A sleep stage estimation algorithm based on cardiorespiratory signals derived from a suprasternal pressure sensor.

Automatic estimation of sleep structure is an important aspect in moving sleep monitoring from clinical laboratories to people's homes. However, the transition to more portable systems should not happen at the expense of important physiological signals, such as respiration. Here, we propose the use of cardiorespiratory signals obtained by a suprasternal pressure (SSP) sensor to estimate sleep stages. The sensor is already used for diagnosis of sleep-disordered breathing (SDB) conditions, but besides respiratory effort it can detect cardiac vibrations transmitted through the trachea. We collected the SSP sensor signal in 100 adults (57 male) undergoing clinical polysomnography for suspected sleep disorders, including sleep apnea syndrome, insomnia, and movement disorders. Here, we separate respiratory effort and cardiac activity related signals, then input these into a neural network trained to estimate sleep stages. Using the original mixed signal the results show a moderate agreement with manual scoring, with a Cohen's kappa of 0.53 in Wake/N1-N2/N3/rapid eye movement sleep discrimination and 0.62 in Wake/Sleep. We demonstrate that decoupling the two signals and using the cardiac signal to estimate the instantaneous heart rate improves the process considerably, reaching an agreement of 0.63 and 0.71. Our proposed method achieves high accuracy, specificity, and sensitivity across different sleep staging tasks. We also compare the total sleep time calculated with our method against manual scoring, with an average error of -1.83 min but a relatively large confidence interval of ±55 min. Compact systems that employ the SSP sensor information-rich signal may enable new ways of clinical assessments, such as night-to-night variability in obstructive sleep apnea and other sleep disorders.

Automated Scoring of Sleep and Associated Events.

Conventionally, sleep and associated events are scored visually by trained technologists according to the rules summarized in the American Academy of Sleep Medicine Manual. Since its first publication in 2007, the manual was continuously updated; the most recent version as of this writing was published in 2020. Human expert scoring is considered as gold standard, even though there is increasing evidence of limited interrater reliability between human scorers. Significant advances in machine learning have resulted in powerful methods for addressing complex classification problems such as automated scoring of sleep and associated events. Evidence is increasing that these autoscoring systems deliver performance comparable to manual scoring and offer several advantages to visual scoring: (1) avoidance of the rather expensive, time-consuming, and difficult visual scoring task that can be performed only by well-trained and experienced human scorers, (2) attainment of consistent scoring results, and (3) proposition of added value such as scoring in real time, sleep stage probabilities per epoch (hypnodensity), estimates of signal quality and sleep/wake-related features, identifications of periods with clinically relevant ambiguities (confidence trends), configurable sensitivity and rule settings, as well as cardiorespiratory sleep staging for home sleep apnea testing. This chapter describes the development of autoscoring systems since the first attempts in the 1970s up to the most recent solutions based on deep neural network approaches which achieve an accuracy that allows to use the autoscoring results directly for review and interpretation by a physician.

Acute autoimmune-like hepatitis with atypical anti-mitochondrial antibody after mRNA COVID-19 vaccination: A novel clinical entity?

Autoimmune phenomena and clinically apparent autoimmune diseases, including autoimmune hepatitis, are increasingly been reported not only after natural infection with the SARS-CoV-2 virus, but also after vaccination against it. We report the case of a 63-year old man without a history of autoimmunity or SARS-CoV-2 natural infection who experienced acute severe autoimmune-like hepatitis seven days after the first dose of the mRNA-1273 SARS-CoV-2 vaccine. Liver histology showed inflammatory portal infiltrate with interface hepatitis, lobular and centrilobular inflammation with centrilobular necrosis, in absence of fibrosis and steatosis. Serum immunoglobulin G was slightly elevated. Autoimmune liver serology showed an indirect immunofluorescence pattern on triple rodent tissue compatible with anti-mitochondrial antibody (AMA), but, unexpectedly, this pattern was not mirrored by positivity for primary biliary cholangitis (PBC)-specific molecular tests, indicating that this antibody is different from classical AMA. Anti-nuclear antibody (ANA) was also positive with a rim-like indirect immunofluorescence pattern on liver and HEp2 cell substrates, similar to PBC-specific ANA; however, anti-gp210 and a large panel of molecular-based assays for nuclear antigens were negative, suggesting a unique ANA in our patient. He carries the HLA DRB1*11:01 allele, which is protective against PBC. Response to prednisone treatment was satisfactory. The clinical significance of these novel specificities needs to be further evaluated in this emerging condition.

