Acta Anaesthesiologica Scandinavica最新文献

Background: Postoperative mortality might be influenced by postoperative care, vigilance, and competence to rescue. This study aims to describe the course of events preceding death in a high-risk surgical cohort.

Methods: We analyzed hospital records of patients who died within 30 days after surgery in 4 high volume hospitals using (1) reflective narrative thematic approach to identify recurring themes reflecting issues with conduct of care and (2) Global Trigger Tool to describe incidence, timing, and types of adverse events (AEs) leading to harm.

Results: Preoperative predicted median risk of death in the studied group was 9%/13% according to SORT/P-POSSUM, respectively. Nine recurring themes were identified. Prominent themes were "consensus concerning aim and/or risk with planned surgery," "level of (intraoperative) competence and monitoring," and in the postoperative period "level of care and vigilance" on signs of deterioration. We found a total of 303 AEs, with only three patients (5%) having no adverse events. Most common severity category was "I," that is "contributed to patient's death" (n = 110, 36% of all AEs). Of these, 60% were classified as preventable or probably preventable. The peak incidence of AEs was seen on the day of index surgery. Most common types of AEs were "failure of vital functions" (n = 79, 26%), followed by infections (n = 45, 15%).

Conclusions: A high predicted risk of death and a peak of adverse events on the day of index surgery were detected. Identified themes reflect lack of documented multi-professional consensus on how to handle prevalent perioperative risk, vigilance, and postoperative level of care.

Background: Intravenous therapies are essential for hospitalised patients. The rapid dissemination of portable ultrasound machines has eased ultrasound-guided intravenous access and facilitated increased use of long peripheral venous catheters (LPCs). This study aimed to evaluate the clinical performance and complications of LPCs.

Methods: Retrospective, observational single-site study. Data from all consecutively inserted LPCs during a period of 18 months was evaluated. The primary endpoint was the all-cause incidence rate of catheter removal. Secondary endpoints included specific reasons for the catheter removal and the associations between predefined characteristics of the patients, the infusions and the catheters with catheter failure.

Results: During the period, 751 PVCs were inserted in 457 patients. The reasons for catheter removal were recorded in 563 cases. The overall incidence rate of catheter removal was 95.8/1000 catheter days (95% CI 88.4-103.8). The median dwell time was 8 days (IQR 5-14), and the total dwell time was 6136 days. Catheter failure occurred in 283 (50.3%) cases, of which the most common cause was phlebitis (n = 101, 17.9%). In multivariable analyses, the use of the cephalic vein was significantly associated with both all-cause catheter failure (p < .001) and catheter failure due to phlebitis (p < .001). In multivariable analyses, vancomycin infusion was not significantly associated with all-cause catheter failure (HR 1.15 (0.55-2.42), p = .71) or catheter failure due to phlebitis (HR 1.49 (0.49-4.53), p = .49).

Conclusion: The overall incidence rate of catheter removal was 95.8/1000 catheter days, and the most common causes of catheter failure were phlebitis, infiltration and unintended catheter removal. The use of the cephalic vein was significantly associated with catheter failure in multivariable analyses. We did not find an association between vancomycin infusion and catheter failure in multivariable analyses.

Background: Ventilator-associated pneumonia (VAP) may be a particular concern in patients with severe coronavirus disease 2019 (COVID-19). We aimed to determine the prevalence and etiology of VAP in critically ill COVID-19 patients in a Danish intensive care unit (ICU) during the first three waves of the COVID-19 pandemic and to study associations between dexamethasone (DXM) use and development of VAP.

Methods: In an observational single-center study patients were retrospectively screened for VAP including causative pathogens, use of DXM and commonly used antibiotics. Diagnosis of VAP required invasive mechanical ventilation (IMV) >48 h with presence of a new bacterial agent and clinical signs of infection. For analysis, common descriptive statistics were applied. Cox proportional hazards models were used to analyze the association between DXM use and VAP.

