Baseline GABA+ levels in areas associated with sensorimotor control predict initial and long-term motor learning progress.

Synaptic plasticity relies on the balance between excitation and inhibition in the brain. As the primary inhibitory and excitatory neurotransmitters, gamma-aminobutyric acid (GABA) and glutamate (Glu), play critical roles in synaptic plasticity and learning. However, the role of these neurometabolites in motor learning is still unclear. Furthermore, it remains to be investigated which neurometabolite levels from the regions composing the sensorimotor network predict future learning outcome. Here, we studied the role of baseline neurometabolite levels in four task-related brain areas during different stages of motor skill learning under two different feedback (FB) conditions. Fifty-one healthy participants were trained on a bimanual motor task over 5 days while receiving either concurrent augmented visual FB (CA-VFB group, N = 25) or terminal intrinsic visual FB (TA-VFB group, N = 26) of their performance. Additionally, MRS-measured baseline GABA+ (GABA + macromolecules) and Glx (Glu + glutamine) levels were measured in the primary motor cortex (M1), primary somatosensory cortex (S1), dorsolateral prefrontal cortex (DLPFC), and medial temporal cortex (MT/V5). Behaviorally, our results revealed that the CA-VFB group outperformed the TA-VFB group during task performance in the presence of augmented VFB, while the TA-VFB group outperformed the CA-VFB group in the absence of augmented FB. Moreover, baseline M1 GABA+ levels positively predicted and DLPFC GABA+ levels negatively predicted both initial and long-term motor learning progress in the TA-VFB group. In contrast, baseline S1 GABA+ levels positively predicted initial and long-term motor learning progress in the CA-VFB group. Glx levels did not predict learning progress. Together, these findings suggest that baseline GABA+ levels predict motor learning capability, yet depending on the FB training conditions afforded to the participants.

Hypoxia alters posterior cingulate cortex metabolism during a memory task: A 1H fMRS study.

Environmental hypoxia (fraction of inspired oxygen (FIO2) ∼ 0.120) is known to trigger a global increase in cerebral blood flow (CBF). However, regionally, a heterogeneous response is reported, particularly within the posterior cingulate cortex (PCC) where decreased CBF is found after two hours of hypoxic exposure. Furthermore, hypoxia reverses task-evoked BOLD signals within the PCC, and other regions of the default mode network, suggesting a reversal of neurovascular coupling. An alternative explanation is that the neural architecture supporting cognitive tasks is reorganised. Therefore, to confirm if this previous result is neural or vascular in origin, a measure of neural activity that is not haemodynamic-dependant is required. To achieve this, we utilised functional magnetic resonance spectroscopy to probe the glutamate response to memory recall in the PCC during normoxia (FIO2 = 0.209) and after two hours of poikilocapnic hypoxia (FIO2 = 0.120). We also acquired ASL-based measures of CBF to confirm previous findings of reduced CBF within the PCC in hypoxia. Consistent with previous findings, hypoxia induced a reduction in CBF within the PCC and other regions of the default mode network. Under normoxic conditions, memory recall was associated with an 8% increase in PCC glutamate compared to rest (P = 0.019); a change which was not observed during hypoxia. However, exploratory analysis of other neurometabolites showed that PCC glucose was reduced during hypoxia compared to normoxia both at rest (P = 0.039) and during the task (P = 0.046). We conclude that hypoxia alters the activity-induced increase in glutamate, which may reflect a reduction in oxidative metabolism within the PCC. The reduction in glucose in hypoxia reflects continued metabolism, presumably by non-oxidative means, without replacement of glucose due to reduced CBF.

Patient and Caregiver-Derived Health Service Improvements for Better Critical Care Recovery.

