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Appropriate interpretation of blood tests is important for risk stratification and guidelines used in the Emergency Department (ED) (such as SIRS or CURB-65). The impact of abnormal blood test values on mortality may change with increasing age due to (patho)-physiologic changes. The aim of this study was therefore to assess the effect of age on the case-mix adjusted association between biomarkers of renal function and homeostasis, inflammation and circulation and in-hospital mortality. This observational multi-center cohort study has used the Netherlands Emergency department Evaluation Database (NEED), including all consecutive ED patients ≥ 18 years of three hospitals. A generalized additive logistic regression model was used to visualize the association between in-hospital mortality, age and five blood tests (creatinine, sodium, leukocytes, C-reactive Protein, and hemoglobin). Multivariable logistic regression analyses were used to assess the association between the number of abnormal blood test values and mortality per age category (18–50; 51–65; 66–80; > 80 years). Of the 94,974 included patients, 2550 (2.7%) patients died in-hospital. Mortality increased gradually for C-reactive Protein (CRP), and had a U-shaped association for creatinine, sodium, leukocytes, and hemoglobin. Age significantly affected the associations of all studied blood tests except in leukocytes. In addition, with increasing age categories, case-mix adjusted mortality increased with the number of abnormal blood tests. In summary, the association between blood tests and (adjusted) mortality depends on age. Mortality increases gradually or in a U-shaped manner with increasing blood test values. Age-adjusted numerical scores may improve risk stratification. Our results have implications for interpretation of blood tests and their use in risk stratification tools and acute care guidelines. Trial registration number Netherlands Trial Register (NTR) NL8422, 03/2020.

Post cardiac arrest syndrome is associated with high morbidity and mortality, which is related not only to a poor neurological outcome but also to respiratory and cardiovascular dysfunctions. The control of gas exchange, and in particular oxygenation and carbon dioxide levels, is fundamental in mechanically ventilated patients after resuscitation, as arterial blood gases derangement might have important effects on the cerebral blood flow and systemic physiology.In particular, the pathophysiological role of carbon dioxide (CO2) levels is strongly underestimated, as its alterations quickly affect also the changes of intracellular pH, and consequently influence metabolic energy and oxygen demand. Hypo/hypercapnia, as well as mechanical ventilation during and after resuscitation, can affect CO2 levels and trigger a dangerous pathophysiological vicious circle related to the relationship between pH, cellular demand, and catecholamine levels. The developing hypocapnia can nullify the beneficial effects of the hypothermia. The aim of this review was to describe the pathophysiology and clinical consequences of arterial blood gases and pH after cardiac arrest.According to our findings, the optimal ventilator strategies in post cardiac arrest patients are not fully understood, and oxygen and carbon dioxide targets should take in consideration a complex pattern of pathophysiological factors. Further studies are warranted to define the optimal settings of mechanical ventilation in patients after cardiac arrest.

BackgroundLung ultrasound can adequately monitor disease severity in pneumonia and acute respiratory distress syndrome. We hypothesize lung ultrasound can adequately monitor COVID-19 pneumonia in critically ill patients.MethodsAdult patients with COVID-19 pneumonia admitted to the intensive care unit of two academic hospitals who underwent a 12-zone lung ultrasound and a chest CT examination were included. Baseline characteristics, and outcomes including composite endpoint death or ICU stay > 30 days were recorded. Lung ultrasound and CT images were quantified as a lung ultrasound score involvement index (LUSI) and CT severity involvement index (CTSI). Primary outcome was the correlation, agreement, and concordance between LUSI and CTSI. Secondary outcome was the association of LUSI and CTSI with the composite endpoints.ResultsWe included 55 ultrasound examinations in 34 patients, which were 88% were male, with a mean age of 63 years and mean P/F ratio of 151. The correlation between LUSI and CTSI was strong (r = 0.795), with an overall 15% bias, and limits of agreement ranging − 40 to 9.7. Concordance between changes in sequentially measured LUSI and CTSI was 81%. In the univariate model, high involvement on LUSI and CTSI were associated with a composite endpoint. In the multivariate model, LUSI was the only remaining independent predictor.ConclusionsLung ultrasound can be used as an alternative for chest CT in monitoring COVID-19 pneumonia in critically ill patients as it can quantify pulmonary involvement, register changes over the course of the disease, and predict death or ICU stay > 30 days.Trial registration: NTR, NL8584. Registered 01 May 2020—retrospectively registered, https://www.trialregister.nl/trial/8584

