Associations Between Physical, Cognitive, and Mental Health Domains of Post-Intensive Care Syndrome and Quality of Life: A Longitudinal Multicenter Cohort Study.

OBJECTIVES: To explore associations between the physical, cognitive, and mental post-intensive care syndrome (PICS) health domains with changes in health-related quality of life (HRQoL) following ICU admission. DESIGN: A longitudinal prospective multicenter cohort study. SETTING/PATIENTS: Patients (n = 4092) from seven Dutch ICUs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: At ICU admission, 3 and 12 months post-ICU, patients completed validated questionnaires regarding physical health problems, cognitive health problems, mental health problems, and HRQoL. Composite scores were created for the physical health domain (physical problems and fatigue) and mental health domain (anxiety, depression, and post-traumatic stress disorder). Adjusted multivariable linear regression analyses were performed, including covariables (e.g., patient characteristics, disease severity, pre-ICU HRQoL, etc.) to explore associations between the physical, cognitive, and mental health domains of PICS and changes in HRQoL at 3 and 12 months post-ICU. At 3 months (n = 3368), physical health problems (ß = -0.04 [95% CI, -0.06 to 0.02]; p < 0.001), cognitive health problems (ß = -0.05 [95% CI, -0.09 to -0.02]; p < 0.001), and mental health problems (ß = -0.08 [95% CI, -0.10 to -0.05]; p < 0.001) were negatively associated with changes in HRQoL. Also, at 12 months (n = 2950), physical health problems (ß = -0.06 [95% CI, -0.08 to -0.03]; p < 0.001), cognitive health problems (ß = -0.04 [95% CI, -0.08 to -0.01]; p < 0.015), and mental health problems (ß = -0.06 [95% CI, -0.08 to -0.03]; p < 0.001) were negatively associated with changes in HRQoL. CONCLUSIONS: PICS symptoms in the physical, cognitive, and mental domains are all negatively associated with changes in HRQoL at 3 and 12 months post-ICU. At 3 months, PICS symptoms in the mental domain seem to have the largest negative associations. At 12 months, the associations of PICS in the mental and physical domains are the same. This implies that daily ICU care and follow-up care should focus on preventing and mitigating health problems across all three PICS domains to prevent a decrease in HRQoL.

Prediction of Long-Term Physical, Mental, and Cognitive Problems Following Critical Illness: Development and External Validation of the PROSPECT Prediction Model.

OBJECTIVES: ICU survivors often suffer from long-lasting physical, mental, and cognitive health problems after hospital discharge. As several interventions that treat or prevent these problems already start during ICU stay, patients at high risk should be identified early. This study aimed to develop a model for early prediction of post-ICU health problems within 48 hours after ICU admission. DESIGN: Prospective cohort study in seven Dutch ICUs. SETTING/PATIENTS: ICU patients older than 16 years and admitted for greater than or equal to 12 hours between July 2016 and March 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Outcomes were physical problems (fatigue or ≥ 3 new physical symptoms), mental problems (anxiety, depression, or post-traumatic stress disorder), and cognitive impairment. Patient record data and questionnaire data were collected at ICU admission, and after 3 and 12 months, of 2,476 patients. Several models predicting physical, mental, or cognitive problems and a composite score at 3 and 12 months were developed using variables collected within 48 hours after ICU admission. Based on performance and clinical feasibility, a model, PROSPECT, predicting post-ICU health problems at 3 months was chosen, including the predictors of chronic obstructive pulmonary disease, admission type, expected length of ICU stay greater than or equal to 2 days, and preadmission anxiety and fatigue. Internal validation using bootstrapping on data of the largest hospital ( n = 1,244) yielded a C -statistic of 0.73 (95% CI, 0.70-0.76). External validation was performed on data ( n = 864) from the other six hospitals with a C -statistic of 0.77 (95% CI, 0.73-0.80). CONCLUSIONS: The developed and externally validated PROSPECT model can be used within 48 hours after ICU admission for identifying patients with an increased risk of post-ICU problems 3 months after ICU admission. Timely preventive interventions starting during ICU admission and follow-up care can prevent or mitigate post-ICU problems in these high-risk patients.