OBJECTIVES: To engage critical care end-users (survivors and caregivers) to describe their emotions and experiences across their recovery trajectory, and elicit their ideas and solutions for health service improvements to improve the ICU recovery experience. DESIGN: End-user engagement as part of a qualitative design using the Framework Analysis method. SETTING: The Society of Critical Care Medicine's THRIVE international collaborative sites (follow-up clinics and peer support groups). SUBJECTS: Patients and caregivers following critical illness and identified through the collaboratives. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Eighty-six interviews were conducted. The following themes were identified: 1) Emotions and experiences of patients-"Loss of former self; Experiences of disability and adaptation"; 2) Emotions and experiences of caregivers-"Emotional impacts, adopting new roles, and caregiver burden; Influence of gender roles; Adaptation, adjustment, recalibration"; and 3) Patient and caregiver-generated solutions to improve recovery across the arc of care-"Family-targeted education; Expectation management; Rehabilitation for patients and caregivers; Peer support groups; Reconnecting with ICU post-discharge; Access to community-based supports post-discharge; Psychological support; Education of issues of ICU survivorship for health professionals; Support across recovery trajectory." Themes were mapped to a previously published recovery framework (Timing It Right) that captures patient and caregiver experiences and their support needs across the phases of care from the event/diagnosis to adaptation post-discharge home. CONCLUSIONS: Patients and caregivers reported a range of emotions and experiences across the recovery trajectory from ICU to home. Through end-user engagement strategies many potential solutions were identified that could be implemented by health services and tested to support the delivery of higher-quality care for ICU survivors and their caregivers that extend from tertiary to primary care settings.

NIfTI-MRS: A standard data format for magnetic resonance spectroscopy.

PURPOSE: Multiple data formats in the MRS community currently hinder data sharing and integration. NIfTI-MRS is proposed as a standard spectroscopy data format, implemented as an extension to the Neuroimaging informatics technology initiative (NIfTI) format. This standardized format can facilitate data sharing and algorithm development as well as ease integration of MRS analysis alongside other imaging modalities. METHODS: A file format using the NIfTI header extension framework incorporates essential spectroscopic metadata and additional encoding dimensions. A detailed description of the specification is provided. An open-source command-line conversion program is implemented to convert single-voxel and spectroscopic imaging data to NIfTI-MRS. Visualization of data in NIfTI-MRS is provided by development of a dedicated plugin for FSLeyes, the FMRIB Software Library (FSL) image viewer. RESULTS: Online documentation and 10 example datasets in the proposed format are provided. Code examples of NIfTI-MRS readers are implemented in common programming languages. Conversion software, spec2nii, currently converts 14 formats where data is stored in image-space to NIfTI-MRS, including Digital Imaging and Communications in Medicine (DICOM) and vendor proprietary formats. CONCLUSION: NIfTI-MRS aims to solve issues arising from multiple data formats being used in the MRS community. Through a single conversion point, processing and analysis of MRS data are simplified, thereby lowering the barrier to use of MRS. Furthermore, it can serve as the basis for open data sharing, collaboration, and interoperability of analysis programs. Greater standardization and harmonization become possible. By aligning with the dominant format in neuroimaging, NIfTI-MRS enables the use of mature tools present in the imaging community, demonstrated in this work by using a dedicated imaging tool, FSLeyes, for visualization.

The macromolecular MR spectrum does not change with healthy aging.

PURPOSE: To acquire the mobile macromolecule (MM) spectrum from healthy participants, and to investigate changes in the signals with age and sex. METHODS: 102 volunteers (49 M/53 F) between 20 and 69 years were recruited for in vivo data acquisition in the centrum semiovale (CSO) and posterior cingulate cortex (PCC). Spectral data were acquired at 3T using PRESS localization with a voxel size of 30 × 26 × 26 mm3 , pre-inversion (TR/TI 2000/600 ms) and CHESS water suppression. Metabolite-nulled spectra were modeled to eliminate residual metabolite signals, which were then subtracted out to yield a "clean" MM spectrum using the Osprey software. Pearson's correlation coefficient was calculated between integrals and age for the 14 MM signals. One-way ANOVA was performed to determine differences between age groups. An independent t-test was carried out to determine differences between sexes. RESULTS: MM spectra were successfully acquired in 99 (CSO) and 96 (PCC) of 102 subjects. No significant correlations were seen between age and MM signals. One-way ANOVA also suggested no age-group differences for any MM peak (all p > .004). No differences were observed between sex groups. WM and GM voxel fractions showed a significant (p < .05) negative linear association with age in the WM-predominant CSO (R = -0.29) and GM-predominant PCC regions (R = -0.57) respectively while CSF increased significantly with age in both regions. CONCLUSION: Our findings suggest that a pre-defined MM basis function can be used for linear combination modeling of metabolite data from different age and sex groups.

Comparison of seven modelling algorithms for γ-aminobutyric acid-edited proton magnetic resonance spectroscopy.

