Regional Intensive Care Research Articles

Reducing administrative burden by implementing a core set of quality indicators in the ICU: a multicentre longitudinal intervention study

BackgroundThe number of quality indicators for which clinicians need to record data is increasing. For many indicators, there are concerns about their efficacy. This study aimed to determine whether working...

Linking Dutch Intensive Care Registry Data to Socioeconomic Status Scores.

This study aimed to gain insight into the success rate of linking the NICE registry with SES data from CBS and to examine whether the characteristics of linked and non-linked patients differ. Although clinically relevant differences were found, in total 93,4% of the admissions were successfully linked.

ICURE: Intensive care unit (ICU) risk evaluation for 30-day mortality. Developing and evaluating a multivariable machine learning prediction model for patients admitted to the general ICU in Sweden.

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

Long-term Mortality and Hospital Readmissions Among Survivors of Sepsis in Sweden: A Population-Based Cohort Study.

Survivors of sepsis may experience long-term risk of increased morbidity and mortality, but estimations of cause-specific effects beyond 1 year after a sepsis episode are lacking. This nationwide population-based cohort study linked data from national registers to compare patients aged ≥18 years in Sweden admitted to an intensive care unit from 2008 to 2019 with severe community-acquired sepsis. Patients were identified through the Swedish Intensive Care Registry, and randomly selected population controls were matched for age, sex, calendar year, and county of residence. Confounding from comorbidities, health care use, and socioeconomic and demographic factors was accounted for by using entropy-balancing methods. Long-term mortality and readmission rates, total and cause specific, were compared for 20 313 patients with sepsis and 396 976 controls via Cox regression. During the total follow-up period, 56% of patients with sepsis died, as opposed to 26% of the weighted controls. The hazard ratio for all-cause mortality was attenuated with time but remained elevated in all periods: 3.0 (95% CI, 2.8-3.2) at 2 to 12 months after admission, 1.8 to 1.9 between 1 and 5 years, and 1.6 (95% CI, 1.5-1.8) at >5 years. The major causes of death and readmission among the sepsis cases were infectious diseases, cancer, and cardiovascular diseases. The hazard ratios were larger among those without underlying comorbidities. Severe community-acquired sepsis was associated with substantial long-term effects beyond 1 year, as measured by mortality and rehospitalization. The cause-specific rates indicate the importance of underlying or undetected comorbidities while suggesting that survivors of sepsis may face increased long-term mortality and morbidity not explained by underlying health factors.

Smoking is associated with higher risk of contracting bacterial infection and pneumonia, intensive care unit admission and death.

Smoking has been associated with a higher risk of contracting pneumonia, but contradictory results have shown that smoking may or may not decrease the risk of dying in pneumonia. The aim of this study is to investigate how smoking is associated with contracting any infection and pneumonia and death. Participants were drawn from the population-based Cohort of Swedish Men and the Swedish Mammography Cohort, which are representative of the Swedish population. Participants have answered detailed lifestyle questionnaires and have been followed in national registers, such as the Patient Register, Cause of Death register and Swedish Intensive Care Registry. The risks of contracting infection and pneumonia or dying in infection and pneumonia were assessed using Cox regression. Of 62,902 cohort participants, 25,297 contracted an infection of which 4,505 died; and 10,471 contracted pneumonia of which 2,851 died. Compared to never smokers, former smokers at baseline had hazard ratio (HR) 1.08 (95% confidence interval (CI) 1.05-1.12) of contracting and HR 1.19 (95% CI 1.11-1.28) of dying in infection and HR 1.17 (95% CI 1.12-1.23) of contracting and HR 1.16 (95% CI 1.06-1.27) of dying in pneumonia during follow-up. Compared to never smokers, current smokers at baseline had HR 1.17 (95% CI 1.13-1.21) of contracting infection and HR 1.64 (95% CI 1.52-1.77) dying in infection; HR 1.42 (95% CI 1.35-1.49) of contracting pneumonia and HR 1.70 (95% CI 1.55-1.87) of dying in pneumonia during follow-up. The risk of contracting and dying in infection and pneumonia increased in a dose-response manner with number of pack years smoked and decreased with years since smoking cessation. Smoking is associated with contracting and dying in any infection and pneumonia and the risk increases with pack years smoked, highlighting the importance of both primary prevention and smoking cessation.

