A prospective study of multimodal cocktail intercostal injection for chest pain relief after costal cartilage harvest for rhinoplasty

Our aim was to evaluate the efficacy and safety of multimodal cocktail intercostal injection for the relief of chest pain after costal cartilage harvest for rhinoplasty. Consecutive patients who underwent costal cartilage harvest during rhinoplasty were prospectively assigned as per patient preference to group A (injection containing ropivacaine, parecoxib sodium, epinephrine, and compound betamethasone), group B (intercostal nerve block (ICNB)), or group C (ICNB plus patient-controlled analgesia (PCA)). The outcomes were visual analogue scale (VAS) scores for chest pain after costal cartilage harvest, rescue analgesia, complications, and cost during the first two days. Of the 66 patients assessed, 63 (29 patients in group A, 13 in group B, and 21 in group C) were eligible and included. The VAS scores in group A were significantly lower than those in groups B and C (all p<0.001). Group A had a significantly lower rate of rescue analgesia due to a VAS score of more than 4 (3.45%, 1/29) compared with group B (46.15%, 6/13; p=0.001) and group C (28.57%, 6/21; p=0.012). Complications were observed only in group C (nausea/vomiting 28.57%; dizziness/headache 23.81%), which differed significantly from group A (p=0.002 and 0.006, respectively). The mean cost for group A (US $15 (0)) was significantly lower than it was for group C (US $113.1 (4.4), p<0.05), but higher than it was for group B (US $5.97 (0), p= -). Multimodal cocktail intercostal injection may be superior for chest pain relief after costal cartilage harvest for rhinoplasty compared with ICNB with or without PCA. Further study is warranted.     

Clinical and Multimodal Imaging Findings and Risk Factors for Ocular Involvement in a Presumed Waterborne Toxoplasmosis Outbreak,Brazil

In 2015, an outbreak of presumed waterborne toxoplasmosis occurred in Gouveia, Brazil. We conducted a 3-year prospective study on a cohort of 52 patients from this outbreak, collected clinical and multimodal imaging findings, and determined risk factors for ocular involvement. At baseline examination, 12 (23%) patients had retinochoroiditis; 4 patients had bilateral and 2 had macular lesions. Multimodal imaging revealed 2 distinct retinochoroiditis patterns: necrotizing focal retinochoroiditis and punctate retinochoroiditis. Older age, worse visual acuity, self-reported recent reduction of visual acuity, and presence of floaters were associated with retinochoroiditis. Among patients, persons >40 years of age had 5 times the risk for ocular involvement. Five patients had recurrences during follow-up, a rate of 22% per person-year. Recurrences were associated with binocular involvement. Two patients had late ocular involvement that occurred >34 months after initial diagnosis. Patients with acquired toxoplasmosis should have long-term ophthalmic follow-up, regardless of initial ocular involvement.     

Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis

Previous structural and functional neuroimaging studies have implicated distributed brain regions and networks in depression. However, there are no robust imaging biomarkers that are specific to depression, which may be due to clinical heterogeneity and neurobiological complexity. A dimensional approach and fusion of imaging modalities may yield a more coherent view of the neuronal correlates of depression. We used linked independent component analysis to fuse cortical macrostructure (thickness, area, gray matter density), white matter diffusion properties and resting‐state functional magnetic resonance imaging default mode network amplitude in patients with a history of depression (n = 170) and controls (n = 71). We used univariate and machine learning approaches to assess the relationship between age, sex, case–control status, and symptom loads for depression and anxiety with the resulting brain components. Univariate analyses revealed strong associations between age and sex with mainly global but also regional specific brain components, with varying degrees of multimodal involvement. In contrast, there were no significant associations with case–control status, nor symptom loads for depression and anxiety with the brain components, nor any interaction effects with age and sex. Machine learning revealed low model performance for classifying patients from controls and predicting symptom loads for depression and anxiety, but high age prediction accuracy. Multimodal fusion of brain imaging data alone may not be sufficient for dissecting the clinical and neurobiological heterogeneity of depression. Precise clinical stratification and methods for brain phenotyping at the individual level based on large training samples may be needed to parse the neuroanatomy of depression.     

