Abstract Background Use of Extracorporeal Membrane Oxygenation during cardiopulmonary resuscitation (ECPR) is increasingly being deployed as an adjunct to conventional CPR. It is unknown if this has ...been associated with improved outcomes. Aims To describe trends in survival and patient demographics for ECPR patients in the international Extracorporeal Life Support Organisation (ELSO) database over the past 12 years and identify factors associated with changes in survival. Methods Patients greater than 16 years of age who received ECPR between January 2003 and December 2014 were extracted from the ELSO registry and were divided into three 4-year cohorts (Cohort 1: 2003–2006, Cohort 2: 2007–2010, Cohort 3: 2011–2014). Univariable analysis was performed to compare demographics and outcomes of patients across the three cohorts. Univariable and multivariable analyses were then performed to identify factors independently associated with survival. Results 1796 patients treated with ECPR were extracted from the registry, aged 50 (±18.5) years. Annual ECPR episodes increased over 10-fold, from 35 to over 400 per year. Survival to hospital discharge was 29% overall (27% cohort 1, 28% cohort 2, 30% cohort 3 (p = 0.71)). Age, body weight and documented comorbidities increased over time. There was a reduction in complications associated with ECMO usage. After adjusting for confounders there was no change in the odds of survival over the time period examined. Interpretation Over the period 2003–2014, survival to hospital discharge was 29% for patients who require ECPR. Despite advances in provision of ECMO care and increasing co-morbidities of patients, there has been no change in risk-adjusted survival over time.
The Sepsis-3 Criteria emphasized the value of a change of 2 or more points in the Sequential Sepsis-related Organ Failure Assessment (SOFA) score, introduced quick SOFA (qSOFA), and removed the ...systemic inflammatory response syndrome (SIRS) criteria from the sepsis definition.
Externally validate and assess the discriminatory capacities of an increase in SOFA score by 2 or more points, 2 or more SIRS criteria, or a qSOFA score of 2 or more points for outcomes among patients who are critically ill with suspected infection.
Retrospective cohort analysis of 184 875 patients with an infection-related primary admission diagnosis in 182 Australian and New Zealand intensive care units (ICUs) from 2000 through 2015.
SOFA, qSOFA, and SIRS criteria applied to data collected within 24 hours of ICU admission.
The primary outcome was in-hospital mortality. In-hospital mortality or ICU length of stay (LOS) of 3 days or more was a composite secondary outcome. Discrimination was assessed using the area under the receiver operating characteristic curve (AUROC). Adjusted analyses were performed using a model of baseline risk determined using variables independent of the scoring systems.
Among 184 875 patients (mean age, 62.9 years SD, 17.4; women, 82 540 44.6%; most common diagnosis bacterial pneumonia, 32 634 17.7%), a total of 34 578 patients (18.7%) died in the hospital, and 102 976 patients (55.7%) died or experienced an ICU LOS of 3 days or more. SOFA score increased by 2 or more points in 90.1%; 86.7% manifested 2 or more SIRS criteria, and 54.4% had a qSOFA score of 2 or more points. SOFA demonstrated significantly greater discrimination for in-hospital mortality (crude AUROC, 0.753 99% CI, 0.750-0.757) than SIRS criteria (crude AUROC, 0.589 99% CI, 0.585-0.593) or qSOFA (crude AUROC, 0.607 99% CI, 0.603-0.611). Incremental improvements were 0.164 (99% CI, 0.159-0.169) for SOFA vs SIRS criteria and 0.146 (99% CI, 0.142-0.151) for SOFA vs qSOFA (P <.001). SOFA (AUROC, 0.736 99% CI, 0.733-0.739) outperformed the other scores for the secondary end point (SIRS criteria: AUROC, 0.609 99% CI, 0.606-0.612; qSOFA: AUROC, 0.606 99% CI, 0.602-0.609). Incremental improvements were 0.127 (99% CI, 0.123-0.131) for SOFA vs SIRS criteria and 0.131 (99% CI, 0.127-0.134) for SOFA vs qSOFA (P <.001). Findings were consistent for both outcomes in multiple sensitivity analyses.
Among adults with suspected infection admitted to an ICU, an increase in SOFA score of 2 or more had greater prognostic accuracy for in-hospital mortality than SIRS criteria or the qSOFA score. These findings suggest that SIRS criteria and qSOFA may have limited utility for predicting mortality in an ICU setting.
