Critical Care Medicine最新文献

Objectives: A narrative expert review aiming to summarize the clinical epidemiology and management of critically ill patients with malignant hyperthermia (MH).

Data sources: Medline searches were conducted to identify relevant articles describing the epidemiology, pathophysiology, and management of MH. Guidelines from key MH organizations were also incorporated into this review.

Study selection: Relevant studies regarding MH in both ICU and perioperative settings were reviewed.

Data extraction: Data from relevant studies were summarized and qualitatively assessed.

Data synthesis: MH is a severe reaction triggered by inhalational volatile anesthetics and succinylcholine in genetically susceptible patients. The condition is characterized by an early onset (min to hr) rise in temperature, hypercarbia, and muscular rigidity following exposure to triggering medications with potential complications of coagulopathy, rhabdomyolysis, and acute kidney injury. Acute management necessitates a coordinated multidisciplinary team approach with specific management using dantrolene, active cooling, and hyperventilation. A suspected MH reaction has important implications for future anesthetic exposure for both the patient and their family. All suspected reactions should be followed up at a specialized MH testing center using muscle contracture and genetic testing.

Conclusions: Increasing use of inhalational anesthetics in the ICU underscores the need for enhanced education on the diagnosis and management of MH to ensure optimal patient sedation care and safety.

Objectives: To validate a mathematical model using porous media theory for alveolar CO2 determination in ventilated patients.

Design: Mathematical modeling study with prospective clinical validation to simulate CO2 exchange from bloodstream to airway entrance.

Setting: ICU.

Patients: Thirteen critically ill patients without chronic or acute lung disease.

Interventions: None.

Measurements and main results: Model outcomes compared with patient data showed correlations for end-tidal CO2 (EtCO 2 ), area under the CO2 curve, and Pa CO2 of 0.918, 0.954, and 0.995. Determination coefficients ( R2 ) were 0.843, 0.910, and 0.990, indicating precision and predictive power.

Conclusions: The mathematical model shows potential in pulmonary critical care. Although promising, practical application demands further validation, clinician training, and patient-specific adjustments. The path to clinical use will be iterative, involving validation and education.

Objective: To determine whether mortality differed between initial invasive mechanical ventilation (IMV) or noninvasive ventilation (NIV) followed by delayed IMV in immunocompromised patients with sepsis.

Design: Retrospective analysis using the National Data Center for Medical Service claims data in China from 2017 to 2019.

Setting: A total of 3530 hospitals across China.

Patients: A total of 36,187 adult immunocompromised patients with sepsis requiring ventilation.

Interventions: None.

Measurements and main results: The primary outcome was hospital mortality. Patients were categorized into NIV initiation or IMV initiation groups based on first ventilation. NIV patients were further divided by time to IMV transition: no transition, immediate (≤ 1 d), early (2-3 d), delayed (4-7 d), or late (≥ 8 d). Mortality was compared between groups using weighted Cox models. Over the median 9-day follow-up, mortality was similar for initial NIV versus IMV (adjusted hazard ratio [HR] 1.006; 95% CI, 0.959-1.055). However, among NIV patients, a longer time to IMV transition is associated with stepwise increases in mortality, from immediate transition (HR 1.65) to late transition (HR 2.51), compared with initial IMV. This dose-response relationship persisted across subgroups and sensitivity analyses.

Conclusions: Prolonged NIV trial before delayed IMV transition is associated with higher mortality in immunocompromised sepsis patients ultimately intubated.

Objectives: This study aimed to provide new insights into the impact of emergency department (ED) to ICU time on hospital mortality, stratifying patients by academic and nonacademic teaching (NACT) hospitals, and considering Acute Physiology and Chronic Health Evaluation (APACHE)-IV probability and ED-triage scores.

Design, setting, and patients: We conducted a retrospective cohort study (2009-2020) using data from the Dutch National Intensive Care Evaluation registry. Patients directly admitted from the ED to the ICU were included from four academic and eight NACT hospitals. Odds ratios (ORs) for mortality associated with ED-to-ICU time were estimated using multivariable regression, both crude and after adjusting for and stratifying by APACHE-IV probability and ED-triage scores.

Interventions: None.

