Does Reinforcement Learning Improve Outcomes for Critically Ill Patients? A Systematic Review and Level-of-Readiness Assessment.

OBJECTIVE: Reinforcement learning (RL) is a machine learning technique uniquely effective at sequential decision-making, which makes it potentially relevant to ICU treatment challenges. We set out to systematically review, assess level-of-readiness and meta-analyze the effect of RL on outcomes for critically ill patients. DATA SOURCES: A systematic search was performed in PubMed, Embase.com, Clarivate Analytics/Web of Science Core Collection, Elsevier/SCOPUS and the Institute of Electrical and Electronics Engineers Xplore Digital Library from inception to March 25, 2022, with subsequent citation tracking. DATA EXTRACTION: Journal articles that used an RL technique in an ICU population and reported on patient health-related outcomes were included for full analysis. Conference papers were included for level-of-readiness assessment only. Descriptive statistics, characteristics of the models, outcome compared with clinician's policy and level-of-readiness were collected. RL-health risk of bias and applicability assessment was performed. DATA SYNTHESIS: A total of 1,033 articles were screened, of which 18 journal articles and 18 conference papers, were included. Thirty of those were prototyping or modeling articles and six were validation articles. All articles reported RL algorithms to outperform clinical decision-making by ICU professionals, but only in retrospective data. The modeling techniques for the state-space, action-space, reward function, RL model training, and evaluation varied widely. The risk of bias was high in all articles, mainly due to the evaluation procedure. CONCLUSION: In this first systematic review on the application of RL in intensive care medicine we found no studies that demonstrated improved patient outcomes from RL-based technologies. All studies reported that RL-agent policies outperformed clinician policies, but such assessments were all based on retrospective off-policy evaluation.

Do Thresholds for Invasive Ventilation in Hypoxemic Respiratory Failure Exist? A Cohort Study.

Rationale: Invasive ventilation is a significant event for patients with respiratory failure. Physiologic thresholds standardize the use of invasive ventilation in clinical trials, but it is unknown whether thresholds prompt invasive ventilation in clinical practice. Objectives: To measure, in patients with hypoxemic respiratory failure, the probability of invasive ventilation within 3 hours after meeting physiologic thresholds. Methods: We studied patients admitted to intensive care receiving FiO2 of 0.4 or more via nonrebreather mask, noninvasive positive pressure ventilation, or high-flow nasal cannula, using data from the Medical Information Mart for Intensive Care (MIMIC)-IV database (2008-2019) and the Amsterdam University Medical Centers Database (AmsterdamUMCdb) (2003-2016). We evaluated 17 thresholds, including the ratio of arterial to inspired oxygen, the ratio of saturation to inspired oxygen ratio, composite scores, and criteria from randomized trials. We report the probability of invasive ventilation within 3 hours of meeting each threshold and its association with covariates using odds ratios (ORs) and 95% credible intervals (CrIs). Measurements and Main Results: We studied 4,726 patients (3,365 from MIMIC, 1,361 from AmsterdamUMCdb). Invasive ventilation occurred in 28% (1,320). In MIMIC, the highest probability of invasive ventilation within 3 hours of meeting a threshold was 20%, after meeting prespecified neurologic or respiratory criteria while on vasopressors, and 19%, after a ratio of arterial to inspired oxygen of <80 mm Hg. In AmsterdamUMCdb, the highest probability was 34%, after vasopressor initiation, and 25%, after a ratio of saturation to inspired oxygen of <90. The probability after meeting the threshold from randomized trials was 9% (MIMIC) and 13% (AmsterdamUMCdb). In MIMIC, a race/ethnicity of Black (OR, 0.75; 95% CrI, 0.57-0.96) or Asian (OR, 0.6; 95% CrI, 0.35-0.95) compared with White was associated with decreased probability of invasive ventilation after meeting a threshold. Conclusions: The probability of invasive ventilation within 3 hours of meeting physiologic thresholds was low and associated with patient race/ethnicity.

Lung Ultrasound Prediction Model for Acute Respiratory Distress Syndrome: A Multicenter Prospective Observational Study.

