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.

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.

Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis.

BACKGROUND: Identification of clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment. However, previous attempts did not take into account temporal dynamics with high granularity. By including the dimension of time, we aim to gain further insights into the heterogeneity of COVID-19. METHODS: We used granular data from 3202 adult COVID patients in the Dutch Data Warehouse that were admitted to one of 25 Dutch ICUs between February 2020 and March 2021. Parameters including demographics, clinical observations, medications, laboratory values, vital signs, and data from life support devices were selected. Twenty-one datasets were created that each covered 24 h of ICU data for each day of ICU treatment. Clinical phenotypes in each dataset were identified by performing cluster analyses. Both evolution of the clinical phenotypes over time and patient allocation to these clusters over time were tracked. RESULTS: The final patient cohort consisted of 2438 COVID-19 patients with a ICU mortality outcome. Forty-one parameters were chosen for cluster analysis. On admission, both a mild and a severe clinical phenotype were found. After day 4, the severe phenotype split into an intermediate and a severe phenotype for 11 consecutive days. Heterogeneity between phenotypes appears to be driven by inflammation and dead space ventilation. During the 21-day period, only 8.2% and 4.6% of patients in the initial mild and severe clusters remained assigned to the same phenotype respectively. The clinical phenotype half-life was between 5 and 6 days for the mild and severe phenotypes, and about 3 days for the medium severe phenotype. CONCLUSIONS: Patients typically do not remain in the same cluster throughout intensive care treatment. This may have important implications for prognostic or predictive enrichment. Prominent dissimilarities between clinical phenotypes are predominantly driven by inflammation and dead space ventilation.

Extended Lung Ultrasound to Differentiate Between Pneumonia and Atelectasis in Critically Ill Patients: A Diagnostic Accuracy Study.

OBJECTIVES: To determine the diagnostic accuracy of extended lung ultrasonographic assessment, including evaluation of dynamic air bronchograms and color Doppler imaging to differentiate pneumonia and atelectasis in patients with consolidation on chest radiograph. Compare this approach to the Simplified Clinical Pulmonary Infection Score, Lung Ultrasound Clinical Pulmonary Infection Score, and the Bedside Lung Ultrasound in Emergency protocol. DESIGN: Prospective diagnostic accuracy study. SETTING: Adult ICU applying selective digestive decontamination. PATIENTS: Adult patients that underwent a chest radiograph for any indication at any time during admission. Patients with acute respiratory distress syndrome, coronavirus disease 2019, severe thoracic trauma, and infectious isolation measures were excluded. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Lung ultrasound was performed within 24 hours of chest radiograph. Consolidated tissue was assessed for presence of dynamic air bronchograms and with color Doppler imaging for presence of flow. Clinical data were recorded after ultrasonographic assessment. The primary outcome was diagnostic accuracy of dynamic air bronchogram and color Doppler imaging alone and within a decision tree to differentiate pneumonia from atelectasis. Of 120 patients included, 51 (42.5%) were diagnosed with pneumonia. The dynamic air bronchogram had a 45% (95% CI, 31-60%) sensitivity and 99% (95% CI, 92-100%) specificity. Color Doppler imaging had a 90% (95% CI, 79-97%) sensitivity and 68% (95% CI, 56-79%) specificity. The combined decision tree had an 86% (95% CI, 74-94%) sensitivity and an 86% (95% CI, 75-93%) specificity. The Bedside Lung Ultrasound in Emergency protocol had a 100% (95% CI, 93-100%) sensitivity and 0% (95% CI, 0-5%) specificity, while the Simplified Clinical Pulmonary Infection Score and Lung Ultrasound Clinical Pulmonary Infection Score had a 41% (95% CI, 28-56%) sensitivity, 84% (95% CI, 73-92%) specificity and 68% (95% CI, 54-81%) sensitivity, 81% (95% CI, 70-90%) specificity, respectively. CONCLUSIONS: In critically ill patients with pulmonary consolidation on chest radiograph, an extended lung ultrasound protocol is an accurate and directly bedside available tool to differentiate pneumonia from atelectasis. It outperforms standard lung ultrasound and clinical scores.

Lung Ultrasound Signs to Diagnose and Discriminate Interstitial Syndromes in ICU Patients: A Diagnostic Accuracy Study in Two Cohorts.