Measurements and main results: A total of 28,455 patients were included. The median ED-to-ICU time was 1.9 hours (interquartile range, 1.2-3.1 hr). No overall association was observed between ED-to-ICU time and hospital mortality after adjusting for APACHE-IV probability (p = 0.36). For patients with an APACHE-IV probability greater than 55.4% (highest quintile) and an ED-to-ICU time greater than 3.4 hours the adjusted OR (ORsadjApache) was 1.24 (95% CI, 1.00-1.54; p < 0.05) as compared with the reference category (< 1.1 hr). In the academic hospitals, the ORsadjApache for ED-to-ICU times of 1.6-2.3, 2.3-3.4, and greater than 3.4 hours were 1.21 (1.01-1.46), 1.21 (1.00-1.46), and 1.34 (1.10-1.64), respectively. In NACT hospitals, no association was observed (p = 0.07). Subsequently, ORs were adjusted for ED-triage score (ORsadjED). In the academic hospitals the ORsadjED for ED-to-ICU times greater than 3.4 hours was 0.98 (0.81-1.19), no overall association was observed (p = 0.08). In NACT hospitals, all time-ascending quintiles had ORsadjED values of less than 1.0 (p < 0.01).

Conclusions: In patients with the highest APACHE-IV probability at academic hospitals, a prolonged ED-to-ICU time was associated with increased hospital mortality. We found no significant or consistent unfavorable association in lower APACHE-IV probability groups and NACT hospitals. The association between longer ED-to-ICU time and higher mortality was not found after adjustment and stratification for ED-triage score.

Objectives: Sepsis survivors have greater healthcare use than those surviving hospitalizations for other reasons, yet factors associated with greater healthcare use in this population remain ill-defined. Rural Americans are older, have more chronic illnesses, and face unique barriers to healthcare access, which could affect postsepsis healthcare use. Therefore, we compared healthcare use and expenditures among rural and urban sepsis survivors. We hypothesized that rural survivors would have greater healthcare use and expenditures.

Design, setting, and patients: To test this hypothesis, we used data from 106,189 adult survivors of a sepsis hospitalization included in the IBM MarketScan Commercial Claims and Encounters database and Medicare Supplemental database between 2013 and 2018.

Interventions: None.

Measurements and main results: We identified hospitalizations for severe sepsis and septic shock using the International Classification of Diseases, 9th Edition (ICD-9) or 1CD-10 codes. We used Metropolitan Statistical Area classifications to categorize rurality. We measured emergency department (ED) visits, inpatient hospitalizations, skilled nursing facility admissions, primary care visits, physical therapy visits, occupational therapy visits, and home healthcare visits for the year following sepsis hospitalizations. We calculated the total expenditures for each of these categories. We compared outcomes between rural and urban patients using multivariable regression and adjusted for covariates. After adjusting for age, sex, comorbidities, admission type, insurance type, U.S. Census Bureau region, employment status, and sepsis severity, those living in rural areas had 17% greater odds of having an ED visit (odds ratio [OR] 1.17; 95% CI, 1.13-1.22; p < 0.001), 9% lower odds of having a primary care visit (OR 0.91; 95% CI, 0.87-0.94; p < 0.001), and 12% lower odds of receiving home healthcare (OR 0.88; 95% CI, 0.84-0.93; p < 0.001). Despite higher levels of ED use and equivalent levels of hospital readmissions, expenditures in these areas were 14% (OR 0.86; 95% CI, 0.80-0.91; p < 0.001) and 9% (OR 0.91; 95% CI, 0.87-0.96; p < 0.001) lower among rural survivors, respectively, suggesting these services may be used for lower-acuity conditions.

Conclusions: In this large cohort study, we report important differences in healthcare use and expenditures between rural and urban sepsis survivors. Future research and policy work is needed to understand how best to optimize sepsis survivorship across the urban-rural continuum.

Objective: The Efficacy of Inhaled Hydrogen on Neurologic Outcome Following Brain Ischemia During Post-Cardiac Arrest Care (HYBRID) II trial (jRCTs031180352) suggested that hydrogen inhalation may reduce post-cardiac arrest brain injury (PCABI). However, the combination of hypothermic target temperature management (TTM) and hydrogen inhalation on outcomes is unclear. The aim of this study was to investigate the combined effect of hydrogen inhalation and hypothermic TTM on outcomes after out-of-hospital cardiac arrest (OHCA).