Results: VAP was detected in 53/119 (44.5%) mechanically ventilated patients across all three COVID-19 waves. Median length of IMV for VAP patients was 24 [15-41] days, and 3 out of 4 were males. VAP was most prevalent (47.0%) during the second wave. Common pathogens included Klebsiella pneumoniae (24.5%), Enterobacter aerogenes (17.0%) and Pseudomonas aeruginosa (13.2%), Staphylococcus aureus (13.2%), and Escherichia coli (13.2%). A change from Gram-negative bacteria only to a combination of Gram-positive and Gram-negative bacteria was observed in the second wave compared to first. Use of DXM was not associated with VAP (adjusted hazard ratio 1.63 95% CI: 0.84-3.17).

Conclusion: The prevalence of VAP was high across all three COVID-19 waves and showed a different distribution of pathogens between the first and second wave. Use of DXM was not associated with VAP development. Further and larger studies are needed to understand the risk factors associated with VAP in patients with COVID-19.

Purpose: The increasing use of advanced medical technologies to detect adverse events, for instance, artificial intelligence-assisted technologies, has shown promise in improving various aspects within health care but may also come with substantial expenses. Therefore, understanding the potential economic benefits can guide decision-making processes regarding implementation. We aimed to estimate the potential cost savings associated with reducing length of stay and avoiding readmissions within the framework of an artificial intelligence-assisted vital signs monitoring system.

Methods: We used data from Danish national registries and coarsened exact matching to estimate the difference in length of stay and probability of readmission among adult in-hospital patients exposed to and not exposed to serious adverse events. We used these estimates to calculate the maximum potential savings that could be achieved by early detection of adverse events to reduce length of stay and avoid readmissions.

Results: Patients exposed to serious adverse events during admission had 2.4 (95% CI: 2.4-2.5) additional hospital bed days and had 14% (95% CI 11%-17%) higher odds of readmissions compared with patients not exposed to such events. A base case scenario yielded maximum potential savings if one patient avoided a serious adverse event of EUR 2040 due to reduced length of stay and EUR 43 due to avoidance of readmissions caused by serious adverse events.

Conclusion: Reductions in serious adverse events are associated with decreased healthcare costs due to reduced length of stay and avoided readmissions. Artificial intelligence-assisted vital signs monitoring systems are one potential approach to reduce serious adverse events, however, the ability of this technology to reduce adverse events remains unclear. Comprehensive prospective analyses of such systems including the intervention and implementation costs are necessary to understand their full economic impact.

Background: Non-shockable in-hospital cardiac arrest (IHCA) is a condition with diverse aetiology, predictive factors, and outcome. This study aimed to compare IHCA with initial asystole or pulseless electrical activity (PEA), focusing specifically on their aetiologies and the significance of predictive factors.

Methods: Using the Swedish Registry of Cardiopulmonary Resuscitation, adult non-shockable IHCA cases from 2018 to 2022 (n = 5788) were analysed. Exposure was initial rhythm, while survival to hospital discharge was the primary outcome. A random forest model with 28 variables was used to generate permutation-based variable importance for outcome prediction.

Results: Overall, 60% of patients (n = 3486) were male and the median age was 75 years (IQR 67-81). The most frequent arrest location (46%) was on general wards. Comorbidities were present in 79% of cases and the most prevalent comorbidity was heart failure (33%). Initial rhythm was PEA in 47% (n = 2702) of patients, and asystole in 53% (n = 3086). The most frequent aetiologies in both PEA and asystole were cardiac ischemia (24% vs. 19%, absolute difference [AD]: 5.4%; 95% confidence interval [CI] 3.0% to 7.7%), and respiratory failure (14% vs. 13%, no significant difference). Survival was higher in asystole (24%) than in PEA (17%) (AD: 7.3%; 95% CI 5.2% to 9.4%). Cardiopulmonary resuscitation (CPR) durations were longer in PEA, 18 vs 15 min (AD 4.9 min, 95% CI 4.0-5.9 min). The duration of CPR was the single most important predictor of survival across all subgroup and sensitivity analyses. Aetiology ranked as the second most important predictor in most analyses, except in the asystole subgroup where responsiveness at cardiac arrest team arrival took precedence.