Edited MRS sequences are widely used for studying γ-aminobutyric acid (GABA) in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multisite study. GABA-edited (GABA+, TE = 68 ms MEGA-PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL-MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor-specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors' hardware, presenting across algorithms. Scale differences across algorithms were also observed. Using the correlation between metabolite estimates and voxel tissue fraction as a benchmark, most algorithms were found to be similarly effective in detecting differences in GABA+. An interclass correlation across all algorithms showed single-rater consistency for GABA+ estimates of around 0.38, indicating moderate agreement. Upon inclusion of a basis set component explicitly modelling the macromolecule signal underlying the observed 3.0 ppm GABA peaks, single-rater consistency improved to 0.44. Correlation between discrete pairs of algorithms varied, and was concerningly weak in some cases. Our findings highlight the need for consensus on appropriate modelling parameters across different algorithms, and for detailed reporting of the parameters adopted in individual studies to ensure reproducibility and meaningful comparison of outcomes between different studies.

Frequency and Intensity of Premonitory Urges-to-Tic in Tourette Syndrome Is Associated With Supplementary Motor Area GABA+ Levels.

BACKGROUND: Individuals with Tourette syndrome (TS) often report that they express tics as a means of alleviating the experience of unpleasant sensations. These sensations are perceived as an urge to act and are referred to as premonitory urges. Premonitory urges have been the focus of recent efforts to develop interventions to reduce tic expression in those with TS. OBJECTIVE: The aim of this study was to examine the contribution of brain γ-aminobutyric acid (GABA) and glutamate levels of the right primary sensorimotor cortex (SM1), supplementary motor area (SMA), and insular cortex (insula) to tic and urge severity in children with TS. METHODS: Edited magnetic resonance spectroscopy was used to assess GABA+ (GABA + macromolecules) and Glx (glutamate + glutamine) of the right SM1, SMA, and insula in 68 children with TS (MAge = 10.59, SDAge = 1.33) and 41 typically developing control subjects (MAge = 10.26, SDAge = 2.21). We first compared GABA+ and Glx levels of these brain regions between groups. We then explored the association between regional GABA+ and Glx levels with urge and tic severity. RESULTS: GABA+ and Glx of the right SM1, SMA, and insula were comparable between the children with TS and typically developing control subjects. In children with TS, lower levels of SMA GABA+ were associated with more severe and more frequent premonitory urges. Neither GABA+ nor Glx levels were associated with tic severity. CONCLUSIONS: These results broadly support the role of GABAergic neurotransmission within the SMA in the experience of premonitory urges in children with TS. © 2021 International Parkinson and Movement Disorder Society.

Hospital Readmission and Post-Acute Care Use After Intensive Care Unit Admissions: New ICU Quality Metrics?

OBJECTIVE: Care coordination is a national priority. Post-acute care use and hospital readmission appear to be common after critical illness. It is unknown whether specialty critical care units have different readmission rates and what these trends have been over time. METHODS: In this retrospective cohort study, a cohort of 53,539 medical/surgical patients who were treated in a critical care unit during their index admission were compared with 209,686 patients who were not treated in a critical care unit. The primary outcome was 30-day all cause hospital readmission. Secondary outcomes included post-acute care resource use and immediate readmission, defined as within 7 days of discharge. RESULTS: Compared to patients discharged after an index hospitalization without critical illness, surviving patients following ICU admission were not more likely to be rehospitalized within 30 days (15.8 vs. 16.1%, p = 0.08). However, they were more likely to receive post-acute care services (45.3% vs. 70.9%, p < 0.001) as well as be rehospitalized within 7 days (5.2 vs. 6.0%, p < 0.001). Post-acute care use and 30-day readmission rates varied by ICU type, the latter ranging from 11.7% after admission in a cardiothoracic critical care unit to 23.1% after admission in a medical critical care unit. 30-day readmission after ICU admission did not decline between 2010 and 2015 (p = 0.38). Readmission rates declined over time for 2 of 4 targeted conditions (heart failure and chronic obstructive pulmonary disease), but only when the hospitalization did not include ICU admission. CONCLUSIONS: Rehospitalization for survivors following ICU admission is common across all specialty critical care units. Post-acute care use is also common for this population of patients. Overall trends for readmission rates after critical illness did not change over time, and readmission reductions for targeted conditions were limited to hospitalizations that did not include an ICU admission.