Background. Klebsiella pneumoniae is an opportunistic pathogen and leading cause of hospital-associated infections. Intensive care unit (ICU) patients are particularly at risk. Klebsiella pneumoniae ...is part of the healthy human microbiome, providing a potential reservoir for infection. However, the frequency of gut colonization and its contribution to infections are not well characterized. Methods. We conducted a 1-year prospective cohort study in which 498 ICU patients were screened for rectal and throat carriage of K. pneumoniae shortly after admission. Klebsiella pneumoniae isolated from screening swabs and clinical diagnostic samples were characterized using whole genome sequencing and combined with epidemiological data to identify likely transmission events. Results. Klebsiella pneumoniae carriage frequencies were estimated at 6% (95% confidence interval CI, 3%–8%) among ICU patients admitted direct from the community, and 19% (95% CI, 14%–51%) among those with recent healthcare contact. Gut colonization on admission was significantly associated with subsequent infection (infection risk 16% vs 3%, odds ratio OR = 6.9, P < .001), and genome data indicated matching carriage and infection isolates in 80% of isolate pairs. Five likely transmission chains were identified, responsible for 12% of K. pneumoniae infections in ICU. In sum, 49% of K. pneumoniae infections were caused by the patients' own unique strain, and 48% of screened patients with infections were positive for prior colonization. Conclusions. These data confirm K. pneumoniae colonization is a significant risk factor for infection in ICU, and indicate ∼50% of K. pneumoniae infections result from patients' own microbiota. Screening for colonization on admission could limit risk of infection in the colonized patient and others.
Coronavirus disease 2019 (COVID-19) pandemic has caused unprecedented pressure on healthcare system globally. Lack of high-quality evidence on the respiratory management of COVID-19-related acute ...respiratory failure (C-ARF) has resulted in wide variation in clinical practice.
Using a Delphi process, an international panel of 39 experts developed clinical practice statements on the respiratory management of C-ARF in areas where evidence is absent or limited. Agreement was defined as achieved when > 70% experts voted for a given option on the Likert scale statement or > 80% voted for a particular option in multiple-choice questions. Stability was assessed between the two concluding rounds for each statement, using the non-parametric Chi-square (χ
) test (p < 0·05 was considered as unstable).
Agreement was achieved for 27 (73%) management strategies which were then used to develop expert clinical practice statements. Experts agreed that COVID-19-related acute respiratory distress syndrome (ARDS) is clinically similar to other forms of ARDS. The Delphi process yielded strong suggestions for use of systemic corticosteroids for critical COVID-19; awake self-proning to improve oxygenation and high flow nasal oxygen to potentially reduce tracheal intubation; non-invasive ventilation for patients with mixed hypoxemic-hypercapnic respiratory failure; tracheal intubation for poor mentation, hemodynamic instability or severe hypoxemia; closed suction systems; lung protective ventilation; prone ventilation (for 16-24 h per day) to improve oxygenation; neuromuscular blocking agents for patient-ventilator dyssynchrony; avoiding delay in extubation for the risk of reintubation; and similar timing of tracheostomy as in non-COVID-19 patients. There was no agreement on positive end expiratory pressure titration or the choice of personal protective equipment.
Using a Delphi method, an agreement among experts was reached for 27 statements from which 20 expert clinical practice statements were derived on the respiratory management of C-ARF, addressing important decisions for patient management in areas where evidence is either absent or limited.
The study was registered with Clinical trials.gov Identifier: NCT04534569.
Purpose
The impact of intensivist workload on intensive care unit (ICU) outcomes is incompletely described and assessed across healthcare systems and countries. We sought to examine the association ...of patient-to-intensivist ratio (PIR) with hospital mortality in Australia/New Zealand (ANZ) ICUs.
Methods
We conducted a retrospective study of adult admissions to ANZ ICUs (August 2016–June 2018) using two cohorts: “narrow”, based on previously used criteria including restriction to ICUs with a single daytime intensivist; and “broad”, refined by individual ICU daytime staffing information. The exposure was average daily PIR and the outcome was hospital mortality. We used summary statistics to describe both cohorts and multilevel multivariable logistic regression models to assess the association of PIR with mortality. In each, PIR was modeled using restricted cubic splines to allow for non-linear associations. The broad cohort model included non-PIR physician and non-physician staffing covariables.
Results
The narrow cohort of 27,380 patients across 67 ICUs (predicted mortality: median 1.2% IQR 0.4–1.4%; mean 5.9% sd 13.2%) had a median PIR of 10.1 (IQR 7–14). The broad cohort of 91,206 patients across 73 ICUs (predicted mortality: 1.9% 0.6–6.5%; 7.6% 14.9%) had a median PIR of 7.8 (IQR 5.8–10.2). We found no association of PIR with mortality in either the narrow (PIR 1st spline term odds ratio 95% CI: 1 0.94, 1.06, Wald testing of spline terms
p
= 0.61) or the broad (1.02 0.97, 1.07,
p
= 0.4) cohort.