Conclusions: In this nationwide registry study of non-shockable IHCA comparing asystole to PEA, cardiac ischemia and respiratory failure were the predominant aetiologies. Duration of CPR was the most important predictor of survival, followed by aetiology. Asystole was associated with higher survival compared to PEA, possibly due to shorter CPR durations and a larger proportion of reversible aetiologies.

Background: A prediction model that estimates mortality at admission to the intensive care unit (ICU) is of potential benefit to both patients and society. Logistic regression models like Simplified Acute Physiology Score 3 (SAPS 3) and APACHE are the traditional ICU mortality prediction models. With the emergence of machine learning (machine learning) and artificial intelligence, new possibilities arise to create prediction models that have the potential to sharpen predictive accuracy and reduce the likelihood of misclassification in the prediction of 30-day mortality.

Methods: We used the Swedish Intensive Care Registry (SIR) to identify and include all patients ≥18 years of age admitted to general ICUs in Sweden from 2008 to 2022 with SAPS 3 score registered. Only data collected within 1 h of ICU admission was used. We had 153 candidate predictors including baseline characteristics, previous medical conditions, blood works, physiological parameters, cause of admission, and initial treatment. We stratified the data randomly on the outcome variable 30-day mortality and created a training set (80% of data) and a test set (20% of data). We evaluated several hundred prediction models using multiple ML frameworks including random forest, gradient boosting, neural networks, and logistic regression models. Model performance was evaluated by comparing the receiver operator characteristic area under the curve (AUC-ROC). The best performing model was fine-tuned by optimizing hyperparameters. The model's calibration was evaluated by a calibration belt. Ultimately, we simplified the best performing model with the top 1-20 predictors.

Results: We included 296,344 first-time ICU admissions. We found age, Glasgow Coma Scale, creatinine, systolic blood pressure, and pH being the most important predictors. The AUC-ROC was 0.884 in test data using all predictors, specificity 95.2%, sensitivity 47.0%, negative predictive value of 87.9% and positive predictive value of 70.7%. The final model showed excellent calibration. The ICU risk evaluation for 30-day mortality (ICURE) prediction model performed equally well to the SAPS 3 score with only eight variables and improved further with the addition of more variables.

Conclusion: The ICURE prediction model predicts 30-day mortality rate at first-time ICU admission superiorly compared to the established SAPS 3 score.

Background: Severe QT interval prolongation requires monitoring QTc intervals during anaesthesia with recommended therapeutic interventions at a threshold of 500 ms. The need for 12-lead ECG and lack of standardisation limit such monitoring. We determined whether automated continuous intraoperative QTc monitoring with 5-lead ECG measures QTc intervals comparable to 12-lead ECG and whether the interpretation of QTc intervals depends on the correction formulae and the patient's sex. We compared intraoperative QTc times to QTc times from resting ECGs of a population from the same region, to substantiate the hypothesis that patients under general anaesthesia may need specific treatment thresholds.

Methods: In this prospective observational study, intraoperative QT/QTc intervals were automatically recorded using 12 and 5-lead ECG in 100 patients (44% males). QTc values were analysed for sex and formula-specific aspects after correction for heart rate according to Bazett, Fridericia, Hodges, Framingham, Charbit and QTcRAS, and compared to a regional community-based cohort. The level of significance was set to α = 0.05.

Results: QT interval duration was not significantly different between 12-lead and 5-lead ECG (difference - 0.09 ms ± 8.5 ms, p = 0.793). The QTc interval duration significantly differed between the correction formulae (p < 0.001) and between sexes (p < 0.001). Mean intraoperative QTc duration was higher than in resting ECGs from a large community-based population with the same regional background (438 vs. 417 ms). The incidence of prolonged values >500 ms significantly depended on the correction formula (p < 0.001) and was up to tenfold higher in women versus men.