Changes in quality of life 1 year after intensive care: a multicenter prospective cohort of ICU survivors.

BACKGROUND: With survival rates of critical illness increasing, quality of life measures are becoming an important outcome of ICU treatment. Therefore, to study the impact of critical illness on quality of life, we explored quality of life before and 1 year after ICU admission in different subgroups of ICU survivors. METHODS: Data from an ongoing prospective multicenter cohort study, the MONITOR-IC, were used. Patients admitted to the ICU in one of eleven participating hospitals between July 2016 and June 2021 were included. Outcome was defined as change in quality of life, measured using the EuroQol five-dimensional (EQ-5D-5L) questionnaire, and calculated by subtracting the EQ-5D-5L score 1 day before hospital admission from the EQ-5D-5L score 1 year post-ICU. Based on the minimal clinically important difference, a change in quality of life was defined as a change in EQ-5D-5L score of ≥ 0.08. Subgroups of patients were based on admission diagnosis. RESULTS: A total of 3913 (50.6%) included patients completed both baseline and follow-up questionnaires. 1 year post-ICU, patients admitted after a cerebrovascular accident, intracerebral hemorrhage, or (neuro)trauma, on average experienced a significant decrease in quality of life. Conversely, 11 other subgroups of ICU survivors reported improvements in quality of life. The largest average increase in quality of life was seen in patients admitted due to respiratory disease (mean 0.17, SD 0.38), whereas the largest average decrease was observed in trauma patients (mean -0.13, SD 0.28). However, in each of the studied 22 subgroups there were survivors who reported a significant increase in QoL and survivors who reported a significant decrease in QoL. CONCLUSIONS:  This large prospective multicenter cohort study demonstrated the diversity in long-term quality of life between, and even within, subgroups of ICU survivors. These findings emphasize the need for personalized information and post-ICU care. TRIAL REGISTRATION: The MONITOR-IC study was registered at ClinicalTrials.gov: NCT03246334 on August 2nd 2017.

Abnormal Iron Status and Adverse Outcome After Elective Cardiac Surgery: A Prospective, Observational Multicenter Study.

OBJECTIVES: To investigate the incidence of preoperative abnormal iron status and its association with packed red blood cell (PRBC) transfusion, postoperative major complications, and new onset of clinically significant disability in patients undergoing elective cardiac surgery. DESIGN: A prospective, observational multicenter cohort study. SETTING: Three cardiac surgical centers in the Netherlands between 2019 and 2021. Recruitment was on hold between March and May 2020 due to COVID-19. PATIENTS: A total of 427 patients aged 60 years and older who underwent elective on-pump cardiac surgery. MEASUREMENTS AND MAIN RESULTS: The primary endpoint was a 30-day PRBC transfusion. Secondary endpoints were postoperative major complications within 30 days (eg, acute kidney injury, sepsis), and new onset of clinically significant disability within 120 days of surgery. Iron status was evaluated before surgery. Abnormal iron status was present in 45.2% of patients (n = 193), and most frequently the result of iron deficiency (27.4%, n = 117). An abnormal iron status was not associated with PRBC transfusion (adjusted relative risk [ARR] 1.2; 95% CI 0.9-1.8: p = 0.227) or new onset of clinically significant disability (ARR 2.0; 95% CI 0.9-4.6: p = 0.098). However, the risk of postoperative major complications was increased in patients with an abnormal iron status (ARR 1.7; 95% CI 1.1-2.5: p = 0.012). CONCLUSIONS: An abnormal iron status before elective cardiac surgery was associated with an increased risk of postoperative major complications but not with PRBC transfusion or a new onset of clinically significant disability.