Excessive bleeding may complicate cardiac surgery, and is associated with increased morbidity and mortality. Pharmacological strategies to decrease perioperative bleeding have been investigated in a large number of controlled trials, most of which have shown a decrease in blood loss. However, most studies lacked sufficient power to detect a beneficial effect on clinically more relevant outcomes. We did a meta-analysis of all randomised, controlled trials of the three most frequently used pharmacological strategies to decrease perioperative blood loss (aprotinin, lysine analogues [aminocaproic acid and tranexamic acid], and desmopressin). Studies were included if they reported at least one clinically relevant outcome (mortality, rethoracotomy, proportion of patients receiving a transfusion, or perioperative myocardial infarction) in addition to perioperative blood loss. In addition, a separate meta-analysis was done for studies concerning complicated cardiac surgery. We identified 72 trials (8409 patients) that met the inclusion criteria. Treatment with aprotinin decreased mortality almost two-fold (odds ratio 0·55 [95% CI 0·34-0·90]) compared with placebo. Treatment with aprotinin and with lysine analogues decreased the frequency of surgical re-exploration (0·37 [0·25-0·55], and 0·44 [0·22-0·90], respectively). These two treatments also significantly decreased the proportion of patients receiving any allogeneic blood transfusion. By contrast, the use of desmopressin resulted in a small decrease in perioperative blood loss, but was not associated with a beneficial effect on other clinical outcomes. Aprotinin and lysine analogues did not increase the risk of perioperative myocardial infarction; however, desmopressin was associated with a 2·4-fold increase in the risk of this complication. Studies in patients undergoing complicated cardiac surgery showed similar results. Pharmacological strategies that decrease perioperative blood loss in cardiac surgery, in particular aprotinin and lysine analogues, also decrease mortality, the need for rethoracotomy, and the proportion of patients receiving a blood transfusion.

Purpose Hyperoxia may induce pulmonary injury and may increase oxidative stress. In this retrospective database study we aimed to evaluate the response to hyperoxia by intensivists in a Dutch academic intensive care unit. Methods All arterial blood gas (ABG) data from mechanically ventilated patients from 2005 until 2009 were extracted from an electronic storage database of a mixed 32-bed intensive care unit in a university hospital in Amsterdam. Mechanical ventilation settings at the time of the ABG tests were retrieved. Results The results of 126,778 ABG tests from 5,498 mechanically ventilated patients were retrieved including corresponding ventilator settings. In 28,222 (22%) of the ABG tests the arterial oxygen tension (PaO 2 ) was >16 kPa (120 mmHg). In only 25% of the tests with PaO 2 >16 kPa (120 mmHg) was the fraction of inspired oxygen (FiO 2 ) decreased. Hyperoxia was accepted without adjustment in ventilator settings if FiO 2 was 0.4 or lower. Conclusion Hyperoxia is frequently seen but in most cases does not lead to adjustment of ventilator settings if FiO 2 <0.41. Implementation of guidelines concerning oxygen therapy should be improved and further research is needed concerning the effects of frequently encountered hyperoxia.

Intensive care units (ICUs) are increasingly interested in assessing and improving their performance. ICU Length of Stay (LoS) could be seen as an indicator for efficiency of care. However, little consensus exists on which prognostic method should be used to adjust ICU LoS for case-mix factors. This study compared the performance of different regression models when predicting ICU LoS. We included data from 32,667 unplanned ICU admissions to ICUs participating in the Dutch National Intensive Care Evaluation (NICE) in the year 2011. We predicted ICU LoS using eight regression models: ordinary least squares regression on untransformed ICU LoS,LoS truncated at 30 days and log-transformed LoS; a generalized linear model with a Gaussian distribution and a logarithmic link function; Poisson regression; negative binomial regression; Gamma regression with a logarithmic link function; and the original and recalibrated APACHE IV model, for all patients together and for survivors and non-survivors separately. We assessed the predictive performance of the models using bootstrapping and the squared Pearson correlation coefficient (R2), root mean squared prediction error (RMSPE), mean absolute prediction error (MAPE) and bias. The distribution of ICU LoS was skewed to the right with a median of 1.7 days (interquartile range 0.8 to 4.0) and a mean of 4.2 days (standard deviation 7.9). The predictive performance of the models was between 0.09 and 0.20 for R2, between 7.28 and 8.74 days for RMSPE, between 3.00 and 4.42 days for MAPE and between -2.99 and 1.64 days for bias. The predictive performance was slightly better for survivors than for non-survivors. We were disappointed in the predictive performance of the regression models and conclude that it is difficult to predict LoS of unplanned ICU admissions using patient characteristics at admission time only.

Background There are many prognostic models and scoring systems in use to predict mortality in ICU patients. The only general ICU scoring system developed and validated for patients after cardiac surgery is the APACHE-IV model. This is, however, a labor-intensive scoring system requiring a lot of data and could therefore be prone to error. The SOFA score on the other hand is a simpler system, has been widely used in ICUs and could be a good alternative. The goal of the study was to compare the SOFA score with the APACHE-IV and other ICU prediction models. Methods We investigated, in a large cohort of cardiac surgery patients admitted to Dutch ICUs, how well the SOFA score from the first 24 h after admission, predict hospital and ICU mortality in comparison with other recalibrated general ICU scoring systems. Measures of discrimination, accuracy, and calibration (area under the receiver operating characteristic curve (AUC), Brier score, R 2 , and Ĉ-statistic) were calculated using bootstrapping. The cohort consisted of 36,632 Patients from the Dutch National Intensive Care Evaluation (NICE) registry having had a cardiac surgery procedure for which ICU admission was necessary between January 1st, 2006 and June 31st, 2018. Results Discrimination of the SOFA-, APACHE-IV-, APACHE-II-, SAPS-II-, MPM 24 -II - models to predict hospital mortality was good with an AUC of respectively: 0.809, 0.851, 0.830, 0.850, 0.801. Discrimination of the SOFA-, APACHE-IV-, APACHE-II-, SAPS-II-, MPM 24 -II - models to predict ICU mortality was slightly better with AUCs of respectively: 0.809, 0.906, 0.892, 0.919, 0.862. Calibration of the models was generally poor. Conclusion Although the SOFA score had a good discriminatory power for hospital- and ICU mortality the discriminatory power of the APACHE-IV and SAPS-II was better. The SOFA score should not be preferred as mortality prediction model above traditional prognostic ICU-models.

