Critical care explorations最新文献

Objectives: Delayed cerebral ischemia (DCI) is a major driver of morbidity after aneurysmal subarachnoid hemorrhage (aSAH). Quantitative pupillometry has been shown to be of prognostic value after acute neurological injury. However, the evidence for the use of pupillometric features for the detection of DCI has been conflicting. The aim of this study was to investigate the prognostic value of frequent pupillometric monitoring for DCI detection.

Design: Observational cohort study from a prospective aSAH registry.

Setting: Tertiary referral center.

Patients: Adult patients with confirmed aSAH admitted to the ICU between March 2019 and December 2023.

Interventions: None.

Measurements and main results: One hundred fourteen patients were included, of which 31 (27.2%) suffered from DCI. All patients underwent frequent pupillometry (every 3 hr). We determined the absolute value of the neurological pupil index (NPi) and constriction velocity (CV), and their value normalized to the maximal recorded value between the admission and the pupillometry measure to account for personalized baselines. The association between pupillometry values and the occurrence of DCI within 6-24 hours was investigated. Normalized CV had the best discriminative performance to identify DCI within 8 hours, with an area under the receiver operating characteristic curve of 0.82 (95% CI, 0.69-0.91). NPi, as well as non-normalized metrics, were not significantly associated with DCI.

Conclusions: Normalized CV has a clinically and statistically significant association with the occurrence of DCI after aSAH. Frequent quantitative pupillometry could improve the multimodal monitoring of patients after aSAH with the goal of improving the identification of patients likely to benefit from therapeutic interventions.

Objective: Survivors of pediatric critical illnesses are at risk of significant long-term organ sequelae. Chronic kidney disease (CKD) is a complication of critical illness (and ICU interventions) associated with growth impairment, cardiovascular disease, and early death. Our objective was to synthesize the evidence on the incidence of CKD among survivors of pediatric critical illness.

Data sources: MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, and Cochrane Register of Controlled Trials from inception to February 2024.

Study selection: Observational studies reporting the incidence of de novo CKD among survivors of pediatric critical illness.

Data extraction: Two reviewers independently extracted data on study design, setting, population, demographics, diagnostic criteria, and outcome.

Data synthesis: Meta-analysis was used to describe the incidence of CKD among survivors, risk of bias (RoB) assessed using the Joanna Briggs Institute Tool, and strength and reliability of evidence assessed with GRADE (Grading of Recommendations, Assessment, Development, and Evaluations). CKD was quantified as an estimated glomerular filtration rate (eGFR) less than 90 mL/min/1.73 m2 (outcome 1), eGFR less than 60 mL/min/1.73 m2 (outcome 2), and end-stage renal disease (ESRD) as eGFR less than 15 mL/min per 1.73 m2 (outcome 3). Twelve studies (3642 patients) met selection criteria and reported at least one measure of CKD. The median duration of follow-up was 2, 3.6, and 5 years, respectively, for outcomes 1, 2, and 3. For each threshold, the pooled estimate of CKD incidence was 24% (95% CI, 16-32%) for eGFR less than 90, 14% (95% CI, 6-23%) less than 60, and 4% (95% CI, 0-7%) for ESRD. The overall quality assessment indicated a moderate RoB.

Conclusions: Among a heterogenous population of pediatric critical illness survivors, an important minority of survivors developed CKD or ESRD. This study highlights the importance of diagnostic criteria for reporting, a greater focus on postcritical care surveillance and follow-up to identify those with CKD. Further study would facilitate the delineation of high-risk groups and strategies for improved outcomes.

Objectives: Cardiogenic shock (CS) is associated with high mortality. Patients treated for CS mostly require heparin therapy, which may be associated with complications such as heparin-induced thrombocytopenia (HIT). HIT represents a serious condition associated with platelet decline and increased hypercoagulability and remains a poorly researched field in intensive care medicine. Primary purpose of this study was to: 1) determine HIT prevalence in CS, 2) assess the performance of common diagnostic tests for the workup of HIT, and 3) compare outcomes in CS patients with excluded and confirmed HIT.

Design: Retrospective dual-center study including adult patients 18 years old or older with diagnosed CS and suspected HIT from January 2010 to November 2022.

Setting: Cardiac ICU at the Ludwig-Maximilians University hospital in Munich and the university hospital of Bonn.

Patients and interventions: In this retrospective analysis, adult patients with diagnosed CS and suspected HIT were included. Differences in baseline characteristics, mortality, neurologic and safety outcomes between patients with excluded and confirmed HIT were evaluated.