Development and External Validation of a Prediction Model for Quality of Life of ICU Survivors: A Subanalysis of the MONITOR-IC Prospective Cohort Study.

OBJECTIVES: To develop and externally validate a prediction model for ICU survivors' change in quality of life 1 year after ICU admission that can support ICU physicians in preparing patients for life after ICU and managing their expectations. DESIGN: Data from a prospective multicenter cohort study (MONITOR-IC) were used. SETTING: Seven hospitals in the Netherlands. PATIENTS: ICU survivors greater than or equal to 16 years old. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Outcome was defined as change in quality of life, measured using the EuroQol 5D questionnaire. The developed model was based on data from an academic hospital, using multivariable linear regression analysis. To assist usability, variables were selected using the least absolute shrinkage and selection operator method. External validation was executed using data of six nonacademic hospitals. Of 1,804 patients included in analysis, 1,057 patients (58.6%) were admitted to the academic hospital, and 747 patients (41.4%) were admitted to a nonacademic hospital. Forty-nine variables were entered into a linear regression model, resulting in an explained variance ( R2 ) of 56.6%. Only three variables, baseline quality of life, admission type, and Glasgow Coma Scale, were selected for the final model ( R2 = 52.5%). External validation showed good predictive power ( R2 = 53.2%). CONCLUSIONS: This study developed and externally validated a prediction model for change in quality of life 1 year after ICU admission. Due to the small number of predictors, the model is appealing for use in clinical practice, where it can be implemented to prepare patients for life after ICU. The next step is to evaluate the impact of this prediction model on outcomes and experiences of patients.

Cardiac Surgery in Jehovah's Witnesses: 329 Consecutive Cases.

OBJECTIVES: This study aimed to describe the outcome of Jehovah's Witnesses (JWs) undergoing cardiac surgery at the authors' center. DESIGN: A single-center retrospective cohort study. SETTING: At a cardiovascular center with a tertiary intensive care unit (ICU) and specific experience with cardiac surgery in JWs. The institutional protocol describing all perioperative care in JWs has been applied for 21 years. PARTICIPANTS: All JWs undergoing cardiac surgery in the Amphia Hospital from January 1, 2001 to January 31, 2022. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The study cohort comprised 329 JWs undergoing cardiac surgery. Twenty-three patients (6.8%) were treated preoperatively for anemia. The mean European System for Cardiac Operative Risk Evaluation score was 5.1 (range 0-18). Coronary artery bypass grafting (53.2%) was performed most frequently, followed by aortic valve replacement (13.4%). Mean preoperative hemoglobin levels were 14.5 g/dL (range 9.8-18.5 g/dL), dropping to 11.6 g/dL (range 6.6-15.6 g/dL) at hospital discharge. Mean blood loss was 439 ± 349 mL in the first 12 hours postsurgery. Maximum mean postoperative troponin levels were 431 ± 424 ng/L. Resternotomy and postoperative myocardial infarction occurred in 3.6% and 4.2% of patients, respectively. On average, patients had an ICU stay of 1.4 ± 1.8 days and a hospital stay of 6.8 ± 4.2 days. Hospital mortality was 0.6% and was related to cardiac failure. CONCLUSIONS: This study demonstrated that cardiac surgery in JWs is safe when adhering to a strict perioperative patient blood management protocol.

Preoperative anaemia and outcome after elective cardiac surgery: a Dutch national registry analysis.