Surviving COVID-19 After Hospital Discharge: Symptom, Functional, and Adverse Outcomes of Home Health Recipients.

BACKGROUND: Little is known about recovery from coronavirus disease 2019 (COVID-19) after hospital discharge. OBJECTIVE: To describe the home health recovery of patients with COVID-19 and risk factors associated with rehospitalization or death. DESIGN: Retrospective observational cohort. SETTING: New York City. PARTICIPANTS: 1409 patients with COVID-19 admitted to home health care (HHC) between 1 April and 15 June 2020 after hospitalization. MEASUREMENTS: Covariates and outcomes were obtained from the mandated OASIS (Outcome and Assessment Information Set). Cox proportional hazards models were used to estimate the hazard ratio (HR) of risk factors associated with rehospitalization or death. RESULTS: After an average of 32 days in HHC, 94% of patients were discharged and most achieved statistically significant improvements in symptoms and function. Activity-of-daily-living dependencies decreased from an average of 6 (95% CI, 5.9 to 6.1) to 1.2 (CI, 1.1 to 1.3). Risk for rehospitalization or death was higher for male patients (HR, 1.45 [CI, 1.04 to 2.03]); White patients (HR, 1.74 [CI, 1.22 to 2.47]); and patients with heart failure (HR, 2.12 [CI, 1.41 to 3.19]), diabetes with complications (HR, 1.71 [CI, 1.17 to 2.52]), 2 or more emergency department visits in the past 6 months (HR, 1.78 [CI, 1.21 to 2.62]), pain daily or all the time (HR, 1.46 [CI, 1.05 to 2.05]), cognitive impairment (HR, 1.49 [CI, 1.04 to 2.13]), or functional dependencies (HR, 1.09 [CI, 1.00 to 1.20]). Eleven patients (1%) died, 137 (10%) were rehospitalized, and 23 (2%) remain on service. LIMITATIONS: Care was provided by 1 home health agency. Information on rehospitalization and death after HHC discharge is not available. CONCLUSION: Symptom burden and functional dependence were common at the time of HHC admission but improved for most patients. Comorbid conditions of heart failure and diabetes, as well as characteristics present at admission, identified patients at greatest risk for an adverse event. PRIMARY FUNDING SOURCE: No direct funding.

Characteristics, Outcomes, and Trends of Patients With COVID-19-Related Critical Illness at a Learning Health System in the United States.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic continues to surge in the United States and globally. OBJECTIVE: To describe the epidemiology of COVID-19-related critical illness, including trends in outcomes and care delivery. DESIGN: Single-health system, multihospital retrospective cohort study. SETTING: 5 hospitals within the University of Pennsylvania Health System. PATIENTS: Adults with COVID-19-related critical illness who were admitted to an intensive care unit (ICU) with acute respiratory failure or shock during the initial surge of the pandemic. MEASUREMENTS: The primary exposure for outcomes and care delivery trend analyses was longitudinal time during the pandemic. The primary outcome was all-cause 28-day in-hospital mortality. Secondary outcomes were all-cause death at any time, receipt of mechanical ventilation (MV), and readmissions. RESULTS: Among 468 patients with COVID-19-related critical illness, 319 (68.2%) were treated with MV and 121 (25.9%) with vasopressors. Outcomes were notable for an all-cause 28-day in-hospital mortality rate of 29.9%, a median ICU stay of 8 days (interquartile range [IQR], 3 to 17 days), a median hospital stay of 13 days (IQR, 7 to 25 days), and an all-cause 30-day readmission rate (among nonhospice survivors) of 10.8%. Mortality decreased over time, from 43.5% (95% CI, 31.3% to 53.8%) to 19.2% (CI, 11.6% to 26.7%) between the first and last 15-day periods in the core adjusted model, whereas patient acuity and other factors did not change. LIMITATIONS: Single-health system study; use of, or highly dynamic trends in, other clinical interventions were not evaluated, nor were complications. CONCLUSION: Among patients with COVID-19-related critical illness admitted to ICUs of a learning health system in the United States, mortality seemed to decrease over time despite stable patient characteristics. Further studies are necessary to confirm this result and to investigate causal mechanisms. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.

Improving transitions and outcomes of sepsis survivors (I-TRANSFER): a type 1 hybrid protocol.

