Critical Care Research and Practice最新文献

Background: The critical care resuscitation unit (CCRU) facilitates interhospital transfer (IHT) of critically ill patients for immediate interventions. Due to these patients' acuity, it is uncommon for patients to be directly discharged home from this unit, but it does happen on occasion. Since there is no literature regarding outcomes of patients being discharged from a resuscitation unit, our study investigated these patients' outcome at greater than 12 months after being discharged directly from the CCRU.

Methods: We performed a retrospective cohort study of all adult patients directly discharged from the CCRU between January 01, 2017, and December 31, 2020. The primary outcome was number of ED visits or hospitalizations within 6 months. Secondary outcomes were number of ED visits or hospitalizations within 6, 12, and >12 months from CCRU discharge.

Results: We analyzed 145 patients' records. Mean age was 56 (standard deviation [SD] ± 19), with a majority being male (72%) and Caucasian (58%). The most common discharge destination was home (139 patients, 96% of total subjects) versus hospice (2%) or nursing facilities (2%). Most patients (55%) did not have any hospital revisits within the first 6 months of discharge, while 31% had 1-2 revisits, and 14% had ≥3 revisits. The most common discharge diagnoses were soft tissue infection (16.5%), aortic dissection (14%), and stroke (11%). Factors which were associated with a greater likelihood of any return hospital visit within 6 months receiving mechanical ventilation during CCRU stay (coefficient -2.23, 95% CI 0.01-0.87, P=0.036), while high hemoglobin on CCRU discharge was associated with no ED revisit (coeff. 0.42, 95% CI 1.15-2.06, P=0.004).

Conclusions: Most patients who were discharged from the CCRU did not require any hospital revisits in the first 6 months. Requiring mechanical ventilation and having soft tissue infection were associated with high unplanned hospital revisits following discharge. Further research is needed to validate these findings.

Introduction: Sepsis, the leading cause of death in hospitalized patients globally, was investigated in this study, examining the varying effects of positive fluid balance on sepsis subtypes through causal inference.

Methods: In this study, data from the eICU database were utilized, extracting 35 features from sepsis patients. Fluid balance during ICU stay was the treatment, and ICU mortality was the primary outcome. Data preprocessing ensured linear assumptions for logistic regression. Binarized positive fluid balance with mortality was examined using DoWhy's logistic regression, while continuous data were analyzed with random forest T-learner. ATE served as the primary metric.

Results: Results revealed that septic patients with higher fluid balance had worse mortality outcomes, with an ATE of 0.042 (95% CI: (0.034, 0.047)) using logistic regression and an ATE of 0.0340 (95% CI: (0.028-0.040)) using T-learner. In the pulmonary sepsis subtype, higher mortality was associated with increased fluid balance, showing an ATE of 0.047 (95% CI: (0.037, 0.055)) using logistic regression and an ATE of 0.28 (95% CI: (0.22, 0.34)) with T-learner. Conversely, urinary sepsis patients had improved mortality with higher fluid balance, presenting an ATE of -0.135 (95% CI: (-0.024, -0.0035)) using logistic regression and an ATE of -0.28 (95% CI: (-0.34, -0.22)) with T-learner.

Conclusion: Our research implies that fluid balance impact on ICU mortality differs among sepsis subtypes. Positive fluid balance raises mortality in sepsis and pulmonary sepsis but may protect against urinary sepsis. Further trials are needed to confirm these findings.

Background: Rapid shallow breathing index (RSBI) has been widely used as a predictor of extubation outcome in mechanically ventilated patients. We hypothesize that the rate of change of RSBI between the beginning and end of a 120-minute spontaneous breathing trial (SBT) could be a better predictor of extubation outcome than a single RSBI measured at the end of SBT in mechanically ventilated patients. Methodology. In this prospective observational study, we enrolled 193 patients who met the inclusion criteria, of whom 33 patients were unable to tolerate a 120-minute SBT and were excluded from the study. The study population consisted of 160 patients, categorized into three subgroups: patients with normal lung (no reported history of respiratory diseases), patients with airway disease, and patients with parenchymal disease who completed 120 minutes of SBT on low levels of pressure support ventilation. RSBI was obtained from the ventilator display at the 5^th and the 120^th minutes of SBT. The rate of change of RSBI (RSBI 5-120) was calculated as (RSBI 2-RSBI 1)/RSBI 1 × 100. Receiver-operating characteristic (ROC) curves were plotted for RSBI 5-120 and RSBI 120 in all patients and among the three subgroups (normal group, airway group, and parenchymal group) to compare the superiority of their best thresholds in predicting extubation failure.