Primary biliary cholangitis with normal alkaline phosphatase: A neglected clinical entity challenging current guidelines.

BACKGROUND & AIM: The diagnosis of primary biliary cholangitis (PBC), an uncommon immune-mediated cholestatic liver disease, is based on positive circulating anti-mitochondrial (AMA) and/or PBC-specific anti-nuclear autoantibodies (ANA), coupled with elevated serum alkaline phopsphatase (ALP) levels. Timely initiation of treatment with ursodeoxycholic acid prevents progression to cirrhosis and liver failure. We aimed at investigating liver histology in patients with normal ALP level and positive AMA and/or PBC-specific ANA. METHODS: We searched the Swiss PBC Cohort Study database, which includes subjects with positive PBC autoimmune serology and normal ALP levels, for patients who underwent a liver biopsy. Histological slides were centrally reviewed by an expert liver pathologist, and sera were centrally re-tested for AMA and ANA. RESULTS: 30 patients were included; 90% females, median age 53 (range 27-72) years. Twenty-four (80%) had liver histology typical for (n = 2), consistent with (n = 16) or suggestive of (n = 6) PBC, including three of four AMA-negative ANA-positive patients. Among 22 ursodeoxycholic acid treated patients, 14 had elevated GGT levels before treatment; a significant decrease of the median GGT level between pre- (1.46 x ULN) and post- (0.43 x ULN) treatment (p = 0.0018) was observed. CONCLUSIONS: In our series, a high proportion of AMA positive patients with normal ALP levels have PBC. For the first time we show histological diagnosis of PBC in AMA-negative/PBC-specific ANA-positive subjects and the potential role of GGT as a biomarker in PBC patients with normal baseline ALP levels. Current guidelines for the diagnosis of PBC do not cover the whole extent of PBC presentation, with important clinical implications in terms of timely treatment initiation.

Safety of mRNA-Based Vaccines for SARS CoV-2.

SARS-CoV-2 has infected more than 100 million people, causing 2 million deaths globally. Studies on the development of a vaccine ended up with different formulations. We herein discuss the safety record of the two approved vaccines.

Autoimmune liver serology before and after successful treatment of chronic hepatitis C by direct acting antiviral agents.

BACKGROUND AND AIMS: Chronic hepatitis C virus (HCV) infection is associated with a wide range of immunopathological manifestations, which are significantly improved by successful interferon-based treatment. There is paucity of data on the impact of interferon-free HCV clearance on immunopathological manifestations, which might be expected to disappear more frequently as compared to what reported in interferon-induced HCV-clearance. We have investigated liver autoimmune serology before and after interferon-free clearance of HCV by treatment with direct acting antiviral agents (DAA). METHOD: Patients within the Swiss Hepatitis C Cohort Study who underwent successful (SVR 12) HCV treatment with DAA were tested for autoimmune liver serology according to dedicated guidelines before and at least 6 months after end of treatment. RESULTS: A total of 235 patients were included; 62% males; median age 56 years; 27% with cirrhosis. Median time between end of DAA treatment and post-treatment serum sampling was 17 months. At least one autoantibody before treatment was found in 175 (74%) patients ; 32 (14%) were positive for 2 autoantibodies; no patient was positive for anti-SLA, anti-LC1 or typical AMA before or after DAA. ANA disappeared in 34%, SMA in 52% and anti-LKM1 in one of two patients after successful treatment, but, unexpectedly, one or more autoantibodies appeared in 27% of pre-treatment negative subjects. CONCLUSION: HCV clearance by DAA is associated with autoantibody disappearance in more than one third of the patients who were positive before treatment. However, the majority of the patients remain autoantibody-positive and 27% of those who were negative before treatment developed autoantibodies after DAA-induced HCV clearance. These data confirm that HCV infection is associated with autoimmunity and show that the autoimmune imprint persists after viral clearance by DAA, suggesting that long-term follow-up may be warranted.

