| 1. |
- Blennow Nordström, Erik, et al.
(författare)
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Serum neurofilament light levels are correlated to long-term neurocognitive outcome measures after cardiac arrest
- 2022
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Ingår i: Brain Injury. - : Informa UK Limited. - 0269-9052 .- 1362-301X. ; 36:6, s. 800-809
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Tidskriftsartikel (refereegranskat)abstract
- Objective To explore associations between four methods assessing long-term neurocognitive outcome after out-of-hospital cardiac arrest and early hypoxic-ischemic neuronal brain injury assessed by the biomarker serum neurofilament light (NFL), and to compare the agreement for the outcome methods. Methods An explorative post-hoc study was conducted on survivor data from the international Target Temperature Management after Out-of-hospital Cardiac Arrest trial, investigating serum NFL sampled 48/72-hours post-arrest and neurocognitive outcome 6 months post-arrest. Results Among the long-term surviving participants (N = 457), serum NFL (n = 384) was associated to all outcome instruments, also when controlling for demographic and cardiovascular risk factors. Associations between NFL and the patient-reported Two Simple Questions (TSQ) were however attenuated when adjusting for vitality and mental health. NFL predicted results on the outcome instruments to varying degrees, with an excellent area under the curve for the clinician-report Cerebral Performance Category (CPC 1-2: 0.90). Most participants were classified as CPC 1 (79%). Outcome instrument correlations ranged from small (Mini-Mental State Examination [MMSE]-TSQ) to strong (CPC-MMSE). Conclusions The clinician-reported CPC was mostly related to hypoxic-ischemic brain injury, but with a ceiling effect. These results may be useful when selecting methods and instruments for clinical follow-up models.
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| 2. |
- Ebner, Florian, et al.
(författare)
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Serum GFAP and UCH-L1 for the prediction of neurological outcome in comatose cardiac arrest patients
- 2020
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Ingår i: Resuscitation. - : Elsevier BV. - 0300-9572. ; 154, s. 61-68
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Neurological outcome prediction is crucial early after cardiac arrest. Serum biomarkers released from brain cells after hypoxic-ischaemic injury may aid in outcome prediction. The only serum biomarker presently recommended in the European Resuscitation Council prognostication guidelines is neuron-specific enolase (NSE), but NSE has limitations. In this study, we therefore analyzed the outcome predictive accuracy of the serum biomarkers glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase-L1 (UCH-L1) in patients after cardiac arrest. Methods: Serum GFAP and UCH-L1 were collected at 24, 48 and 72 h after cardiac arrest. The primary outcome was neurological function at 6-month follow-up assessed by the cerebral performance category scale (CPC), dichotomized into good (CPC1-2) and poor (CPC3-5). Prognostic accuracies were tested with receiver-operating characteristics by calculating the area under the receiver-operating curve (AUROC) and compared to the AUROC of NSE. Results: 717 patients were included in the study. GFAP and UCH-L1 discriminated between good and poor neurological outcome at all time-points when used alone (AUROC GFAP 0.88–0.89; UCH-L1 0.85–0.87) or in combination (AUROC 0.90–0.91). The combined model was superior to GFAP and UCH-L1 separately and NSE (AUROC 0.75–0.85) at all time-points. At specificities ≥95%, the combined model predicted poor outcome with a higher sensitivity than NSE at 24 h and with similar sensitivities at 48 and 72 h. Conclusion: GFAP and UCH-L1 predicted poor neurological outcome with high accuracy. Their combination may be of special interest for early prognostication after cardiac arrest where it performed significantly better than the currently recommended biomarker NSE.
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| 3. |
- Grindegård, Linnéa, et al.
(författare)
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Association Between EEG Patterns and Serum Neurofilament Light After Cardiac Arrest: A Post Hoc Analysis of the TTM Trial.
