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Intensive care services for children have undergone substantial centralisation in the UK. Along with the establishment of regional paediatric intensive care units (PICUs), specialist retrieval teams were set up to transport critically ill children from other hospitals. We studied the outcome of children transferred from local hospitals to PICUs. We analysed data that were gathered for a cohort of children (≤16 years) admitted consecutively to 29 PICUs in England and Wales during 4 years (Jan 1, 2005, to Dec 31, 2008). We compared unplanned admissions from wards within the same hospital as the PICU and from other hospitals; interhospital transfers by non-specialist and specialist retrieval teams; and patients transferred to their nearest PICU and those who were not. Primary outcome measures were mortality rate in PICU and length of stay in PICU. We analysed data by use of logistic regression analysis. There were 57 997 admissions to PICUs during the study. Nearly half of unplanned admissions (17 649 [53%] of 33 492) were from other hospitals. Although children admitted from other hospitals were younger (median 10 months [IQR 1–55] vs 18 months [3–85]), sicker at admission (median predicted risk of mortality 6% [4–10] vs 4% [2–7]), stayed longer in PICUs (75 h [33–153] vs 43 h [18–116]), and had higher crude mortality rates (1384 [8%] of 17 649 vs 996 [6%] of 15 843; odds ratio 1·27, 95% CI 1·16–1·38), the risk-adjusted mortality rate in PICUs was lower than among children admitted from within the same hospital (0·65, 0·53–0·80). In a multivariable analysis, use of a specialist retrieval team for transfer was associated with improved survival (0·58, 0·39–0·87). These findings support the policy of combining centralisation of intensive care services for children with transfer by specialist retrieval teams. National Clinical Audit and Patient Outcomes Programme through Healthcare Quality Improvement Partnership, Health Commission Wales Specialised Services, National Health Service (NHS) Lothian and National Service Division NHS Scotland, the Royal Belfast Hospital for Sick Children, and the Pan Thames PICU Commissioning Consortium.

We report the stepwise application of the RIFLE classification in 155,624 admissions in the UK Intensive Care National Audit & Research Centre Case Mix Programme database. The assumptions required to define RIFLE and their relationship with renal replacement therapy (RRT) and ICU mortality were assessed. Previous reports had not explored the method of estimating baseline creatinine, the position of class boundaries, or interactions between urine volume (AKI-U) and the peak/estimated baseline creatinine (AKI-Cr) within 24 h of ICU admission. The risk of developing AKI strongly depended on the assumed GFR increasing from 36 to 58% across the recommended range. AKI-U was often seen without AKI-Cr, and moderate oliguria (under 850 ml/24 h) was a stronger predictor of mortality than any degree of AKI-Cr partly because mortality fell when peak/estimated baseline creatinine ratios exceed fourfold. Mild oliguria (850–1500 ml/24 h) was common (38,928 admissions, 26%) and had a similar association with mortality (relative risk 1.6, 95% CI: 1.5–1.6) as did AKI-Cr defined Failure (risk ratio 1.5, 95% CI: 1.5–1.6). However, AKI-Cr was a strong predictor for RRT, which was used in 17,802 (11%) of admissions. Nearly half (48%) of the Failure patients never received RRT; nonetheless, most (66%) survived critical care. Thus, although the RIFLE classification may be attempted in large population cohorts, there is significant heterogeneity of both renal and, in particular, vital outcomes within each class.

Objective Safety culture may influence patient outcomes, but evidence is limited. We sought to determine if intensive care unit (ICU) safety culture is independently associated with outcomes. Design Cohort study combining safety culture survey data with the Project IMPACT Critical Care Medicine (PICCM) clinical database. Setting Thirty ICUs participating in the PICCM database. Participants A total of 65 978 patients admitted January 2001–March 2005. Interventions None. Main outcome measures Hospital mortality and length of stay (LOS). Methods From December 2003 to April 2004, we surveyed study ICUs using the Safety Attitudes Questionnaire-ICU version, a validated instrument that assesses safety culture across six factors. We calculated factor mean and percent-positive scores (% respondents with mean score ≥75 on a 0–100 scale) for each ICU, and generated case-mix adjusted, patient-level, ICU-clustered regression analyses to determine the independent association of safety culture and outcome. Results We achieved a 47.9% response (2103 of 4373 ICU personnel). Culture scores were mostly low to moderate and varied across ICUs (range: 13–88, percent-positive scores). After adjustment for patient, hospital and ICU characteristics, for every 10% decrease in ICU perceptions of management percent-positive score, the odds ratio for hospital mortality was 1.24 (95% CI: 1.07–1.44; P = 0.005). For every 10% decrease in ICU safety climate percent-positive score, LOS increased 15% (95% CI: 1−30%; P = 0.03). Sensitivity analyses for non-response bias consistently associated safety climate with outcome, but also yielded some counterintuitive results. Conclusion In a multicenter study conducted in the USA, perceptions of management and safety climate were moderately associated with outcomes. Future work should further develop methods of assessing safety culture and association with outcomes.