Measurements and main results: In cases of suspected HIT, positive screening antibodies were detected in 159 of 2808 patients (5.7%). HIT was confirmed via positive functional assay in 57 of 2808 patients, corresponding to a prevalence rate of 2.0%. The positive predictive value for anti-platelet factor 4/heparin screening antibodies was 35.8%. Total in-hospital mortality (58.8% vs. 57.9%; p > 0.999), 1-month mortality (47.1% vs. 43.9%; p = 0.781), and 12-month mortality (58.8% vs. 59.6%; p > 0.999) were similar between patients with excluded and confirmed HIT, respectively. Furthermore, no significant difference in neurologic outcome among survivors was found between groups (Cerebral Performance Category [CPC] score 1: 8.8% vs. 8.8%; p > 0.999 and CPC 2: 7.8% vs. 12.3%; p = 0.485).

Conclusions: HIT was a rare complication in CS patients treated with unfractionated heparin and was not associated with increased mortality. Also, HIT confirmation was not associated with worse neurologic outcome in survivors. Future studies should aim at developing more precise, standardized, and cost-effective strategies to diagnose HIT and prevent complications.

Objectives: Cardiogenic shock (CS) is associated with high mortality. Patients treated for CS mostly require heparin therapy, which may be associated with complications such as heparin-induced thrombocytopenia (HIT). HIT represents a serious condition associated with platelet decline and increased hypercoagulability and remains a poorly researched field in intensive care medicine. Primary purpose of this study was to: 1) determine HIT prevalence in CS, 2) assess the performance of common diagnostic tests for the workup of HIT, and 3) compare outcomes in CS patients with excluded and confirmed HIT.

Design: Retrospective dual-center study including adult patients 18 years old or older with diagnosed CS and suspected HIT from January 2010 to November 2022.

Setting: Cardiac ICU at the Ludwig-Maximilians University hospital in Munich and the university hospital of Bonn.

Patients and interventions: In this retrospective analysis, adult patients with diagnosed CS and suspected HIT were included. Differences in baseline characteristics, mortality, neurologic and safety outcomes between patients with excluded and confirmed HIT were evaluated.

Measurements and main results: In cases of suspected HIT, positive screening antibodies were detected in 159 of 2808 patients (5.7%). HIT was confirmed via positive functional assay in 57 of 2808 patients, corresponding to a prevalence rate of 2.0%. The positive predictive value for anti-platelet factor 4/heparin screening antibodies was 35.8%. Total in-hospital mortality (58.8% vs. 57.9%; p > 0.999), 1-month mortality (47.1% vs. 43.9%; p = 0.781), and 12-month mortality (58.8% vs. 59.6%; p > 0.999) were similar between patients with excluded and confirmed HIT, respectively. Furthermore, no significant difference in neurologic outcome among survivors was found between groups (Cerebral Performance Category [CPC] score 1: 8.8% vs. 8.8%; p > 0.999 and CPC 2: 7.8% vs. 12.3%; p = 0.485).

Conclusions: HIT was a rare complication in CS patients treated with unfractionated heparin and was not associated with increased mortality. Also, HIT confirmation was not associated with worse neurologic outcome in survivors. Future studies should aim at developing more precise, standardized, and cost-effective strategies to diagnose HIT and prevent complications.

Background and objective: To develop the COVid Veteran (COVet) score for clinical deterioration in Veterans hospitalized with COVID-19 and further validate this model in both Veteran and non-Veteran samples. No such score has been derived and validated while incorporating a Veteran sample.

Derivation cohort: Adults (age ≥ 18 yr) hospitalized outside the ICU with a diagnosis of COVID-19 for model development to the Veterans Health Administration (VHA) (n = 80 hospitals).

Validation cohort: External validation occurred in a VHA cohort of 34 hospitals, as well as six non-Veteran health systems for further external validation (n = 21 hospitals) between 2020 and 2023.

Prediction model: eXtreme Gradient Boosting machine learning methods were used, and performance was assessed using the area under the receiver operating characteristic curve and compared with the National Early Warning Score (NEWS). The primary outcome was transfer to the ICU or death within 24 hours of each new variable observation. Model predictor variables included demographics, vital signs, structured flowsheet data, and laboratory values.