BACKGROUND: Previous studies have shown that preoperative anaemia in patients undergoing cardiac surgery is associated with adverse outcomes. However, most of these studies were retrospective, had a relatively small sample size, and were from a single centre. The aim of this study was to analyse the relationship between the severity of preoperative anaemia and short- and long-term mortality and morbidity in a large multicentre national cohort of patients undergoing cardiac surgery. METHODS: A nationwide, prospective, multicentre registry (Netherlands Heart Registration) of patients undergoing elective cardiac surgery between January 2013 and January 2019 was used for this observational study. Anaemia was defined according to the WHO criteria, and the main study endpoint was 120-day mortality. The association was investigated using multivariable logistic regression analysis. RESULTS: In total, 35 484 patients were studied, of whom 6802 (19.2%) were anaemic. Preoperative anaemia was associated with an increased risk of 120-day mortality (adjusted odds ratio [aOR] 1.7; 95% confidence interval [CI]: 1.4-1.9; P<0.001). The risk of 120-day mortality increased with anaemia severity (mild anaemia aOR 1.6; 95% CI: 1.3-1.9; P<0.001; and moderate-to-severe anaemia aOR 1.8; 95% CI: 1.4-2.4; P<0.001). Preoperative anaemia was associated with red blood cell transfusion and postoperative morbidity, the causes of which included renal failure, pneumonia, and myocardial infarction. CONCLUSIONS: Preoperative anaemia was associated with mortality and morbidity after cardiac surgery. The risk of adverse outcomes increased with anaemia severity. Preoperative anaemia is a potential target for treatment to improve postoperative outcomes.

Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care: Development and validation of a prognostic tool for in-hospital mortality.

BACKGROUND: The prediction of in-hospital mortality for ICU patients with COVID-19 is fundamental to treatment and resource allocation. The main purpose was to develop an easily implemented score for such prediction. METHODS: This was an observational, multicenter, development, and validation study on a national critical care dataset of COVID-19 patients. A systematic literature review was performed to determine variables possibly important for COVID-19 mortality prediction. Using a logistic multivariable model with a LASSO penalty, we developed the Rapid Evaluation of Coronavirus Illness Severity (RECOILS) score and compared its performance against published scores. RESULTS: Our development (validation) cohort consisted of 1480 (937) adult patients from 14 (11) Dutch ICUs admitted between March 2020 and April 2021. Median age was 65 (65) years, 31% (26%) died in hospital, 74% (72%) were males, average length of ICU stay was 7.83 (10.25) days and average length of hospital stay was 15.90 (19.92) days. Age, platelets, PaO2/FiO2 ratio, pH, blood urea nitrogen, temperature, PaCO2, Glasgow Coma Scale (GCS) score measured within +/-24 h of ICU admission were used to develop the score. The AUROC of RECOILS score was 0.75 (CI 0.71-0.78) which was higher than that of any previously reported predictive scores (0.68 [CI 0.64-0.71], 0.61 [CI 0.58-0.66], 0.67 [CI 0.63-0.70], 0.70 [CI 0.67-0.74] for ISARIC 4C Mortality Score, SOFA, SAPS-III, and age, respectively). CONCLUSIONS: Using a large dataset from multiple Dutch ICUs, we developed a predictive score for mortality of COVID-19 patients admitted to ICU, which outperformed other predictive scores reported so far.

Clinical Outcomes Among Patients With 1-Year Survival Following Intensive Care Unit Treatment for COVID-19.