OBJECTIVES: To determine the diagnostic accuracy of lung ultrasound signs for both the diagnosis of interstitial syndrome and for the discrimination of noncardiogenic interstitial syndrome (NCIS) from cardiogenic pulmonary edema (CPE) in a mixed ICU population. DESIGN: A prospective diagnostic accuracy study with derivation and validation cohorts. SETTING: Three academic mixed ICUs in the Netherlands. PATIENTS: Consecutive adult ICU patients that received a lung ultrasound examination. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULT: The reference standard was the diagnosis of interstitial syndrome (NCIS or CPE) or noninterstitial syndromes (other pulmonary diagnoses and no pulmonary diagnoses) based on full post-hoc clinical chart review except lung ultrasound. The index test was a lung ultrasound examination performed and scored by a researcher blinded to clinical information. A total of 101 patients were included in the derivation and 122 in validation cohort. In the derivation cohort, patients with interstitial syndrome ( n = 56) were reliably discriminated from other patients based on the presence of a B-pattern (defined as greater than or equal to 3 B-lines in one frame) with an accuracy of 94.7% (sensitivity, 90.9%; specificity, 91.1%). For discrimination of NCIS ( n = 29) from CPE ( n = 27), the presence of bilateral pleural line abnormalities (at least two: fragmented, thickened or irregular) had the highest diagnostic accuracy (94.6%; sensitivity, 89.3%; specificity, 100%). A diagnostic algorithm (Bedside Lung Ultrasound for Interstitial Syndrome Hierarchy protocol) using B-pattern and bilateral pleural abnormalities had an accuracy of 0.86 (95% CI, 0.77-0.95) for diagnosis and discrimination of interstitial syndromes. In the validation cohort, which included 122 patients with interstitial syndrome, bilateral pleural line abnormalities discriminated NCIS ( n = 98) from CPE ( n = 24) with a sensitivity of 31% (95% CI, 21-40%) and a specificity of 100% (95% CI, 86-100%). CONCLUSIONS: Lung ultrasound can diagnose and discriminate interstitial syndromes in ICU patients with moderate-to-good accuracy. Pleural line abnormalities are highly specific for NCIS, but sensitivity is limited.

Lung- and Diaphragm-Protective Ventilation by Titrating Inspiratory Support to Diaphragm Effort: A Randomized Clinical Trial.

OBJECTIVES: Lung- and diaphragm-protective ventilation is a novel concept that aims to limit the detrimental effects of mechanical ventilation on the diaphragm while remaining within limits of lung-protective ventilation. The premise is that low breathing effort under mechanical ventilation causes diaphragm atrophy, whereas excessive breathing effort induces diaphragm and lung injury. In a proof-of-concept study, we aimed to assess whether titration of inspiratory support based on diaphragm effort increases the time that patients have effort in a predefined "diaphragm-protective" range, without compromising lung-protective ventilation. DESIGN: Randomized clinical trial. SETTING: Mixed medical-surgical ICU in a tertiary academic hospital in the Netherlands. PATIENTS: Patients (n = 40) with respiratory failure ventilated in a partially-supported mode. INTERVENTIONS: In the intervention group, inspiratory support was titrated hourly to obtain transdiaphragmatic pressure swings in the predefined "diaphragm-protective" range (3-12 cm H2O). The control group received standard-of-care. MEASUREMENTS AND MAIN RESULTS: Transdiaphragmatic pressure, transpulmonary pressure, and tidal volume were monitored continuously for 24 hours in both groups. In the intervention group, more breaths were within "diaphragm-protective" range compared with the control group (median 81%; interquartile range [64-86%] vs 35% [16-60%], respectively; p < 0.001). Dynamic transpulmonary pressures (20.5 ± 7.1 vs 18.5 ± 7.0 cm H2O; p = 0.321) and tidal volumes (7.56 ± 1.47 vs 7.54 ± 1.22 mL/kg; p = 0.961) were not different in the intervention and control group, respectively. CONCLUSIONS: Titration of inspiratory support based on patient breathing effort greatly increased the time that patients had diaphragm effort in the predefined "diaphragm-protective" range without compromising tidal volumes and transpulmonary pressures. This study provides a strong rationale for further studies powered on patient-centered outcomes.

Targeted Temperature Management in Out-of-Hospital Cardiac Arrest With Shockable Rhythm: A Post Hoc Analysis of the Coronary Angiography After Cardiac Arrest Trial.