BACKGROUND: This protocol is based on home health care (HHC) best practice evidence showing the value of coupling timely post-acute care visits by registered nurses and early outpatient provider follow-up for sepsis survivors. We found that 30-day rehospitalization rates were 7 percentage points lower (a 41% relative reduction) when sepsis survivors received a HHC nursing visit within 2 days of hospital discharge, at least 1 more nursing visit the first week, and an outpatient provider follow-up visit within 7 days compared to those without timely follow-up. However, nationwide, only 28% of sepsis survivors who transitioned to HHC received this timely visit protocol. The opportunity exists for many more sepsis survivors to benefit from timely home care and outpatient services. This protocol aims to achieve this goal.  METHODS: Guided by the Consolidated Framework for Implementation Research, this Type 1 hybrid pragmatic study will test the effectiveness of the Improving Transitions and Outcomes of Sepsis Survivors (I-TRANSFER) intervention compared to usual care on 30-day rehospitalization and emergency department use among sepsis survivors receiving HHC. The study design includes a baseline period with no intervention, a six-month start-up period followed by a one-year intervention period in partnership with five dyads of acute and HHC sites. In addition to the usual care/control periods from the dyad sites, additional survivors from national data will serve as control observations for comparison, weighted to produce covariate balance. The hypotheses will be tested using generalized mixed models with covariates guided by the Andersen Behavioral Model of Health Services. We will produce insights and generalizable knowledge regarding the context, processes, strategies, and determinants of I-TRANSFER implementation. DISCUSSION: As the largest HHC study of its kind and the first to transform this novel evidence through implementation science, this study has the potential to produce new knowledge about the impact of timely attention in HHC to alleviate symptoms and support sepsis survivor's recovery at home. If effective, the impact of this intervention could be widespread, improving the quality of life and health outcomes for a growing, vulnerable population of sepsis survivors. A national advisory group will assist with widespread results dissemination.

Gamma-aminobutyric acid (GABA) levels in the midcingulate cortex and clozapine response in patients with treatment-resistant schizophrenia: A proton magnetic resonance spectroscopy (1 H-MRS) study.

BACKGROUND: Gamma-Aminobutyric Acid (GABA) is the primary inhibitory neurotransmitter in the central nervous system. GABAergic dysfunction has been implicated in the pathophysiology of schizophrenia. Clozapine, the only approved drug for treatment-resistant schizophrenia (TRS), involves the GABAergic system as one of its targets. However, no studies have investigated the relationship between brain GABA levels, as measured by proton magnetic resonance spectroscopy (1 H-MRS), and clozapine response in patients with TRS. METHODS: This study enrolled patients with TRS who did not respond to clozapine (ultra-resistant schizophrenia: URS) and who responded to clozapine (non-URS), patients with schizophrenia who responded to first-line antipsychotics (first-line responders: FLR), and healthy controls (HCs). We measured GABA levels in the midcingulate cortex (MCC) using 3T 1 H-MRS and compared these levels among the groups. The associations between GABA levels and symptom severity were also explored within the patient groups. RESULTS: A total of 98 participants (URS: n = 22; non-URS: n = 25; FLR: n = 16; HCs: n = 35) completed the study. We found overall group differences in MCC GABA levels (F(3,86) = 3.25, P = 0.04). Specifically, patients with URS showed higher GABA levels compared to those with non-URS (F(1,52) = 8.40, P = 0.03, Cohen's d = 0.84). MCC GABA levels showed no associations with any of the symptom severity scores within each group or the entire patient group. CONCLUSION: Our study is the first to report elevated GABA levels in the MCC in patients with schizophrenia resistant to clozapine treatment compared with those responsive to clozapine. Longitudinal studies are required to evaluate if GABA levels are a suitable biomarker to predict clozapine resistance.

Comparison of methods for spectral alignment and signal modelling of GABA-edited MR spectroscopy data.