IMPORTANCE: One-year outcomes in patients who have had COVID-19 and who received treatment in the intensive care unit (ICU) are unknown. OBJECTIVE: To assess the occurrence of physical, mental, and cognitive symptoms among patients with COVID-19 at 1 year after ICU treatment. DESIGN, SETTING, AND PARTICIPANTS: An exploratory prospective multicenter cohort study conducted in ICUs of 11 Dutch hospitals. Patients (N = 452) with COVID-19, aged 16 years and older, and alive after hospital discharge following admission to 1 of the 11 ICUs during the first COVID-19 surge (March 1, 2020, until July 1, 2020) were eligible for inclusion. Patients were followed up for 1 year, and the date of final follow-up was June 16, 2021. EXPOSURES: Patients with COVID-19 who received ICU treatment and survived 1 year after ICU admission. MAIN OUTCOMES AND MEASURES: The main outcomes were self-reported occurrence of physical symptoms (frailty [Clinical Frailty Scale score ≥5], fatigue [Checklist Individual Strength-fatigue subscale score ≥27], physical problems), mental symptoms (anxiety [Hospital Anxiety and Depression {HADS} subscale score ≥8], depression [HADS subscale score ≥8], posttraumatic stress disorder [mean Impact of Event Scale score ≥1.75]), and cognitive symptoms (Cognitive Failure Questionnaire-14 score ≥43) 1 year after ICU treatment and measured with validated questionnaires. RESULTS: Of the 452 eligible patients, 301 (66.8%) patients could be included, and 246 (81.5%) patients (mean [SD] age, 61.2 [9.3] years; 176 men [71.5%]; median ICU stay, 18 days [IQR, 11 to 32]) completed the 1-year follow-up questionnaires. At 1 year after ICU treatment for COVID-19, physical symptoms were reported by 182 of 245 patients (74.3% [95% CI, 68.3% to 79.6%]), mental symptoms were reported by 64 of 244 patients (26.2% [95% CI, 20.8% to 32.2%]), and cognitive symptoms were reported by 39 of 241 patients (16.2% [95% CI, 11.8% to 21.5%]). The most frequently reported new physical problems were weakened condition (95/244 patients [38.9%]), joint stiffness (64/243 patients [26.3%]) joint pain (62/243 patients [25.5%]), muscle weakness (60/242 patients [24.8%]) and myalgia (52/244 patients [21.3%]). CONCLUSIONS AND RELEVANCE: In this exploratory study of patients in 11 Dutch hospitals who survived 1 year following ICU treatment for COVID-19, physical, mental, or cognitive symptoms were frequently reported.

The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients.

BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. METHODS: A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract-transform-load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. RESULTS: Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. CONCLUSIONS: In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.

Predictors for extubation failure in COVID-19 patients using a machine learning approach.

INTRODUCTION: Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. METHODS: We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. RESULTS: A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. CONCLUSION: The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records.

Maintaining endotracheal tube cuff pressure at 20 mmHg during anterior cervical spine surgery to prevent dysphagia: a double-blind randomized controlled trial.

PURPOSE: Anterior cervical spine surgery is associated with postoperative dysphagia, sore throat and dysphonia. It is unclear, whether this is caused by increased endotracheal tube (ETT) cuff pressure after retractor placement. This study aims to assess the effect of ETT cuff pressure adjustment on postoperative dysphagia, sore throat and dysphonia. METHODS: In this, single-centre, observer and patient-blinded randomized controlled trial patients treated with anterior cervical spine surgery were randomized to adjustment of the ETT cuff pressure to 20 mmHg after placement of the retractor versus no adjustment. Primary outcome was the incidence and severity of postoperative dysphagia. Secondary outcomes were sore throat and dysphonia. Outcomes were evaluated on day one and 2 months after the operation. RESULTS: Of 177 enrolled patients, 162 patients (92.5%) could be evaluated. The incidence of dysphagia was 75.9% on day one and 34.6% 2 months after surgery. Dysphagia in the intervention and control group was present in 77.8% versus 74.1% of patients on day one (odds ratio (OR) 1.2, 95% confidence interval (CI) (0.6-2.5)) and 28.4% versus 40.7% of patients after 2 months (OR 0.6, 95% CI 0.3-1.1), respectively. Severity of dysphagia, sore throat and dysphonia was similar in both groups. CONCLUSIONS: Anterior cervical spine surgery is accompanied by a high incidence of postoperative dysphagia, lasting until at least 2 months after surgery in over a third of our patients. Adjusting ETT cuff pressure to 20 mmHg after retractor placement, as compared to controls, did not lower the risk for both short- and long-term dysphagia. Netherlands National Trial Registry Number: NTR 3542. These slides can be retrieved under electronic supplementary material.

Impact of Intraoperative Hypotension During Cardiopulmonary Bypass on Acute Kidney Injury After Coronary Artery Bypass Grafting.