OBJECTIVES: The optimal targeted temperature in patients with shockable rhythm is unclear, and current guidelines recommend targeted temperature management with a correspondingly wide range between 32°C and 36°C. Our aim was to study survival and neurologic outcome associated with targeted temperature management strategy in postarrest patients with initial shockable rhythm. DESIGN: Observational substudy of the Coronary Angiography after Cardiac Arrest without ST-segment Elevation trial. SETTING: Nineteen hospitals in The Netherlands. PATIENTS: The Coronary Angiography after Cardiac Arrest trial randomized successfully resuscitated patients with shockable rhythm and absence of ST-segment elevation to a strategy of immediate or delayed coronary angiography. In this substudy, 459 patients treated with mild therapeutic hypothermia (32.0-34.0°C) or targeted normothermia (36.0-37.0°C) were included. Allocation to targeted temperature management strategy was at the discretion of the physician. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: After 90 days, 171 patients (63.6%) in the mild therapeutic hypothermia group and 129 (67.9%) in the targeted normothermia group were alive (hazard ratio, 0.86 [95% CI, 0.62-1.18]; log-rank p = 0.35; adjusted odds ratio, 0.89; 95% CI, 0.45-1.72). Patients in the mild therapeutic hypothermia group had longer ICU stay (4 d [3-7 d] vs 3 d [2-5 d]; ratio of geometric means, 1.32; 95% CI, 1.15-1.51), lower blood pressures, higher lactate levels, and increased need for inotropic support. Cerebral Performance Category scores at ICU discharge and 90-day follow-up and patient-reported Mental and Physical Health Scores at 1 year were similar in the two groups. CONCLUSIONS: In the context of out-of-hospital cardiac arrest with shockable rhythm and no ST-elevation, treatment with mild therapeutic hypothermia was not associated with improved 90-day survival compared with targeted normothermia. Neurologic outcomes at 90 days as well as patient-reported Mental and Physical Health Scores at 1 year did not differ between the groups.

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.

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.

Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example.

OBJECTIVES: Critical care medicine is a natural environment for machine learning approaches to improve outcomes for critically ill patients as admissions to ICUs generate vast amounts of data. However, technical, legal, ethical, and privacy concerns have so far limited the critical care medicine community from making these data readily available. The Society of Critical Care Medicine and the European Society of Intensive Care Medicine have identified ICU patient data sharing as one of the priorities under their Joint Data Science Collaboration. To encourage ICUs worldwide to share their patient data responsibly, we now describe the development and release of Amsterdam University Medical Centers Database (AmsterdamUMCdb), the first freely available critical care database in full compliance with privacy laws from both the United States and Europe, as an example of the feasibility of sharing complex critical care data. SETTING: University hospital ICU. SUBJECTS: Data from ICU patients admitted between 2003 and 2016. INTERVENTIONS: We used a risk-based deidentification strategy to maintain data utility while preserving privacy. In addition, we implemented contractual and governance processes, and a communication strategy. Patient organizations, supporting hospitals, and experts on ethics and privacy audited these processes and the database. MEASUREMENTS AND MAIN RESULTS: AmsterdamUMCdb contains approximately 1 billion clinical data points from 23,106 admissions of 20,109 patients. The privacy audit concluded that reidentification is not reasonably likely, and AmsterdamUMCdb can therefore be considered as anonymous information, both in the context of the U.S. Health Insurance Portability and Accountability Act and the European General Data Protection Regulation. The ethics audit concluded that responsible data sharing imposes minimal burden, whereas the potential benefit is tremendous. CONCLUSIONS: Technical, legal, ethical, and privacy challenges related to responsible data sharing can be addressed using a multidisciplinary approach. A risk-based deidentification strategy, that complies with both U.S. and European privacy regulations, should be the preferred approach to releasing ICU patient data. This supports the shared Society of Critical Care Medicine and European Society of Intensive Care Medicine vision to improve critical care outcomes through scientific inquiry of vast and combined ICU datasets.

Why we should sample sparsely and aim for a higher target: Lessons from model-based therapeutic drug monitoring of vancomycin in intensive care patients.