Intravenous fluids are recommended for the treatment of patients who are in septic shock, but higher fluid volumes have been associated with harm in patients who are in the intensive care unit (ICU). In this international, randomized trial, we assigned patients with septic shock in the ICU who had received at least 1 liter of intravenous fluid to receive restricted intravenous fluid or standard intravenous fluid therapy; patients were included if the onset of shock had been within 12 hours before screening. The primary outcome was death from any cause within 90 days after randomization. We enrolled 1554 patients; 770 were assigned to the restrictive-fluid group and 784 to the standard-fluid group. Primary outcome data were available for 1545 patients (99.4%). In the ICU, the restrictive-fluid group received a median of 1798 ml of intravenous fluid (interquartile range, 500 to 4366); the standard-fluid group received a median of 3811 ml (interquartile range, 1861 to 6762). At 90 days, death had occurred in 323 of 764 patients (42.3%) in the restrictive-fluid group, as compared with 329 of 781 patients (42.1%) in the standard-fluid group (adjusted absolute difference, 0.1 percentage points; 95% confidence interval [CI], -4.7 to 4.9; P = 0.96). In the ICU, serious adverse events occurred at least once in 221 of 751 patients (29.4%) in the restrictive-fluid group and in 238 of 772 patients (30.8%) in the standard-fluid group (adjusted absolute difference, -1.7 percentage points; 99% CI, -7.7 to 4.3). At 90 days after randomization, the numbers of days alive without life support and days alive and out of the hospital were similar in the two groups. Among adult patients with septic shock in the ICU, intravenous fluid restriction did not result in fewer deaths at 90 days than standard intravenous fluid therapy. (Funded by the Novo Nordisk Foundation and others; CLASSIC ClinicalTrials.gov number, NCT03668236.).

Our main outcome was to identify organizational characteristics that help to evaluate the differences between the intensive care mortality ratios adjusted by APACHE II. We incorporated the variation associated with the ranking of institutions simulating its random effects under a binomial distribution. A nationwide survey on structure, technology, and staffing resources available in Colombian intensive care units during 1997–1998 was conducted. We collected data on admissions from 20 randomly selected adult medical and surgical intensive care units. The mortality ratio from the 20 intensive care units ranged from 0.59 to 2.36; 80% of the intensive care units had a mortality ratio greater than 1. All four intensive care units with the lowest mortality ratio belonged to private institutions, while four of five institutions with the highest mortality belonged to the public sector. Intensive care units in private institutions also had fewer number of beds, lower median length of stay, lower occupancy rates, higher education training for specialists and nurses and fewer emergency nonelective surgical procedures. We successfully accounted for intensive care mortality baseline differences and random effects variations. There were substantial differences between intensive care units in institution type, bed availability, technology, staffing resources, and degree of training, which may have been associated with patient outcome. These results are of crucial importance to track, detect and assess future changes.