- 2022
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Ingår i: Neurology. - 1526-632X .- 0028-3878. ; 98:24
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Tidskriftsartikel (refereegranskat)abstract
- Electroencephalography (EEG) is widely used for prediction of neurological outcome after cardiac arrest. To better understand the relationship between EEG and neuronal injury, we explore the association between EEG and neurofilament light (NFL) as a marker of neuroaxonal injury. We evaluate whether highly malignant EEG patterns are reflected by high NFL levels. Additionally, we explore the association of EEG backgrounds and EEG discharges with NFL.Post-hoc analysis of the Target Temperature Management after out-of-hospital cardiac arrest (TTM)-trial. Routine EEGs were prospectively performed after the temperature intervention ≥36 hours post-arrest. Patients who awoke or died prior to 36 hours post-arrest were excluded. EEG-experts blinded to clinical information classified EEG background, amount of discharges and highly malignant EEG patterns according to the standardized American Clinical Neurophysiology Society terminology. Prospectively collected serum samples were analyzed for NFL after trial completion. The highest available concentration at 48 or 72-hours post-arrest was used.262/939 patients with EEG and NFL data were included. Patients with highly malignant EEG patterns had 2.9 times higher NFL levels than patients with malignant patterns and NFL levels were 13 times higher in patients with malignant patterns than those with benign patterns (95% CI: 1.4-6.1 and 6.5-26.2 respectively, effect size 0.47, p<0.001). Both background and the amount of discharges were independently strongly associated with NFL levels (p<0.001). The EEG background had a stronger association with NFL levels than EEG discharges (R2=0.30 and R2=0.10, respectively). NFL levels in patients with a continuous background were lower than for any other background (95% CI for discontinuous, burst-suppression and suppression, respectively: 2.26-18.06, 3.91-41.71 and 5.74-41.74, effect size 0.30 and p<0.001 for all). NFL levels did not differ between suppression and burst-suppression. Superimposed discharges were only associated with higher NFL levels if the EEG background was continuous.Benign, malignant, and highly malignant EEG patterns reflect the extent of brain injury as measured by NFL in serum. The extent of brain injury is more strongly related to the EEG background than superimposed discharges. Combining EEG and NFL may be useful to better identify patients misclassified by single methods.clinicaltrials.gov, NCT01020916.
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| 4. |
- Lindh-Rengifo, Magnus, et al.
(författare)
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Components of gait in people with and without mild cognitive impairment
- 2022
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Ingår i: Gait & Posture. - : Elsevier BV. - 0966-6362. ; 93, s. 83-89
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Tidskriftsartikel (refereegranskat)abstract
- Background: Several objective gait parameters are associated with cognitive impairment, but there is limitedknowledge of gait models in people with mild cognitive impairment (MCI).Research question: How can 18 objective gait characteristics be used to define different components of gait inpeople with MCI (with suspected incipient neurocognitive disorder) and cognitively unimpaired people (CU),respectively?Methods: Spatiotemporal gait data were collected by using an electronic walkway (GAITRite®), i.e. assessmentsin comfortable gait speed. Using cross-sectional gait data, two principal component analyses (PCA) were performed(varimax rotation) to define different components of gait in people with MCI (n = 114) and CU (n = 219),respectively, from the BioFINDER-2 study.Results: Both PCAs produced four components, here called Variability, Pace/Stability, Rhythm and Asymmetry.Total variance explained was 81.0% (MCI) versus 80.3% (CU). The Variability component explained the largestamount of variance (about 25%) in both groups. The highest loading gait parameter was the same for bothgroups in three out of four components, i.e. step velocity variability (Variability), mean step length (Pace/Stability)and mean step time (Rhythm). In the asymmetry component, stance time asymmetry (MCI) and swingtime asymmetry (CU) loaded the highest.Significance: The gait components seem similar in people with and without MCI, although there were somedifferences. This study may aid the identification of gait variables that represent different components of gait.Gait parameters such as step velocity variability, mean step length, mean step time as well as swing and stancetime asymmetry could serve as interesting core variables of different gait components in future research in peoplewith MCI (with suspected incipient neurocognitive disorder) and CU. However, the selection of gait variablesdepends on the purpose. It needs to be noted that assessment of variability measures requires more advancedtechnology than is usually used in the clinic.
