OBJECTIVES:Correct classification of the source of infection is important in observational and interventional studies of sepsis. Centers for Disease Control and Prevention criteria are most commonly ...used for this purpose, but the robustness of these definitions in critically ill patients is not known. We hypothesized that in a mixed ICU population, the performance of these criteria would be generally reduced and would vary among diagnostic subgroups.
DESIGN:Prospective cohort.
SETTING:Data were collected as part of a cohort of 1,214 critically ill patients admitted to two hospitals in The Netherlands between January 2011 and June 2011.
PATIENTS:Eight observers assessed a random sample of 168 of 554 patients who had experienced at least one infectious episode in the ICU. Each patient was assessed by two randomly selected observers who independently scored the source of infection (by affected organ system or site), the plausibility of infection (rated as none, possible, probable, or definite), and the most likely causative pathogen. Assessments were based on a post hoc review of all available clinical, radiological, and microbiological evidence. The observed diagnostic agreement for source of infection was classified as partial (i.e., matching on organ system or site) or complete (i.e., matching on specific diagnostic terms), for plausibility as partial (2-point scale) or complete (4-point scale), and for causative pathogens as an approximate or exact pathogen match. Interobserver agreement was expressed as a concordant percentage and as a kappa statistic.
INTERVENTIONS:None.
MEASUREMENTS AND MAIN RESULTS:A total of 206 infectious episodes were observed. Agreement regarding the source of infection was 89% (183/206) and 69% (142/206) for a partial and complete diagnostic match, respectively. This resulted in a kappa of 0.85 (95% CI, 0.79–0.90). Agreement varied from 63% to 91% within major diagnostic categories and from 35% to 97% within specific diagnostic subgroups, with the lowest concordance observed in cases of ventilator-associated pneumonia. In the 142 episodes for which a complete match on source of infection was obtained, the interobserver agreement for plausibility of infection was 83% and 65% on a 2- and 4-point scale, respectively. For causative pathogen, agreement was 78% and 70% for an approximate and exact pathogen match, respectively.
CONCLUSIONS:Interobserver agreement for classifying sources of infection using Centers for Disease Control and Prevention criteria was excellent overall. However, full concordance on all aspects of the diagnosis between independent observers was rare for some types of infection, in particular for ventilator-associated pneumonia.
Purpose
To quantify the effects of minor variations in the definition and measurement of systemic inflammatory response syndrome (SIRS) criteria and organ failure on the observed incidences of ...sepsis, severe sepsis and septic shock.
Methods
We conducted a prospective, observational study in a tertiary intensive care unit in The Netherlands between January 2009 and October 2010. A total of 1,072 consecutive adults were included. We determined the upper and lower limits of the measured incidence of sepsis by evaluating the influence of the use of an automated versus a manual method of data collection, and variations in the number of SIRS criteria, concurrency of SIRS criteria, and duration of abnormal values required to make a particular diagnosis.
Results
The measured incidence of SIRS varied from 49 % (most restrictive setting) to 99 % (most liberal setting). Subsequently, the incidences of sepsis, severe sepsis and septic shock ranged from 22 to 31 %, from 6 to 27 % and from 4 to 9 % for the most restrictive versus the most liberal measurement settings, respectively. In non-infected patients, 39–98 % of patients had SIRS, whereas still 17–6 % of patients without SIRS had an infection.
Conclusions
The apparent incidence of sepsis heavily depends on minor variations in the definition of SIRS and mode of data recording. As a consequence, the current consensus criteria do not ensure uniform recruitment of patients into sepsis trials.
PurposePostoperative complications increase mortality, disability and costs. Advanced understanding of the risk factors for postoperative complications is needed to improve surgical outcomes. This ...paper discusses the rationale and profile of the BIGPROMISE (biomarkers to guide perioperative management and improve outcome in high-risk surgery) cohort, that aims to investigate risk factors, pathophysiology and outcomes related to postoperative complications.ParticipantsAdult patients undergoing major surgery in two tertiary teaching hospitals. Clinical data and blood samples are collected before surgery, at the end of surgery and on the first, second and third postoperative day. At each time point a panel of cardiovascular, inflammatory, renal, haematological and metabolic biomarkers is assessed. Aliquots of plasma, serum and whole blood of each time point are frozen and stored. Data on severe complications are prospectively collected during 30 days after surgery. Functional status is assessed before surgery and after 120 days using the WHO Disability Assessment Schedule (WHODAS) 2.0. Mortality is followed up until 2 years after surgery.Findings to dateThe first patient was enrolled on 8 October 2021. Currently (1 January 2024) 3086 patients were screened for eligibility, of whom 1750 (57%) provided informed consent for study participation. Median age was 66 years (60; 73), 28% were female, and 68% of all patients were American Society of Anaesthesiologists (ASA) physical status class 3. Most common types of major surgery were cardiac (49%) and gastro-intestinal procedures (26%). The overall incidence of 30-day severe postoperative complications was 16%.Future plansBy the end of the recruitment phase, expected in 2026, approximately 3000 patients with major surgery will have been enrolled. This cohort allows us to investigate the role of pathophysiological perioperative processes in the cause of postoperative complications, and to discover and develop new biomarkers to improve risk stratification for adverse postoperative outcomes.Trial registration number NCT05199025.