Rationale: Lung ultrasound (LUS) is a promising tool for diagnosis of acute respiratory distress syndrome (ARDS), but adequately sized studies with external validation are lacking. Objectives: To develop and validate a data-driven LUS score for diagnosis of ARDS and compare its performance with that of chest radiography (CXR). Methods: This multicenter prospective observational study included invasively ventilated ICU patients who were divided into a derivation cohort and a validation cohort. Three raters scored ARDS according to the Berlin criteria, resulting in a classification of "certain no ARDS," or "certain ARDS" when experts agreed or "uncertain ARDS" when evaluations conflicted. Uncertain cases were classified in a consensus meeting. Results of a 12-region LUS exam were used in a logistic regression model to develop the LUS-ARDS score. Measurements and Main Results: Three hundred twenty-four (16% certain ARDS) and 129 (34% certain ARDS) patients were included in the derivation cohort and the validation cohort, respectively. With an ARDS diagnosis by the expert panel as the reference test, the LUS-ARDS score, including the left and right LUS aeration scores and anterolateral pleural line abnormalities, had an area under the receiver operating characteristic (ROC) curve of 0.90 (95% confidence interval [CI], 0.85-0.95) in certain patients of the derivation cohort and 0.80 (95% CI, 0.72-0.87) in all patients of the validation cohort. Within patients who had imaging-gold standard chest computed tomography available, diagnostic accuracy of eight independent CXR readers followed the ROC curve of the LUS-ARDS score. Conclusions: The LUS-ARDS score can be used to accurately diagnose ARDS also after external validation. The LUS-ARDS score may be a useful adjunct to a diagnosis of ARDS after further validation, as it showed performance comparable with that of the current practice with experienced CXR readers but more objectifiable diagnostic accuracy at each cutoff.

Performance of Noninvasive Airway Occlusion Maneuvers to Assess Lung Stress and Diaphragm Effort in Mechanically Ventilated Critically Ill Patients.

BACKGROUND: Monitoring and controlling lung stress and diaphragm effort has been hypothesized to limit lung injury and diaphragm injury. The occluded inspiratory airway pressure (Pocc) and the airway occlusion pressure at 100 ms (P0.1) have been used as noninvasive methods to assess lung stress and respiratory muscle effort, but comparative performance of these measures and their correlation to diaphragm effort is unknown. The authors hypothesized that Pocc and P0.1 correlate with diaphragm effort and lung stress and would have strong discriminative performance in identifying extremes of lung stress and diaphragm effort. METHODS: Change in transdiaphragmatic pressure and transpulmonary pressure was obtained with double-balloon nasogastric catheters in critically ill patients (n = 38). Pocc and P0.1 were measured every 1 to 3 h. Correlations between Pocc and P0.1 with change in transdiaphragmatic pressure and transpulmonary pressure were computed from patients from the first cohort. Accuracy of Pocc and P0.1 to identify patients with extremes of lung stress (change in transpulmonary pressure > 20 cm H2O) and diaphragm effort (change in transdiaphragmatic pressure < 3 cm H2O and >12 cm H2O) in the preceding hour was assessed with area under receiver operating characteristic curves. Cutoffs were validated in patients from the second cohort (n = 13). RESULTS: Pocc and P0.1 correlate with change in transpulmonary pressure (R2 = 0.62 and 0.51, respectively) and change in transdiaphragmatic pressure (R2 = 0.53 and 0.22, respectively). Area under receiver operating characteristic curves to detect high lung stress is 0.90 (0.86 to 0.94) for Pocc and 0.88 (0.84 to 0.92) for P0.1. Area under receiver operating characteristic curves to detect low diaphragm effort is 0.97 (0.87 to 1.00) for Pocc and 0.93 (0.81 to 0.99) for P0.1. Area under receiver operating characteristic curves to detect high diaphragm effort is 0.86 (0.81 to 0.91) for Pocc and 0.73 (0.66 to 0.79) for P0.1. Performance was similar in the external dataset. CONCLUSIONS: Pocc and P0.1 correlate with lung stress and diaphragm effort in the preceding hour. Diagnostic performance of Pocc and P0.1 to detect extremes in these parameters is reasonable to excellent. Pocc is more accurate in detecting high diaphragm effort.

A structured diagnostic algorithm for patients with ARDS.

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2023. Other selected articles can be found online at  https://www.biomedcentral.com/collections/annualupdate2023 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from  https://link.springer.com/bookseries/8901 .

Oxygenation thresholds for invasive ventilation in hypoxemic respiratory failure: a target trial emulation in two cohorts.