Results: A total of 96,908 admissions occurred during the study period, of which 59,897 were in the Veteran sample and 37,011 were in the non-Veteran sample. During external validation in the Veteran sample, the model demonstrated excellent discrimination, with an area under the receiver operating characteristic curve of 0.88. This was significantly higher than NEWS (0.79; p < 0.01). In the non-Veteran sample, the model also demonstrated excellent discrimination (0.86 vs. 0.79 for NEWS; p < 0.01). The top three variables of importance were eosinophil percentage, mean oxygen saturation in the prior 24-hour period, and worst mental status in the prior 24-hour period.

Conclusions: We used machine learning methods to develop and validate a highly accurate early warning score in both Veterans and non-Veterans hospitalized with COVID-19. The model could lead to earlier identification and therapy, which may improve outcomes.

Objective: During the COVID-19 pandemic, some centers converted intermediate care units (IMCUs) to COVID-19 ICUs (IMCU/ICUs). In this study, we compared adherence to lung protective ventilation (LPV) and outcomes for patients with COVID-19-related acute respiratory distress syndrome (ARDS) treated in an IMCU/ICU versus preexisting medical ICUs (MICUs).

Design: Retrospective observational study using electronic medical record data.

Setting: Two academic medical centers from March 2020 to September 2020 (period 1) and October 2020 to May 2021 (period 2), which capture the first two COVID-19 surges in this health system.

Patients: Adults with COVID-19 receiving invasive mechanical ventilation who met ARDS oxygenation criteria (Pao2/Fio2 ≤ 300 mm Hg or Spo2/Fio2 ≤ 315).

Interventions: None.

Measurements and main results: We defined LPV adherence as the percent of the first 48 hours of mechanical ventilation that met a restrictive definition of LPV of, tidal volume/predicted body weight (Vt/PBW) less than or equal to 6.5 mL/kg and plateau pressure (Pplat) less than or equal to 30 cm H2o. In an expanded definition, we added that if Pplat is greater than 30 cm H2o, Vt/PBW had to be less than 6.0 mL/kg. Using the restricted definition, period 1 adherence was lower among 133 IMCU/ICU versus 199 MICU patients (92% [95% CI, 50-100] vs. 100% [86-100], p = 0.05). Period 2 adherence was similar between groups (100% [75-100] vs. 95% CI [65-100], p = 0.68). A similar pattern was observed using the expanded definition. For the full study period, the adjusted hazard of death at 90 days was lower in IMCU/ICU versus MICU patients (hazard ratio [HR] 0.73 [95% CI, 0.55-0.99]), whereas ventilator liberation by day 28 was similar between groups (adjusted subdistribution HR 1.09 [95% CI, 0.85-1.39]).

Conclusions: In patients with COVID-19 ARDS treated in an IMCU/ICU, LPV adherence was similar to, and observed survival better than those treated in preexisting MICUs. With adequate resources, protocols, and staffing, IMCUs provide an effective source of additional ICU capacity for patients with acute respiratory failure.

Importance: The opioid crisis is impacting people across the country and deserves attention to be able to curb the rise in opioid-related deaths.

Objectives: To evaluate practice patterns in opioid infusion administration and dosing for patients with acute respiratory failure receiving invasive mechanical ventilation.

Design: Retrospective cohort study.

Setting and participants: Patients from 21 hospitals in Kaiser Permanente Northern California and 96 hospitals in Philips electronic ICU Research Institute.

Main outcomes and measures: We assessed whether patients received opioid infusion and the dose of said opioid infusion.

Results: We identified patients with a diagnosis of acute respiratory failure who were initiated on invasive mechanical ventilation. From each patient, we determined if opioid infusions were administered and, among those who received an opioid infusion, the median daily dose of fentanyl infusion. We used hierarchical regression models to quantify variation in opioid infusion use and the median daily dose of fentanyl equivalents across hospitals. We included 13,140 patients in the KPNC cohort and 52,033 patients in the eRI cohort. A total of 7,023 (53.4%) and 16,311 (31.1%) patients received an opioid infusion in the first 21 days of mechanical ventilation in the KPNC and eRI cohorts, respectively. After accounting for patient- and hospital-level fixed effects, the hospital that a patient was admitted to explained 7% (95% CI, 3-11%) and 39% (95% CI, 28-49%) of the variation in opioid infusion use in the KPNC and eRI cohorts, respectively. Among patients who received an opioid infusion, the median daily fentanyl equivalent dose was 692 µg (interquartile range [IQR], 129-1341 µg) in the KPNC cohort and 200 µg (IQR, 0-1050 µg) in the eRI cohort. Hospital explained 4% (95% CI, 1-7%) and 20% (95% CI, 15-26%) of the variation in median daily fentanyl equivalent dose in the KPNC and eRI cohorts, respectively.