Results: The RSBI 5-120 threshold for extubation failure in the entire patient group was 23% with an overall accuracy of 88% (AUC = 0.933, sensitivity = 91%, and specificity = 86%) and the threshold of RSBI 120 for extubation failure in the entire patient group was 70 breaths/min/L with an overall accuracy of 82% (AUC = 0.899, sensitivity = 85%, and specificity = 81%). In patients in the normal lung group, the threshold of RSBI 5-120 was 22%, with an overall accuracy of 89% (AUC = 0.892, sensitivity = 87.5%, and specificity = 90%), and the RSBI 120 threshold was 70 breaths/min/L, with an overall accuracy of 89% (AUC = 0.956, sensitivity = 88%, and specificity = 90%). The RSBI 5-120 threshold in patients with airway disease was 25% with an accuracy of 86% (AUC = 0.892, sensitivity = 85%, and specificity = 86%) and the threshold of RSBI 120 was 73 breaths/min/L with an accuracy of 83% (AUC = 0.874, sensitivity = 85%, and specificity = 82%). In patients in the parenchymal disease group, the threshold of RSBI 5-120 was 24%, with an accuracy of 90% (AUC = 0.966, sensitivity = 92%, and specificity = 89%) and RSBI 120 threshold was 71 breaths/min/L, which was 88% accurate (AUC = 0.893, sensitivity = 85%, and specificity = 89%).

Conclusion: The rate of change of RSBI between the 5^th and 120^th minutes was moderately more accurate than the single value of RSBI measured at the 120^th minute in predicting extubation outcome.

Background: Chronic kidney disease (CKD) is often associated with multiple comorbidities including diabetes mellitus, and each has its own complications and impact after cardiac surgery including coronary revascularization. The objective of this work was to study the impact of CKD on clinical outcomes after coronary artery bypass grafting (CABG) and to compare outcomes in patients with different grades of renal functions. We retrospectively reviewed all patients who underwent CABG from January 2016 to August 2020 at our tertiary care hospital using electronic medical records.

Results: The study included 410 patients with a median age of 60 years, and 28.6% of them had CKD and hospital mortality of 2.7%. About 71.4% of the patients had GFR > 60 mL/min per 1.73 m², 18.1% had early CKD (GFR 30-60), 2.7% had late CKD (GFR < 30), and 7.8% of them had end-stage renal disease (ESRD) requiring dialysis. The CKD group had significantly more frequent hospital mortality (p = 0.04), acute cerebrovascular stroke (p = 0.03), acute kidney injury (AKI) (p < 0.001), longer ICU stay (p = 0.002), post-ICU stay (p = 0.001), and sternotomy wound debridement (p = 0.03) compared to the non-CKD group. The frequencies of new need for dialysis were 2.4% vs. 14.9% vs. 45.5% (p < 0.001) in the patients with GFR > 60 mL/min per 1.73 m², early CKD, and late CKD, respectively. Acute cerebral stroke (OR: 10.29, 95% CI: 1.82-58.08, and p = 0.008), new need for dialysis (OR: 25.617, 95% CI: 13.78-85.47, and p < 0.001), and emergency surgery (OR: 3.1, 95% CI: 1.82-12.37, and p = 0.036) were the independent predictors of hospital mortality after CABG. The patients with CKD had an increased risk of strokes (HR: 2.14, 95% CI: 1.20-3.81, and p = 0.01) but insignificant mortality increase (HR: 1.44, 95% CI: 0.42-4.92, and p = 0.56) during follow-up.