BACKGROUND: The optimal thresholds for the initiation of invasive ventilation in patients with hypoxemic respiratory failure are unknown. Using the saturation-to-inspired oxygen ratio (SF), we compared lower versus higher hypoxemia severity thresholds for initiating invasive ventilation. METHODS: This target trial emulation included patients from the Medical Information Mart for Intensive Care (MIMIC-IV, 2008-2019) and the Amsterdam University Medical Centers (AmsterdamUMCdb, 2003-2016) databases admitted to intensive care and receiving inspired oxygen fraction ≥ 0.4 via non-rebreather mask, noninvasive ventilation, or high-flow nasal cannula. We compared the effect of using invasive ventilation initiation thresholds of SF < 110, < 98, and < 88 on 28-day mortality. MIMIC-IV was used for the primary analysis and AmsterdamUMCdb for the secondary analysis. We obtained posterior means and 95% credible intervals (CrI) with nonparametric Bayesian G-computation. RESULTS: We studied 3,357 patients in the primary analysis. For invasive ventilation initiation thresholds SF < 110, SF < 98, and SF < 88, the predicted 28-day probabilities of invasive ventilation were 72%, 47%, and 19%. Predicted 28-day mortality was lowest with threshold SF < 110 (22.2%, CrI 19.2 to 25.0), compared to SF < 98 (absolute risk increase 1.6%, CrI 0.6 to 2.6) or SF < 88 (absolute risk increase 3.5%, CrI 1.4 to 5.4). In the secondary analysis (1,279 patients), the predicted 28-day probability of invasive ventilation was 50% for initiation threshold SF < 110, 28% for SF < 98, and 19% for SF < 88. In contrast with the primary analysis, predicted mortality was highest with threshold SF < 110 (14.6%, CrI 7.7 to 22.3), compared to SF < 98 (absolute risk decrease 0.5%, CrI 0.0 to 0.9) or SF < 88 (absolute risk decrease 1.9%, CrI 0.9 to 2.8). CONCLUSION: Initiating invasive ventilation at lower hypoxemia severity will increase the rate of invasive ventilation, but this can either increase or decrease the expected mortality, with the direction of effect likely depending on baseline mortality risk and clinical context.

Red Blood Cell Transfusion in the Intensive Care Unit.

Importance: Red blood cell (RBC) transfusion is common among patients admitted to the intensive care unit (ICU). Despite multiple randomized clinical trials of hemoglobin (Hb) thresholds for transfusion, little is known about how these thresholds are incorporated into current practice. Objective: To evaluate and describe ICU RBC transfusion practices worldwide. Design, Setting, and Participants: International, prospective, cohort study that involved 3643 adult patients from 233 ICUs in 30 countries on 6 continents from March 2019 to October 2022 with data collection in prespecified weeks. Exposure: ICU stay. Main Outcomes and Measures: The primary outcome was the occurrence of RBC transfusion during ICU stay. Additional outcomes included the indication(s) for RBC transfusion (consisting of clinical reasons and physiological triggers), the stated Hb threshold and actual measured Hb values before and after an RBC transfusion, and the number of units transfused. Results: Among 3908 potentially eligible patients, 3643 were included across 233 ICUs (median of 11 patients per ICU [IQR, 5-20]) in 30 countries on 6 continents. Among the participants, the mean (SD) age was 61 (16) years, 62% were male (2267/3643), and the median Sequential Organ Failure Assessment score was 3.2 (IQR, 1.5-6.0). A total of 894 patients (25%) received 1 or more RBC transfusions during their ICU stay, with a median total of 2 units per patient (IQR, 1-4). The proportion of patients who received a transfusion ranged from 0% to 100% across centers, from 0% to 80% across countries, and from 19% to 45% across continents. Among the patients who received a transfusion, a total of 1727 RBC transfusions were administered, wherein the most common clinical indications were low Hb value (n = 1412 [81.8%]; mean [SD] lowest Hb before transfusion, 7.4 [1.2] g/dL), active bleeding (n = 479; 27.7%), and hemodynamic instability (n = 406 [23.5%]). Among the events with a stated physiological trigger, the most frequently stated triggers were hypotension (n = 728 [42.2%]), tachycardia (n = 474 [27.4%]), and increased lactate levels (n = 308 [17.8%]). The median lowest Hb level on days with an RBC transfusion ranged from 5.2 g/dL to 13.1 g/dL across centers, from 5.3 g/dL to 9.1 g/dL across countries, and from 7.2 g/dL to 8.7 g/dL across continents. Approximately 84% of ICUs administered transfusions to patients at a median Hb level greater than 7 g/dL. Conclusions and Relevance: RBC transfusion was common in patients admitted to ICUs worldwide between 2019 and 2022, with high variability across centers in transfusion practices.

