight gain and activity levels during the antenatal period have been ineffective in women who are already overweight. Pedometer-guided activity may offer a novel solution for increasing activity levels in this population. ObjectiveThis initial feasibility randomized controlled trial aimed to test a pedometer-based intervention to increase activity and reduce excessive GWG in pregnant women. MethodsWe supplied 30 pregnant women with obesity a Fitbit Zip pedometer and randomized them into 1 of 3 groups: control (pedometer only), app (pedometer synced to patients’ personal smartphone, with self-monitoring of activity), or app-coach (addition of a health coach–delivered behavioral change program). Feasibility outcomes included participant compliance with wearing pedometers (days with missing pedometer data), data syncing, and data integrity. Activity outcomes (step counts and active minutes) were analyzed using linear mixed models and generalized estimating equations. ResultsA total of 30 participants were recruited within a 10-week period, with a dropout rate of 10% (3/30; 2 withdrawals and 1 stillbirth); 27 participants thus completed the study. Mean BMI in all groups was ≥35 kg/m2. Mean (SD) percentage of missing data days were 23.4% (20.6%), 39.5% (32.4%), and 21.1% (16.0%) in control, app group, and app-coach group patients, respectively. Estimated mean baseline activity levels were 14.5 active min/day and 5455 steps/day, with no significant differences found in activity levels between groups, with mean daily step counts in all groups remaining in the sedentary (5000 steps/day) or low activity (5000-7499 steps/day) categories for the entire study duration. There was a mean decrease of 7.8 steps/day for each increase in gestation day over the study period (95% CI 2.91 to 12.69, P=.002). ConclusionsActivity data syncing with a personal smartphone is feasible in a cohort of pregnant women with obesity. However, our results do not support a future definitive study in its present form. Recruitment and retention rates were adequate, as was activity data syncing to participants’ smartphones. A follow-up interventional trial seeking to reduce GWG and improve activity in this population must focus on improving compliance with activity data recording and behavioral interventions delivered. Trial RegistrationAustralian and New Zealand Clinical Trials Registry ACTRN12617000038392; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370884

The article discusses the challenges faced by surgeons due to the backlog of elective surgeries caused by the COVID-19 pandemic. It suggests that this situation presents an opportunity to reevaluate the role and expectations of surgery. The article highlights the need for evidence-driven surgery and mentions that some operations may not be more beneficial than non-surgical alternatives. It also discusses the impact of technological advancements on the cost of surgery and emphasizes the importance of balancing technological progress with limited resources. The article calls for system-wide changes, patient-centered approaches, and improved health literacy to ensure the best outcomes for patients. [Extracted from the article]

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. [ABSTRACT FROM AUTHOR]