Immunomodulatory therapies that improve the outcome of sepsis are not available. We sought to determine whether treatment of critically ill patients with sepsis with low-dose erythromycin-a macrolide ...antibiotic with broad immunomodulatory effects-decreased mortality and ameliorated underlying disease pathophysiology.
We conducted a target trial emulation, comparing patients with sepsis admitted to two intensive care units (ICU) in the Netherlands for at least 72 h, who were either exposed or not exposed during this period to treatment with low-dose erythromycin (up to 600 mg per day, administered as a prokinetic agent) but no other macrolides. We used two common propensity score methods (matching and inverse probability of treatment weighting) to deal with confounding by indication and subsequently used Cox regression models to estimate the treatment effect on the primary outcome of mortality rate up to day 90. Secondary clinical outcomes included change in SOFA, duration of mechanical ventilation and the incidence of ICU-acquired infections. We used linear mixed models to assess differences in 15 host response biomarkers reflective of key pathophysiological processes from admission to day 4.
In total, 235 patients started low-dose erythromycin treatment, 470 patients served as controls. Treatment started at a median of 38 IQR 25-52 hours after ICU admission for a median of 5 IQR 3-8 total doses in the first course. Matching and weighting resulted in populations well balanced for proposed confounders. We found no differences between patients treated with low-dose erythromycin and control subjects in mortality rate up to day 90: matching HR 0.89 (95% CI 0.64-1.24), weighting HR 0.95 (95% CI 0.66-1.36). There were no differences in secondary clinical outcomes. The change in host response biomarker levels from admission to day 4 was similar between erythromycin-treated and control subjects.
In this target trial emulation in critically ill patients with sepsis, we could not demonstrate an effect of treatment with low-dose erythromycin on mortality, secondary clinical outcomes or host response biomarkers.
Systemic inflammation is a whole body reaction having an infection-positive (i.e., sepsis) or infection-negative origin. It is important to distinguish between these two etiologies early and ...accurately because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on peripheral blood RNAs could be discovered that would (1) determine which patients with systemic inflammation had sepsis, (2) be robust across independent patient cohorts, (3) be insensitive to disease severity, and (4) provide diagnostic utility. The goal of this study was to identify and validate such a molecular classifier.
We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICUs). Biomarker discovery utilized an Australian cohort (n = 105) consisting of 74 cases (sepsis patients) and 31 controls (post-surgical patients with infection-negative systemic inflammation) recruited at five tertiary care settings in Brisbane, Australia, from June 3, 2008, to December 22, 2011. A four-gene classifier combining CEACAM4, LAMP1, PLA2G7, and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte Lab, was validated using reverse transcription quantitative PCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Patients for validation were selected from the Molecular Diagnosis and Risk Stratification of Sepsis study (ClinicalTrials.gov, NCT01905033), which recruited ICU patients from the Academic Medical Center in Amsterdam and the University Medical Center Utrecht. Patients recruited from November 30, 2012, to August 5, 2013, were eligible for inclusion in the present study. Validation cohort 1 (n = 59) consisted entirely of unambiguous cases and controls; SeptiCyte Lab gave an area under curve (AUC) of 0.95 (95% CI 0.91-1.00) in this cohort. ROC curve analysis of an independent, more heterogeneous group of patients (validation cohorts 2-5; 249 patients after excluding 37 patients with an infection likelihood of "possible") gave an AUC of 0.89 (95% CI 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility of SeptiCyte Lab was evaluated by comparison to various clinical and laboratory parameters available to a clinician within 24 h of ICU admission. SeptiCyte Lab was significantly better at differentiating cases from controls than all tested parameters, both singly and in various logistic combinations, and more than halved the diagnostic error rate compared to procalcitonin in all tested cohorts and cohort combinations. Limitations of this study relate to (1) cohort compositions that do not perfectly reflect the composition of the intended use population, (2) potential biases that could be introduced as a result of the current lack of a gold standard for diagnosing sepsis, and (3) lack of a complete, unbiased comparison to C-reactive protein.
SeptiCyte Lab is a rapid molecular assay that may be clinically useful in managing ICU patients with systemic inflammation. Further study in population-based cohorts is needed to validate this assay for clinical use.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background
Indirect indices for measuring impaired ventilation, such as the estimated dead space fraction and the ventilatory ratio, have been shown to be independently associated with an increased ...risk of mortality. This study aimed to compare various methods for dead space estimation and the ventilatory ratio in patients with acute respiratory distress syndrome (ARDS) and to determine their independent values for predicting death at day 30. The present study is a post hoc analysis of a prospective observational cohort study of ICUs of two tertiary care hospitals in the Netherlands.