The primary aim of this study was to evaluate computed tomography (CT)-based bone density analysis at the level of thoracic vertebra 12 (Th12) as a screening method for decreased bone density in patients admitted to the intensive care unit (ICU). Interobserver variability was analyzed. Secondary aims were to assess the prevalence of CT-based low bone density upon ICU admission in a cohort of COVID-19 patients and to assess the potential effect of long-term ICU stay on bone density in these patients. Retrospective single-center cohort study. ICU of the Leiden University Medical Center (LUMC), the Netherlands. Patients admitted to the ICU of the LUMC between March 1st, 2020 and February 1st, 2022 with a diagnosis of COVID-19, and a length of ICU stay of ≥ 21 days. In the included patients both baseline chest CT scans (obtained upon ICU admission) and follow-up chest CT scans (obtained ≥ 21 days after ICU admission) were available for analysis. A total of 118 CT scans in 38 patients were analyzed. There was a good interobserver variability, with an overall mean absolute difference (between measurements of three observers) of 9.7 Hounsfield Units (HU) and an intraclass correlation coefficient (ICC) of 0.93 (95% CI 0.88–0.96). The effect of intravenous contrast administration on bone density measurements was small (+ 7.5 HU (95% CI 3.4–11.5 HU)) higher in contrast enhanced CT images compared to non contrast enhanced CT images). Thirty-seven percent of patients had a bone density < 140 HU, suggestive of osteoporosis. No significant difference was found between bone density upon ICU admission and bone density at follow-up (≥ 21 days after ICU admission). Vertebral CT-based bone density analysis using routine CT scans is an easily applicable method to identify ICU patients with decreased bone density, which could enable enrollment in osteoporosis prevention programs. A high prevalence of low bone density was found in our cohort of ICU patients. There were no changes observed in bone density between baseline and follow-up measurements.

Here, we compare the number of mutant molecules and the variant allele frequency as units of measurement for circulating tumor DNA. We conclude that when using digital droplet PCR, both units of measurement yield greater agreement than when using next generation sequencing. Low frequent mutations and molecular coverage are important factors affecting agreement. These results will improve circulating tumor DNA analysis, contributing to better cancer patient management. Quantification of tumor‐specific variants (TSVs) in cell‐free DNA is rapidly evolving as a prognostic and predictive tool in patients with cancer. Currently, both variant allele frequency (VAF) and number of mutant molecules per mL plasma are used as units of measurement to report those TSVs. However, it is unknown to what extent both units of measurement agree and what are the factors underlying an existing disagreement. To study the agreement between VAF and mutant molecules in current clinical studies, we analyzed 1116 TSVs from 338 patients identified with next‐generation sequencing (NGS) or digital droplet PCR (ddPCR). On different study cohorts, a Deming regression analysis was performed and its 95% prediction interval was used as surrogate for the limits of agreement between VAF and number of mutant molecules per mL and to identify outliers. VAF and number of mutant molecules per mL plasma yielded greater agreement when using ddPCR than NGS. In case of discordance between VAF and number of mutant molecules per mL, insufficient molecular coverage in NGS and high cell‐free DNA concentration were the main responsible factors. We propose several optimization steps needed to bring monitoring of TSVs in cell‐free DNA to its full potential.

Clear and detectable signs of deterioration have been shown to be present in many patients multiple hours before undergoing a serious life-threatening event. To date, few studies are available describing normal practice and the possible effectiveness of structured tools regarding recognition of deteriorating patients. The aim of this study was to describe the current practice in measurement and documentation of vital signs and the possible usefulness of the Modified Early Warning Score (MEWS) to identify deteriorating patients on hospital wards. A retrospective observational study of medical and surgical patients from 2007 with a severe adverse event including cardiopulmonary arrest, unplanned intensive care unit admission, emergency surgery, or unexpected death was performed. We studied all vital parameters that were collected and documented in the 48 hours before these events, and the MEWS was retrospectively calculated. Two hundred four patients were included. In the 48 hours before the event, a total of 2688 measurements of one or more vital signs were taken. Overall, 81% of the patients had an MEWS value of 3 or more at least once during the 48 hours before their event. Recordings of vital signs were mostly incomplete. Even when the MEWS was 3 or more, respiratory rate, diuresis, and oxygen saturation were documented in only 30% to 66% of assessments.