Mid-regional proadrenomedullin, C-terminal proendothelin-1 values, and disease course are not different in critically ill SARS-CoV-2 pneumonia patients with obesity.

BACKGROUND/OBJECTIVES: Patients affected by obesity and Coronavirus disease 2019, the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), appear to have a higher risk for intensive care (ICU) admission. A state of low-grade chronic inflammation in obesity has been suggested as one of the underlying mechanisms. We investigated whether obesity is associated with differences in new inflammatory biomarkers mid-regional proadrenomedullin (MR-proADM), C-terminal proendothelin-1 (CT-proET-1), and clinical outcomes in critically ill patients with SARS-CoV-2 pneumonia. SUBJECTS/METHODS: A total of 105 critically ill patients with SARS-CoV-2 pneumonia were divided in patients with obesity (body mass index (BMI) ≥ 30 kg/m2, n = 42) and patients without obesity (BMI < 30 kg/m2, n = 63) and studied in a retrospective observational cohort study. MR-proADM, CT-proET-1 concentrations, and conventional markers of white blood count (WBC), C-reactive protein (CRP), and procalcitonin (PCT) were collected during the first 7 days. RESULTS: BMI was 33.5 (32-36.1) and 26.2 (24.7-27.8) kg/m2 in the group with and without obesity. There were no significant differences in concentrations MR-proADM, CT-proET-1, WBC, CRP, and PCT at baseline and the next 6 days between patients with and without obesity. Only MR-proADM changed significantly over time (p = 0.039). Also, BMI did not correlate with inflammatory biomarkers (MR-proADM rho = 0.150, p = 0.125, CT-proET-1 rho = 0.179, p = 0.067, WBC rho = -0.044, p = 0.654, CRP rho = 0.057, p = 0.564, PCT rho = 0.022, p = 0.842). Finally, no significant differences in time on a ventilator, ICU length of stay, and 28-day mortality between patients with or without obesity were observed. CONCLUSIONS: In critically ill patients with confirmed SARS-CoV-2 pneumonia, obesity was not associated with differences in MR-proADM, and CT-proET-1, or impaired outcome. TRIAL REGISTRATION: Netherlands Trial Register, NL8460.

Association between early cumulative fluid balance and successful liberation from invasive ventilation in COVID-19 ARDS patients - insights from the PRoVENT-COVID study: a national, multicenter, observational cohort analysis.

BACKGROUND: Increasing evidence indicates the potential benefits of restricted fluid management in critically ill patients. Evidence lacks on the optimal fluid management strategy for invasively ventilated COVID-19 patients. We hypothesized that the cumulative fluid balance would affect the successful liberation of invasive ventilation in COVID-19 patients with acute respiratory distress syndrome (ARDS). METHODS: We analyzed data from the multicenter observational 'PRactice of VENTilation in COVID-19 patients' study. Patients with confirmed COVID-19 and ARDS who required invasive ventilation during the first 3 months of the international outbreak (March 1, 2020, to June 2020) across 22 hospitals in the Netherlands were included. The primary outcome was successful liberation of invasive ventilation, modeled as a function of day 3 cumulative fluid balance using Cox proportional hazards models, using the crude and the adjusted association. Sensitivity analyses without missing data and modeling ARDS severity were performed. RESULTS: Among 650 patients, three groups were identified. Patients in the higher, intermediate, and lower groups had a median cumulative fluid balance of 1.98 L (1.27-7.72 L), 0.78 L (0.26-1.27 L), and - 0.35 L (- 6.52-0.26 L), respectively. Higher day 3 cumulative fluid balance was significantly associated with a lower probability of successful ventilation liberation (adjusted hazard ratio 0.86, 95% CI 0.77-0.95, P = 0.0047). Sensitivity analyses showed similar results. CONCLUSIONS: In a cohort of invasively ventilated patients with COVID-19 and ARDS, a higher cumulative fluid balance was associated with a longer ventilation duration, indicating that restricted fluid management in these patients may be beneficial. Trial registration Clinicaltrials.gov ( NCT04346342 ); Date of registration: April 15, 2020.