Design: Post hoc analysis of a multicenter, randomized, controlled trial.

Setting: Fifteen Japanese ICUs.

Patients: Cardiogenic OHCA enrolled in the HYBRID II trial.

Interventions: Hydrogen mixed oxygen (hydrogen group) versus oxygen alone (control group).

Measurements and main results: TTM was performed at a target temperature of 32-34°C (TTM32-TTM34) or 35-36°C (TTM35-TTM36) per the institutional protocol. The association between hydrogen + TTM32-TTM34 and 90-day good neurologic outcomes was analyzed using generalized estimating equations. The 90-day survival was compared between the hydrogen and control groups under TTM32-TTM34 and TTM35-TTM36, respectively. The analysis included 72 patients (hydrogen [ n = 39] and control [ n = 33] groups) with outcome data. TTM32-TTM34 was implemented in 25 (64%) and 24 (73%) patients in the hydrogen and control groups, respectively ( p = 0.46). Under TTM32-TTM34, 17 (68%) and 9 (38%) patients achieved good neurologic outcomes in the hydrogen and control groups, respectively (relative risk: 1.81 [95% CI, 1.05-3.66], p < 0.05). Hydrogen + TTM32-TTM34 was independently associated with good neurologic outcomes (adjusted odds ratio 16.10 [95% CI, 1.88-138.17], p = 0.01). However, hydrogen + TTM32-TTM34 did not improve survival compared with TTM32-TTM34 alone (adjusted hazard ratio: 0.22 [95% CI, 0.05-1.06], p = 0.06).

Conclusions: Hydrogen + TTM32-TTM34 was associated with improved neurologic outcomes after cardiogenic OHCA compared with TTM32-TTM34 monotherapy. Hydrogen inhalation is a promising treatment option for reducing PCABI when combined with TTM32-TTM34.

Machine learning (ML) tools for acute respiratory distress syndrome (ARDS) detection and prediction are increasingly used. Therefore, understanding risks and benefits of such algorithms is relevant at the bedside. ARDS is a complex and severe lung condition that can be challenging to define precisely due to its multifactorial nature. It often arises as a response to various underlying medical conditions, such as pneumonia, sepsis, or trauma, leading to widespread inflammation in the lungs. ML has shown promising potential in supporting the recognition of ARDS in ICU patients. By analyzing a variety of clinical data, including vital signs, laboratory results, and imaging findings, ML models can identify patterns and risk factors associated with the development of ARDS. This detection and prediction could be crucial for timely interventions, diagnosis and treatment. In summary, leveraging ML for the early prediction and detection of ARDS in ICU patients holds great potential to enhance patient care, improve outcomes, and contribute to the evolving landscape of precision medicine in critical care settings. This article is a concise definitive review on artificial intelligence and ML tools for the prediction and detection of ARDS in critically ill patients.

Objectives: Continuous electroencephalogram (cEEG) monitoring is recommended for status epilepticus (SE) management in ICU but is still underused due to resource limitations and inconclusive evidence regarding its impact on outcome. Furthermore, the term "continuous monitoring" often implies continuous recording with variable intermittent review. The establishment of a dedicated ICU-electroencephalogram unit may fill this gap, allowing cEEG with nearly real-time review and multidisciplinary management collaboration. This study aimed to evaluate the effect of ICU-electroencephalogram unit establishing on SE outcome and management.

Design: Single-center retrospective before-after study.

Setting: Neuro-ICU of a Swiss academic tertiary medical care center.

Patients: Adult patients treated for nonhypoxic SE between November 1, 2015, and December 31, 2023.

Interventions: None.

Measurement and main results: Data from all SE patients were assessed, comparing those treated before and after ICU-electroencephalogram unit introduction. Primary outcomes were return to premorbid neurologic function, ICU mortality, SE duration, and ICU SE management. Secondary outcomes were SE type and etiology. Two hundred seven SE patients were included, 149 (72%) before and 58 (38%) after ICU-electroencephalogram unit establishment. ICU-electroencephalogram unit introduction was associated with increased detection of nonconvulsive SE (p = 0.003) and SE due to acute symptomatic etiology (p = 0.019). Regression analysis considering age, comorbidities, SE etiology, and SE semeiology revealed a higher chance of returning to premorbid neurologic function (p = 0.002), reduced SE duration (p = 0.024), and a shift in SE management with increased use of antiseizure medications (p = 0.007) after ICU-electroencephalogram unit introduction.

