34 research outputs found

    Impact of cardiac surgery and neurosurgery patients on variation in severity-adjusted resource use in intensive care units

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    Publisher Copyright: © 2022Purpose: The resource use of cardiac surgery and neurosurgery patients likely differ from other ICU patients. We evaluated the relevance of these patient groups on overall ICU resource use. Methods: Secondary analysis of 69,862 patients in 17 ICUs in Finland, Estonia, and Switzerland in 2015–2017. Direct costs of care were allocated to patients using daily Therapeutic Intervention Scoring System (TISS) scores and ICU length of stay (LOS). The ratios of observed to severity-adjusted expected resource use (standardized resource use ratios; SRURs), direct costs and outcomes were assessed before and after excluding cardiac surgery or cardiac and neurosurgery. Results: Cardiac surgery and neurosurgery, performed only in university hospitals, represented 22% of all ICU admissions and 15–19% of direct costs. Cardiac surgery and neurosurgery were excluded with no consistent effect on SRURs in the whole cohort, regardless of cost separation method. Excluding cardiac surgery or cardiac surgery plus neurosurgery had highly variable effects on SRURs of individual university ICUs, whereas the non-university ICU SRURs decreased. Conclusions: Cardiac and neurosurgery have major effects on the cost structure of multidisciplinary ICUs. Extending SRUR analysis to patient subpopulations facilitates comparison of resource use between ICUs and may help to optimize resource allocation.Peer reviewe

    Variation in Severity-Adjusted Resource use and Outcome for Neurosurgical Emergencies in the Intensive Care Unit.

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    BACKGROUND The correlation between the standardized resource use ratio (SRUR) and standardized hospital mortality ratio (SMR) for neurosurgical emergencies is not known. We studied SRUR and SMR and the factors affecting these in patients with traumatic brain injury (TBI), nontraumatic intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). METHODS We extracted data of patients treated in six university hospitals in three countries (2015-2017). Resource use was measured as SRUR based on purchasing power parity-adjusted direct costs and either intensive care unit (ICU) length of stay (costSRURlength of stay) or daily Therapeutic Intervention Scoring System scores (costSRURTherapeutic Intervention Scoring System). Five a priori defined variables reflecting differences in structure and organization between the ICUs were used as explanatory variables in bivariable models, separately for the included neurosurgical diseases. RESULTS Out of 28,363 emergency patients treated in six ICUs, 6,162 patients (22%) were admitted with a neurosurgical emergency (41% nontraumatic ICH, 23% SAH, 13% multitrauma TBI, and 23% isolated TBI). The mean costs for neurosurgical admissions were higher than for nonneurosurgical admissions, and the neurosurgical admissions corresponded to 23.6-26.0% of all direct costs related to ICU emergency admissions. A higher physician-to-bed ratio was associated with lower SMRs in the nonneurosurgical admissions but not in the neurosurgical admissions. In patients with nontraumatic ICH, lower costSRURs were associated with higher SMRs. In the bivariable models, independent organization of an ICU was associated with lower costSRURs in patients with nontraumatic ICH and isolated/multitrauma TBI but with higher SMRs in patients with nontraumatic ICH. A higher physician-to-bed ratio was associated with higher costSRURs for patients with SAH. Larger units had higher SMRs for patients with nontraumatic ICH and isolated TBI. None of the ICU-related factors were associated with costSRURs in nonneurosurgical emergency admissions. CONCLUSIONS Neurosurgical emergencies constitute a major proportion of all emergency ICU admissions. A lower SRUR was associated with higher SMR in patients with nontraumatic ICH but not for the other diagnoses. Different organizational and structural factors seemed to affect resource use for the neurosurgical patients compared with nonneurosurgical patients. This emphasizes the importance of case-mix adjustment when benchmarking resource use and outcomes

    Mortality prediction in intensive care units including premorbid functional status improved performance and internal validity