Objective and subjective cognitive status after intensive care unit treatment for COVID-19

PurposeIntensive care unit (ICU) survivors can experience wide-ranging and long-lasting symptoms after hospital discharge. Cognitive impairment has received increased attention in relation to the COVID-19 pandemic and can affect patients’ long-term quality of life. This study aimed to investigate the prevalence of cognitive impairment using an objective neurocognitive test 6 and 12 months following ICU admission and possible predictive factors for scoring below the defined cut-off. We also explored the prevalence of subjective cognitive complaints at 12 months, including the associated factors. MethodsThis was a prospective observational study of a national cohort of COVID-19 ICU survivors during the three first pandemic waves in Norway. Data was collected by the Norwegian Intensive Care and Pandemic Registry and the study group. ResultsAt the six-month follow-up, 23.1% (95% CI [18.2─28.5]) of the 273 respondents scored below the cut-off on the Mini-MoCA, indicating mild cognitive impairment. At the 12-month follow-up, the prevalence declined to 11.1% (95% CI [7.5─15.6]) in 253 respondents. Older age (OR 1.06, 95% CI [1.02─1.12]) and depression (OR 1.25, 95% CI [1.07─1.55]) were associated with cognitive impairment at six months. At 12 months, almost half of the patients reported subjective cognitive complaints. Symptoms of mental health problems and fatigue were associated with subjective cognitive complaints in our exploratory analyses. ConclusionCognitive impairment declined significantly from 6 to 12 months in this cohort of COVID-19 ICU patients, while subjective cognitive complaints remained high at 12 months, perhaps attributed to a high total symptom burden.

Physical activity is associated with a lower risk of contracting and dying in infection and sepsis: a Swedish population-based cohort study

BackgroundSepsis is a condition where the immune response to infection becomes dysregulated and life-threatening. It is not known whether lifestyle factors influence the risk of sepsis. The aim of the present study is to investigate the association between physical activity and the risk of acquiring and dying in infection or sepsis.MethodsThe population-based Swedish Mammography Cohort and Cohort of Swedish Men sent participants lifestyle questionnaires in 1997 and have subsequently followed participants in national Swedish registers, including the National Patient Register, the Swedish Intensive Care Registry and the Cause of Death Register. The risk of contracting infection and sepsis, the risk of intensive care unit admission and the risk of death were estimated using multivariable Cox regression.ResultsAmong 64,850 cohort participants, 26,124 individuals suffered at least one episode of infection or sepsis and 4708 individuals died of infection or sepsis during the study period. In adjusted analyses, compared to exercising less than one hour per week, stated exercise one hour per week was associated with lower risk of contracting infection or sepsis, hazard ratio (HR) 0.93 (95% confidence interval (CI) 0.90–0.97), and lower risk of dying in infection or sepsis, HR 0.87 (95% CI 0.80–0.96). Further exercise was associated with even lower risk, and similar patterns were observed for walking. The population-attributable risks of contracting and dying in infection or sepsis for not exercising were 2.6% and 4.5%, respectively.ConclusionsExercise and walking demonstrate inverse dose–response associations with both the risk of contracting and dying in infection and sepsis, presenting possible preventative interventions for this critical condition.

Unit-to-unit transfer due to shortage of intensive care beds in Sweden 2015–2019 was associated with a lower risk of death but a longer intensive care stay compared to no transfer: a registry study

BackgroundIntensive care unit-to-unit transfer due to temporary shortage of beds is increasing in Sweden. Transportation induces practical hazards, and the change of health care provider may prolong the length of stay in intensive care. We previously showed that the risk of death at 90 days did not differ between patients transferred due to a shortage of beds and non-transferred patients with a similar burden of illness in a tertiary intensive care unit. The aim of this study was to widen the analysis to a nation-wide cohort of critically ill patients transferred to another intensive care unit in Sweden due to shortage of intensive care beds.MethodsRetrospective comparison between capacity transferred and non-transferred patients, based on data from the Swedish Intensive Care Registry during a 5-year period before the COVID-19 pandemic. Patients with insufficient data entries or a recurring capacity transfer within 90 days were excluded. To assess the association between capacity transfer and death as well as intensive care stay within 90 days after ICU admission, logistic regression models with step-wise adjustment for SAPS3 score, primary ICD-10 ICU diagnosis and the number of days in the intensive care unit before transfer were applied.ResultsFrom 161,140 eligible intensive care admissions, 2912 capacity transfers were compared to 135,641 discharges or deaths in the intensive care unit. Ninety days after ICU admission, 28% of transferred and 21% of non-transferred patients were deceased. In the fully adjusted model, capacity transfer was associated with a lower risk of death within 90 days than no transfer; OR (95% CI) 0.71 (0.65–0.69) and the number of days spent in intensive care was longer: 12.4 [95% CI 12.2–12.5] vs 3.3 [3.3–3.3].ConclusionsIntensive care unit-to-unit transfer due to shortage of bed capacity as compared to no transfer during a 5-year period preceding the COVID-19 pandemic in Sweden was associated with lower risk of death within 90 days but with longer stay in intensive care.