Autoimmune liver disease serology in acute hepatitis E virus infection.

The etiology of autoimmune hepatitis (AIH) is unknown, though hepatotropic viruses may be potential triggers. Hepatitis E virus (HEV) infection, an increasingly recognized cause of acute hepatitis, has been misdiagnosed as AIH due to the occurrence of autoantibodies during its acute phase. It has also been suggested that HEV infection may lead to or unmask AIH. The HEV seroprevalence has been ascertained in patients with AIH, but the prevalence of AIH-related autoantibodies in patients with HEV infection has not been systematically tested. We aimed to investigate whether acute HEV infection is associated with the presence of AIH-relevant autoantibodies, following the liver autoimmune serology guidelines of the International AIH Group. We tested 48 patients with acute HEV infection. Half of them had at least one autoantibody, 17% two autoantibodies. Anti-nuclear antibody (ANA) were detected in 16 (33%), anti-smooth muscle antibody (SMA) in 10 (21%), and anti-neutrophil cytoplasmic antibody (ANCA) in 7 (14.6%). Of note, two patients showed SMA with VG or VGT patterns and five had ANA with homogeneous appearance, both being typical of AIH type 1. Other AIH-specific autoantibodies were negative. Atypical anti-mitochondrial antibody, without evidence of primary biliary cholangitis, was positive in one patient, disappearing at follow-up. Follow-up (median 12 months) serum was available from seven autoantibody positive patients: two became negative, while five remained positive, although no patient developed AIH to date. In conclusion, autoantibodies are frequently present during acute HEV infection, indicating that HEV should always be excluded before diagnosing AIH. Importantly, a minority of patients with acute hepatitis E develops AIH-specific autoantibodies, and, though they did not progress to autoimmune liver disease in the short-term, they warrant long-term monitoring.

A new 3p25 locus is associated with liver fibrosis progression in human immunodeficiency virus/hepatitis C virus-coinfected patients.

There is growing evidence that human genetic variants contribute to liver fibrosis in subjects with hepatitis C virus (HCV) monoinfection, but this aspect has been little investigated in patients coinfected with HCV and human immunodeficiency virus (HIV). We performed the first genome-wide association study of liver fibrosis progression in patients coinfected with HCV and HIV, using the well-characterized French National Agency for Research on AIDS and Viral Hepatitis CO13 HEPAVIH cohort. Liver fibrosis was assessed by elastography (FibroScan), providing a quantitative fibrosis score. After quality control, a genome-wide association study was conducted on 289 Caucasian patients, for a total of 8,426,597 genotyped (Illumina Omni2.5 BeadChip) or reliably imputed single-nucleotide polymorphisms. Single-nucleotide polymorphisms with P values <10-6 were investigated in two independent replication cohorts of European patients infected with HCV alone. Two signals of genome-wide significance (P < 5 × 10-8 ) were obtained. The first, on chromosome 3p25 and corresponding to rs61183828 (P = 3.8 × 10-9 ), was replicated in the two independent cohorts of patients with HCV monoinfection. The cluster of single-nucleotide polymorphisms in linkage disequilibrium with rs61183828 was located close to two genes involved in mechanisms affecting both cell signaling and cell structure (CAV3) or HCV replication (RAD18). The second signal, obtained with rs11790131 (P = 9.3 × 10-9 ) on chromosome region 9p22, was not replicated. CONCLUSION: This genome-wide association study identified a new locus associated with liver fibrosis severity in patients with HIV/HCV coinfection, on chromosome 3p25, a finding that was replicated in patients with HCV monoinfection; these results provide new relevant hypotheses for the pathogenesis of liver fibrosis in patients with HIV/HCV coinfection that may help define new targets for drug development or new prognostic tests, to improve patient care. (Hepatology 2016;64:1462-1472).