AIMS: To explore the optimal data sampling scheme and the pharmacokinetic (PK) target exposure on which dose computation is based in the model-based therapeutic drug monitoring (TDM) practice of vancomycin in intensive care (ICU) patients. METHODS: We simulated concentration data for 1 day following four sampling schemes, Cmin , Cmax + Cmin , Cmax + Cmid-interval + Cmin , and rich sampling where a sample was drawn every hour within a dose interval. The datasets were used for Bayesian estimation to obtain PK parameters, which were used to compute the doses for the next day based on five PK target exposures: AUC24 = 400, 500, and 600 mg·h/L and Cmin = 15 and 20 mg/L. We then simulated data for the next day, adopting the computed doses, and repeated the above procedure for 7 days. Thereafter, we calculated the percentage error and the normalized root mean square error (NRMSE) of estimated against "true" PK parameters, and the percentage of optimal treatment (POT), defined as the percentage of patients who met 400 ≤ AUC24 ≤ 600 mg·h/L and Cmin ≤ 20 mg/L. RESULTS: PK parameters were unbiasedly estimated in all investigated scenarios and the 6-day average NRMSE were 32.5%/38.5% (CL/V, where CL is clearance and V is volume of distribution) in the trough sampling scheme and 27.3%/26.5% (CL/V) in the rich sampling scheme. Regarding POT, the sampling scheme had marginal influence, while target exposure showed clear impacts that the maximum POT of 71.5% was reached when doses were computed based on AUC24 = 500 mg·h/L. CONCLUSIONS: For model-based TDM of vancomycin in ICU patients, sampling more frequently than taking only trough samples adds no value and dosing based on AUC24 = 500 mg·h/L lead to the best POT.

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.

Lung ultrasound in a tertiary intensive care unit population: a diagnostic accuracy study.

BACKGROUND: Evidence from previous studies comparing lung ultrasound to thoracic computed tomography (CT) in intensive care unit (ICU) patients is limited due to multiple methodologic weaknesses. While addressing methodologic weaknesses of previous studies, the primary aim of this study is to investigate the diagnostic accuracy of lung ultrasound in a tertiary ICU population. METHODS: This is a single-center, prospective diagnostic accuracy study conducted at a tertiary ICU in the Netherlands. Critically ill patients undergoing thoracic CT for any clinical indication were included. Patients were excluded if time between the index and reference test was over eight hours. Index test and reference test consisted of 6-zone lung ultrasound and thoracic CT, respectively. Hemithoraces were classified by the index and reference test as follows: consolidation, interstitial syndrome, pneumothorax and pleural effusion. Sensitivity, specificity, positive and negative likelihood ratio were estimated. RESULTS: In total, 87 patients were included of which eight exceeded the time limit and were subsequently excluded. In total, there were 147 respiratory conditions in 79 patients. The estimated sensitivity and specificity to detect consolidation were 0.76 (95%CI: 0.68 to 0.82) and 0.92 (0.87 to 0.96), respectively. For interstitial syndrome they were 0.60 (95%CI: 0.48 to 0.71) and 0.69 (95%CI: 0.58 to 0.79). For pneumothorax they were 0.59 (95%CI: 0.33 to 0.82) and 0.97 (95%CI: 0.93 to 0.99). For pleural effusion they were 0.85 (95%CI: 0.77 to 0.91) and 0.77 (95%CI: 0.62 to 0.88). CONCLUSIONS: In conclusion, lung ultrasound is an adequate diagnostic modality in a tertiary ICU population to detect consolidations, interstitial syndrome, pneumothorax and pleural effusion. Moreover, one should be careful not to interpret lung ultrasound results in deterministic fashion as multiple respiratory conditions can be present in one patient. Trial registration This study was retrospectively registered at Netherlands Trial Register on March 17, 2021, with registration number NL9344.

Duration of antibiotic treatment using procalcitonin-guided treatment algorithms in older patients: a patient-level meta-analysis from randomized controlled trials.