Conclusion: The patients with CKD, especially the late grade, had worse postoperative early and late outcomes compared to non-CKD patients after CABG. Patients with dialysis-independent CKD had increased risks of needing dialysis, hospital mortality, and permanent dialysis after CABG.

Introduction: Daily evaluation of mechanically ventilated (MV) patients is essential for successful extubation. Proper withdrawal prevents complications and reduces the cost of hospitalization in the intensive care unit (ICU). Diaphragm ultrasonography (DUS) has emerged as a potential instrument for determining whether a patient is ready to be extubated. This study compared the efficacy rate of extubation using a standard withdrawal protocol and DUS in patients with MV.

Methods: A randomized, parallel, single-blind, controlled study was conducted on ICU patients undergoing MV. Patients were randomly assigned to either the control (conventional weaning protocol) group or intervention (DUS-guided weaning) group in a 1 : 1 ratio. The primary outcome measure was the rate of reintubation and hospital mortality.

Results: Forty patients were randomized to the trial. The mean age of the sample was 70 years, representing an older population. The extubation success rate was 90% in both groups. There was no reintubation in the first 48 hours and only two reintubations in both groups between the second and seventh days. The hospital mortality risk in patients with acute kidney injury was positively correlated with age and the need for hemodialysis. Discussion. This study demonstrates the usefulness of DUS measurement protocols for withdrawing MV. The rate of reintubation was low for both cessation methods. As a parameter, the diaphragm thickness fraction comprehensively evaluates the diaphragm function. The results demonstrate that DUS has the potential to serve as a noninvasive tool for guiding extubation decisions. In conclusion, using DUS in patients with respiratory failure revealed no difference in reintubation rates or mortality compared with the conventional method. Future research should concentrate on larger, multicentered, randomized trials employing a multimodal strategy that combines diaphragmatic parameters with traditional clinical withdrawal indices.

Introduction: Fungal infection is a cause of increased morbidity and mortality in intensive care patients. Critically unwell patients are at increased risk of developing invasive fungal infections. COVID-19 patients in the intensive care unit (ICU) may be at a particularly high risk. The primary aim of this study was to establish the incidence of secondary fungal infections in patients admitted to the ICU with COVID-19. Secondary aims were to investigate factors that may contribute to an increased risk of fungal infections and to calculate the mortality between fungal and nonfungal groups.

Methods: We undertook a retrospective observational study in a tertiary ICU in Wales, United Kingdom. 174 patients admitted with COVID-19 infection from March 2020 until May 2021 were included. Data were collected through a retrospective review of patient's clinical notes and microbiology investigation results obtained from the online clinical portal.

Results: 81/174 (47%) COVID-19 patients developed fungal infections, 93% of which were Candida species, including Candida albicans (88%), and 6% had an Aspergillus infection. Age and smoking history did not appear to be contributing factors. The nonfungal group had a significantly higher body mass index (33 ± 8 vs. 31 ± 7, p=0.01). The ICU length of stay (23 (1-116) vs. 8 (1-60), p < 0.001), hospital length of stay (30 (3-183) vs. 15 (1-174) ± 7, p < 0.001), steroid days (10 (1-116) vs. 4 (0-28), p=0.02), and ventilation days (18 (0-120) vs. 2 (0-55), p < 0.001) were significantly higher in the fungal group. The mortality rate in both groups was similar (51% vs. 52%). The Kaplan-Meier survival analysis showed that the fungal group survived more than the nonfungal group (log rank (Mantel-Cox), p < 0.001).

Conclusion: Secondary fungal infections are common in COVID-19 patients admitted to the ICU. Longer treatment with corticosteroids, increased length of hospital and ICU stay, and greater length of mechanical ventilation significantly increase the risk of fungal infections. Fungal infection, however, was not associated with an increase in mortality.

Introduction: Various quality improvement (QI) interventions have been individually assessed for the quality of cardiopulmonary resuscitation (CPR). We aimed to assess the QI bundle (hands-on training and debriefing) for the quality of CPR in our children's hospital. We hypothesized that the QI bundle improves the quality of CPR in hospitalized children.

