A systematic review and meta-analysis of randomized control trials: efficacy of cognitive behavioral therapies for the management of functional and recurrent abdominal pain disorders in children and adolescents.

Cognitive behavioral therapy (CBT) is effective for pain relief in children and adolescents with functional abdominal pain disorders (FAPDs). However, few studies have focused on the FAPDs specifically and the medium-term or long-term results of CBT. In this meta-analysis, we investigated the efficacy of CBT in pediatric FAPDs and unclassified chronic or recurrent abdominal pain (CAP and RAP, respectively). We searched the PubMed, Embase, and Cochrane Library databases for related randomized controlled trials until August 2021. Eventually, 10 trials with 872 participants were included. The methodological quality of the studies was assessed, and data on two primary and four secondary outcomes of interest were extracted. We used the standardized mean difference (SMD) to measure the same outcome, and precisions of effect sizes were reported as 95% confidence intervals (CIs). We found that CBT had significantly positive effects on reducing pain intensity immediately (SMD: -0.54 [CI: -0.9, -0.19], p = 0.003), 3 months after the intervention (SMD: -0.55; [CI: -1.01, -0.1], p = 0.02) and 12 months after the intervention (SMD: -0.32; [CI: -0.56, -0.08], p = 0.008). CBT also reduced the severity of gastrointestinal symptoms, depression, and solicitousness, improved the quality of life and decreased the total social cost. Future studies should consider uniform interventions in the control group and comparing different CBT delivery methods.

Automatic recognition of whole-spine sagittal alignment and curvature analysis through a deep learning technique.

PURPOSE: Artificial intelligence based on deep learning (DL) approaches enables the automatic recognition of anatomic landmarks and subsequent estimation of various spinopelvic parameters. The locations of inflection points (IPs) and apices (APs) in whole-spine lateral radiographs could be mathematically determined by a fully automatic spinal sagittal curvature analysis system. METHODS: We developed a DL model for automatic spinal curvature analysis of whole-spine lateral plain radiographs by using 1800 annotated images of various spinal disease etiologies. The DL model comprised a landmark localizer to detect 25 vertebral landmarks and a numerical algorithm for the generation of an individualized spinal sagittal curvature. The characteristics of the spinal curvature, including the IPs, APs, and curvature angle, could thus be analyzed using mathematical definitions. The localization error of each landmark was calculated from the predictions of 300 test images to evaluate the performance of the landmark localizer. The interrater reliability among a senior orthopedic surgeon, a radiologist, and the DL model was assessed using the intraclass correlation coefficient (ICC). RESULTS: The accuracy of the landmark localizer was within an acceptable range (median error: 1.7-4.1 mm), and the interrater reliabilities between the proposed DL model and each expert were good to excellent (all ICCs > 0.85) for the measurement of spinal curvature characteristics. CONCLUSION: The interrater reliability between the proposed DL model and human experts was good to excellent in predicting the locations of IPs, APs, and curvature angles. Future applications should be explored to validate this system and improve its clinical efficiency.

Peripheral inflammatory markers associated with brain volume reduction in patients with bipolar I disorder.

BACKGROUND: Neuroinflammation and brain structural abnormalities are found in bipolar disorder (BD). Elevated levels of cytokines and chemokines have been detected in the serum and cerebrospinal fluid of patients with BD. This study investigated the association between peripheral inflammatory markers and brain subregion volumes in BD patients. METHODS: Euthymic patients with bipolar I disorder (BD-I) aged 20-45 years underwent whole-brain magnetic resonance imaging. Plasma levels of monocyte chemoattractant protein-1 (MCP-1), chitinase-3-like protein 1 (also known as YKL-40), fractalkine (FKN), soluble tumour necrosis factor receptor-1 (sTNF-R1), interleukin-1ß, and transforming growth factor-ß1 were measured on the day of neuroimaging. Clinical data were obtained from medical records and interviewing patients and reliable others. RESULTS: We recruited 31 patients with a mean age of 29.5 years. In multivariate regression analysis, plasma level YKL-40, a chemokine, was the most common inflammatory marker among these measurements displaying significantly negative association with the volume of various brain subareas across the frontal, temporal, and parietal lobes. Higher YKL-40 and sTNF-R1 levels were both significantly associated with lower volumes of the left anterior cingulum, left frontal lobe, right superior temporal gyrus, and supramarginal gyrus. A greater number of total lifetime mood episodes were also associated with smaller volumes of the right caudate nucleus and bilateral frontal lobes. CONCLUSIONS: The volume of brain regions known to be relevant to BD-I may be diminished in relation to higher plasma level of YKL-40, sTNF-R1, and more lifetime mood episodes. Macrophage and macrophage-like cells may be involved in brain volume reduction among BD-I patients.