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| 5. |
- Lindh-Rengifo, Magnus, et al.
(författare)
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Effects of Brain Pathologies on Spatiotemporal Gait Parameters in Patients with Mild Cognitive Impairment
- 2023
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Ingår i: Journal of Alzheimer's Disease. - 1387-2877. ; 96:1, s. 161-171
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Tidskriftsartikel (refereegranskat)abstract
- Background: Impaired gait can precede dementia. The associations between gait parameters and brain pathologies are therefore of interest. Objective: To explore how different brain pathologies (i.e., vascular and Alzheimer's) are associated with specific gait parameters from various gait components in persons with mild cognitive impairment (MCI), who have an increased risk of developing dementia. Methods: This cross-sectional study included 96 patients with MCI (mean 72, ±7.5 years; 52% women). Gait was evaluated by using an electronic walkway, GAITRite®. Four gait parameters (step velocity variability; step length; step time; stance time asymmetry) were used as dependent variables in multivariable linear regression analyses. Independent variables included Alzheimer's disease pathologies (amyloid-β and tau) by using PET imaging and white matter hyperintensities (WMH) by using MRI. Covariates included age, sex, comorbidities (and intracranial volume in analyses that includedWMH). Results: Increased tau-PET (Braak I-IV region of interest [ROI]) was associated with step velocity variability (standardized regression coefficient, β= 0.383, p < 0.001) and step length (β= 0.336, p < 0.001), which remained significant when using different Braak ROIs (I-II, III-IV, V-VI). The associations remained significant when adjusting for WMH (p < 0.001). When also controlling for gait speed, tau was no longer significantly (p = 0.168) associated with an increased step length. No significant associations between gait and Aβ-PET load or WMH were identified. Conclusions: The results indicate that one should pay specific attention to assess step velocity variability when targeting single task gait in patients with MCI. Future studies should address additional gait variability measures and dual tasking in larger cohorts.
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| 6. |
- Lindh-Rengifo, Magnus, et al.
(författare)
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Perceived walking difficulties in Parkinson’s disease – predictors and changes over time
- 2021
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Ingår i: BMC Geriatrics. - : Springer Science and Business Media LLC. - 1471-2318. ; 21:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: People with Parkinson’s disease (PD) have described their walking difficulties as linked to activity avoidance, social isolation, reduced independence and quality of life. There is a knowledge gap regarding predictive factors of perceived walking difficulties in people with PD. Such knowledge could be useful when designing intervention studies. This study aimed to investigate how perceived walking difficulties evolve over a 3-year period in people with PD. A specific aim was to identify predictive factors of perceived walking difficulties. Methods: One hundred forty-eight people with PD (mean age 67.9 years) completed the Generic Walk-12 (Walk-12G) questionnaire (which assesses perceived walking difficulties) at both baseline and the 3-year follow-up. Paired samples t-test was used for comparing baseline and follow-up mean scores. Multivariable linear regression analyses were used to identify predictive factors of perceived walking difficulties. Results: Perceived walking difficulties increased after 3 years: mean Walk-12G score 14.8 versus 18.7, p < 0.001. Concerns about falling was the strongest predictor (β = 0.445) of perceived walking difficulties, followed by perceived balance problems while dual tasking (β = 0.268) and pain (β = 0.153). Perceived balance problems while dual tasking was the strongest predictor (β = 0.180) of a change in perceived walking difficulties, followed by global cognitive functioning (β = − 0.107). Conclusions: Perceived walking difficulties increase over time in people with PD. Both personal factors (i.e. concerns about falling) and motor aspects (i.e. balance problems while dual tasking) seem to have a predictive role. Importantly, our study indicates that also non-motor symptoms (e.g. pain and cognitive functioning) seem to be of importance for future perceived walking difficulties. Future intervention studies that address these factors need to confirm their preventative effect on perceived walking difficulties.