Methods: We initiated a QI bundle (hands-on training and debriefing) in August 2017. We conducted a before-after analysis comparing the CPR quality during July 2013-May 2017 (before) and January 2018-December 2020 (after). We collected data from the critical events logbook on CPR duration, chest compressions (CC) rate, ventilation rate (VR), the timing of first dose of epinephrine, blood pressure (BP), end-tidal CO₂ (EtCO₂), and vital signs monitoring during CPR. We performed univariate analysis and presented data as the median interquartile range (IQR) and in percentage as appropriate.

Results: We compared data from 58 CPR events versus 41 CPR events before and after QI bundle implementation, respectively. The median (IQR) CPR duration for the pre- and post-QI bundle was 5 (1-13) minutes and 3 minutes (1.25-10), and the timing of the first dose of epinephrine was 2 (1-2) minutes and 2 minutes (1-5), respectively. We observed an improvement in compliance with the CC rate (100-120 per minute) from 72% events before versus 100% events after QI bundle implementation (p=0.0009). Similarly, there was a decrease in CC interruptions and hyperventilation rates from 100% to 50% (p=0.016) and 100% vs. 63% (p=<0.0001) events before vs. after QI bundle implementation, respectively. We also observed improvement in BP monitoring from 36% before versus 60% after QI bundle (p=0.014).

Conclusion: Our QI bundle (hands-on training and debriefing) was associated with improved compliance with high-quality CPR in children.

Introduction: There is evidence that prolonged invasive mechanical ventilation has negative consequences for critically ill patients and that performing tracheostomy (TQT) could help to reduce these consequences. The ideal period for performing TQT is still not clear in the literature since few studies have compared clinical aspects between patients undergoing early or late TQT.

Objective: To compare the mortality rate, length of stay in the intensive care unit, length of hospital stay, and number of days free of mechanical ventilation in patients undergoing TQT before or after ten days of orotracheal intubation.

Methods: A retrospective cohort study carried out by collecting data from patients admitted to an intensive care unit between January 2008 and December 2017. Patients who underwent TQT were divided into an early TQT group (i.e., time to TQT ≤ 10 days) or late TQT (i.e., time to TQT > 10 days) and the clinical outcomes of the two groups were compared.

Results: Patients in the early TQT group had a shorter ICU stay than the late TQT group (19 ± 16 vs. 32 ± 22 days, p < 0.001), a shorter stay in the hospital (42 ± 32 vs. 52 ± 50 days, p < 0.001), a shorter duration of mechanical ventilation (17 ± 14 vs. 30 ± 18 days, p < 0.001), and a higher proportion of survivors in the ICU outcome (57% vs. 46%, p < 0.001).

Conclusion: Tracheostomy performed within 10 days of mechanical ventilation provides several benefits to the patient and should be considered by the multidisciplinary team as a part of their clinical practice.

Background: The predictive factors of prognosis in patients with pneumonia complicated with heart failure (HF) have not been fully investigated yet, especially with the use of next-generation sequencing (NGS) of metagenome.

Methods: Patients diagnosed with pneumonia complicated with HF were collected and divided into control group and NGS group. Univariate and multivariate logistic regression and LASSO regression analysis were conducted to screen the predictive factors for the prognosis, followed by nomogram construction, ROC curve plot, and internal validation. Data analysis was conducted in SPSS and R software.

Results: The NGS of metagenome detected more microbial species. Univariate and multivariate logistic regression and LASSO regression analysis revealed that Enterococcus (χ² = 7.449, P = 0.006), Hb (Wals = 6.289, P = 0.012), and ProBNP (Wals = 4.037, P = 0.045) were screened out as potential predictive factors for the prognosis. Nomogram was constructed with these 3 parameters, and the performance of nomogram was checked in ROC curves (AUC = 0.772). The specificity and sensitivity of this model were calculated as 0.579 and 0.851, respectively, with the threshold of 0.630 in ROC curve. Further internal verification indicated that the predictive value of our constructed model was efficient.

Conclusion: This study developed a preliminary clinical prediction model for the prognosis of pneumonia complicated with HF based on NGS of metagenome. More objects will be collected and tested to improve the predictive model in the near future.