Characteristics and Outcome of ICU Unplanned Readmission in Trauma Patients During the Same Hospitalization.

This study aimed to determine the rate of readmission for trauma patients in ICUs, as well as the factors that predict this outcome. This retrospective cohort study was conducted at Emtiaz Hospital, a level I referral trauma center (Shiraz, Iran). It analyzed the ICU readmission rates among trauma patients over three years. The required data were extracted from the Iranian Intensive Care Registry (IICUR), which included patient demographics, injury severity, physiological parameters, and clinical outcomes. Statistical analysis was performed using SPSS version 25.0. Descriptive statistics and different statistical tests, such as T-tests, Mann-Whitney tests, Chi-square tests, and logistic binary regression test were utilized. Among the 5273 patients discharged from the ICU during the study period, 195 (3.7%) were readmitted during the same hospitalization. Patients readmitted to the ICU had a significantly higher mean age (54.83±22.73 years) than those who were not readmitted (47.08 years, p<0.001). Lower Glasgow Coma Scale (GCS) scores at admission and discharge were associated with ICU readmission, implying that neurological status and readmission risk were correlated with each other. Furthermore, respiratory challenges were identified as the leading cause of unexpected readmission, including respiratory failure, hypoxic respiratory failure, respiratory distress, and respiratory infections such as pneumonia. Injury patterns analysis revealed a higher frequency of poly-trauma and head and neck injuries among patients readmitted to the ICU. This study underscored the importance of ICU readmission among trauma patients, with a high readmission rate during the same hospitalization. By developing comprehensive guidelines and optimizing discharge processes, healthcare providers could potentially mitigate ICU readmissions and associated complications, ultimately enhancing patient outcomes and resource utilization in trauma ICU settings. This research provided valuable insights to inform evidence-based practices and improve the quality of care delivery for trauma patients in intensive care settings.

COVID-19 in the neighbourhood: the socio-spatial selectivity of severe COVID-19 cases in Sweden, March 2020–June 2021

AbstractIn this paper we analyse spatial and temporal variation in the risk of intensive care unit (ICU) admission for COVID-19 in Sweden. The analysis is based on geocoded and time-stamped data from the Swedish Intensive Care Registry (SIR). We merge this data with a classification of Swedish neighbourhood cluster types constructed from multi-scalar measures of socio-economic and country of birth segregation (Kawalerowicz and Malmberg in Multiscalar typology of residential areas in Sweden, 2021 available from https://doi.org/10.17045/sthlmuni.14753826.v1). We examine 1) if residence in more socio-economically deprived or diverse neighbourhood cluster types was associated with a higher risk of ICU admission for COVID-19, 2) if residence in more affluent neighbourhoods was associated with a lower risk of ICU admission for COVID-19, and 3) how these patterns changed over time during the three first waves of the pandemic. While the highest overall risk was associated with residence in urban disadvantage coupled with diversity, models where neighbourhood cluster types were interacted with waves reveal that the highest risk was associated with living in a neighbourhood cluster type characterised by rural town disadvantage coupled with diversity under the 3rd wave (February 2021–June 2021). Residence in such a neighbourhood cluster type was associated with a four times higher risk of ICU admission, compared to the reference category of living in a homogeneous rural neighbourhood cluster type with average levels of deprivation under wave 1. Looking at disparities within each wave we found that residence in most affluent urban areas was at first associated with a slightly higher risk of ICU admission for COVID-19 as compared with the reference category of living in a homogeneous rural neighbourhood cluster type, but under waves 2 and 3 this risk was no longer statistically significant. The largest inequalities between different neighbourhood cluster types could be seen during the 1st wave. Over time, the risks converged between different neighbourhood cluster types.