Background: Frailty is associated with poor outcomes in critical illness. However, it is unclear whether frailty screening on admission to the ICU can be conducted routinely at the population level and whether it has prognostic importance.Research Question: Can population-scale frailty screening with the Clinical Frailty Scale (CFS) be implemented for critically ill adults in Australia and New Zealand (ANZ) and can it identify patients at risk of negative outcomes?Study Design and Methods: We conducted a binational prospective cohort study of critically ill adult patients admitted between July 1, 2018, and June 30, 2020, in 175 ICUs in ANZ. We classified frailty with the CFS on admission to the ICU. The primary outcome was in-hospital mortality; secondary outcomes were length of stay (LOS), discharge destination, complications (delirium, pressure injury), and duration of survival.Results: We included 234,568 critically ill patients; 45,245 (19%) were diagnosed as living with frailty before ICU admission. Patients with vs without frailty had higher in-hospital mortality (16% vs 5%; P < .001), delirium (10% vs 4%; P < .001), longer LOS in the ICU and hospital, and increased new chronic care discharge (3% vs 1%; P < .001), with worse outcomes associated with increasing CFS category. Of patients with very severe frailty (CFS score, 8), 39% died in hospital vs 2% of very fit patients (CFS score, 1; multivariate categorical CFS score, 8 [reference, 1]; OR, 7.83 [95% CI, 6.39-9.59]; P < .001). After adjustment for illness severity, frailty remained highly significantly predictive of mortality, including among patients younger than 50 years, with improvement in the area under the receiver operating characteristic curve of the Acute Physiology and Chronic Health Evaluation III-j score to 0.882 (95% CI, 0.879-0.885) from 0.868 (95% CI, 0.866-0.871) with the addition of frailty (P < .001).Interpretation: Large-scale population screening for frailty degree in critical illness was possible and prognostically important, with greater frailty (especially CFS score of ≥ 6) associated with worse outcomes, including among younger patients. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has led to unprecedented demand for ICUs, with the need to triage admissions along with the development of ICU triage criteria. However, how these criteria relate to outcomes in patients already admitted to the ICU is unknown, as is the incremental ICU capacity that triage of these patients might create given existing admission practices.Research Question: What is the short- and long-term survival of low- vs high-priority patients for ICU admission according to current pandemic triage criteria?Study Design and Methods: This study analyzed prospectively collected registry data (2007-2018) in 23 ICUs in Victoria, Australia, with probabilistic linkage with death registries. After excluding elective surgery, admissions were stratified according to existing ICU triage protocol prioritization as low (age ≥ 85 years, or severe chronic illness, or Sequential Organ Failure Assessment [SOFA] score = 0 or ≥ 12), medium (SOFA score = 8-11) or high (SOFA score = 1-7) priority. The primary outcome was long-term survival. Secondary outcomes were in-hospital mortality, ICU length of stay (LOS) and bed-day usage.Results: This study examined 126,687 ICU admissions. After 5 years of follow-up, 1,093 of 3,296 (33%; 95% CI, 32-34) of "low-priority" patients aged ≥ 85 years or with severe chronic illness and 86 of 332 (26%; 95% CI, 24-28) with a SOFA score ≥ 12 were still alive. Sixty-three of 290 (22%; 95% CI, 17-27) of patients in these groups followed up for 10 years were still alive. Together, low-priority patients accounted for 27% of all ICU bed-days and had lower in-hospital mortality (22%) than the high-priority patients (28%). Among nonsurvivors, low-priority admissions had shorter ICU LOS than medium- or high-priority admissions.Interpretation: Current SOFA score or age or severe comorbidity-based ICU pandemic triage protocols exclude patients with a close to 80% hospital survival, a > 30% five-year survival, and 27% of ICU bed-day use. These findings imply the need for stronger evidence-based ICU triage protocols. [ABSTRACT FROM AUTHOR]

BACKGROUND/OBJECTIVES: Frailty is common in surgical and intensive care unit (ICU) populations, yet it is not routinely measured. Frailty indices are able to quantify this condition across a range of health deficits. We aimed to develop a frailty index (FI) from routinely collected hospital data in a surgical and ICU population. DESIGN: Prospective observational single‐center cohort study. SETTING: Tertiary referral metropolitan Australian hospital. PARTICIPANTS: A total of 336 individuals aged 65 and older undergoing surgery or aged 50 and older admitted to the ICU. MEASUREMENTS: Routine admission health data were used to derive an FI comprising 36 health deficits. We examined the FI correlation with existing frailty tools (Clinical Frailty Scale [CFS] and Edmonton Frail Scale [EFS]) and assessed its predictive ability for negative outcomes including 30‐day mortality. RESULTS: Median FI was.17 (interquartile range [IQR]) =.10–.24) for ICU patients and.17 (IQR =.11–.25) for surgical patients; maximum FI was.58, and 25% (95% confidence interval [CI] = 10.4–29.6) of patients overall were diagnosed with frailty (FI score ≥.25). Correlation was strong between the FI and the EFS: ρ =.76 (95% CI =.70–.83) for ICU patients and.71 (95% CI =.64–.78) for surgical patients, and the CFS was.77 (95% CI =.70–.84) for ICU patients and.72 (95% CI =.65–.79) for surgical patients. The FI had good discriminative ability for prediction of 30‐day mortality in ICU patients (multivariate odds ratio for each increase in FI of.1 = 2.04 [95% CI = 1.19–3.48]), comparable with the performance of the Acute Physiology and Chronic Health Evaluation III score (ICU patients) and the Portsmouth Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity score (surgical patients). CONCLUSION: It is feasible to construct an FI from hospital admission data in a cohort of critically ill and surgical patients. [ABSTRACT FROM AUTHOR]