Smartphone-assisted fluorescent analysis of polyT-Cu-nanoprobes using nucleic acid amplification test for the diagnosis of tuberculosis.

Tuberculosis is one of devastating infectious diseases in the world, and early diagnosis and treatment can help overcome this global burden. In this work, a new detection platform combining smartphone-assisted fluorescent analysis and highly sensitive fluorescent copper nanoprobes (CuNPs) in a specific nucleic acid amplification test (NAAT) for the diagnosis of tuberculosis (TB) was demonstrated and validated using clinical samples. To enhance the precision and accuracy of detection, polymerase chain reaction (PCR), padlock probe (PLP) ligation, and rolling circle amplification (RCA) were combined. Long poly(thymine) (polyT) single-stranded DNA was synthesized through RCA, and polyT-CuNPs were formed by adding copper(II) ions and sodium ascorbate as reducing agents; subsequently, the results were visualized through the excitation from a UV transilluminator and quantified with just a smartphone. After optimization, this proposed platform was validated by testing 18 residual DNA samples after TB PCR, including 8 TB-negative and 10 TB-positive samples, and exhibited a detection limit of 5 fg/µL. The findings indicate the potential of this platform for practical application, where it can be combined with a smartphone for image analysis to achieve accurate on-site detection of TB, especially in resource-limited settings.

Comparison of efficacy and safety of gabapentin and duloxetine in painful diabetic peripheral neuropathy: A systematic review and meta-analysis of randomised controlled trials.

BACKGROUND: In patients with diabetes mellitus, painful diabetic peripheral neuropathy (PDPN) is a frequent complication and can cause poor quality of life. We compared the efficacy and safety of duloxetine with those of gabapentin in patients with PDPN through a systematic review and meta-analysis of randomised controlled trials. MATERIALS AND METHODS: PubMed, Embase and the Cochrane Library were searched for eligible studies published from database inception to January 2021. Visual Analogue Scale (VAS), sleep interference score, Clinical Global Impression of Change (CGIC), Patient Global Impression of Change (PGIC), Diabetic Neuropathy Symptom (DNS) score, Diabetic Neuropathic Examination (DNE) score, Neuropathic Disability Score (NDS) and side effects were used to compare duloxetine and gabapentin in patients with PDPN. RESULTS: Three eligible randomised controlled trials involving 290 patients were included. No significant differences were observed between patients receiving duloxetine and gabapentin with respect to VAS (mean change difference = -1.23, 95% CI, -6.09 to 3.62; P = .62), sleep interference score (mean change difference = 0.42, 95% CI, -0.15 to 1.00; P = .15), CGIC (mean difference = 0.04, 95% CI, -0.11 to 0.20; P = .60), PGIC (mean difference= 0.24, 95% CI, -0.13 to 0.60; P = .21), DNS (mean change difference = 0.14, 95% CI, -0.35 to 0.63; P = .58), DNE (mean change difference = 0.26, 95% CI, -0.35 to 0.86; P = .41) and NDS (mean change difference = 0.30, 95% CI, -0.02 to 0.63; P = .07). CONCLUSIONS: No significant differences were observed in the efficacy of duloxetine and gabapentin when treating patients with PDPN.

Body mass index, residual psychotic symptoms, and inflammation associated with brain volume reduction in older patients with schizophrenia.