Improved prediction of brain age using multimodal neuroimaging data

Brain age prediction based on imaging data and machine learning (ML) methods has great potential to provide insights into the development of cognition and mental disorders. Though different ML models have been proposed, a systematic comparison of ML models in combination with imaging features derived from different modalities is still needed. In this study, we evaluate the prediction performance of 36 combinations of imaging features and ML models including deep learning. We utilize single and multimodal brain imaging data including MRI, DTI, and rs‐fMRI from a large data set with 839 subjects. Our study is a follow‐up to the initial work (Liang et al., 2019. Human Brain Mapping) to investigate different analytic strategies to combine data from MRI, DTI, and rs‐fMRI with the goal to improve brain age prediction accuracy. Additionally, the traditional approach to predicting the brain age gap has been shown to have a systematic bias. The potential nonlinear relationship between the brain age gap and chronological age has not been thoroughly tested. Here we propose a new method to correct the systematic bias of brain age gap by taking gender, chronological age, and their interactions into consideration. As the true brain age is unknown and may deviate from chronological age, we further examine whether various levels of behavioral performance across subjects predict their brain age estimated from neuroimaging data. This is an important step to quantify the practical implication of brain age prediction. Our findings are helpful to advance the practice of optimizing different analytic methodologies in brain age prediction.     

Does Nefopam Provide Analgesic Effect and Reduce Morphine Consumption After Primary Total Knee Arthroplasty? A Prospective,Double-Blind,Randomized Controlled Trial

BackgroundOne of the most undesirable results after total knee arthroplasty (TKA) is severe immediate postoperative pain, resulting in patient dissatisfaction. We aimed to evaluate nefopam’s analgesic efficacy after primary TKA along with related outcomes, including morphine consumption and adverse events.MethodsWe conducted a double-blind, randomized controlled trial of patients undergoing unilateral primary TKA, comparing 24 hours of 80 mg of continuous intravenous nefopam to placebo infusion. A 100-mm Visual Analog Scale (VAS) for pain-at-rest and in-motion ≤48 hours was the primary outcome measure. Secondary outcomes were morphine and antiemetic consumption, adverse events, and functional outcomes: time-to-walk, timed up-and-go test, postoperative knee range of motion at 24 and 48 hours, time-to-discharge, and patient satisfaction scores.ResultsPatients in the nefopam group had significantly lower VAS at rest 6 hours postop (20.3 ± 27.3 vs 35 ± 24.3, P = .01). Other timepoints and in-motion VAS did not significantly differ. Total morphine consumption (0-48 hours) was 37% less, significantly lower, in the nefopam group (5.3 ± 4.5 vs 8.4 ± 7.5 mg, P = .03). Antiemetic consumption was also 61% lower in the nefopam group but not statistically significant (0.8 ± 2.3 vs 2.0 ± 3.8 mg, P = .08). There were no variations in adverse events, functional outcomes, and satisfaction scores between groups.ConclusionContinuous nefopam administration as part of multimodal analgesia for 24 hours post-TKA produced a significant analgesic effect but only within the first 6 hours. However, there was a notable reduction in morphine use 48 hours postop. Nefopam is a useful agent for contemporary pain control after TKA.Level of EvidenceTherapeutic Level I.     

Toward neuroimaging‐based network biomarkers for transient ischemic attack

Stroke is associated with topological disruptions of large‐scale functional brain networks. However, whether these disruptions occur in transient ischemic attack (TIA), an important risk factor for stroke, remains largely unknown. Combining multimodal MRI techniques, we systematically examined TIA‐related topological alterations of functional brain networks, and tested their reproducibility, structural, and metabolic substrates, associations with clinical risk factors and abilities as diagnostic and prognostic biomarkers. We found that functional networks in patients with TIA exhibited decreased whole‐brain network efficiency, reduced nodal centralities in the bilateral insula and basal ganglia, and impaired connectivity of inter‐hemispheric communication. These alterations remained largely unchanged when using different brain parcellation schemes or correcting for micro head motion or for regional gray matter volume, cerebral blood flow or hemodynamic lag of BOLD signals in the patients. Moreover, some alterations correlated with the levels of high‐density lipoprotein cholesterol (an index related to ischemic attacks via modulation of atherosclerosis) in the patients, distinguished the patients from healthy individuals, and predicted future ischemic attacks in the patients. Collectively, these findings highlight the emergence of characteristic network dysfunctions in TIA, which may aid in elucidating pathological mechanisms and establishing diagnostic and prognostic biomarkers for the disease.