A systematic review and meta-analysis of HCV clearance.

While hepatitis C exemplifies the role of host genetics in infectious diseases outcomes, there is no comprehensive overview of polymorphisms influencing spontaneous and/or treatment-induced hepatitis C virus clearance. We performed a systematic review and meta-analysis of host polymorphisms associated with these phenotypes. Literature search was conducted using combinations of keywords in three databases. Studies were reviewed and relevant data systematically extracted for subsequent meta-analyses. Polymorphisms from candidate gene studies were tested in two cohorts of HCV-infected patients with available genomic data. The literature search yielded 8'294 citations, among which 262 studies were selected. In the meta-analysis of 27 HLA studies, the most significant associations with spontaneous hepatitis C virus clearance included DQB1*02, DQB1*03, DRB1*04 and DRB1*11. In the meta-analysis of 16 studies of KIR genes and their HLA-ligands, KIR2DS3 was associated with both spontaneous and treatment-induced clearance, and the HLA-C2 ligand with failure to spontaneously clear the virus. In a pooled analysis of 105 candidate genes and two genome-wide association studies, we observed associations of single nucleotide polymorphisms from nine genes (EIF2AK2, IFNAR2, ITPA, MBL2, MX1, OASL, SPP1, TGFB1, TNK2) with response to interferon-based therapy. Meta-analysis of 141 studies confirmed the association of IFNL3/4 polymorphisms with spontaneous and treatment-induced hepatitis C virus clearance, even in previously underpowered groups, such as hepatitis C virus genotypes 2/3-infected patients. This study may contribute to a better understanding of hepatitis C virus immunopathogenesis and highlights the complex role of host genetics in hepatitis C virus clearance.

Elderly age is not a negative predictive factor for virological response to therapy with pegylated interferon-α and ribavirin in chronic hepatitis C virus patients.

BACKGROUND & AIMS: Age is frequently discussed as negative host factor to achieve a sustained virological response (SVR) to antiviral therapy of chronic hepatitis C. However, elderly patients often show advanced fibrosis/cirrhosis as known negative predictive factor. The aim of this study was to assess age as an independent predictive factor during antiviral therapy. METHODS: Overall, 516 hepatitis C patients were treated with pegylated interferon-α and ribavirin, thereof 66 patients ≥60 years. We analysed the impact of host factors (age, gender, fibrosis, haemoglobin, previous hepatitis C treatment) and viral factors (genotype, viral load) on SVR per therapy course by performing a generalized estimating equations (GEE) regression modelling, a matched pair analysis and a classification tree analysis. RESULTS: Overall, SVR per therapy course was 42.9 and 26.1%, respectively, in young and elderly patients with hepatitis C virus (HCV) genotypes 1/4/6. The corresponding figures for HCV genotypes 2/3 were 74.4 and 84%. In the GEE model, age had no significant influence on achieving SVR. In matched pair analysis, SVR was not different in young and elderly patients (54.2 and 55.9% respectively; P = 0.795 in binominal test). In classification tree analysis, age was not a relevant splitting variable. CONCLUSIONS: Age is not a significant predictive factor for achieving SVR, when relevant confounders are taken into account. As life expectancy in Western Europe at age 60 is more than 20 years, it is reasonable to treat chronic hepatitis C in selected elderly patients with relevant fibrosis or cirrhosis but without major concomitant diseases, as SVR improves survival and reduces carcinogenesis.

Estimating the severity of obstructive sleep apnea using ECG, respiratory effort and neural networks.