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    Objective: Prognostic models are key for benchmarking intensive care units (ICUs). They require up-to-date predictors and should report transportability properties for reliable predictions. We developed and validated an in-hospital mortality risk prediction model to facilitate benchmarking, quality assurance, and health economics evaluation. Study Design and Setting: We retrieved data from the database of an international (Finland, Estonia, Switzerland) multicenter ICU cohort study from 2015 to 2017. We used a hierarchical logistic regression model that included age, a modified Simplified Acute Physiology Score-II, admission type, premorbid functional status, and diagnosis as grouping variable. We used pooled and meta-analytic cross-validation approaches to assess temporal and geographical transportability. Results: We included 61,224 patients treated in the ICU (hospital mortality 10.6%). The developed prediction model had an area under the receiver operating characteristic curve 0.886, 95% confidence interval (CI) 0.882-0.890; a calibration slope 1.01, 95% CI (0.99-1.03); a mean calibration -0.004, 95% CI (-0.035 to 0.027). Although the model showed very good internal validity and geographic discrimination transportability, we found substantial heterogeneity of performance measures between ICUs (I-squared: 53.4-84.7%). Conclusion: A novel framework evaluating the performance of our prediction model provided key information to judge the validity of our model and its adaptation for future use. (c) 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license ( http:// creativecommons.org/ licenses/ by/ 4.0/ )Peer reviewe

    Variation in severity-adjusted resource use and outcome in intensive care units

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    Purpose Intensive care patients have increased risk of death and their care is expensive. We investigated whether risk-adjusted mortality and resources used to achieve survivors change over time and if their variation is associated with variables related to intensive care unit (ICU) organization and structure. Methods Data of 207,131 patients treated in 2008-2017 in 21 ICUs in Finland, Estonia and Switzerland were extracted from a benchmarking database. Resource use was measured using ICU length of stay, daily Therapeutic Intervention Scoring System Scores (TISS) and purchasing power parity-adjusted direct costs (2015-2017; 17 ICUs). The ratio of observed to severity-adjusted expected resource use (standardized resource use ratio; SRUR) was calculated. The number of expected survivors and the ratio of observed to expected mortality (standardized mortality ratio; SMR) was based on a mortality prediction model covering 2015-2017. Fourteen a priori variables reflecting structure and organization were used as explanatory variables for SRURs in multivariable models. Results SMR decreased over time, whereas SRUR remained unchanged, except for decreased TISS-based SRUR. Direct costs of one ICU day, TISS score and ICU admission varied between ICUs 2.5-5-fold. Differences between individual ICUs in both SRUR and SMR were up to > 3-fold, and their evolution was highly variable, without clear association between SRUR and SMR. High patient turnover was consistently associated with low SRUR but not with SMR. Conclusion The wide and independent variation in both SMR and SRUR suggests that they should be used together to compare the performance of different ICUs or an individual ICU over time.Peer reviewe

    Mean arterial pressure and vasopressor load after out-of-hospital cardiac arrest : Associations with one-year neurologic outcome

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    The aim of the study: There are limited data on blood pressure targets and vasopressor use following cardiac arrest. We hypothesized that hypotension and high vasopressor load are associated with poor neurological outcome following out-of-hospital cardiac arrest (OHCA). Methods: We included 412 patients with OHCA included in FINNRESUSCI study conducted between 2010 and 2011. Hemodynamic data and vasopressor doses were collected electronically in one, two or five minute intervals. We evaluated thresholds for time-weighted (TW) mean arterial pressure (MAP) and outcome by receiver operating characteristic (ROC) curve analysis, and used multivariable analysis adjusting for co-morbidities, factors at resuscitation, an illness severity score, TW MAP and total vasopressor load (VL) to test associations with one-year neurologic outcome, dichotomized into either good (1-2) or poor (3-5) according to the cerebral performance category scale. Results: Of 412 patients, 169 patients had good and 243 patients had poor one-year outcomes. The lowest MAP during the first six hours was 58 (inter-quartile range [IQR] 56-61) mmHg in those with a poor outcome and 61 (59-63) mmHg in those with a good outcome (p <0.01), and lowest MAP was independently associated with poor outcome (OR 1.02 per mmHg, 95% CI 1.00-1.04, p = 0.03). During the first 48h the median (IQR) of the 1W mean MAP was 80 (78-82) mmHg in patients with poor, and 82 (81-83) mmHg in those with good outcomes (p=0.03) but in multivariable analysis TWA MAP was not associated with outcome. Vasopressor load did not predict one-year neurologic outcome. Conclusions: Hypotension occurring during the first six hours after cardiac arrest is an independent predictor of poor one-year neurologic outcome. High vasopressor load was not associated with poor outcome and further randomized trials are needed to define optimal MAP targets in OHCA patients. (C) 2016 Elsevier Ireland Ltd. All rights reserved.Peer reviewe