Obesity, aging, and pathophysiology of schizophrenia (SCZ) may collectively contribute to the gray matter loss in brain regions of SCZ. We attempted to examine the association between volumes of specific brain regions, body mass index (BMI), inflammatory markers, and clinical features in older SCZ patients. METHOD: Clinically stable outpatients with schizophrenia (DSM-IV) aged ≥50 years were recruited to undergo whole-brain magnetic resonance imaging. We measured patients' plasma levels of soluble tumor necrosis factor receptor-1, soluble interleukin (IL)-2 receptor (sIL-2R), IL-1ß, and IL-1 receptor antagonist (IL-1Ra). Clinical data were obtained from medical records and interviewing patients along with their reliable others. RESULTS: There were 32 patients with mean age 58.8 years in this study. Multivariate regression analysis found only higher BMI significantly associated with lower volume of total gray matter, bilateral orbitofrontal and prefrontal cortexes, and the right hippocampal and frontal cortexes. Increased intensity of residual symptoms (higher Positive and Negative Syndrome Scale scores) was related to lower volumes of frontal lobe, prefrontal cortex, insula, hippocampus, left hemisphere amygdala, and total white matter. The lower volume of left anterior cingulum was associated with older age and higher sIL-2R plasma level; and higher IL-1Ra level was associated with greater right anterior cingulate volume. Older age at illness onset was significantly associated with the smaller right insula volume. CONCLUSIONS: Higher BMI, more residual symptoms, and inflammatory activity in IL-2 and IL-1 systems may play a role in gray matter loss in various brain regions of schizophrenia across the life span.

Differences in outcomes between older community-dwelling patients with bipolar disorder and schizophrenia with illness onset at young age.

AIM: Older community-dwelling patients with severe mental illness (SMI), particularly those with illness onset at young age, constitute a group of survivors with unique long-term care needs. Using an Asian sample in Taiwan, we attempted to find out the differences in outcomes related to physical health, cognition, and social functioning between older community-dwelling adults with bipolar disorder and schizophrenia with early age onset. METHODS: Community-dwelling patients aged >50 years with bipolar I disorder or schizophrenia whose illness developed before the age of 40 years were recruited. Clinical data were obtained by reviewing all available medical records and by interviewing the patients and their reliable family members. Medical morbidities, Mini-Mental State Examination (MMSE), Cumulative Illness Rating Scale for Geriatrics (CIRS-G), and Global Assessment of Functioning (GAF) scores were compared between the two groups. RESULTS: In total, 113 bipolar patients and 104 schizophrenic ones (mean ages = 59.8 and 59.2 years, respectively) became the final subjects. The rates of cognitive impairment (MMSE score <24) were comparable in bipolar disorder (26.5%) and schizophrenia (24.0%) and the mean MMSE scores did not significantly differ from each other. The concurrence (54.9%) of cardiovascular disease (CVD) in the bipolar group was also similar to 51.0% in the schizophrenic one. In a multiple logistic regression analysis, the bipolar group exhibited significantly higher CIRS-G total scores (95% confidence interval (CI) for odds ratio (OR) = 1.01-1.27), body mass index (95% CI for OR = 1.02-1.21), and GAF scores (95% CI for OR = 1.04-1.14). CONCLUSION: Given better social functioning and the same cognitive function in older community-dwelling patients with bipolar disorder, they may remain at higher risk for obesity and medical morbidity than schizophrenic patients. Treatments targeting cognitive impairment and CVDs across their life span are both necessary to promote the health of community-dwellers with SMI.

High risk of silent stroke in older bipolar patients with typical-onset age.