OBJECTIVE: wearable sensor technology has progressed significantly in the last decade, but its clinical usability for the assessment of obstructive sleep apnea (OSA) is limited by the lack of large and representative datasets simultaneously acquired with polysomnography (PSG). The objective of this study was to explore the use of cardiorespiratory signals commonly available in standard PSGs which can be easily measured with wearable sensors, to estimate the severity of OSA. METHODS: an artificial neural network was developed for detecting sleep disordered breathing events using electrocardiogram (ECG) and respiratory effort. The network was combined with a previously developed cardiorespiratory sleep staging algorithm and evaluated in terms of sleep staging classification performance, apnea-hypopnea index (AHI) estimation, and OSA severity estimation against PSG on a large cohort of 653 participants with a wide range of OSA severity. RESULTS: four-class sleep staging achieved a κ of 0.69 with PSG, distinguishing wake, combined N1-N2, N3 and REM. AHI estimation achieved an intraclass correlation coefficient of 0.91, and high diagnostic performance for different OSA severity thresholds. CONCLUSIONS: this study highlights the potential of using cardiorespiratory signals to estimate OSA severity, even without the need for airflow or oxygen saturation (SpO2), traditionally used for assessing OSA. SIGNIFICANCE: while further research is required to translate these findings to practical and unobtrusive sensors, this study demonstrates how existing, large datasets can serve as a foundation for wearable systems for OSA monitoring. Ultimately, this approach could enable long-term assessment of sleep disordered breathing, facilitating new avenues for clinical research in this field.

Performance of cardiorespiratory-based sleep staging in patients using beta blockers.

STUDY OBJECTIVES: Automatic sleep staging based on cardiorespiratory signals from home sleep monitoring devices holds great clinical potential. Using state-of-the-art machine learning, promising performance has been reached in patients with sleep disorders. However, it is unknown whether performance would hold in individuals with potentially altered autonomic physiology, for example under the influence of medication. Here, we assess an existing sleep staging algorithm in patients with sleep disorders with and without the use of beta blockers. METHODS: We analyzed a retrospective dataset of sleep recordings of 57 patients with sleep disorders using beta blockers and 57 age-matched patients with sleep disorders not using beta blockers. Sleep stages were automatically scored based on electrocardiography and respiratory effort from a thoracic belt, using a previously developed machine-learning algorithm (CReSS algorithm). For both patient groups, sleep stages classified by the model were compared to gold standard manual polysomnography scoring using epoch-by-epoch agreement. Additionally, for both groups, overall sleep parameters were calculated and compared between the two scoring methods. RESULTS: Substantial agreement was achieved for four-class sleep staging in both patient groups (beta blockers: kappa = 0.635, accuracy = 78.1%; controls: kappa = 0.660, accuracy = 78.8%). No statistical difference in epoch-by-epoch agreement was found between the two groups. Additionally, the groups did not differ on agreement of derived sleep parameters. CONCLUSIONS: We showed that the performance of the CReSS algorithm is not deteriorated in patients using beta blockers. Results do not indicate a fundamental limitation in leveraging autonomic characteristics to obtain a surrogate measure of sleep in this clinically relevant population. CITATION: Hermans L, van Meulen F, Anderer P, et al. Performance of cardiorespiratory-based sleep staging in patients using beta blockers. J Clin Sleep Med. 2024;20(4):575-581.

Comparative genetic analyses point to HCP5 as susceptibility locus for HCV-associated hepatocellular carcinoma.