Many methods exist for aligning and quantifying magnetic resonance spectroscopy (MRS) data to measure in vivo γ-aminobutyric acid (GABA). Research comparing the performance of these methods is scarce partly due to the lack of ground-truth measurements. The concentration of GABA is approximately two times higher in grey matter than in white matter. Here we use the proportion of grey matter within the MRS voxel as a proxy for ground-truth GABA concentration to compare the performance of four spectral alignment methods (i.e., retrospective frequency and phase drift correction) and six GABA signal modelling methods. We analyse a diverse dataset of 432 MEGA-PRESS scans targeting multiple brain regions and find that alignment to the creatine (Cr) signal produces GABA+ estimates that account for approximately twice as much of the variance in grey matter as the next best performing alignment method. Further, Cr alignment was the most robust, producing the fewest outliers. By contrast, all signal modelling methods, except for the single-Lorentzian model, performed similarly well. Our results suggest that variability in performance is primarily caused by differences in the zero-order phase estimated by each alignment method, rather than frequency, resulting from first-order phase offsets within subspectra. These results provide support for Cr alignment as the optimal method of processing MEGA-PRESS to quantify GABA. However, more broadly, they demonstrate a method of benchmarking quantification of in vivo metabolite concentration from other MRS sequences.

Neurophysiological modulations in the (pre)motor-motor network underlying age-related increases in reaction time and the role of GABA levels - a bimodal TMS-MRS study.

It has been argued that age-related changes in the neurochemical and neurophysiological properties of the GABAergic system may underlie increases in reaction time (RT) in older adults. However, the role of GABA levels within the sensorimotor cortices (SMC) in mediating interhemispheric interactions (IHi) during the processing stage of a fast motor response, as well as how both properties explain interindividual differences in RT, are not yet fully understood. In this study, edited magnetic resonance spectroscopy (MRS) was combined with dual-site transcranial magnetic stimulation (dsTMS) for probing GABA+ levels in bilateral SMC and task-related neurophysiological modulations in corticospinal excitability (CSE), and primary motor cortex (M1)-M1 and dorsal premotor cortex (PMd)-M1 IHi, respectively. Both CSE and IHi were assessed during the preparatory and premotor period of a delayed choice RT task. Data were collected from 25 young (aged 18-33 years) and 28 older (aged 60-74 years) healthy adults. Our results demonstrated that older as compared to younger adults exhibited a reduced bilateral CSE suppression, as well as a reduced magnitude of long latency M1-M1 and PMd-M1 disinhibition during the preparatory period, irrespective of the direction of the IHi. Importantly, in older adults, the GABA+ levels in bilateral SMC partially accounted for task-related neurophysiological modulations as well as individual differences in RT. In contrast, in young adults, neither task-related neurophysiological modulations, nor individual differences in RT were associated with SMC GABA+ levels. In conclusion, this study contributes to a comprehensive initial understanding of how age-related differences in neurochemical properties and neurophysiological processes are related to increases in RT.

Age-related GABAergic differences in the primary sensorimotor cortex: A multimodal approach combining PET, MRS and TMS.

Healthy aging is associated with mechanistic changes in gamma-aminobutyric acid (GABA), the most abundant inhibitory neurotransmitter in the human brain. While previous work mainly focused on magnetic resonance spectroscopy (MRS)-based GABA+ levels and transcranial magnetic stimulation (TMS)-based GABAA receptor (GABAAR) activity in the primary sensorimotor (SM1) cortex, the aim of the current study was to identify age-related differences in positron emission tomography (PET)-based GABAAR availability and its relationship with GABA+ levels (i.e. GABA with the contribution of macromolecules) and GABAAR activity. For this purpose, fifteen young (aged 20-28 years) and fifteen older (aged 65-80 years) participants were recruited. PET and MRS images were acquired using simultaneous time-of-flight PET/MR to evaluate age-related differences in GABAAR availability (distribution volume ratio with pons as reference region) and GABA+ levels. TMS was applied to identify age-related differences in GABAAR activity by measuring short-interval intracortical inhibition (SICI). Whereas GABAAR availability was significantly higher in the SM cortex of older as compared to young adults (18.5%), there were neither age-related differences in GABA+ levels nor SICI. A correlation analysis revealed no significant associations between GABAAR availability, GABAAR activity and GABA+ levels. Although the exact mechanisms need to be further elucidated, it is possible that a higher GABAAR availability in older adults is a compensatory mechanism to ensure optimal inhibitory functionality during the aging process.

Frequency drift in MR spectroscopy at 3T.

PURPOSE: Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. METHOD: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). RESULTS: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. DISCUSSION: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.

Transitions of Care After Critical Illness-Challenges to Recovery and Adaptive Problem Solving.