AIM: Older patients with bipolar disorder (BD) are at a high risk of stroke. Silent stroke could be neglected in BD patients after middle age, particularly in those with illness onset at the young age. Therefore, we investigated the morbidity and related factors for stroke in older BD patients with typical-onset age. METHODS: Older patients with bipolar I disorder (age > 50 years) and their illness onset prior to the age of 40 years were recruited. After whole-brain magnetic resonance imaging was conducted, the patients were divided into stroke and non-stroke groups. Clinical data were obtained by reviewing all available medical records and directly interviewing the patients along with their reliable family members. RESULTS: We recruited 62 patients with a mean age of 60.4 years and illness onset at the mean age of 28.4 years. Cerebral infarction or old stroke was observed in 24 (38.7%) patients, including 22 without any reported clinical history of stroke. That is, silent stroke (n = 22) was detected in 36.7% of 60 patients without clinical history of stroke. The stroke group had significantly higher mean numbers of lifetime mood episodes (P = 0.006) than the non-stroke one. Logistic regression analysis showed that 10 or more prior mood episodes (odds ratio = 3.43, 95% confidence interval = 1.12-10.47, P < 0·04) was significantly associated with the occurrence of stroke. The two study groups did not exhibit any other differences in demographic and clinical variables, such as age, laboratory or physical measurements during the last acute psychiatric hospitalisation, body mass index, and substance use problems and concurrent medical diseases. CONCLUSIONS: High morbidity of stroke, particularly silent stroke, could be found in older bipolar patients with typical-onset age. In addition to traditional risk factors, the number of recurrent mood episodes in a lifetime may increase the risk of stroke in older BD patients.

State-dependent alterations of lipid profiles in patients with bipolar disorder.

Objective Serum lipid levels may be associated with the affective severity of bipolar disorder, but data on lipid profiles in Asian patients with bipolar disorder and the lipid alterations in different states of opposite polarities are scant. We investigated the lipid profiles of patients in the acute affective, partial, and full remission state in bipolar mania and depression. Methods The physically healthy patients aged between 18 and 45 years with bipolar I disorder, as well as age-matched healthy normal controls were enrolled. We compared the fasting blood levels of glucose, cholesterol, triglyceride, low-density lipoprotein, and high-density lipoprotein of manic or depressed patients in the acute phase and subsequent partial and full remission with those of their normal controls. Results A total of 32 bipolar manic patients (12 women and 20 men), 32 bipolar depressed participants (18 women and 14 men), and 64 healthy control participants took part in this study. The mean cholesterol level in acute mania was significantly lower than that in acute depression (p < 0.025). The lowest rate of dyslipidemia (hypertriglyceridemia or low high-density lipoprotein cholesterol) was observed in acute bipolar mania. Conclusion Circulating lipid profiles may be easily affected by affective states. The acute manic state may be accompanied by state-dependent lower cholesterol and triglyceride levels relative to that in other mood states.

Efficacy and safety of duloxetine in painful diabetic peripheral neuropathy: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Painful diabetic peripheral neuropathy (PDPN) is a key concern in clinical practice. In this systematic review and meta-analysis, we compared duloxetine and placebo treatments in terms of their efficacy and safety in patients with PDPN. METHODS: Following the PRISMA guidelines, we searched the Cochrane Library, PubMed, and Embase databases for relevant English articles published before January 11, 2021. Treatment efficacy and safety were assessed in terms of pain improvement, patient-reported health-related performance, and patients' quality of life. RESULTS: We reviewed a total of 7 randomized controlled trials. Regarding pain improvement, duloxetine was more efficacious than placebo (mean difference [MD] - 0.89; 95% confidence interval [CI] - 1.09 to - 0.69; P < .00001). Furthermore, duloxetine significantly improved the patients' quality of life, which was assessed using the Clinical Global Impression severity subscale (MD - 0.48; 95% CI - 0.61 to - 0.36; P < .00001), Patient Global Impression of Improvement scale (MD - 0.50; 95% CI - 0.64 to - 0.37; P < .00001), and European Quality of Life Instrument 5D version (MD 0.04; 95% CI 0.02 to 0.07; P = .0002). Severe adverse events were rare, whereas nausea, somnolence, dizziness, fatigue, constipation, and decreased appetite were common; approximately, 12.6% of all patients dropped out because of the common symptoms. CONCLUSIONS: Duloxetine is more efficacious than placebo treatments in patients with PDPN. The rarity of severe adverse events indicates that duloxetine is safe. When a 60-mg dose is insufficient, 120 mg of duloxetine may improve PDPN symptoms. Our findings may help devise optimal treatment strategies for PDPN. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021225451.

Inflammation associated with left ventricular hypertrophy in bipolar disorder: A cross-sectional study.