Conclusions: Integrating neurology expertise in the ICU setting through the establishment of an ICU-electroencephalogram unit with nearly real-time cEEG review, shortened SE duration, and increased likelihood of returning to premorbid neurologic function, with an increased number of antiseizure medications used. Further studies are warranted to validate these findings and assess long-term prognosis.

Objectives: To derive a pooled estimate of the incidence and outcomes of sepsis-associated acute kidney injury (SA-AKI) in ICU patients and to explore the impact of differing definitions of SA-AKI on these estimates.

Data sources: Medline, Medline Epub, EMBASE, and Cochrane CENTRAL between 1990 and 2023.

Study selection: Randomized clinical trials and prospective cohort studies of adults admitted to the ICU with either sepsis and/or SA-AKI.

Data extraction: Data were extracted in duplicate. Risk of bias was assessed using adapted standard tools. Data were pooled using a random-effects model. Heterogeneity was assessed by using a single covariate logistic regression model. The primary outcome was the proportion of participants in ICU with sepsis who developed AKI.

Data synthesis: A total of 189 studies met inclusion criteria. One hundred fifty-four reported an incidence of SA-AKI, including 150,978 participants. The pooled proportion of patients who developed SA-AKI across all definitions was 0.40 (95% CI, 0.37-0.42) and 0.52 (95% CI, 0.48-0.56) when only the Risk Injury Failure Loss End-Stage, Acute Kidney Injury Network, and Improving Global Outcomes definitions were used to define SA-AKI. There was significant variation in the incidence of SA-AKI depending on the definition of AKI used and whether AKI defined by urine output criteria was included; the incidence was lowest when receipt of renal replacement therapy was used to define AKI (0.26; 95% CI, 0.24-0.28), and highest when the Acute Kidney Injury Network score was used (0.57; 95% CI, 0.45-0.69; p < 0.01). Sixty-seven studies including 29,455 participants reported at least one SA-AKI outcome. At final follow-up, the proportion of patients with SA-AKI who had died was 0.48 (95% CI, 0.43-0.53), and the proportion of surviving patients who remained on dialysis was 0.10 (95% CI, 0.04-0.17).

Conclusions: SA-AKI is common in ICU patients with sepsis and carries a high risk of death and persisting kidney impairment. The incidence and outcomes of SA-AKI vary significantly depending on the definition of AKI used.

Objectives: Some studies have examined survival trends among critically ill COVID-19 patients, but most were case reports, small cohorts, and had relatively short follow-up periods. We aimed to examine the survival trend among critically ill COVID-19 patients during the first two and a half years of the pandemic and investigate potential predictors across different variants of concern periods.

Design: Prospective cohort study.

Setting: Swedish ICUs, between March 6, 2020, and December 31, 2022.

Patients: Adult COVID-19 ICU patients of 18 years old or older from the Swedish Intensive Care Register (SIR) that were linked to multiple other national registers.

Measurement and main results: Survival probability and predictors of COVID-19 death were estimated using Kaplan-Meier and Cox regression analysis. Of 8975 patients, 2927 (32.6%) died. The survival rate among COVID-19 critically ill patients appears to have changed over time, with a worse survival in the Omicron period overall. The adjusted hazard ratios (aHRs) comparing older and younger ages were consistently strong but slightly attenuated in the Omicron period. After adjustment, the aHR of death was significantly higher for men, older age (40+ yr), low income, and with comorbid chronic heart disease, chronic lung disease, impaired immune disease, chronic renal disease, stroke, and cancer, and for those requiring invasive or noninvasive respiratory supports, who developed septic shock or had organ failures ( p < 0.05). In contrast, foreign-born patients, those with booster vaccine, and those who had taken steroids had better survival (aHR = 0.87; 95% CI, 0.80-0.95; 0.74, 0.65-0.84, and 0.91, 0.84-0.98, respectively). Observed associations were similar across different variant periods.

Conclusions: In this nationwide Swedish cohort covering over two and a half years of the pandemic, ICU survival rates changed over time. Older age was a strong predictor across all periods. Furthermore, most other mortality predictors remained consistent across different variant periods.