Risk of atrial tachycardias after covid-19: nationwide self-controlled cases series and matched cohort study

Abstract Background COVID-19 is a multiorgan disease. We previously identified COVID-19 as a risk factor for myocardial infarction, stroke (1), venous thromboembolism and bleeding (2). Less evidence exists on the risk of arrhythmias after COVID-19. Previous studies included mainly hospitalized patients with severe COVID-19, and there are no nationwide studies published. Purpose The aim of this study was to estimate the risk of atrial tachycardias (atrial fibrillation and atrial flutter) following COVID-19, including all individuals tested positive for SARS-CoV-2 in Sweden, regardless of disease severity. Method COVID-19 has been a notifiable disease in Sweden. All individuals in Sweden who were tested positive for SARS-CoV-2 between February 1, 2020 and May 25, 2021 were included in the study. We identified four control individuals for each COVID-19 individual matched on age, sex, and county of residence. Using Personal Identification Numbers, we cross-linked data from national registries: COVID-19 registry; Inpatient and Outpatient Registry; Cause of Death Registry; Prescribed Pharmaceutical Registry and Intensive Care Registry. Outcomes are cardiovascular events, defined using ICD-10 diagnosis codes for atrial fibrillation and atrial flutter in the registries. We performed a ‘’first-ever event’’ analysis, i.e., we excluded individuals with events before the study period. The self-controlled case series (SCCS) method was used to determine the incidence rate ratio (IRR) of a first atrial tachycardia during the risk periods 1-7, 8-14, 15-30, 31-60, 61-90, and 91-180 days after COVID-19. In the matched cohort study (MCS), Poisson regression was performed to calculate the risk ratio (RR) of a first arrhythmia event in the risk period 1-30 days following COVID-19, after adjusting for the effect of confounders, such as cardiac disease, treatment with antiarrhythmics, comorbidities and vaccination status. Results 1 057 174 cases and 4 074 844 controls were included in the study. In the SCCS, the risk of first atrial tachycardia was significantly increased up to 60 days following COVID-19. Specifically, during days 1-7 and 8-14 post-COVID-19 the IRRs were approximately 12 and 10 respectively. Similarly, in the MCS the RR for the first atrial tachycardia during day 1-30 post-COVID-19 was approximately 11. The risks were higher in patients with more severe COVID-19; and during the first pandemic wave compared to the second and third wave. Conclusions This study suggests that COVID-19 is a risk factor for atrial tachycardias, based on information obtained on all people who tested positive for SARS-CoV-2 in Sweden, regardless of disease severity. These results could impact recommendations on diagnostic and prophylactic strategies against atrial tachycardias after COVID-19. The importance of preventive strategies, such as risk factor control; vaccination to prevent severe COVID-19; and early review of high-risk individuals after COVID-19, is indicated.Overview of the SCCS study design.Results of the SCCS- and MCS-studies.

Simplified Selvester QRS Score as an Infarct Size Parameter in STEMI Patients Undergoing Pharmacoinvasive or Primary Percutaneous Coronary Intervention

Background:Cardiovascular disease especially acute myocardial infarct (AMI) is one of the highest cause of mortality worldwide. Majority of AMI comes in the form of ST elevation myocardial infarct (STEMI) that requires timely diagnosis and revascularization management to restore myocardial circulation. The simple method to estimate infarct size is by using simplified Selvester QRS Score to electrocardiogram records, which is a tested method that have good correlation with gold standard, namely cardiac magnetic resonance imaging. &#x0D; Objectives : To investigate difference of infarct size with simplified Selvester QRS score parameter between STEMI patients undergoing pharmacoinvasive compared to primary PCI.&#x0D; Methods: Eighty-two STEMI patients, 41 of pharmacoinvasive and 41 of primary PCI was scored with simplified Selvester QRS score from electrocardiogram recording. Patient data are retroactively taken form Sardjito Cardiovascular Intensive Care (SCIENCE) registry. Scoring of simplified Selvester QRS Score was done by two experienced cardiologist blinded to patient procedure, and results then measured for interobserver agreement with Bland-Altman test. Comparison of QRS Score in pharmacoinvasive and primary PCI group was done with independent sample T test followed with multivariable linear regression test.&#x0D; Results: The means of simplified Selvester QRS score in pharmacoinvasive and primary PCI group is 7.240±3.015 and 8.900±4.188, p=0.043, respectively. Independent sample T test shows significant difference in the simplified Selvester QRS score in pharmacoinvasive and primary PCI group. The multivariable analysis shows that variables other than revascularization method independently influences QRS score are onset, anterior segment ST elevation and ST segment elevation in more &gt; 3 leads in electrocardiogram.&#x0D; Conclusion: There is significant difference in infarct size measured by simplified Selvester QRS score betweem STEMI patient undergoing pharmacoinvasive method compared to primary PCI procedure, which is lower in the pharmacoinvasive group