OBJECTIVE: Inflammation has received increasing attention as a contributor to the pathophysiology of bipolar disorder (BD) and cardiac hypertrophy into heart failure (HF). Accordingly, we chose BD-related inflammatory markers to investigate their relationships with cardiac left ventricular function and structure in BD. METHODS: Sixty physically healthy and euthymic patients with bipolar I disorder were recruited to compare with 50 healthy normal controls. The echocardiography was performed to estimate left ventricular mass index (LVMI) as a parameter of LV hypertrophy (LVH) and left ventricle ejection fraction (LVEF) as a parameter of systolic function. An LVEF above the normal range (>70%) was defined as a hyperdynamic heart. Participants' levels of inflammatory and atherosclerosis-related parameters were measured. RESULTS: Compared with normal controls, BD group had significantly higher rates of LVH (63% vs. 42%) and hyperdynamic heart (32% vs. 2%) and higher mean values of LVMI and LVEF. After adjustment for the effects of BMI and age, multiple regression analyses of BD group showed that the peripheral level of interleukin-8 was positively associated with LVMI and the level of soluble tumor necrosis factor receptor 1 (sTNF-R1) was positively associated with LVEF. CONCLUSIONS: Patients with BD from young adulthood are likely to have LVH with normal LV function and hyperdynamic heart associated with diastolic dysfunction. Low-grade inflammation may underlie the mechanisms of LV hypertrophy and cardiac dysfunction in BD patients.

Distinguishing different types of attention deficit hyperactivity disorder in children using artificial neural network with clinical intelligent test.

Background: Attention deficit hyperactivity disorder (ADHD) is a well-studied topic in child and adolescent psychiatry. ADHD diagnosis relies on information from an assessment scale used by teachers and parents and psychological assessment by physicians; however, the assessment results can be inconsistent. Purpose: To construct models that automatically distinguish between children with predominantly inattentive-type ADHD (ADHD-I), with combined-type ADHD (ADHD-C), and without ADHD. Methods: Clinical records with age 6-17 years-old, for January 2011-September 2020 were collected from local general hospitals in northern Taiwan; the data were based on the SNAP-IV scale, the second and third editions of Conners' Continuous Performance Test (CPT), and various intelligence tests. This study used an artificial neural network to construct the models. In addition, k-fold cross-validation was applied to ensure the consistency of the machine learning results. Results: We collected 328 records using CPT-3 and 239 records using CPT-2. With regard to distinguishing between ADHD-I and ADHD-C, a combination of demographic information, SNAP-IV scale results, and CPT-2 results yielded overall accuracies of 88.75 and 85.56% in the training and testing sets, respectively. The replacement of CPT-2 with CPT-3 results in this model yielded an overall accuracy of 90.46% in the training set and 89.44% in the testing set. With regard to distinguishing between ADHD-I, ADHD-C, and the absence of ADHD, a combination of demographic information, SNAP-IV scale results, and CPT-2 results yielded overall accuracies of 86.74 and 77.43% in the training and testing sets, respectively. Conclusion: This proposed model distinguished between the ADHD-I and ADHD-C groups with 85-90% accuracy, and it distinguished between the ADHD-I, ADHD-C, and control groups with 77-86% accuracy. The machine learning model helps clinicians identify patients with ADHD in a timely manner.

Two meta-analyses of the association between atopic diseases and core symptoms of attention deficit hyperactivity disorder.

Studies in the field of neuroscience and psychology have hypothesized that a causal association exists between atopic diseases and attention-deficit/hyperactivity disorder (ADHD). Previous systematic reviews and meta-analyses have reported a higher risk of ADHD in children with atopic diseases; however, the relationship between ADHD symptoms and atopic diseases remains unclear. We systematically reviewed observational cross-sectional and longitudinal studies to investigate the relationship between atopic diseases and ADHD symptom severity (hyperactivity/impulsivity and inattention). The majority of studies showed a statistically significant association between atopic diseases and both ADHD symptoms, with substantial heterogeneity in the outcome of hyperactivity/impulsivity. Remarkably decreased heterogeneity and statistical significance were observed in the second meta-analysis of ADHD-related behavior symptoms in atopic patients without ADHD. Our study indicated that atopic diseases not only associated with ADHD but also ADHD symptoms severity. This association was even observed in children with subthreshold ADHD, indicating that atopic diseases may play a role in the spectrum of ADHD symptom severity. Trial registration: This study was registered on PROSPERO (registration ID: CRD42020213219).