Development and validation of a multivariable prediction model of central venous catheter-tip colonization in a cohort of five randomized trials.

BACKGROUND: The majority of central venous catheters (CVC) removed in the ICU are not colonized, including when a catheter-related infection (CRI) is suspected. We developed and validated a predictive score to reduce unnecessary CVC removal. METHODS: We conducted a retrospective cohort study from five multicenter randomized controlled trials with systematic catheter-tip culture of consecutive CVCs. Colonization was defined as growth of ≥103 colony-forming units per mL. Risk factors for colonization were identified in the training cohort (CATHEDIA and 3SITES trials; 3899 CVCs of which 575 (15%) were colonized) through multivariable analyses. After internal validation in 500 bootstrapped samples, the CVC-OUT score was computed by attaching points to the robust (> 50% of the bootstraps) risk factors. External validation was performed in the testing cohort (CLEAN, DRESSING2 and ELVIS trials; 6848 CVCs, of which 588 (9%) were colonized). RESULTS: In the training cohort, obesity (1 point), diabetes (1 point), type of CVC (dialysis catheter, 1 point), anatomical insertion site (jugular, 4 points; femoral 5 points), rank of the catheter (second or subsequent, 1 point) and catheterization duration (≥ 5 days, 2 points) were significantly and independently associated with colonization . Area under the ROC curve (AUC) for the CVC-OUT score was 0.69, 95% confidence interval (CI) [0.67-0.72]. In the testing cohort, AUC for the CVC-OUT score was 0.60, 95% CI [0.58-0.62]. Among 1,469 CVCs removed for suspected CRI in the overall population, 1200 (82%) were not colonized. The negative predictive value (NPV) of a CVC-OUT score < 6 points was 94%, 95% CI [93%-95%]. CONCLUSION: The CVC-OUT score had a moderate ability to discriminate catheter-tip colonization, but the high NPV may contribute to reduce unnecessary CVCs removal. Preference of the subclavian site is the strongest and only modifiable risk factor that reduces the likelihood of catheter-tip colonization and consequently the risk of CRI. CLINICAL TRIALS REGISTRATION: NCT00277888, NCT01479153, NCT01629550, NCT01189682, NCT00875069.

Co-infection and ICU-acquired infection in COIVD-19 ICU patients: a secondary analysis of the UNITE-COVID data set.

BACKGROUND: The COVID-19 pandemic presented major challenges for critical care facilities worldwide. Infections which develop alongside or subsequent to viral pneumonitis are a challenge under sporadic and pandemic conditions; however, data have suggested that patterns of these differ between COVID-19 and other viral pneumonitides. This secondary analysis aimed to explore patterns of co-infection and intensive care unit-acquired infections (ICU-AI) and the relationship to use of corticosteroids in a large, international cohort of critically ill COVID-19 patients. METHODS: This is a multicenter, international, observational study, including adult patients with PCR-confirmed COVID-19 diagnosis admitted to ICUs at the peak of wave one of COVID-19 (February 15th to May 15th, 2020). Data collected included investigator-assessed co-infection at ICU admission, infection acquired in ICU, infection with multi-drug resistant organisms (MDRO) and antibiotic use. Frequencies were compared by Pearson's Chi-squared and continuous variables by Mann-Whitney U test. Propensity score matching for variables associated with ICU-acquired infection was undertaken using R library MatchIT using the "full" matching method. RESULTS: Data were available from 4994 patients. Bacterial co-infection at admission was detected in 716 patients (14%), whilst 85% of patients received antibiotics at that stage. ICU-AI developed in 2715 (54%). The most common ICU-AI was bacterial pneumonia (44% of infections), whilst 9% of patients developed fungal pneumonia; 25% of infections involved MDRO. Patients developing infections in ICU had greater antimicrobial exposure than those without such infections. Incident density (ICU-AI per 1000 ICU days) was in considerable excess of reports from pre-pandemic surveillance. Corticosteroid use was heterogenous between ICUs. In univariate analysis, 58% of patients receiving corticosteroids and 43% of those not receiving steroids developed ICU-AI. Adjusting for potential confounders in the propensity-matched cohort, 71% of patients receiving corticosteroids developed ICU-AI vs 52% of those not receiving corticosteroids. Duration of corticosteroid therapy was also associated with development of ICU-AI and infection with an MDRO. CONCLUSIONS: In patients with severe COVID-19 in the first wave, co-infection at admission to ICU was relatively rare but antibiotic use was in substantial excess to that indication. ICU-AI were common and were significantly associated with use of corticosteroids. Trial registration ClinicalTrials.gov: NCT04836065 (retrospectively registered April 8th 2021).