External validation of SAPS II score reported to the Norwegian Intensive Care and Pandemic Registry (NIPaR)

Background: Simplified Acute Physiology Score II (SAPS II) is a mortality prediction model widely usedto compensate for differences between intensive care units (ICU) in benchmarking and research. Accuracyof SAPS II is sparsely documented. We investigate accuracy by comparing patient journal SAPS II valueswith registry SAPS II values in the Norwegian Intensive Care and Pandemic Registry (NIPaR).Method: NIPaR personnel collected data from the patient journal during visitations to ICUs in ten differenthospitals between 2017 and 2022 while blinded for registry SAPS II data. The patient journal SAPS II valueswere subsequently compared with the registry SAPS II values.Results: Difference of means for SAPS II score between patient journal and registry data was 5.2 points(95% CI 2.8–7.6; p &lt; 0.001). SAPS II score depended significantly on ICU (p &lt; 0.001) and data origin (p =0.006), whereas the interaction term for these two variables was not significant.Conclusion: We find low accuracy of SAPS II score in a registry setting.

Risk of malignant disease in 1-year sepsis survivors, a registry-based nationwide follow-up study

BackgroundCancer and sepsis share risk factors, and sepsis patients may have impaired immune response and increased morbidity long after intensive care. This study aimed to assess whether sepsis survivors are at increased risk for cancer. Our objective was to assess the incidence of new cancer in 1-year sepsis survivors and test the hypothesis that it is higher than that of the general population.MethodsWe obtained data on ICU admissions of adult patients from Swedish Intensive care registry (SICR) from 2005 to 2017. We included patients with an explicit ICD-10 code for sepsis for the primary ICU admission. We obtained data on cancer diagnoses (2001–2018), death (2005–2018) and emigration (2005–2018) from Cancer and Cause of death and National Patient Registry databases of the National Board of Health and Welfare; age and sex-specific cancer incidence rates in Sweden from NORDCAN registry from 2006 to 2018. One-year survivors formed the final cohort, that was followed for new cancer diagnoses until death, emigration, or end of 2018, whichever came first. The main outcome measure was standardized incidence rate ratio (SIR) to compare the incidence of cancer in 1-year sepsis survivors to that in the general population (NORDCAN). We also performed several sensitivity analyses.ResultsIn a cohort of 18,550 1-year survivors, 75,427 person years accumulated during a median follow-up (FU) of 3.36 years (IQR 1.72–5.86), 6366 (34.3%) patients died, and 1625 (8.8%) patients were diagnosed with a new cancer after a median FU of 2.51 (IQR 1.09–4.48) years. The incidence ratio of any new cancer over the whole FU was 1.31 (95% CI 1.23–1.40) for men and 1.74 (95% CI 1.61–1.88) for women. The difference in incidence rates persisted in several sensitivity analyses. The SIRs were highest in cancers of gastrointestinal tract, genital organs, and skin.Conclusion and relevanceCompared to general population, incidence of cancer is increased in 1-year sepsis survivors. Variation in the findings depending on follow-up time suggests that factors other than sepsis alone are involved. Surveillance for malignant disease may be warranted in sepsis survivors.Graphical abstract

Prior physical illness predicts death better than acute physiological derangement on intensive care unit admission in COVID-19: A Swedish registry study.

