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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]

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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.)