Conclusion
We found no association of PIR with hospital mortality across ANZ ICUs. The low cohort predicted mortality may limit external validity.
To investigate the association of socioeconomic status as measured by the average socioeconomic status of the area where a person resides on short-term mortality in adults admitted to an ICU in ...Queensland, Australia.
Secondary data analysis using de-identified data from the Australian and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation linked to the publicly available area-level Index of Relative Socioeconomic Advantage and Disadvantage from the Australian Bureau of Statistics.
Adult ICUs from 35 hospitals in Queensland, Australia, from 2006 to 2015.
A total of 218,462 patient admissions.
None.
The outcome measure was inhospital mortality. The main study variable was decile of Index of Relative Socioeconomic Advantage and Disadvantage. The overall crude inhospital mortality was 7.8%; 9% in the most disadvantaged decile and 6.9% in the most advantaged decile (p < 0.001). Increasing socioeconomic disadvantage was associated with increasing severity of illness as measured by Acute Physiology and Chronic Health Evaluation III score, admission with a diagnosis of sepsis or trauma, cardiac, respiratory, renal, and hepatic comorbidities, and remote location. Increasing socioeconomic advantage was associated with elective surgical admission, hematological and oncology comorbidities, and admission to a private hospital (all p < 0.001). After excluding patients admitted after elective surgery, in the remaining 106,843 patients, the inhospital mortality was 13.6%, 13.3% in the most disadvantaged, and 14.1% in the most advantaged. There was no trend in mortality across deciles of socioeconomic status after excluding elective surgery patients. In the logistic regression model adjusting for severity of illness and diagnosis, there was no statistically significant difference in the odds ratio of inhospital mortality for the most disadvantaged decile compared with other deciles. This suggests variables used for risk adjustment may lie on the causal pathway between socioeconomic status and outcome in ICU patients.
Socioeconomic status as defined as Index of Relative Socioeconomic Advantage and Disadvantage of the area in which a patient lives was associated with ICU admission diagnosis, comorbidities, severity of illness, and crude inhospital mortality in this study. Socioeconomic status was not associated with inhospital mortality after excluding elective surgical patients or when adjusted for severity of illness and admission diagnosis. Commonly used measures for risk adjustment in intensive care improve understanding of the pathway between socioeconomic status and outcomes.
Klebsiella pneumoniae is a major cause of opportunistic healthcare-associated infections, which are increasingly complicated by the presence of extended-spectrum beta-lactamases (ESBLs) and ...carbapenem resistance. We conducted a year-long prospective surveillance study of K. pneumoniae clinical isolates in hospital patients. Whole-genome sequence (WGS) data reveals a diverse pathogen population, including other species within the K. pneumoniae species complex (18%). Several infections were caused by K. variicola/K. pneumoniae hybrids, one of which shows evidence of nosocomial transmission. A wide range of antimicrobial resistance (AMR) phenotypes are observed, and diverse genetic mechanisms identified (mainly plasmid-borne genes). ESBLs are correlated with presence of other acquired AMR genes (median n = 10). Bacterial genomic features associated with nosocomial onset are ESBLs (OR 2.34, p = 0.015) and rhamnose-positive capsules (OR 3.12, p < 0.001). Virulence plasmid-encoded features (aerobactin, hypermucoidy) are observed at low-prevalence (<3%), mostly in community-onset cases. WGS-confirmed nosocomial transmission is implicated in just 10% of cases, but strongly associated with ESBLs (OR 21, p < 1 × 10
). We estimate 28% risk of onward nosocomial transmission for ESBL-positive strains vs 1.7% for ESBL-negative strains. These data indicate that K. pneumoniae infections in hospitalised patients are due largely to opportunistic infections with diverse strains, with an additional burden from nosocomially-transmitted AMR strains and community-acquired hypervirulent strains.
ICU resource strain leads to adverse patient outcomes. Simple, well-validated measures of ICU strain are lacking. Our objective was to assess whether the "Activity index," an indicator developed ...during the COVID-19 pandemic, was a valid measure of ICU strain.
Retrospective national registry-based cohort study.
One hundred seventy-five public and private hospitals in Australia (June 2020 through March 2022).
Two hundred seventy-seven thousand seven hundred thirty-seven adult ICU patients.
None.