Right dose, right now: bedside, real-time, data-driven, and personalised antibiotic dosing in critically ill patients with sepsis or septic shock-a two-centre randomised clinical trial.

BACKGROUND: Adequate antibiotic dosing may improve outcomes in critically ill patients but is challenging due to altered and variable pharmacokinetics. To address this challenge, AutoKinetics was developed, a decision support system for bedside, real-time, data-driven and personalised antibiotic dosing. This study evaluates the feasibility, safety and efficacy of its clinical implementation. METHODS: In this two-centre randomised clinical trial, critically ill patients with sepsis or septic shock were randomised to AutoKinetics dosing or standard dosing for four antibiotics: vancomycin, ciprofloxacin, meropenem, and ceftriaxone. Adult patients with a confirmed or suspected infection and either lactate > 2 mmol/L or vasopressor requirement were eligible for inclusion. The primary outcome was pharmacokinetic target attainment in the first 24 h after randomisation. Clinical endpoints included mortality, ICU length of stay and incidence of acute kidney injury. RESULTS: After inclusion of 252 patients, the study was stopped early due to the COVID-19 pandemic. In the ciprofloxacin intervention group, the primary outcome was obtained in 69% compared to 3% in the control group (OR 62.5, CI 11.4-1173.78, p < 0.001). Furthermore, target attainment was faster (26 h, CI 18-42 h, p < 0.001) and better (65% increase, CI 49-84%, p < 0.001). For the other antibiotics, AutoKinetics dosing did not improve target attainment. Clinical endpoints were not significantly different. Importantly, higher dosing did not lead to increased mortality or renal failure. CONCLUSIONS: In critically ill patients, personalised dosing was feasible, safe and significantly improved target attainment for ciprofloxacin. TRIAL REGISTRATION: The trial was prospectively registered at Netherlands Trial Register (NTR), NL6501/NTR6689 on 25 August 2017 and at the European Clinical Trials Database (EudraCT), 2017-002478-37 on 6 November 2017.

C-Terminal Proarginine Vasopressin is Associated with Disease Outcome and Mortality, but not with Delayed Cerebral Ischemia in Critically Ill Patients with an Aneurysmal Subarachnoid Hemorrhage: A Prospective Cohort Study.

BACKGROUND: Aneurysmal subarachnoid hemorrhage (aSAH) is an important indication for intensive care unit admission and may lead to significant morbidity and mortality. We assessed the ability of C-terminal proarginine vasopressin (CT-proAVP) to predict disease outcome, mortality, and delayed cerebral ischemia (DCI) in critically ill patients with aSAH compared with the World Federation of Neurological Surgeons (WFNS) score and Acute Physiological and Chronic Health Evaluation IV (APACHE IV) model. METHODS: C-terminal proarginine vasopressin was collected on admission in this single-center, prospective, observational cohort study. The primary aim was to investigate the relationship between CT-proAVP and poor functional outcome at 1 year (Glasgow Outcome Scale score 1-3) in a multivariable logistic regression model adjusted for WFNS and APACHE IV scores. Secondary aims were mortality and DCI. The multivariable logistic regression model for DCI was also adjusted for the modified Fisher scale. RESULTS: In 100 patients, the median CT-proAVP level was 24.9 pmol/L (interquartile range 11.5-53.8); 45 patients had a poor 1-year functional outcome, 19 patients died within 30 days, 25 patients died within 1 year, and DCI occurred in 28 patients. Receiver operating characteristics curves revealed high accuracy for CT-proAVP to identify patients with poor 1-year functional outcome (area under the curve [AUC] 0.84, 95% confidence interval [CI] 0.77-0.92, p < 0.001), 30-day mortality (AUC 0.84, 95% CI 0.76-0.93, p < 0.001), and 1-year mortality (AUC 0.79, 95% CI 0.69-0.89, p < 0.001). CT-proAVP had a low AUC for identifying patients with DCI (AUC 0.67, 95% CI 0.55-0.79, p 0.008). CT-proAVP ≥ 24.9 pmo/L proved to be a significant predictor for poor 1-year functional outcome (odds ratio [OR] 8.04, 95% CI 2.97-21.75, p < 0.001), and CT-proAVP ≥ 29.1 pmol/L and ≥ 27.7 pmol/L were significant predictors for 30-day and 1-year mortality (OR 9.31, 95% CI 1.55-56.07, p 0.015 and OR 5.15, 95% CI 1.48-17.93, p 0.010) in multivariable models with WFNS and APACHE IV scores. CT-proAVP ≥ 29.5 pmol/L was not a significant predictor for DCI in a multivariable model adjusted for the modified Fisher scale (p = 0.061). CONCLUSIONS: C-terminal proarginine vasopressin was able to predict poor functional outcome and mortality in critically ill patients with aSAH. Its prognostic ability to predict DCI was low. TRIAL REGISTRATION: Nederlands Trial Register: NTR4118.