BACKGROUND: Older patients have a less pronounced immune response to infection, which may also influence infection biomarkers. There is currently insufficient data regarding clinical effects of procalcitonin (PCT) to guide antibiotic treatment in older patients. OBJECTIVE AND DESIGN: We performed an individual patient data meta-analysis to investigate the association of age on effects of PCT-guided antibiotic stewardship regarding antibiotic use and outcome. SUBJECTS AND METHODS: We had access to 9,421 individual infection patients from 28 randomized controlled trials comparing PCT-guided antibiotic therapy (intervention group) or standard care. We stratified patients according to age in four groups (<75 years [n = 7,079], 75-80 years [n = 1,034], 81-85 years [n = 803] and >85 years [n = 505]). The primary endpoint was the duration of antibiotic treatment and the secondary endpoints were 30-day mortality and length of stay. RESULTS: Compared to control patients, mean duration of antibiotic therapy in PCT-guided patients was significantly reduced by 24, 22, 26 and 24% in the four age groups corresponding to adjusted differences in antibiotic days of -1.99 (95% confidence interval [CI] -2.36 to -1.62), -1.98 (95% CI -2.94 to -1.02), -2.20 (95% CI -3.15 to -1.25) and - 2.10 (95% CI -3.29 to -0.91) with no differences among age groups. There was no increase in the risk for mortality in any of the age groups. Effects were similar in subgroups by infection type, blood culture result and clinical setting (P interaction >0.05). CONCLUSIONS: This large individual patient data meta-analysis confirms that, similar to younger patients, PCT-guided antibiotic treatment in older patients is associated with significantly reduced antibiotic exposures and no increase in mortality.

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.

Ultrasound to Detect Central Venous Catheter Placement Associated Complications: A Multicenter Diagnostic Accuracy Study.

BACKGROUND: Mechanical complications arising after central venous catheter placement are mostly malposition or pneumothorax. To date, to confirm correct position and detect pneumothorax, chest x-ray film has been the reference standard, while ultrasound might be an accurate alternative. The aim of this study was to evaluate diagnostic accuracy of ultrasound to detect central venous catheter malposition and pneumothorax. METHODS: This was a prospective, multicenter, diagnostic accuracy study conducted at the intensive care unit and postanesthesia care unit. Adult patients who underwent central venous catheterization of the internal jugular vein or subclavian vein were included. Index test consisted of venous, cardiac, and lung ultrasound. Standard reference test was chest x-ray film. Primary outcome was diagnostic accuracy of ultrasound to detect malposition and pneumothorax; for malposition, sensitivity, specificity, and other accuracy parameters were estimated. For pneumothorax, because chest x-ray film is an inaccurate reference standard to diagnose it, agreement and Cohen's κ-coefficient were determined. Secondary outcomes were accuracy of ultrasound to detect clinically relevant complications and feasibility of ultrasound. RESULTS: In total, 758 central venous catheterizations were included. Malposition occurred in 23 (3.3%) out of 688 cases included in the analysis. Ultrasound sensitivity was 0.70 (95% CI, 0.49 to 0.86) and specificity 0.99 (95% CI, 0.98 to 1.00). Pneumothorax occurred in 5 (0.7%) to 11 (1.5%) out of 756 cases according to chest x-ray film and ultrasound, respectively. In 748 out of 756 cases (98.9%), there was agreement between ultrasound and chest x-ray film with a Cohen's κ-coefficient of 0.50 (95% CI, 0.19 to 0.80). CONCLUSIONS: This multicenter study shows that the complication rate of central venous catheterization is low and that ultrasound produces a moderate sensitivity and high specificity to detect malposition. There is moderate agreement with chest x-ray film for pneumothorax. In conclusion, ultrasound is an accurate diagnostic modality to detect malposition and pneumothorax.

Optimizing Predictive Performance of Bayesian Forecasting for Vancomycin Concentration in Intensive Care Patients.

PURPOSE: Bayesian forecasting is crucial for model-based dose optimization based on therapeutic drug monitoring (TDM) data of vancomycin in intensive care (ICU) patients. We aimed to evaluate the performance of Bayesian forecasting using maximum a posteriori (MAP) estimation for model-based TDM. METHODS: We used a vancomycin TDM data set (n = 408 patients). We compared standard MAP-based Bayesian forecasting with two alternative approaches: (i) adaptive MAP which handles data over multiple iterations, and (ii) weighted MAP which weights the likelihood contribution of data. We evaluated the percentage error (PE) for seven scenarios including historical TDM data from the preceding day up to seven days. RESULTS: The mean of median PEs of all scenarios for the standard MAP, adaptive MAP and weighted MAP method were - 7.7%, -4.5% and - 6.7%. The adaptive MAP also showed the narrowest inter-quartile range of PE. In addition, regardless of MAP method, including historical TDM data further in the past will increase prediction errors. CONCLUSIONS: The proposed adaptive MAP method outperforms standard MAP in predictive performance and may be considered for improvement of model-based dose optimization. The inclusion of historical data beyond either one day (standard MAP and weighted MAP) or two days (adaptive MAP) reduces predictive performance.