Data from the Australian and New Zealand Intensive Care Society Adult Patient Database were matched to the Critical Health Resources Information System. The mean daily Activity index of each ICU (census total of "patients with 1:1 nursing" + "invasive ventilation" + "renal replacement" + "extracorporeal membrane oxygenation" + "active COVID-19," divided by total staffed ICU beds) during the patient's stay in the ICU was calculated. Patients were categorized as being in the ICU during very quiet (Activity index < 0.1), quiet (0.1 to < 0.6), intermediate (0.6 to < 1.1), busy (1.1 to < 1.6), or very busy time-periods (≥ 1.6). The primary outcome was in-hospital mortality. Secondary outcomes included after-hours discharge from the ICU, readmission to the ICU, interhospital transfer to another ICU, and delay in discharge from the ICU. Median Activity index was 0.87 (interquartile range, 0.40-1.24). Nineteen thousand one hundred seventy-seven patients died (6.9%). In-hospital mortality ranged from 2.4% during very quiet to 10.9% during very busy time-periods. After adjusting for confounders, being in an ICU during time-periods with higher Activity indices, was associated with an increased risk of in-hospital mortality (odds ratio OR, 1.49; 99% CI, 1.38-1.60), after-hours discharge (OR, 1.27; 99% CI, 1.21-1.34), readmission (OR, 1.18; 99% CI, 1.09-1.28), interhospital transfer (OR, 1.92; 99% CI, 1.72-2.15), and less delay in ICU discharge (OR, 0.58; 99% CI, 0.55-0.62): findings consistent with ICU strain.
The Activity index is a simple and valid measure that identifies ICUs in which increasing strain leads to progressively worse patient outcomes.
Although it is intense in health care resources, by facilitating assessment and reconditioning, ex vivo lung perfusion (EVLP) has the potential to expand the donor pool and improve lung transplant ...outcomes. However, inclusion criteria used in EVLP trials have not been validated.
This retrospective study from 2014 to 2018 reviewed our local state-based donation organization donor records as well as subsequent recipient outcomes to explore the relation between EVLP indications used in clinical trials and recipient outcomes. The primary outcome was primary graft dysfunction grade 3 at 24 hours, with 30-day mortality and posttransplant survival time as secondary outcomes, compared with univariate and multivariate analysis.
From 705 lung donor referrals, 304 lung transplantations were performed (use rate of 42%); 212 of recipients (70%) met at least 1 of the commonly cited EVLP initiation criteria. There was no significant difference in primary graft dysfunction grade 3 or 30-day mortality between recipients with or without an EVLP indication (10.2% versus 7.8%, P = .51; and 2.4% versus 0%, P = .14, respectively). Multivariate analyses showed no significant relationship between commonly cited EVLP criteria and primary graft dysfunction grade 3 or survival time. Recipient outcomes were significantly associated with recipient diagnosis.
At least 1 commonly cited criterion for EVLP initiation was present in 70% of the transplanted donors, and yet it did not predict clinical results; acceptable outcomes were seen in both subgroups. To discover the true utility of EVLP beyond good clinical management and focus EVLP on otherwise unacceptable lungs, a reconsideration of EVLP inclusion criteria is required.
Policy makers, clinicians and researchers are demonstrating increasing interest in using data linked from multiple sources to support measurement of clinical performance and patient health outcomes. ...However, the utility of data linkage may be compromised by sub-optimal or incomplete linkage, leading to systematic bias. In this study, we synthesize the evidence identifying participant or population characteristics that can influence the validity and completeness of data linkage and may be associated with systematic bias in reported outcomes.
A narrative review, using structured search methods was undertaken. Key words "data linkage" and Mesh term "medical record linkage" were applied to Medline, EMBASE and CINAHL databases between 1991 and 2007. Abstract inclusion criteria were; the article attempted an empirical evaluation of methodological issues relating to data linkage and reported on patient characteristics, the study design included analysis of matched versus unmatched records, and the report was in English. Included articles were grouped thematically according to patient characteristics that were compared between matched and unmatched records.
The search identified 1810 articles of which 33 (1.8%) met inclusion criteria. There was marked heterogeneity in study methods and factors investigated. Characteristics that were unevenly distributed among matched and unmatched records were; age (72% of studies), sex (50% of studies), race (64% of studies), geographical/hospital site (93% of studies), socio-economic status (82% of studies) and health status (72% of studies).
A number of relevant patient or population factors may be associated with incomplete data linkage resulting in systematic bias in reported clinical outcomes. Readers should consider these factors in interpreting the reported results of data linkage studies.
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