Changes in Respiratory Muscle Thickness during Mechanical Ventilation: Focus on Expiratory Muscles.

BACKGROUND: The lateral abdominal wall muscles are recruited with active expiration, as may occur with high breathing effort, inspiratory muscle weakness, or pulmonary hyperinflation. The effects of critical illness and mechanical ventilation on these muscles are unknown. This study aimed to assess the reproducibility of expiratory muscle (i.e., lateral abdominal wall muscles and rectus abdominis muscle) ultrasound and the impact of tidal volume on expiratory muscle thickness, to evaluate changes in expiratory muscle thickness during mechanical ventilation, and to compare this to changes in diaphragm thickness. METHODS: Two raters assessed the interrater and intrarater reproducibility of expiratory muscle ultrasound (n = 30) and the effect of delivered tidal volume on expiratory muscle thickness (n = 10). Changes in the thickness of the expiratory muscles and the diaphragm were assessed in 77 patients with at least two serial ultrasound measurements in the first week of mechanical ventilation. RESULTS: The reproducibility of the measurements was excellent (interrater intraclass correlation coefficient: 0.994 [95% CI, 0.987 to 0.997]; intrarater intraclass correlation coefficient: 0.992 [95% CI, 0.957 to 0.998]). Expiratory muscle thickness decreased by 3.0 ± 1.7% (mean ± SD) with tidal volumes of 481 ± 64 ml (P < 0.001). The thickness of the expiratory muscles remained stable in 51 of 77 (66%), decreased in 17 of 77 (22%), and increased in 9 of 77 (12%) patients. Reduced thickness resulted from loss of muscular tissue, whereas increased thickness mainly resulted from increased interparietal fasciae thickness. Changes in thickness of the expiratory muscles were not associated with changes in the thickness of the diaphragm (R2 = 0.013; P = 0.332). CONCLUSIONS: Thickness measurement of the expiratory muscles by ultrasound has excellent reproducibility. Changes in the thickness of the expiratory muscles occurred in 34% of patients and were unrelated to changes in diaphragm thickness. Increased expiratory muscle thickness resulted from increased thickness of the fasciae.

Breathing variability-implications for anaesthesiology and intensive care.

The respiratory system reacts instantaneously to intrinsic and extrinsic inputs. This adaptability results in significant fluctuations in breathing parameters, such as respiratory rate, tidal volume, and inspiratory flow profiles. Breathing variability is influenced by several conditions, including sleep, various pulmonary diseases, hypoxia, and anxiety disorders. Recent studies have suggested that weaning failure during mechanical ventilation may be predicted by low respiratory variability. This review describes methods for quantifying breathing variability, summarises the conditions and comorbidities that affect breathing variability, and discusses the potential implications of breathing variability for anaesthesia and intensive care.

Effect of Low-Normal vs High-Normal Oxygenation Targets on Organ Dysfunction in Critically Ill Patients: A Randomized Clinical Trial.