A large volume of literature has become available to practitioners prescribing anticoagulants. The aim of this study was to analyze the bibliometric characteristics of the top 100 most cited articles related to anticoagulation over the past 25 years, with special consideration to impact of direct or "nonvitamin K antagonist" oral anticoagulants (NOACs) compared with vitamin K antagonists. A bibliometric analysis of the 100 most cited journal articles related to anticoagulants published between 1994 and 2019 was performed in April 2019. The top 100 articles by citation count were analyzed to extract bibliometric data related to journal title, impact factor, year of publication, place of publication, anticoagulant studied, indication for anticoagulation, study design, and conflicts of interest. The median (interquartile range) number of citations per article was 806 (621–1,085). The anticoagulant most frequently researched was warfarin (37%). NOAC publications (21%) grew at a relative rate of 3.4 times faster compared with all publications. The indication most commonly researched was venous thromboembolism (26%). Eighty articles constituted level I or II evidence, with randomized controlled trials the most common type of study (74). A financial conflict of interest was declared in 87% of articles with private, for-profit organizations the most common source of funding (26%). In summary, top research related to anticoagulation is highly impactful but may be at risk of sponsorship bias. High-level evidence for NOACs continues to expand across a range of indications with citation metrics likely to soon approach or surpass that of older drugs. [ABSTRACT FROM AUTHOR]

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Objective: To explore associations between frailty (Clinical Frailty Scale score of 5 or more) in very old patients in intensive care units (ICUs) and their clinical outcomes (mortality, discharge destination).Design, Setting and Participants: Retrospective population cohort analysis of Australian and New Zealand Intensive Care Society (ANZICS) Adult Patient Database data for all patients aged 80 years or more admitted to participating ICUs between 1 January 2017 and 31 December 2018.Main Outcome Measures: Primary outcome: in-hospital mortality; secondary outcomes: length of stay (hospital, ICU), re-admission to ICU during the same hospital admission, discharge destination (including new chronic care or nursing home admission).Results: Frailty status data were available for 15 613 of 45 773 patients aged 80 years or more admitted to 178 ICUs (34%); 6203 of these patients (39.7%) were deemed frail. A smaller proportion of frail than non-frail patients were men (47% v 57%), the mean illness severity scores of frail patients were slightly higher than those of non-frail patients, and they were more frequently admitted from the emergency department (28% v 21%) or with sepsis (12% v 7%) or respiratory complications (16% v 12%). In-hospital mortality was higher for frail patients (17.6% v 8.2%; adjusted odds ratio [OR], 1.87 [95% CI, 1.65-2.11]). Median lengths of ICU and hospital stay were slightly longer for frail patients, and they were more frequently discharged to new nursing home or chronic care (4.9% v 2.8%; adjusted OR, 1.61 [95% CI, 1.34-1.95]).Conclusions: Many very old critically ill patients in Australia and New Zealand are frail, and frailty is associated with considerably poorer health outcomes. Routine screening of older ICU patients for frailty could improve outcome prediction and inform intensive care and community health care planning. [ABSTRACT FROM AUTHOR]

Frailty is one of the major challenges for intensive care, affecting one-third of intensive care unit patients and being associated with a range of poor health outcomes. Determination of frailty in critical illness using the Clinical Frailty Scale has recently been adopted by the Australian and New Zealand Intensive Care Society, but it is not known whether this is able to be measured from the clinical record without interviewing patients or their relatives. The aims of this retrospective cohort study were to test whether a Clinical Frailty Scale score could be assigned in an intensive care unit population from the clinical record, and to assess the inter-rater reliability of frailty measured in this manner. A total of 144 patients were enrolled. Of these, 137 (95%) were able to have a Clinical Frailty Scale score assigned, and 22 (15%) were scored as frail (Clinical Frailty Scale ≥5). Cohen's kappa coefficient for inter-rater reliability between assessors was 0.67, confirming substantial agreement. Consistent with other critically ill cohorts, frailty was associated on multivariate analysis with age, Charlson comorbidity score, dependence with activities of daily living, and limitation of medical treatment, indicating validity of this approach to frailty measurement. Our results imply that frailty measurement is possible and feasible from the intensive care unit clinical record, which is of importance as routine measurement and reporting of frailty in intensive care units in our region increases. Future work should seek to validate an assigned Clinical Frailty Scale score with that obtained directly from patients or their next of kin. [ABSTRACT FROM AUTHOR]