COVID-19 is associated with prolonged intensive care unit (ICU) stay and considerable mortality. The onset of persistent critical illness, defined as when prior illness predicts death better than acute physiological derangement, has not been studied in COVID-19. This national cohort study based on the Swedish Intensive Care Registry (SIR) included all patients admitted to a Swedish ICU due to COVID-19 from 6 March 2020 to 9 November 2021. Simplified Acute Physiology Score-3 (SAPS3) Box 1 was used as a measure of prior illness and Box 3 as a measure of acute derangement to evaluate the onset and importance of persistent critical illness in COVID-19. To compare predictive capacity, the area under receiver operating characteristic (AUC) of SAPS3 and its constituent Box 1 and 3 was calculated for 30-day mortality. In 7 969 patients, of which 1 878 (23.6%) died within 30 days of ICU admission, the complete SAPS3 score had acceptable discrimination: AUC 0.75 (95% CI 0.74 to 0.76) but showed under prediction in low-risk patients and over prediction in high-risk patients. SAPS3 Box 1 showed markedly better discrimination than Box 3 (AUC 0.74 vs 0.65, P<0,0001). Using custom logistic models, the difference in predictive performance of prior and acute illness was validated, AUC 0.76 vs AUC 0.69, p<0.0001. Prior physical illness predicts death in COVID-19 better than acute physiological derangement during ICU stay, and the whole SAPS3 score is not significantly better than just prior illness. The results suggests that COVID-19 may exhibit similarities to persistent critical illness immediately from ICU admission, potentially because of long median ICU length-of-stay. Alternatively, the variables in the acute physiological derangement model may not adequately capture the severity of illness in COVID-19.

Trends in Childhood Oncology Admissions to ICUs in Australia and New Zealand.

There are few robust, national-level reports of contemporary trends in pediatric oncology admissions, resource use, and mortality. We aimed to describe national-level data on trends in intensive care admissions, interventions, and survival for children with cancer. Cohort study using a binational pediatric intensive care registry. Australia and New Zealand. Patients younger than 16 years, admitted to an ICU in Australia or New Zealand with an oncology diagnosis between January 1, 2003, and December 31, 2018. None. We examined trends in oncology admissions, ICU interventions, and both crude and risk-adjusted patient-level mortality. Eight thousand four hundred ninety admissions were identified for 5,747 patients, accounting for 5.8% of PICU admissions. Absolute and population-indexed oncology admissions increased from 2003 to 2018, and median length of stay increased from 23.2 hours (interquartile range [IQR], 16.8-62 hr) to 38.8 hours (IQR, 20.9-81.1 hr) ( p < 0.001). Three hundred fifty-seven of 5,747 patients died (6.2%). There was a 45% reduction in risk-adjusted ICU mortality, which reduced from 3.3% (95% CI, 2.1-4.4) in 2003-2004 to 1.8% (95% CI, 1.1-2.5%) in 2017-2018 ( p trend = 0.02). The greatest reduction in mortality seen in hematological cancers and in nonelective admissions. Mechanical ventilation rates were unchanged from 2003 to 2018, while the use of high-flow nasal prong oxygen increased (incidence rate ratio, 2.43; 95% CI, 1.61-3.67 per 2 yr). In Australian and New Zealand PICUs, pediatric oncology admissions are increasing steadily and such admissions are staying longer, representing a considerable proportion of ICU activity. The mortality of children with cancer who are admitted to ICU is low and falling.

The Nordic perioperative and intensive care registries-Collaboration and research possibilities.

The Nordic perioperative and intensive care registries have been built up during the last 25 years to improve quality in intensive and perioperative care. We aimed to describe the Nordic perioperative and intensive care registries and to highlight possibilities and challenges in future research collaboration between these registries. We present an overview of the following Nordic registries: Swedish Perioperative Registry (SPOR), the Danish Anesthesia Database (DAD), the Finnish Perioperative Database (FIN-AN), the Icelandic Anesthesia Database (IS-AN), the Danish Intensive Care Database (DID), the Swedish Intensive Care Registry (SIR), the Finnish Intensive Care Consortium, the Norwegian Intensive Care and Pandemic Registry (NIPaR), and the Icelandic Intensive Care Registry (IS-ICU). Health care systems and patient populations are similar in the Nordic countries. Despite certain differences in data structure and clinical variables, the perioperative and intensive care registries have enough in common to enable research collaboration. In the future, even a common Nordic registry could be possible. Collaboration between the Nordic perioperative and intensive care registries is both possible and likely to produce research of high quality. Research collaboration between registries may have several add-on effects and stimulate international standardization regarding definitions, scoring systems, and benchmarks, thereby improving overall quality of care.