OBJECTIVE: The aim of this study was to investigate whether acute kidney injury (AKI) after coronary artery bypass grafting can be attributed to intraoperative hypotension during cardiopulmonary bypass (IOH-CPB). DESIGN: Retrospective analysis. SETTING: Tertiary-care hospital. PARTICIPANTS: Patients undergoing on-pump coronary artery bypass grafting from June 2011 to January 2014. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: IOH-CPB was defined as blood pressure below several absolute and relative mean arterial pressure (MAP) thresholds and as the area under the curve for absolute MAP thresholds. AKI was defined as an absolute increase in serum creatinine of≥26 µmol/L within 48 hours or an increase to 150% or more within 7 days of surgery. Poisson regression with robust standard errors both before and after adjustment for confounders was used. Of the 1,891 patients included, 386 (20%) developed AKI. In univariable analysis, all IOH-CPB thresholds defined as a MAP of 50 mmHg or less and as a decrease in MAP of 60% from baseline were associated with a 1.07-to-1.11 times increased risk of AKI per 10 minutes of IOH-CPB (p<0.01). After adjustment for potential confounders, IOH-CPB, irrespective of the definition chosen, was not associated with an increased risk of AKI. CONCLUSIONS: In the authors' study population, univariable analysis showed an association of IOH-CPB with AKI in patients undergoing isolated CABG, but this relationship disappeared after correction for well-known risk factors for AKI.

Postoperative Interleukin-6 Level and Early Detection of Complications After Elective Major Abdominal Surgery.

OBJECTIVE: To assess the association of systemic inflammation and outcome after major abdominal surgery. BACKGROUND: Major abdominal surgery carries a high postoperative morbidity and mortality rate. Studies suggest that inflammation is associated with unfavorable outcome. METHODS: Levels of C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-α and the systemic inflammatory response syndrome (SIRS) were assessed in 137 patients undergoing major abdominal surgery. Blood samples were drawn on days 0, 1, 3, and 7, and SIRS was scored during 48 hours after surgery. Primary outcome was a composite of mortality, pneumonia, sepsis, anastomotic dehiscence, wound infection, noncardiac respiratory failure, atrial fibrillation, congestive heart failure, myocardial infarction, and reoperation within 30 days of surgery. RESULTS: An IL-6 level more than 432 pg/mL on day 1 was associated with an increased risk of complications (adjusted odds ratio: 3.3; 95% confidence interval [CI]: 1.3-8.5) and a longer median length of hospital stay (7 vs 12 days, P < 0.001). As a single test, an IL-6 cut-off level of 432 pg/mL on day 1 yielded a specificity of 70% and a sensitivity of 64% for the prediction of complications (area under the curve: 0.67; 95% CI: 0.56-0.77). Levels of CRP started to discriminate from day 3 onward with a specificity of 87% and a sensitivity of 58% for a cut-off level of 203 mg/L (AUC: 0.73; 95% CI: 0.63-0.83). CONCLUSIONS: A high IL-6 level on day 1 is associated with postoperative complications. Levels of IL-6 help distinguish between patients at low and high risk for complications before changes in levels of CRP.

The systemic inflammatory response syndrome predicts short-term outcome after transapical transcatheter aortic valve implantation.