To establish priorities for research in critical care medicine in the UK using survey and nominal group (NG) techniques. The senior doctor and nurse from 325 intensive care units (ICUs) in the UK were invited to contribute up to ten research questions relevant to intensive care organisation, practice or outcomes. These were then ranked twice using a Likert scale by a panel (nominal group) consisting of ten doctors (two trainees) and two nurses from university teaching and district general (community) hospitals. The first ratings were performed privately, and the second after group discussion. Thirty questions, ten each with strong, moderate or weak support, were then returned for rating by the originating ICU staff and the results compared with those of the NG. One hundred eighty-five respondents (35.6 % university teaching, 62.1% district general, 2.3 % not stated) provided 811 questions of which 722 were research hypotheses. The most frequently identified topics were the evaluation of high dependency care, ICU characteristics, treatments for acute lung injury and acute renal failure, nurse:patient ratios, pulmonary artery catheterisation, aspects of medical and nursing practice, protocol evaluation, and interhospital transfers. These were condensed into 100 topics for consideration by the NG. Discussion and re-rating by the group resulted in strong support being offered for 37 topics, moderate support for 48, and weak support for 21. Following circulation of ten questions from each category, nine questions achieved strong support from both ICU staff and the NG. These were the effect on outcomes from critical illness of early intervention, high dependency care, nurse:patient ratios, interhospital transfers, early enteral feeding, optimisation of perioperative care, hospital type, regionalisation of paediatric intensive care and the use of pulmonary artery catheters. The absence of any questions relating to interventions targetting mediators of the immuno-inflammatory response could be a consequence of the failure of recent studies in sepsis to demonstrate benefits in outcome. The intensive care community in the UK appears to prioritise research into organisational aspects of clinical practice and practical aspects of organ-system support. Health services research and the biological sciences need to develop collaborative methods for evaluating interventions and outcomes.

In this review, we seek to highlight how critical illness and critical care affect longer-term outcomes, to underline the contribution of ICU delirium to cognitive dysfunction several months after ICU discharge, to give new insights into ICU acquired weakness, to emphasize the importance of value-based healthcare, and to delineate the elements of family-centered care. This consensus of 29 also provides a perspective and a research agenda about post-ICU recovery.

COVID-19 has disproportionately affected minority ethnic populations in the UK. Our aim was to quantify ethnic differences in SARS-CoV-2 infection and COVID-19 outcomes during the first and second waves of the COVID-19 pandemic in England. We conducted an observational cohort study of adults (aged ≥18 years) registered with primary care practices in England for whom electronic health records were available through the OpenSAFELY platform, and who had at least 1 year of continuous registration at the start of each study period (Feb 1 to Aug 3, 2020 [wave 1], and Sept 1 to Dec 31, 2020 [wave 2]). Individual-level primary care data were linked to data from other sources on the outcomes of interest: SARS-CoV-2 testing and positive test results and COVID-19-related hospital admissions, intensive care unit (ICU) admissions, and death. The exposure was self-reported ethnicity as captured on the primary care record, grouped into five high-level census categories (White, South Asian, Black, other, and mixed) and 16 subcategories across these five categories, as well as an unknown ethnicity category. We used multivariable Cox regression to examine ethnic differences in the outcomes of interest. Models were adjusted for age, sex, deprivation, clinical factors and comorbidities, and household size, with stratification by geographical region. Of 17 288 532 adults included in the study (excluding care home residents), 10 877 978 (62·9%) were White, 1 025 319 (5·9%) were South Asian, 340 912 (2·0%) were Black, 170 484 (1·0%) were of mixed ethnicity, 320 788 (1·9%) were of other ethnicity, and 4 553 051 (26·3%) were of unknown ethnicity. In wave 1, the likelihood of being tested for SARS-CoV-2 infection was slightly higher in the South Asian group (adjusted hazard ratio 1·08 [95% CI 1·07–1·09]), Black group (1·08 [1·06–1·09]), and mixed ethnicity group (1·04 [1·02–1·05]) and was decreased in the other ethnicity group (0·77 [0·76–0·78]) relative to the White group. The risk of testing positive for SARS-CoV-2 infection was higher in the South Asian group (1·99 [1·94–2·04]), Black group (1·69 [1·62–1·77]), mixed ethnicity group (1·49 [1·39–1·59]), and other ethnicity group (1·20 [1·14–1·28]). Compared with the White group, the four remaining high-level ethnic groups had an increased risk of COVID-19-related hospitalisation (South Asian group 1·48 [1·41–1·55], Black group 1·78 [1·67–1·90], mixed ethnicity group 1·63 [1·45–1·83], other ethnicity group 1·54 [1·41–1·69]), COVID-19-related ICU admission (2·18 [1·92–2·48], 3·12 [2·65–3·67], 2·96 [2·26–3·87], 3·18 [2·58–3·93]), and death (1·26 [1·15–1·37], 1·51 [1·31–1·71], 1·41 [1·11–1·81], 1·22 [1·00–1·48]). In wave 2, the risks of hospitalisation, ICU admission, and death relative to the White group were increased in the South Asian group but attenuated for the Black group compared with these risks in wave 1. Disaggregation into 16 ethnicity groups showed important heterogeneity within the five broader categories. Some minority ethnic populations in England have excess risks of testing positive for SARS-CoV-2 and of adverse COVID-19 outcomes compared with the White population, even after accounting for differences in sociodemographic, clinical, and household characteristics. Causes are likely to be multifactorial, and delineating the exact mechanisms is crucial. Tackling ethnic inequalities will require action across many fronts, including reducing structural inequalities, addressing barriers to equitable care, and improving uptake of testing and vaccination. Medical Research Council.