Lithium exposure and chronic inflammation with activated macrophages and monocytes associated with atherosclerosis in bipolar disorder.

BACKGROUND: Atherosclerosis accounts for cardiovascular diseases (CVDs). This study aimed to explore the association between carotid intima-media thickness (CIMT), psycho-pharmacotherapy, and inflammatory markers along with other molecules related to atherosclerosis in bipolar disorder (BD). METHODS: The euthymic patients with bipolar I disorder (BD-I) aged over 20 years were recruited to measure CIMT through ultrasound and the blood levels of lipid profiles, soluble tumor necrosis factor receptor-1 (sTNF-R1), soluble interleukin-6 receptor (sIL-6R), monocyte chemoattractant protein-1, chitinase 3-like 1, endothelial adhesive proteins, and thrombin-antithrombin complex. RESULTS: Participants were 103 BD-I patients with mean 44.3 years old. The ratio of lithium exposure in relation to illness chronicity and the current daily dosage of lithium therapy exhibited an inverse relationship with CIMT in the entire sample. After controlling for age and BMI, multivariate regression indicated that a higher lithium level was significantly associated with decreased CIMT in the entire sample, high-risk (those with CVDs or endocrine diseases, N = 48), middle-risk (those without CVDs and endocrine diseases, N = 55), and low-risk (those aged <45 years in the middle-risk subgroup, N = 43) subgroups. Furthermore, higher levels of sTNF-R1 in the entire sample and high-risk subgroup and sIL-6R in the middle- and low-risk subgroups were statistically associated with greater CIMT. LIMITATION: The age range was too wide to control for the effect of age on CIMT and medication. CONCLUSIONS: Lithium exposure may be a protective factor for atherosclerosis progression in BD-I. The chronic inflammation in BD-I with activated macrophages and monocytes may link with the atherosclerosis development over time.

Deep learning approach for automatic landmark detection and alignment analysis in whole-spine lateral radiographs.

Human spinal balance assessment relies considerably on sagittal radiographic parameter measurement. Deep learning could be applied for automatic landmark detection and alignment analysis, with mild to moderate standard errors and favourable correlations with manual measurement. In this study, based on 2210 annotated images of various spinal disease aetiologies, we developed deep learning models capable of automatically locating 45 anatomic landmarks and subsequently generating 18 radiographic parameters on a whole-spine lateral radiograph. In the assessment of model performance, the localisation accuracy and learning speed were the highest for landmarks in the cervical area, followed by those in the lumbosacral, thoracic, and femoral areas. All the predicted radiographic parameters were significantly correlated with ground truth values (all p < 0.001). The human and artificial intelligence comparison revealed that the deep learning model was capable of matching the reliability of doctors for 15/18 of the parameters. The proposed automatic alignment analysis system was able to localise spinal anatomic landmarks with high accuracy and to generate various radiographic parameters with favourable correlations with manual measurements.

Factors Predicting the Surgical Risk of Osteoporotic Vertebral Compression Fractures.

The aim of our study was to investigate the association between global spinal alignment, spinopelvic parameters, and outcomes of osteoporotic vertebral compression fractures (OVCF). Patients with vertebral compression fractures seen at our hospital between October 2017 and November of 2018 with a bone mineral density (BMD) T-score < -2.5 were recruited for the study. Surgical intervention was performed after eight weeks of conservative treatment depending on clinical symptoms and the willingness of patients. Spinopelvic and sagittal alignment parameters were compared between patients who had surgery and those that did not. Seventy-nine patients were included in the study. Twenty-five patients (31.6%, mean age: 73.28 ± 9.78 years) received surgery, and 54 (68.3%, mean age: 73 ± 8.58 years) conservative treatment only. Pelvic tilt, pelvic incidence, and local kyphotic angle were statistically different between the groups (all p < 0.05). A sagittal vertical axis ≥ 50 mm, distance between the C7 plumb line and the center of the fractured vertebra (DSVA) ≥ 60 mm, pelvic incidence outside of the range of 44 to 62°), and pelvic tilt ≥ 27° were associted with the need for surgical intervention. Measurement of spinopelvic parameters can predict the need for surgery in patients with OVCF.