BACKGROUND & AIMS: Recently, genetic variations in MICA (lead single nucleotide polymorphism [SNP] rs2596542) were identified by a genome-wide association study (GWAS) to be associated with hepatitis C virus (HCV)-related hepatocellular carcinoma (HCC) in Japanese patients. In the present study, we sought to determine whether this SNP is predictive of HCC development in the Caucasian population as well. METHODS: An extended region around rs2596542 was genotyped in 1924 HCV-infected patients from the Swiss Hepatitis C Cohort Study (SCCS). Pair-wise correlation between key SNPs was calculated both in the Japanese and European populations (HapMap3: CEU and JPT). RESULTS: To our surprise, the minor allele A of rs2596542 in proximity of MICA appeared to have a protective impact on HCC development in Caucasians, which represents an inverse association as compared to the one observed in the Japanese population. Detailed fine-mapping analyses revealed a new SNP in HCP5 (rs2244546) upstream of MICA as strong predictor of HCV-related HCC in the SCCS (univariable p=0.027; multivariable p=0.0002, odds ratio=3.96, 95% confidence interval=1.90-8.27). This newly identified SNP had a similarly directed effect on HCC in both Caucasian and Japanese populations, suggesting that rs2244546 may better tag a putative true variant than the originally identified SNPs. CONCLUSIONS: Our data confirms the MICA/HCP5 region as susceptibility locus for HCV-related HCC and identifies rs2244546 in HCP5 as a novel tagging SNP. In addition, our data exemplify the need for conducting meta-analyses of cohorts of different ethnicities in order to fine map GWAS signals.

Genome-wide association study identifies variants associated with progression of liver fibrosis from HCV infection.

BACKGROUND & AIMS: Polymorphisms in IL28B were shown to affect clearance of hepatitis C virus (HCV) infection in genome-wide association (GWA) studies. Only a fraction of patients with chronic HCV infection develop liver fibrosis, a process that might also be affected by genetic factors. We performed a 2-stage GWA study of liver fibrosis progression related to HCV infection. METHODS: We studied well-characterized HCV-infected patients of European descent who underwent liver biopsies before treatment. We defined various liver fibrosis phenotypes on the basis of METAVIR scores, with and without taking the duration of HCV infection into account. Our GWA analyses were conducted on a filtered primary cohort of 1161 patients using 780,650 single nucleotide polymorphisms (SNPs). We genotyped 96 SNPs with P values <5 × 10(-5) from an independent replication cohort of 962 patients. We then assessed the most interesting replicated SNPs using DNA samples collected from 219 patients who participated in separate GWA studies of HCV clearance. RESULTS: In the combined cohort of 2342 HCV-infected patients, the SNPs rs16851720 (in the total sample) and rs4374383 (in patients who received blood transfusions) were associated with fibrosis progression (P(combined) = 8.9 × 10(-9) and 1.1 × 10(-9), respectively). The SNP rs16851720 is located within RNF7, which encodes an antioxidant that protects against apoptosis. The SNP rs4374383, together with another replicated SNP, rs9380516 (P(combined) = 5.4 × 10(-7)), were linked to the functionally related genes MERTK and TULP1, which encode factors involved in phagocytosis of apoptotic cells by macrophages. CONCLUSIONS: Our GWA study identified several susceptibility loci for HCV-induced liver fibrosis; these were linked to genes that regulate apoptosis. Apoptotic control might therefore be involved in liver fibrosis.

Serum ferritin levels are associated with a distinct phenotype of chronic hepatitis C poorly responding to pegylated interferon-alpha and ribavirin therapy.

UNLABELLED: Elevated serum ferritin levels may reflect a systemic inflammatory state as well as increased iron storage, both of which may contribute to an unfavorable outcome of chronic hepatitis C (CHC). We therefore performed a comprehensive analysis of the role of serum ferritin and its genetic determinants in the pathogenesis and treatment of CHC. To this end, serum ferritin levels at baseline of therapy with pegylated interferon-alpha and ribavirin or before biopsy were correlated with clinical and histological features of chronic hepatitis C virus (HCV) infection, including necroinflammatory activity (N = 970), fibrosis (N = 980), steatosis (N = 886), and response to treatment (N = 876). The association between high serum ferritin levels (> median) and the endpoints was assessed by logistic regression. Moreover, a candidate gene as well as a genome-wide association study of serum ferritin were performed. We found that serum ferritin ≥ the sex-specific median was one of the strongest pretreatment predictors of treatment failure (univariate P < 0.0001, odds ratio [OR] = 0.45, 95% confidence interval [CI] = 0.34-0.60). This association remained highly significant in a multivariate analysis (P = 0.0002, OR = 0.35, 95% CI = 0.20-0.61), with an OR comparable to that of interleukin (IL)28B genotype. When patients with the unfavorable IL28B genotypes were stratified according to high versus low ferritin levels, SVR rates differed by > 30% in both HCV genotype 1- and genotype 3-infected patients (P < 0.001). Serum ferritin levels were also independently associated with severe liver fibrosis (P < 0.0001, OR = 2.67, 95% CI = 1.68-4.25) and steatosis (P = 0.002, OR = 2.29, 95% CI = 1.35-3.91), but not with necroinflammatory activity (P = 0.3). Genetic variations had only a limited impact on serum ferritin levels. CONCLUSION: In patients with CHC, elevated serum ferritin levels are independently associated with advanced liver fibrosis, hepatic steatosis, and poor response to interferon-alpha-based therapy.