    Common Inflammation-Related Candidate Gene Variants and Acute Kidney Injury in 2647 Critically Ill Finnish Patients

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    Acute kidney injury (AKI) is a syndrome with high incidence among the critically ill. Because the clinical variables and currently used biomarkers have failed to predict the individual susceptibility to AKI, candidate gene variants for the trait have been studied. Studies about genetic predisposition to AKI have been mainly underpowered and of moderate quality. We report the association study of 27 genetic variants in a cohort of Finnish critically ill patients, focusing on the replication of associations detected with variants in genes related to inflammation, cell survival, or circulation. In this prospective, observational Finnish Acute Kidney Injury (FINNAKI) study, 2647 patients without chronic kidney disease were genotyped. We defined AKI according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria. We compared severe AKI (Stages 2 and 3, n = 625) to controls (Stage 0, n = 1582). For genotyping we used iPLEX(TM) Assay (Agena Bioscience). We performed the association analyses with PLINK software, using an additive genetic model in logistic regression. Despite the numerous, although contradictory, studies about association between polymorphisms rs1800629 in TNFA and rs1800896 in IL10 and AKI, we found no association (odds ratios 1.06 (95% CI 0.89-1.28, p = 0.51) and 0.92 (95% CI 0.80-1.05, p = 0.20), respectively). Adjusting for confounders did not change the results. To conclude, we could not confirm the associations reported in previous studies in a cohort of critically ill patients.Peer reviewe

    Heme oxygenase-1 repeat polymorphism in septic acute kidney injury

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    Acute kidney injury (AKI) is a syndrome that frequently affects the critically ill. Recently, an increased number of dinucleotide repeats in the HMOX1 gene were reported to associate with development of AKI in cardiac surgery. We aimed to test the replicability of this finding in a Finnish cohort of critically ill septic patients. This multicenter study was part of the national FINNAKI study. We genotyped 300 patients with severe AKI (KDIGO 2 or 3) and 353 controls without AKI (KDIGO 0) for the guanine-thymine (GTn) repeat in the promoter region of the HMOX1 gene. The allele calling was based on the number of repeats, the cut off being 27 repeats in the S-L (short to long) classification, and 27 and 34 repeats for the S-M-L2 (short to medium to very long) classification. The plasma concentrations of heme oxygenase-1 (HO-1) enzyme were measured on admission. The allele distribution in our patients was similar to that published previously, with peaks at 23 and 30 repeats. The S-allele increases AKI risk. An adjusted OR was 1.30 for each S-allele in an additive genetic model (95% CI 1.01-1.66; p = 0.041). Alleles with a repeat number greater than 34 were significantly associated with lower HO-1 concentration (p<0.001). In septic patients, we report an association between a short repeat in HMOX1 and AKI risk

    Effect of mortality prediction models on resource use benchmarking of intensive care units.

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    PURPOSE Intensive care requires extensive resources. The ICUs' resource use can be compared using standardized resource use ratios (SRURs). We assessed the effect of mortality prediction models on the SRURs. MATERIALS AND METHODS We compared SRURs using different mortality prediction models: the recent Finnish Intensive Care Consortium (FICC) model and the SAPS-II model (n = 68,914 admissions). We allocated the resources to severity of illness strata using deciles of predicted mortality. In each risk and year stratum, we calculated the expected resource use per survivor from our modelling approaches using length of ICU stay and Therapeutic Intervention Scoring System (TISS) points. RESULTS Resource use per survivor increased from one length of stay (LOS) day and around 50 TISS points in the first decile to 10 LOS-days and 450 TISS in the tenth decile for both risk scoring systems. The FICC model predicted mortality risk accurately whereas the SAPS-II grossly overestimated the risk of death. Despite this, SRURs were practically identical and consistent. CONCLUSIONS SRURs provide a robust tool for benchmarking resource use within and between ICUs. SRURs can be used for benchmarking even if recently calibrated risk scores for the specific population are not available
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