Association of kidney function with effectiveness of procalcitonin-guided antibiotic treatment: a patient-level meta-analysis from randomized controlled trials.

Objectives: Patients with impaired kidney function have a significantly slower decrease of procalcitonin (PCT) levels during infection. Our aim was to study PCT-guided antibiotic stewardship and clinical outcomes in patients with impairments of kidney function as assessed by creatinine levels measured upon hospital admission. Methods: We pooled and analyzed individual data from 15 randomized controlled trials who were randomly assigned to receive antibiotic therapy based on a PCT-algorithms or based on standard of care. We stratified patients on the initial glomerular filtration rate (GFR, ml/min/1.73 m2) in three groups (GFR >90 [chronic kidney disease; CKD 1], GFR 15-89 [CKD 2-4] and GFR<15 [CKD 5]). The main efficacy and safety endpoints were duration of antibiotic treatment and 30-day mortality. Results: Mean duration of antibiotic treatment was significantly shorter in PCT-guided (n=2,492) compared to control patients (n=2,510) (9.5-7.6 days; adjusted difference in days -2.01 [95% CI, -2.45 to -1.58]). CKD 5 patients had overall longer treatment durations, but a 2.5-day reduction in treatment duration was still found in patients receiving in PCT-guided care (11.3 vs. 8.6 days [95% CI -3.59 to -1.40]). There were 397 deaths in 2,492 PCT-group patients (15.9%) compared to 460 deaths in 2,510 control patients (18.3%) (adjusted odds ratio, 0.88 [95% CI 0.78 to 0.98)]. Effects of PCT-guidance on antibiotic treatment duration and mortality were similar in subgroups stratified by infection type and clinical setting (p interaction >0.05). Conclusions: This individual patient data meta-analysis confirms that the use of PCT in patients with impaired kidney function, as assessed by admission creatinine levels, is associated with shorter antibiotic courses and lower mortality rates.

Breath-synchronized electrical stimulation of the expiratory muscles in mechanically ventilated patients: a randomized controlled feasibility study and pooled analysis.

BACKGROUND: Expiratory muscle weakness leads to difficult ventilator weaning. Maintaining their activity with functional electrical stimulation (FES) may improve outcome. We studied feasibility of breath-synchronized expiratory population muscle FES in a mixed ICU population ("Holland study") and pooled data with our previous work ("Australian study") to estimate potential clinical effects in a larger group. METHODS: Holland: Patients with a contractile response to FES received active or sham expiratory muscle FES (30 min, twice daily, 5 days/week until weaned). Main endpoints were feasibility (e.g., patient recruitment, treatment compliance, stimulation intensity) and safety. Pooled: Data on respiratory muscle thickness and ventilation duration from the Holland and Australian studies were combined (N = 40) in order to estimate potential effect size. Plasma cytokines (day 0, 3) were analyzed to study the effects of FES on systemic inflammation. RESULTS: Holland: A total of 272 sessions were performed (active/sham: 169/103) in 20 patients (N = active/sham: 10/10) with a total treatment compliance rate of 91.1%. No FES-related serious adverse events were reported. Pooled: On day 3, there was a between-group difference (N = active/sham: 7/12) in total abdominal expiratory muscle thickness favoring the active group [treatment difference (95% confidence interval); 2.25 (0.34, 4.16) mm, P = 0.02] but not on day 5. Plasma cytokine levels indicated that early FES did not induce systemic inflammation. Using a survival analysis approach for the total study population, median ventilation duration and ICU length of stay were 10 versus 52 (P = 0.07), and 12 versus 54 (P = 0.03) days for the active versus sham group. Median ventilation duration of patients that were successfully extubated was 8.5 [5.6-12.2] versus 10.5 [5.3-25.6] days (P = 0.60) for the active (N = 16) versus sham (N = 10) group, and median ICU length of stay was 10.5 [8.0-14.5] versus 14.0 [9.0-19.5] days (P = 0.36) for those active (N = 16) versus sham (N = 8) patients that were extubated and discharged alive from the ICU. During ICU stay, 3/20 patients died in the active group versus 8/20 in the sham group (P = 0.16). CONCLUSION: Expiratory muscle FES is feasible in selected ICU patients and might be a promising technique within a respiratory muscle-protective ventilation strategy. The next step is to study the effects on weaning and ventilator liberation outcome. TRIAL REGISTRATION: ClinicalTrials.gov, ID NCT03453944. Registered 05 March 2018-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03453944 .