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| 7. |
- Moseby-Knappe, Marion, et al.
(författare)
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Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest
- 2020
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Ingår i: Intensive Care Medicine. - : Springer Science and Business Media LLC. - 0342-4642 .- 1432-1238. ; 46:10, s. 1852-62
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Tidskriftsartikel (refereegranskat)abstract
- © 2020, The Author(s). Purpose: To assess the performance of a 4-step algorithm for neurological prognostication after cardiac arrest recommended by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM). Methods: Retrospective descriptive analysis with data from the Target Temperature Management (TTM) Trial. Associations between predicted and actual neurological outcome were investigated for each step of the algorithm with results from clinical neurological examinations, neuroradiology (CT or MRI), neurophysiology (EEG and SSEP) and serum neuron-specific enolase. Patients examined with Glasgow Coma Scale Motor Score (GCS-M) on day 4 (72–96h) post-arrest and available 6-month outcome were included. Poor outcome was defined as Cerebral Performance Category 3–5. Variations of the ERC/ESICM algorithm were explored within the same cohort. Results: The ERC/ESICM algorithm identified poor outcome patients with 38.7% sensitivity (95% CI 33.1–44.7) and 100% specificity (95% CI 98.8–100) in a cohort of 585 patients. An alternative cut-off for serum neuron-specific enolase, an alternative EEG-classification and variations of the GCS-M had minor effects on the sensitivity without causing false positive predictions. The highest overall sensitivity, 42.5% (95% CI 36.7–48.5), was achieved when prognosticating patients irrespective of GCS-M score, with 100% specificity (95% CI 98.8–100) remaining. Conclusion: The ERC/ESICM algorithm and all exploratory multimodal variations thereof investigated in this study predicted poor outcome without false positive predictions and with sensitivities 34.6–42.5%. Our results should be validated prospectively, preferably in patients where withdrawal of life-sustaining therapy is uncommon to exclude any confounding from self-fulfilling prophecies.
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| 8. |
- Moseby-Knappe, Marion, et al.
(författare)
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Serum markers of brain injury can predict good neurological outcome after out-of-hospital cardiac arrest
- 2021
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Ingår i: Intensive Care Medicine. - : Springer Science and Business Media LLC. - 0342-4642 .- 1432-1238. ; 47, s. 984-994
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Tidskriftsartikel (refereegranskat)abstract
- Purpose The majority of unconscious patients after cardiac arrest (CA) do not fulfill guideline criteria for a likely poor outcome, their prognosis is considered "indeterminate". We compared brain injury markers in blood for prediction of good outcome and for identifying false positive predictions of poor outcome as recommended by guidelines. Methods Retrospective analysis of prospectively collected serum samples at 24, 48 and 72 h post arrest within the Target Temperature Management after out-of-hospital cardiac arrest (TTM)-trial. Clinically available markers neuron-specific enolase (NSE) and S100B, and novel markers neurofilament light chain (NFL), total tau, ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) were analysed. Normal levels with a priori cutoffs specified by reference laboratories or defined from literature were used to predict good outcome (no to moderate disability, Cerebral Performance Category scale 1-2) at 6 months. Results Seven hundred and seventeen patients were included. Normal NFL, tau and GFAP had the highest sensitivities (97.2-98% of poor outcome patients had abnormal serum levels) and NPV (normal levels predicted good outcome in 87-95% of patients). Normal S100B and NSE predicted good outcome with NPV 76-82.2%. Normal NSE correctly identified 67/190 (35.3%) patients with good outcome among those classified as "indeterminate outcome" by guidelines. Five patients with single pathological prognostic findings despite normal biomarkers had good outcome. Conclusion Low levels of brain injury markers in blood are associated with good neurological outcome after CA. Incorporating biomarkers into neuroprognostication may help prevent premature withdrawal of life-sustaining therapy.
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