Inflammation associated with volume reduction in the gray matter and hippocampus of older patients with bipolar disorder.

BACKGROUND: Bipolar disorder (BD) and aging appear to be associated with inflammatory activation. Inflammatory processes might affect hippocampal function, neurogenesis, and gray matter loss. This study investigated the relationship between BD-specific brain regions and the total gray matter volume, peripheral inflammatory markers, and clinical features in older patients with BD. METHODS: We recruited euthymic patients with bipolar I disorder aged ≥50 years to undergo whole-brain magnetic resonance imaging. Each brain region was divided by an individual's total intracranial volume to obtain that brain region's volume in percentage relative to the total intracranial volume. We measured the plasma levels of soluble tumor necrosis factor receptor-1 (sTNF-R1), soluble interleukin (IL)-2 receptor (sIL-2R), sIL-6R, IL-1ß, and IL-1 receptor antagonist when patients were euthymic. Clinical data were obtained by reviewing available medical records and interviewing patients along with their reliable others. RESULTS: There were 32 patients with a mean age of 61.2 ±â€¯8.3 years and a mean age at illness onset of 33.4 ±â€¯13.8 years in this study. Stepwise regression showed that the right hippocampal volume was negatively associated with the levels of sIL-2R and sTNF-R1. The left hippocampal volume were negatively associated with the sIL-2R level and body mass index. The total gray matter volume had an inverse relationship with sTNF-R1 and IL-1ß levels. The duration of bipolar illness, lithium treatment, and antipsychotic use were not associated with hippocampal and total gray matter volumes. CONCLUSIONS: It is suggested that persistent inflammation is associated with reduction of hippocampal and gray matter volumes in older patients with BD. This phenomenon is supported by increases in sTNF-R1, sIL-2R, and IL-1ß levels. Neuroinflammation due to aging, obesity, and BD pathophysiology may play a role in BD neuroprogression across the life span.

Artificial Intelligence for Automatic Measurement of Sagittal Vertical Axis Using ResUNet Framework.

We present an automated method for measuring the sagittal vertical axis (SVA) from lateral radiography of whole spine using a convolutional neural network for keypoint detection (ResUNet) with our improved localization method. The algorithm is robust to various clinical conditions, such as degenerative changes or deformities. The ResUNet was trained and evaluated on 990 standing lateral radiographs taken at Chang Gung Memorial Hospital, Linkou and performs SVA measurement with median absolute error of 1.183 ± 0.166 mm. The 5-mm detection rate of the C7 body and the sacrum are 91% and 87%, respectively. The SVA calculation takes approximately 0.2 s per image. The intra-class correlation coefficient of the SVA estimates between the algorithm and physicians of different years of experience ranges from 0.946 to 0.993, indicating an excellent consistency. The superior performance of the proposed method and its high consistency with physicians proved its usefulness for automatic measurement of SVA in clinical settings.

Remission of classic rapid cycling bipolar disorder with levothyroxine augmentation therapy in a male patient having clinical hypothyroidism.

The literature suggests that patients with bipolar disorder, particularly females, have greater vulnerability to rapid cycling features. Levothyroxine therapy might be potentially useful to attenuate mood instability in this patient group. In contrast, reports on male patients remain limited and controversial. Herein, we report a 32-year-old male patient who had bipolar 1 disorder for 12 years who developed a breakthrough rapid cycling course and first-onset clinical hypothyroidism at the age of 31 years during lithium therapy. After levothyroxine augmentation therapy was introduced, the patient had remission from the rapid cycling illness course along with normalization of serum levels of free T4 and thyroid stimulating hormone in the subsequent year. This observation suggested that investigation of both levothyroxine pharmacology and thyroid pathology in male patients with rapid cycling bipolar disorder might be of much value.