OBJECTIVE: Despite the minimally invasive nature of transcatheter aortic valve implantation (TAVI), the incidence of acute kidney injury (AKI) and mortality is of major concern. Several studies showed that outcome was influenced by the systemic inflammatory response syndrome (SIRS) in patients undergoing percutaneous TAVI. The purpose of this study was to investigate whether SIRS after transapical TAVI was associated with short-term outcome. DESIGN: Retrospective analysis of prospectively collected data. SETTING: Intensive care unit in a tertiary-care hospital. PARTICIPANTS: In 121 patients undergoing transapical TAVI for severe aortic stenosis between March 2010 and October 2013, the incidence of SIRS during the first 48 hours was studied. The relation between the occurrence of SIRS and any adverse event during hospital stay was investigated. Any adverse event was defined as the composite of mortality, AKI, infection, stroke, myocardial infarction, and bleeding. INTERVENTION: none. MEASUREMENTS AND MAIN RESULTS: Sixty-five (53.7%) patients developed SIRS during 48 hours after transapical TAVI. The occurrence of SIRS was associated independently with an increased risk of any adverse event (adjusted odds ratio: 4.0, 95% confidence interval [CI]: 1.6-9.6; p=0.002), which was mainly an increased risk of death (odds ratio: 5.5, 95% CI: 1.1-25.9; p=0.031). Patients with SIRS had a longer median duration of intensive care unit stay compared with patients without SIRS (2 v 1 day; p<0.001). CONCLUSIONS: SIRS predicts short-term outcome in patients undergoing transapical TAVI.

One-year outcomes in COVID-19 and non-COVID-19 intensive care unit survivors.

PURPOSE: To determine differences in one-year multi-domain health outcomes in COVID-19 and non-COVID-19 intensive care unit (ICU) survivors. MATERIALS AND METHODS: Adult ICU survivors treated for COVID-19 were compared to a control group consisting of survivors admitted for respiratory distress due to other causes, i.e. non-COVID-19 ARDS or pneumonia. Occurrence of physical (frailty, fatigue, physical symptoms), mental (anxiety, depression, post-traumatic stress) and cognitive symptoms, and quality of life (QoL) scores were measured, using validated questionnaires, before and one year after ICU treatment. RESULTS: In total, 506 COVID-19 survivors could be compared to 228 non-COVID-19 survivors. At one-year follow-up, COVID-19 ICU survivors had less physical (76.2% vs. 86.9%, p = 0.001) and mental symptoms (32.0% vs. 47.1%, p < 0.001) than the control group. Cognitive symptoms were comparable (22.5% vs. 17.2%, p = 0.12). However, compared to pre-ICU health symptoms and scores, COVID-19 survivors experienced an increase in symptom occurrence rates in all domains and a decrease in QoL, whereas the control group only experienced an increase in mental and cognitive symptoms, with a similar QoL at one-year follow-up. CONCLUSIONS: COVID-19 ICU survivors experience equal or less health problems but a greater decline in QoL one year after ICU admission compared to non-COVID-19 ARDS or pneumonia survivors.

Discrepancy Between Functional Outcomes and Perceived Health post-ICU: A Prospective Cohort Study.

RATIONALE: Despite functional impairments, ICU survivors can perceive their quality of life as acceptable. OBJECTIVES: To investigate discrepancies between calculated health, based on self-reported physical, mental and cognitive functioning, and perceived health one year after ICU admission. METHODS: Data from an ongoing prospective multicenter cohort study, MONITOR-IC, were used. Patient-reported physical, mental and cognitive functioning, and perceived health (EQ-VAS, range 0-100) one year post-ICU of patients admitted to one of eleven participating ICUs between July 2016 and September 2021 were analyzed. The relationship between functional outcomes and perceived health was modeled using linear regression. Calculated health for each patient was estimated using this model and compared to patients' perceived health, the difference reflecting a discrepancy. Based on a minimal clinically important difference of eight points, three groups were defined: patients who rated their health better than calculated (positive discrepancy), patients who rated their health worse than calculated (negative discrepancy), and patients whose perceived health was concordant with their calculated health. RESULTS: 2,545 patients were analyzed, of whom 45.0% (n = 1,146) showed a discrepancy between calculated and perceived health. Patients with a negative discrepancy rated their health significantly lower (median 50, IQR 36 - 66) than patients with a positive discrepancy (median 84, IQR 75 - 90). Importantly, there were no significant differences in physical, mental and cognitive functioning between patients with a negative and positive discrepancy. Patients with a negative discrepancy had a higher education level and were more often unemployed. CONCLUSIONS: One year post-ICU, almost half of ICU survivors showed a discrepancy between calculated health and perceived health.