Introduction Frailty is of increasing importance to perioperative and critical care medicine, as the proportion of older patients increases globally. Evidence continues to emerge of the considerable impact frailty has on adverse outcomes from both surgery and critical care, which has led to a proliferation of different frailty measurement tools in recent years. Despite this, there remains a lack of easily implemented, comprehensive frailty assessment tools specific to these complex populations. Development of a frailty index using routinely collected hospital data, able to leverage the automated aspects of an electronic medical record, would aid risk stratification and benefit clinicians and patients alike. Methods and analysis This is a prospective observational study. 150 intensive care unit (ICU) patients aged =50 years and 200 surgical patients aged =65 years will be enrolled. The primary objective is to develop a frailty index. Secondary objectives include assessing its ability to predict in-hospital mortality and/or discharge to a new non-home location; the performance of the frailty index in predicting postoperative and ICU complications, as well as health-related quality of life at 6 months; to compare the performance of the frailty index against existing frailty measurement and risk stratification tools; and to assess its modification by patients' health assets. Ethics and dissemination This study has been approved by the Melbourne Health Human Research Ethics Committee(20 January 2017, HREC/16/MH/321). Dissemination will be via international and national anaesthetic and critical care conferences, and publication in the peer-reviewed literature. [ABSTRACT FROM AUTHOR]

Highlights • Frailty indexes of health deficits may represent the most comprehensive frailty measurement. • In surgery and intensive care, frailty indexes accurately identify at risk patients. • Frailty indexes also predict mortality, complications, and length of stay in surgery and ICU. • Better standardisation of frailty indexes used in future studies is required. Abstract Background/objectives Frail patients are increasingly presenting for both perioperative and intensive care, highlighting the need for simple, valid and scaleable frailty measurement. Frailty indexes comprehensively assess a range of deficits in health, and can incorporate routinely collected data. The purpose of this systematic review was to evaluate the effect of frailty indexes on surgical and intensive care risk stratification and patient outcomes (mortality, complications, length of stay, and discharge location). Methods A prospectively registered systematic review was performed. MEDLINE, EMBASE, and CINAHL were searched to identify studies enrolling adult surgical or intensive care patients which used a frailty index. Included studies were those published subsequent to 1990, of any study design, which utilised a frailty index consisting of ≥30 health deficits. Primary outcome was mortality; secondary outcomes were complications, length of stay (LOS) and discharge location. Study and frailty index quality were critically appraised by three independent reviewers, with findings narratively described. Results 2026 articles were screened, from which nine prospective and four retrospective cohort studies (enrolling 2539 patients) were included. Frailty prevalence ranged between 19–62%; frailty indexes identified patients at risk of increased death [mortality rates ranging between 1.9–73.1%; reported odds ratios (ORs) for death ranging between 1.76–3.09 for frail vs. non-frail patients], surgical complications (ORs = 1.67–4.4), increased LOS, and discharge to residential care (ORs = 1.9–3.64). The term "frailty index" was found to be applied to a number of alternative measurement scales. Conclusion Frail patients are at significantly increased risk in critical illness and the perioperative period. Better standardisation of frailty indexes is recommended. [ABSTRACT FROM AUTHOR]

Objective: To test the effectiveness of chewing gum in the prophylaxis of postoperative nausea and vomiting (PONV) in patients admitted to the intensive care unit (ICU) after surgery. Design: Prospective, open label, pilot randomised controlled trial. Setting: Two metropolitan ICUs. Participants: Ninety postoperative adult patients admitted to the ICU. Intervention: Patients administered chewing gum, who chewed for at least 15 minutes every 4 hours, were compared with a control group, who were administered a 20 mL sip of water orally every 4 hours. Main outcome measures: The primary outcome was the number of patient-reported episodes of nausea in the first 24 hours after the operation. Secondary outcomes included vomiting or dry retching episodes, and duration and severity of nausea. Results: Forty-six patients were randomly allocated to chewing gum and 44 patients to water. There was no difference between groups in the number of patients with nausea (10 [22%] chewing gum v 12 [27%] control patients; P = 0.72), nausea episodes (22 episodes; [median, 0; IQR, 0-0] v 21 episodes [median, 0; IQR, 0-1] per patient in each group respectively), vomiting/retching (2 [4%] chewing gum v 6 [14%] control patients; P = 0.24), or duration/severity of nausea. Conclusion: Regular postoperative administration of chewing gum in a surgical ICU patient cohort did not reduce nausea, vomiting or retching. The prevalence of PONV is less than previously reported. Our findings can inform future studies of PONV prophylaxis in post-surgical ICU patients. Trial registration: Australian New Zealand Clinical Trial Registry No. ACTRN12617001185358., Competing Interests: None declared., (© 2020 College of Intensive Care Medicine of Australia and New Zealand.)