Conclusion: Intraoperative QTc interval measurement using a 5-lead ECG is valid. Correction formulae and gender influence the intraoperative QTc interval duration and the incidence of pathologically prolonged values according to current limits. The consideration and definition of sex-specific normal limits for QTc times under general anaesthesia, therefore, warrant further investigation.

Background: A careful approach is required when providing nutritional support to patients with acute respiratory distress syndrome (ARDS). This study investigated whether implementing a multidisciplinary nutritional support team (NST) is associated with improved survival outcomes in patients with ARDS.

Methods: In a nationwide population-based cohort study, all adult patients admitted to the intensive care unit (ICU) in South Korea with a primary diagnosis of ARDS from January 1, 2017, to December 31, 2021, were included. The NST comprised four professionals (physicians, full-time nurses, full-time pharmacists, and full-time clinical dietitians). Patients admitted to ICUs with and without the NST system were allocated to the NST and non-NST groups, respectively.

Results: The analysis comprised a total of 15,555 patients with ARDS. Among them, 6615 (42.5%) were in the NST group, and 8940 (57.5%) were in the non-NST group. After adjusting for covariates in the multivariable logistic regression, the NST group showed a 19% lower 30-day mortality than the non-NST group (odds ratio: 0.81, 95% confidence interval: 0.75-0.87, p < .001). Furthermore, after adjusting for covariates in multivariable Cox regression, the NST group showed a 12% lower 1-year all-cause mortality than the non-NST group (hazard ratio: 0.88, 95% confidence interval: 0.85-0.92, p < .001).

Conclusions: NST implementation was associated with enhanced 30-day and 1-year survival rates in patients with ARDS. These findings indicate that nutritional support provided by the NST may influence the survival outcomes of patients with ARDS in the ICU.

Background: Previous findings support the claim intensive care unit (ICU) patients have a higher rate of comorbidities and reduction of health- and functional status compared with the normal population.

Aim: In this prospective observational study, our aim was to determine those health-related factors at the age of 31 years which were associated with a later critical illness among previously un-hospitalized individuals by exploring data obtained from the Northern Finland Birth Cohort 1966 (NFBC1966).

Methods: NFBC1966 is a Finnish birth cohort, which includes 12,058 live births with expected dates of delivery during 1966. The study was conducted among cohort participants who had not been hospitalized for any reason before the cohort follow-up visit at the age of 31. The study group included NFBC1966 participants who were admitted to the ICU of the Oulu University Hospital. The control group included participants who were treated for any reason in regular hospital wards. The data considering the participants' health status and behavior at the age of 31 were collected from the NFBC1966 database. The gathering of ICU and hospitalization data was concluded on December 31, 2016.

Results: 849 NFBC1966 participants met the inclusion criteria: 69 were treated in the ICU (study group) and 780 on regular hospital wards (controls). In the study group, the rate of neurological diseases (26% vs. 16%, 95% CI: -21.8%, -0.2%), malignancy (3% vs. 0.7%, 95% CI: -9.7%, 0.0%), alcohol abuse (4.5% vs. 1%, 95% CI: -11.5%, -0.3%) and smoking (77% vs. 65%, 95% CI: -21.6%, -0.3%) were higher compared with the control group. The patients in the ICU group were also more prone to violent injuries, (17% vs. 7%, 95% CI: -20.2%, -1.9%), practiced less hard physical activity (65% vs. 78%, 95% CI: 2.1%, 25.3%) and had lower maximal muscle strength according to the hand grip test (30 vs. 34 kg, 95% CI: -8.2, 8.6 kg).

Conclusions: In this study examining previously un-hospitalized patients, the main factors associated with future critical illness were neurological comorbidities, malignancy, alcohol misuse, smoking, low maximum muscle strength, and less frequent physical exercise compared with those with hospitalization not requiring ICU admission.