Initial fluid resuscitation guided by the Parkland formula leads to high fluid volumes in the first 72 h, increasing mortality and the risk for kidney injury

BackgroundOur Burn center has used the Parkland formula (4 ml/kg/TBSA%) adjusted by physiological parameters to guide fluid resuscitation in burn patients. Our main objective was to examine fluid resuscitation in patients with major burn injury and its effect on mortality, need for renal replacement therapy (RRT) and the length of stay (LOS) in the Intensive Care Unit (ICU). Further aims were to determine which factors were associated with fluid resuscitation volumes during the first 24 h, and whether these fluid volumes had an association with the volumes infused during the next 48 h. MethodsThis retrospective observational study accrued patients (N = 46) admitted to the Helsinki Burn Center between 2016 and 2018 with burn injuries ≥ 20% TBSA. The national intensive care registry and the electronic patient record system provided data on fluid infusions, urine output, laboratory measurements, presence of inhalation injury, surgical procedures within 72 h from injury, patient demographics, need for renal replacement therapy and mortality. Patients were divided into groups based on infused fluid volumes and univariate regressions were performed to identify factors associated with fluid volumes. Results48% of the patients received fluids more than 6 ml/kg/TBSA% during the first 24 h. 35% of the patients received fluid volumes exceeding the Ivy index (250 ml/kg/d) and was associated with higher TBSA%, SOFA and SAPS scores as well as increased mortality and need for RRT. Higher lactate and lower base excess were associated with higher fluid volumes. Urine output had no association with the resuscitation volumes. Larger resuscitation volumes during the first 24 h were associated with larger fluid volumes given also during the next 48 h. Higher cumulative fluid volume in 0–72 h resulted in increased need of RRT and higher ICU mortality. ConclusionUsing the Parkland formula and adjusting the infusion based on physiological parameters leads to over resuscitation in many of the patients. It seems that the more fluids are given during the initial resuscitation phase, the more fluids are also administered during the subsequent phase. Higher cumulative fluid volumes are associated with RRT requirements and higher mortality. We postulate that starting fluid resuscitation with a lower infusion rate could be beneficial, as it may lead to smaller cumulative fluid volumes during the first 72 h, leading to reduced mortality and kidney injury.

A first-level customization study of SAPS II with Norwegian Intensive Care and Pandemic Registry (NIPaR) data.

Severity scores and mortality prediction models (MPMs) are important tools for benchmarking and stratification in the intensive care unit (ICU) and need to be regularly updated using data from a local and contextual cohort. Simplified acute physiology score II (SAPS II) is widely used in European ICUs. A first-level customization was performed on the SAPS II model using data from the Norwegian Intensive Care and Pandemic Registry (NIPaR). Two previous SAPS II models (Model A: the original SAPS II model and Model B: a SAPS II model based on NIPaR data from 2008 to 2010) were compared to the new Model C. Model C was based on patients from 2018 to 2020 (corona virus disease 2019 patients omitted; n=43,891), and its performances (calibration, discrimination, and uniformity of fit) compared to the previous models (Model A and Model B). Model C was better calibrated than Model A with a Brier score 0.132 (95% confidence interval 0.130-0.135) versus 0.143 (95% confidence interval 0.141-0.146). The Brier score for Model B was 0.133 (95% confidence interval 0.130-0.135). In the Cox's calibration regression and for both Model C and Model B but not for Model A. Uniformity of fit was similar for Model B and for Model C, both better than for Model A, across age groups, sex, length of stay, type of admission, hospital category, and days on respirator. The area under the receiver operating characteristic curve was 0.79 (95% confidence interval 0.79-0.80), showing acceptable discrimination. The observed mortality and corresponding SAPS II scores have significantly changed during the last decades and an updated MPM is superior to the original SAPS II. However, proper external validation is required to confirm our findings. Prediction models need to be regularly customized using local datasets in order to optimize their performances.

Thirty years of ANZICS CORE: A clinical quality success story

In 2023, the Australian and New Zealand Intensive Care Society (ANZICS) Registry run by the Centre for Outcomes and Resources Evaluation (CORE) turns 30 years old. It began with the Adult Patient Database, the Australian and New Zealand Paediatric Intensive Care Registry, and the Critical Care Resources Registry, and it now includes Central Line Associated Bloodstream Infections Registry, the Extra-Corporeal Membrane Oxygenation Database, and the Critical Health Resources Information System. The ANZICS Registry provides comparative case-mix reports, risk-adjusted clinical outcomes, process measures, and quality of care indicators to over 200 intensive care units describing more than 200 000 adult and paediatric admissions annually. The ANZICS CORE outlier management program has been a major contributor to the improved patient outcomes and provided significant cost savings to the healthcare sector. Over 200 peer-reviewed papers have been published using ANZICS Registry data. The ANZICS Registry was a vital source of information during the COVID-19 pandemic. Upcoming developments include reporting of long-term survival and patient-reported outcome and experience measures.