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- Howells, Tim, et al.
(författare)
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Optimal Cerebral Perfusion Pressure in Centers With Different Treatment Protocols
- 2018
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Ingår i: Critical Care Medicine. - : LIPPINCOTT WILLIAMS & WILKINS. - 0090-3493 .- 1530-0293. ; 46:3, s. e235-e241
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: The three centers in this study have different policies regarding cerebral perfusion pressure targets and use of vasopressors in traumatic brain injury patients. The aim was to determine if the different policies affected the estimation of cerebral perfusion pressure which optimizes the strength of cerebral autoregulation, termed "optimal cerebral perfusion pressure." Design: Retrospective analysis of prospectively collected data. Setting: Three neurocritical care units at university hospitals in Cambridge, United Kingdom, Groningen, the Netherlands, and Uppsala, Sweden. Patients: A total of 104 traumatic brain injury patients were included: 35 each from Cambridge and Groningen, and 34 from Uppsala. Interventions: None. Measurements and Main Results: In Groningen, the cerebral perfusion pressure target was greater than or equal to 50 and less than 70mm Hg, in Uppsala greater than or equal to 60, and in Cambridge greater than or equal to 60 or preferably greater than or equal to 70. Despite protocol differences, median cerebral perfusion pressure for each center was above 70mm Hg. Optimal cerebral perfusion pressure was calculated as previously published and implemented in the Intensive Care Monitoring+ software by the Cambridge group, now replicated in the Odin software in Uppsala. Periods with cerebral perfusion pressure above and below optimal cerebral perfusion pressure were analyzed, as were absolute difference between cerebral perfusion pressure and optimal cerebral perfusion pressure and percentage of monitoring time with a valid optimal cerebral perfusion pressure. Uppsala had the highest cerebral perfusion pressure/optimal cerebral perfusion pressure difference. Uppsala patients were older than the other centers, and age is positively correlated with cerebral perfusion pressure/optimal cerebral perfusion pressure difference. Optimal cerebral perfusion pressure was significantly lower in Groningen than in Cambridge. There were no significant differences in percentage of monitoring time with valid optimal cerebral perfusion pressure. Summary optimal cerebral perfusion pressure curves were generated for the combined patient data for each center. These summary curves could be generated for Groningen and Cambridge, but not Uppsala. The older age of the Uppsala patient cohort may explain the absence of a summary curve. Conclusions: Differences in optimal cerebral perfusion pressure calculation were found between centers due to demographics (age) and treatment (cerebral perfusion pressure targets). These factors should be considered in the design of trials to determine the efficacy of autoregulation-guided treatment.
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| 2. |
- Huijben, Jilske A., et al.
(författare)
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Development of a quality indicator set to measure and improve quality of ICU care for patients with traumatic brain injury
- 2019
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Ingår i: Critical Care. - : BioMed Central. - 1364-8535 .- 1466-609X. ; 23
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Tidskriftsartikel (refereegranskat)abstract
- Background: We aimed to develop a set of quality indicators for patients with traumatic brain injury (TBI) in intensive care units (ICUs) across Europe and to explore barriers and facilitators for implementation of these quality indicators.Methods: A preliminary list of 66 quality indicators was developed, based on current guidelines, existing practice variation, and clinical expertise in TBI management at the ICU. Eight TBI experts of the Advisory Committee preselected the quality indicators during a first Delphi round. A larger Europe-wide expert panel was recruited for the next two Delphi rounds. Quality indicator definitions were evaluated on four criteria: validity (better performance on the indicator reflects better processes of care and leads to better patient outcome), feasibility (data are available or easy to obtain), discriminability (variability in clinical practice), and actionability (professionals can act based on the indicator). Experts scored indicators on a 5-point Likert scale delivered by an electronic survey tool.Results. The expert panel consisted of 50 experts from 18 countries across Europe, mostly intensivists (N=24, 48%) and neurosurgeons (N=7, 14%). Experts agreed on a final set of 42 indicators to assess quality of ICU care: 17 structure indicators, 16 process indicators, and 9 outcome indicators. Experts are motivated to implement this finally proposed set (N=49, 98%) and indicated routine measurement in registries (N=41, 82%), benchmarking (N=42, 84%), and quality improvement programs (N=41, 82%) as future steps. Administrative burden was indicated as the most important barrier for implementation of the indicator set (N=48, 98%).Conclusions: This Delphi consensus study gives insight in which quality indicators have the potential to improve quality of TBI care at European ICUs. The proposed quality indicator set is recommended to be used across Europe for registry purposes to gain insight in current ICU practices and outcomes of patients with TBI. This indicator set may become an important tool to support benchmarking and quality improvement programs for patients with TBI in the future.
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| 3. |
- Zeiler, Frederick Adam, et al.
(författare)
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Statistical cerebrovascular reactivity signal properties after secondary decompressive craniectomy in traumatic brain injury : A CENTER-TBI pilot analysis
- 2020
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Ingår i: Journal of Neurotrauma. - : Mary Ann Liebert. - 0897-7151 .- 1557-9042. ; 37:11, s. 1306-1314
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Tidskriftsartikel (refereegranskat)abstract
- Decompressive craniectomy (DC) in traumatic brain injury (TBI) has been suggested to influence cerebrovascular reactivity. We aimed to determine if the statistical properties of vascular reactivity metrics and slow-wave relationships were impacted after DC, as such information would allow us to comment on whether vascular reactivity monitoring remains reliable after craniectomy. Using the CENTER-TBI high-resolution intensive care unit (ICU) cohort, we selected those secondary DC patients with high-frequency physiologic data for both: at least 24 hours before DC, and more than 48 hours post-DC. Data for all physiology measures was separated into: the 24 hours before DC, the first 48 hours post DC, and beyond 48 hours post-DC. We produced slow-wave data sheets for intra-cranial pressure (ICP) and mean arterial pressure (MAP) per patient. We also derived pressure reactivity index (PRx) as continuous cerebrovascular reactivity metrics updated every minute. The time-series behavior of PRx was modeled for each time period per patient. Finally, the relationship between ICP and MAP during these 3 time periods was assessed using time-series vector autoregressive integrative moving average (VARIMA) models, impulse response function (IRF) plots, and Granger causality testing. Ten patients were included in this study. Mean PRx and proportion of time above PRx thresholds were not affected by craniectomy. Similarly, PRx time-series structure was not affected by DC, when assessed in each individual patient. This was confirmed with Granger causality testing, and VARIMA IRF plotting for the MAP/ICP slow-wave relationship. PRx metrics and statistical time-series behavior appears not to be substantially influenced by DC. Similarly, there is little change in the relationship between slow-waves of ICP and MAP before and after DC. This may suggest that cerebrovascular reactivity monitoring in the setting of DC may still provide valuable information regarding autoregulation. Keywords: cerebrovascular reactivity, decompressive craniectomy, DC, PRx, TBI.
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