OBJECTIVES: Investigate the challenges experienced by survivors of critical illness and their caregivers across the transitions of care from intensive care to community, and the potential problem-solving strategies used to navigate these challenges. DESIGN: Qualitative design-data generation via interviews and data analysis via the framework analysis method. SETTING: Patients and caregivers from three continents, identified through the Society of Critical Care Medicine's THRIVE international collaborative sites (follow-up clinics and peer support groups). SUBJECTS: Patients and caregivers following critical illness. INTERVENTIONS: Nil. MEASUREMENTS AND MAIN RESULTS: From 86 interviews (66 patients, 20 caregivers), we identified the following major themes: 1) Challenges for patients-interacting with the health system and gaps in care; managing others' expectations of illness and recovery. 2) Challenges for caregivers-health system shortfalls and inadequate communication; lack of support for caregivers. 3) Patient and caregiver-driven problem solving across the transitions of care-personal attributes, resources, and initiative; receiving support and helping others; and acceptance. CONCLUSIONS: Survivors and caregivers experienced a range of challenges across the transitions of care. There were distinct and contrasting themes related to the caregiver experience. Survivors and caregivers used comparable problem-solving strategies to navigate the challenges encountered across the transitions of care.

Frequency and phase correction of J-difference edited MR spectra using deep learning.

PURPOSE: To investigate whether a deep learning-based (DL) approach can be used for frequency-and-phase correction (FPC) of MEGA-edited MRS data. METHODS: Two neural networks (1 for frequency, 1 for phase) consisting of fully connected layers were trained and validated using simulated MEGA-edited MRS data. This DL-FPC was subsequently tested and compared to a conventional approach (spectral registration [SR]) and to a model-based SR implementation (mSR) using in vivo MEGA-edited MRS datasets. Additional artificial offsets were added to these datasets to further investigate performance. RESULTS: The validation showed that DL-based FPC was capable of correcting within 0.03 Hz of frequency and 0.4°of phase offset for unseen simulated data. DL-based FPC performed similarly to SR for the unmanipulated in vivo test datasets. When additional offsets were added to these datasets, the networks still performed well. However, although SR accurately corrected for smaller offsets, it often failed for larger offsets. The mSR algorithm performed well for larger offsets, which was because the model was generated from the in vivo datasets. In addition, the computation times were much shorter using DL-based FPC or mSR compared to SR for heavily distorted spectra. CONCLUSION: These results represent a proof of principle for the use of DL for preprocessing MRS data.

Functional outcomes following critical illness: epidemiology, current management strategies and the future priorities.

PURPOSE OF REVIEW: Intensive care unit (ICU) survivorship has gained significant attention over the course of the COVID-19 pandemic. In this review, we summarize the contemporary literature in relation to the epidemiology and management of post-ICU problems. RECENT FINDINGS: Survivors of critical illness can have complex physical, social, emotional and cognitive needs in the months following hospital discharge. Emerging evidence has shown that pre-ICU characteristics such as educational attainment, alongside in-ICU factors such as delirium, may contribute to worsening outcomes. Evidence regarding the impact of post-ICU recovery services is evolving, but models such as post-ICU clinics and peer support programs are gaining rapid momentum. SUMMARY: Future research should focus on modifiable risk factors and how identification and treatment of these can improve outcomes. Furthermore, rigorous evaluation of postacute critical care recovery services is necessary.

Upper brainstem GABA levels in Parkinson's disease.

OBJECTIVE: The dopaminergic pathology of Parkinson's disease (PD) impacts circuits involving GABAergic neurons, especially in the brainstem, where the disease manifests early. The aim of this study is to test the hypothesis that levels of gamma-aminobutyric acid (GABA) in the upper brainstem are reduced in patients with PD compared to healthy controls, using edited magnetic resonance spectroscopy (MRS of GABA +). MATERIALS AND METHODS: GABA + levels were examined in 18 PD patients and 18 age- and sex-matched healthy controls (HCs). GABA + -edited MRS was performed in 7.5-ml voxels in the upper brainstem, and the spectra were processed using the Gannet software. Differences in GABA + levels between the two groups were analyzed using independent t test analysis. RESULTS: GABA + levels were significantly lower (p < 0.05) in the upper brainstem of the patients with PD (4.57 ± 0.94 mM) than the HCs (5.89 ± 1.16 mM). CONCLUSION: The lower GABA + levels in the upper brainstem of the PD patients suggest that a GABAergic deficit in the brainstem may contribute to the pathology in PD.