Conclusions and relevance: In the context of efforts to limit healthcare-associated opioid exposure, our findings highlight the considerable opioid exposure that accompanies mechanical ventilation and suggest potential under and over-treatment with analgesia. Our results facilitate benchmarking of hospitals' analgesia practices against risk-adjusted averages and can be used to inform usual care control arms of analgesia and sedation clinical trials.

Importance: Treatment for intracranial pressure (ICP) has been increasingly informed by machine learning (ML)-derived ICP waveform characteristics. There are gaps, however, in understanding how ICP monitor type may bias waveform characteristics used for these predictive tools since differences between external ventricular drain (EVD) and intraparenchymal monitor (IPM)-derived waveforms have not been well accounted for.

Objectives: We sought to develop a proof-of-concept ML model differentiating ICP waveforms originating from an EVD or IPM.

Design, setting, and participants: We examined raw ICP waveform data from the ICU physiology cohort within the prospective Transforming Research and Clinical Knowledge in Traumatic Brain Injury multicenter study.

Main outcomes and measures: Nested patient-wise five-fold cross-validation and group analysis with bagged decision trees (BDT) and linear discriminant analysis were used for feature selection and fair evaluation. Nine patients were kept as unseen hold-outs for further evaluation.

Results: ICP waveform data totaling 14,110 hours were included from 82 patients (EVD, 47; IPM, 26; both, 9). Mean age, Glasgow Coma Scale (GCS) total, and GCS motor score upon admission, as well as the presence and amount of midline shift, were similar between groups. The model mean area under the receiver operating characteristic curve (AU-ROC) exceeded 0.874 across all folds. In additional rigorous cluster-based subgroup analysis, targeted at testing the resilience of models to cross-validation with smaller subsets constructed to develop models in one confounder set and test them in another subset, AU-ROC exceeded 0.811. In a similar analysis using propensity score-based rather than cluster-based subgroup analysis, the mean AU-ROC exceeded 0.827. Of 842 extracted ICP features, 62 were invariant within every analysis, representing the most accurate and robust differences between ICP monitor types. For the nine patient hold-outs, an AU-ROC of 0.826 was obtained using BDT.

Conclusions and relevance: The developed proof-of-concept ML model identified differences in EVD- and IPM-derived ICP signals, which can provide missing contextual data for large-scale retrospective datasets, prevent bias in computational models that ingest ICP data indiscriminately, and control for confounding using our model's output as a propensity score by to adjust for the monitoring method that was clinically indicated. Furthermore, the invariant features may be leveraged as ICP features for anomaly detection.

Objectives background: Under normal conditions, pulmonary megakaryocytes are an important source of circulating thrombocytes, causing thrombocyte counts to be higher in arterial than venous blood. In critical COVID-19, thrombocytes may be removed from the circulation by the lungs because of immunothrombosis, possibly causing venous thrombocyte counts to be higher than arterial thrombocyte counts. In the present study, we investigated time-dependent changes in pulmonary turnover of thrombocytes during critical COVID-19 by measuring arteriovenous thrombocyte differences. We hypothesized that the early stages of the disease would be characterized by a net pulmonary removal of circulating thrombocytes because of immunothrombosis and that later stages would be characterized by a net pulmonary release of thrombocytes as normal pulmonary function is restored.

Design: Cohort study with repeated measurements of arterial and central venous thrombocyte counts.

Setting: ICU in a large university hospital.

Patients: Thirty-one patients with critical COVID-19 that were admitted to the ICU and received invasive or noninvasive mechanical ventilation.

Interventions: None.

Measurements and main results: We found a significant positive association between the arteriovenous thrombocyte difference and time since symptom debut. This finding indicates a negative arteriovenous thrombocyte difference and hence pulmonary removal of thrombocytes in the early stages of the disease and a positive arteriovenous thrombocyte difference and hence pulmonary release of thrombocytes in later stages. Most individual arteriovenous thrombocyte differences were smaller than the variance coefficient of the analysis.

Conclusions: The results of this study support our hypothesis that early stages of critical COVID-19 are characterized by pulmonary removal of circulating thrombocytes because of immunothrombosis and that later stages are characterized by the return of normal pulmonary release of thrombocytes. However, in most cases, the arteriovenous thrombocyte difference was too small to say anything about pulmonary thrombocyte removal and release on an individual level.