Importance: Hyperoxemia may increase organ dysfunction in critically ill patients, but optimal oxygenation targets are unknown. Objective: To determine whether a low-normal Pao2 target compared with a high-normal target reduces organ dysfunction in critically ill patients with systemic inflammatory response syndrome (SIRS). Design, Setting, and Participants: Multicenter randomized clinical trial in 4 intensive care units in the Netherlands. Enrollment was from February 2015 to October 2018, with end of follow-up to January 2019, and included adult patients admitted with 2 or more SIRS criteria and expected stay of longer than 48 hours. A total of 9925 patients were screened for eligibility, of whom 574 fulfilled the enrollment criteria and were randomized. Interventions: Target Pao2 ranges were 8 to 12 kPa (low-normal, n = 205) and 14 to 18 kPa (high-normal, n = 195). An inspired oxygen fraction greater than 0.60 was applied only when clinically indicated. Main Outcomes and Measures: Primary end point was SOFARANK, a ranked outcome of nonrespiratory organ failure quantified by the nonrespiratory components of the Sequential Organ Failure Assessment (SOFA) score, summed over the first 14 study days. Participants were ranked from fastest organ failure improvement (lowest scores) to worsening organ failure or death (highest scores). Secondary end points were duration of mechanical ventilation, in-hospital mortality, and hypoxemic measurements. Results: Among the 574 patients who were randomized, 400 (70%) were enrolled within 24 hours (median age, 68 years; 140 women [35%]), all of whom completed the trial. The median Pao2 difference between the groups was -1.93 kPa (95% CI, -2.12 to -1.74; P < .001). The median SOFARANK score was -35 points in the low-normal Pao2 group vs -40 in the high-normal Pao2 group (median difference, 10 [95% CI, 0 to 21]; P = .06). There was no significant difference in median duration of mechanical ventilation (3.4 vs 3.1 days; median difference, -0.15 [95% CI, -0.88 to 0.47]; P = .59) and in-hospital mortality (32% vs 31%; odds ratio, 1.04 [95% CI, 0.67 to 1.63]; P = .91). Mild hypoxemic measurements occurred more often in the low-normal group (1.9% vs 1.2%; median difference, 0.73 [95% CI, 0.30 to 1.20]; P < .001). Acute kidney failure developed in 20 patients (10%) in the low-normal Pao2 group and 21 patients (11%) in the high-normal Pao2 group, and acute myocardial infarction in 6 patients (2.9%) in the low-normal Pao2 group and 7 patients (3.6%) in the high-normal Pao2 group. Conclusions and Relevance: Among critically ill patients with 2 or more SIRS criteria, treatment with a low-normal Pao2 target compared with a high-normal Pao2 target did not result in a statistically significant reduction in organ dysfunction. However, the study may have had limited power to detect a smaller treatment effect than was hypothesized. Trial Registration: ClinicalTrials.gov Identifier: NCT02321072.

Observational Research for Therapies Titrated to Effect and Associated With Severity of Illness: Misleading Results From Commonly Used Statistical Methods.

OBJECTIVES: In critically ill patients, treatment dose or intensity is often related to severity of illness and mortality risk, whereas overtreatment or undertreatment (relative to the individual need) may further increase the odds of death. We aimed to investigate how these relationships affect the results of common statistical methods used in observational studies. DESIGN: Using Monte Carlo simulation, we generated data for 5,000 patients with a treatment dose related to the pretreatment mortality risk but with randomly distributed overtreatment or undertreatment. Significant overtreatment or undertreatment (relative to the optimal dose) further increased the mortality risk. A prognostic score that reflects the mortality risk and an outcome of death or survival was then generated. The study was analyzed: 1) using logistic regression to estimate the effect of treatment dose on outcome while controlling for prognostic score and 2) using propensity score matching and inverse probability weighting of the effect of high treatment dose on outcome. The data generation and analyses were repeated 1,500 times over sample sizes between 200 and 30,000 patients, with an increasing accuracy of the prognostic score and with different underlying assumptions. SETTING: Computer-simulated studies. MEASUREMENTS AND MAIN RESULTS: In the simulated 5,000-patient observational study, higher treatment dose was found to be associated with increased odds of death (p = 0.00001) while controlling for the prognostic score with logistic regression. Propensity-matched analysis led to similar results. Larger sample sizes led to equally biased estimates with narrower CIs. A perfect risk predictor negated the bias only under artificially perfect assumptions. CONCLUSIONS: When a treatment dose is associated with severity of illness and should be dosed "enough," logistic regression, propensity score matching, and inverse probability weighting to adjust for confounding by severity of illness lead to biased results. Larger sample sizes lead to more precisely wrong estimates.