Background In Africa, severe pneumonia remains the major cause of paediatric hospitalisation, resulting in high requirements for oxygen therapy. Adequate supplies of oxygen are key challenges for many low-resource hospitals. The World Health Organization manual for oxygen therapy advises 2–3 days of oxygen therapy for pneumonia and recommends against early weaning, even in the absence of hypoxaemia. Few data support this recommendation. We describe the oxygen use and timing of weaning in the COAST trial of oxygen therapy (ISRCTN15622505). Methods Children aged 28 days to 12 years presenting to 6 hospitals in Uganda and Kenya with severe pneumonia and hypoxaemia (saturations < 92% on pulse oximetry (SpO 2 ) were eligible for the trial. Children in two strata (a) severe hypoxaemia (SpO 2  < 80%) and (b) moderate hypoxaemia (SpO 2 80–91%) were allocated to receive high flow nasal therapy (HFNT), low flow oxygen delivery (LFO) or control (no immediate oxygen (moderate hypoxaemia stratum only)). Children were closely monitored over 48 h by pulse oximetry and weaned off oxygen once SpO 2  > 92%. We describe the oxygen use and proportion requiring respiratory support over time by intervention strategy. Results Of the 1842 children enroled the majority, 1454 (79%) had moderate hypoxaemia. In this stratum, by 2 and 8 h, 148 (41%) and 200/360 (55.6%) in the LFO arm had been weaned; in the HFNT arm, 213/362 (59%) were receiving respiratory support at 2 h in room alone, and by 8 h, 164/362 (45%) had been weaned. At 48 h, in the respective strata, 77–80% and 53–63% still had respiratory distress but without hypoxaemia and were thus not receiving oxygen. Median oxygen use at 48 h in the moderate hypoxaemia group was highest in LFO am 480L (IQR 236.2, 2132.2) compared to 113.4 L (IQR 0.0, 1453.9) in the HFNT and 0 L (IQR 0.0) in the control arms. Children requiring oxygen beyond 48 h, 17/33 (51.1%) and 9/46 (19.5%) in the respective strata, had additional cardiac conditions. Conclusions Closely monitoring SpO 2 resulted in early weaning and reduced the use of and exposure to oxygen. Where oxygen supplies are at a premium, this approach may improve equitable access for children with severe pneumonia.

Purpose Delays in adjuvant breast cancer (BC) therapy have been shown to worsen outcomes. However, thus far studies have only evaluated delays to initial treatment, or a particular modality, such as chemotherapy, leaving uncertainty about the role of delay to subsequent therapy and the effects of cumulative delay, on outcomes. We investigated the associations of delays across treatment modalities with survival. Methods We included 3368 women with incident stage I–III BC in the Women’s Health Initiative (WHI) enrolled in fee-for-service Medicare who underwent definitive surgery. This prospective analysis characterized treatment delays by linking WHI study records to Medicare claims. Delays were defined as > 8 weeks to surgery, chemotherapy, and radiation from diagnosis or prior treatment. We used Cox proportional hazards models to estimate BC-specific mortality (BCSM) and all-cause mortality (ACM) in relation to treatment delays. Results We found 21.8% of women experienced delay to at least one therapy modality. In adjusted analysis, delay to chemotherapy was associated with a higher risk of BCSM (HR = 1.71; 95% CI 1.07–2.75) and ACM (HR = 1.39; 95% CI 1.02–1.90); delay in radiation increased BCSM risk (HR = 1.49; 95% CI 1.00–2.21) but not ACM risk (HR = 1.19; 95% CI 0.99–1.42). Delays across multiple treatment modalities increased BCSM risk threefold (95% CI 1.51–6.12) and ACM risk 2.3-fold (95% CI 1.50–3.50). Conclusions A delay to a single treatment modality and delay to a greater extent an accumulation of delays were associated with higher BCSM and ACM after BC. Timely care throughout the continuum of breast cancer treatment is important for optimal outcomes.