Results
Individual patient data from 940 ARDS patients were analyzed. Estimated dead space fraction and the ventilatory ratio at days 1 and 2 were significantly higher among non-survivors (
p
< 0.01). Dead space fraction calculation using the estimate from physiological variables
V
D
/
V
T phys
and the ventilatory ratio at day 2 showed independent association with mortality at 30 days (odds ratio 1.28 95% CI 1.02–1.61,
p
< 0.03 and 1.20 95% CI, 1.01–1.40,
p
< 0.03, respectively); whereas, the Harris–Benedict
V
D
/
V
T HB
and Penn State
V
D
/
V
T PS
estimations were not associated with mortality. The predicted validity of the estimated dead space fraction and the ventilatory ratio improved the baseline model based on PEEP, PaO
2
/FiO
2
, driving pressure and compliance of the respiratory system at day 2 (AUROCC 0.72 vs. 0.69,
p
< 0.05).
Conclusions
Estimated methods for dead space calculation and the ventilatory ratio during the early course of ARDS are associated with mortality at day 30 and add statistically significant but limited improvement in the predictive accuracy to indices of oxygenation and respiratory system mechanics at the second day of mechanical ventilation.
Purpose
To provide an overview and evaluate the performance of mortality prediction models for patients requiring extracorporeal membrane oxygenation (ECMO) support for refractory cardiocirculatory ...or respiratory failure.
Methods
A systematic literature search was undertaken to identify studies developing and/or validating multivariable prediction models for all-cause mortality in adults requiring or receiving veno-arterial (V-A) or veno-venous (V-V) ECMO. Estimates of model performance (observed versus expected (O:E) ratio and c-statistic) were summarized using random effects models and sources of heterogeneity were explored by means of meta-regression. Risk of bias was assessed using the Prediction model Risk Of BiAS Tool (PROBAST).
Results
Among 4905 articles screened, 96 studies described a total of 58 models and 225 external validations. Out of all 58 models which were specifically developed for ECMO patients, 14 (24%) were ever externally validated. Discriminatory ability of frequently validated models developed for ECMO patients (i.e., SAVE and RESP score) was moderate on average (pooled c-statistics between 0.66 and 0.70), and comparable to general intensive care population-based models (pooled c-statistics varying between 0.66 and 0.69 for the Simplified Acute Physiology Score II (SAPS II), Acute Physiology and Chronic Health Evaluation II (APACHE II) score and Sequential Organ Failure Assessment (SOFA) score). Nearly all models tended to underestimate mortality with a pooled O:E > 1. There was a wide variability in reported performance measures of external validations, reflecting a large between-study heterogeneity. Only 1 of the 58 models met the generally accepted Prediction model Risk Of BiAS Tool criteria of good quality. Importantly, all predicted outcomes were conditional on the fact that ECMO support had already been initiated, thereby reducing their applicability for patient selection in clinical practice.
Conclusions
A large number of mortality prediction models have been developed for ECMO patients, yet only a minority has been externally validated. Furthermore, we observed only moderate predictive performance, large heterogeneity between-study populations and model performance, and poor methodological quality overall. Most importantly, current models are unsuitable to provide decision support for selecting individuals in whom initiation of ECMO would be most beneficial, as all models were developed in ECMO patients only and the decision to start ECMO had, therefore, already been made.
Enteral and respiratory tract colonization with gram-negative bacteria may lead to subsequent infections in critically ill patients. We aimed to clarify the interdependence between gut and ...respiratory tract colonization and their associations with intensive care unit (ICU)-acquired infections in patients receiving selective digestive tract decontamination (SDD).
Colonization status of the rectum and respiratory tract was determined using twice-weekly microbiological surveillance in mechanically ventilated subjects receiving SDD between May 2011 and June 2015 in a tertiary medical-surgical ICU in the Netherlands. Acquisition of infections was monitored daily by dedicated observers. Marginal structural models were used to determine the associations between gram-negative rectal colonization and respiratory tract colonization, ICU-acquired gram-negative infection, and ICU-acquired gram-negative bacteremia.
Among 2066 ICU admissions, 1157 (56.0%) ever had documented gram-negative carriage in the rectum during ICU stay. Cumulative incidences of ICU-acquired gram-negative infection and bacteremia were 6.0% (n = 124) and 2.1% (n = 44), respectively. Rectal colonization was an independent risk factor for both respiratory tract colonization (cause-specific hazard ratio CSHR, 2.93 95% confidence interval {CI}, 2.02-4.23) and new gram-negative infection in the ICU (CSHR, 3.04 95% CI, 1.99-4.65). Both rectal and respiratory tract colonization were associated with bacteremia (CSHR, 7.37 95% CI, 3.25-16.68 and 2.56 95% CI, 1.09-6.03, respectively). Similar associations were observed when Enterobacteriaceae and glucose nonfermenting gram-negative bacteria were analyzed separately.
Gram-negative rectal colonization tends to be stronger associated with subsequent ICU-acquired gram-negative infections than gram-negative respiratory tract colonization. Gram-negative rectal colonization seems hardly associated with subsequent ICU-acquired gram-negative respiratory tract colonization.
PDF