IL28B alleles associated with poor hepatitis C virus (HCV) clearance protect against inflammation and fibrosis in patients infected with non-1 HCV genotypes.

UNLABELLED: Genetic polymorphisms near IL28B are associated with spontaneous and treatment-induced clearance of hepatitis C virus (HCV), two processes that require the appropriate activation of the host immune responses. Intrahepatic inflammation is believed to mirror such activation, but its relationship with IL28B polymorphisms has yet to be fully appreciated. We analyzed the association of IL28B polymorphisms with histological and follow-up features in 2335 chronically HCV-infected Caucasian patients. Assessable phenotypes before any antiviral treatment included necroinflammatory activity (n = 1,098), fibrosis (n = 1,527), fibrosis progression rate (n = 1,312), and hepatocellular carcinoma development (n = 1,915). Associations of alleles with the phenotypes were evaluated by univariate analysis and multivariate logistic regression, accounting for all relevant covariates. The rare G allele at IL28B marker rs8099917-previously shown to be at risk of treatment failure-was associated with lower activity (P = 0.04), lower fibrosis (P = 0.02) with a trend toward lower fibrosis progression rate (P = 0.06). When stratified according to HCV genotype, most significant associations were observed in patients infected with non-1 genotypes (P = 0.003 for activity, P = 0.001 for fibrosis, and P = 0.02 for fibrosis progression rate), where the odds ratio of having necroinflammation or rapid fibrosis progression for patients with IL28B genotypes TG or GG versus TT were 0.48 (95% confidence intervals 0.30-0.78) and 0.56 (0.35-0.92), respectively. IL28B polymorphisms were not predictive of the development of hepatocellular carcinoma. CONCLUSION: In chronic hepatitis C, IL28B variants associated with poor response to interferon therapy may predict slower fibrosis progression, especially in patients infected with non-1 HCV genotypes.

Autonomic arousal detection and cardio-respiratory sleep staging improve the accuracy of home sleep apnea tests.

Introduction: The apnea-hypopnea index (AHI), defined as the number of apneas and hypopneas per hour of sleep, is still used as an important index to assess sleep disordered breathing (SDB) severity, where hypopneas are confirmed by the presence of an oxygen desaturation or an arousal. Ambulatory polygraphy without neurological signals, often referred to as home sleep apnea testing (HSAT), can potentially underestimate the severity of sleep disordered breathing (SDB) as sleep and arousals are not assessed. We aim to improve the diagnostic accuracy of HSATs by extracting surrogate sleep and arousal information derived from autonomic nervous system activity with artificial intelligence. Methods: We used polysomnographic (PSG) recordings from 245 subjects (148 with simultaneously recorded HSATs) to develop and validate a new algorithm to detect autonomic arousals using artificial intelligence. A clinically validated auto-scoring algorithm (Somnolyzer) scored respiratory events, cortical arousals, and sleep stages in PSGs, and provided respiratory events and sleep stages from cardio-respiratory signals in HSATs. In a four-fold cross validation of the newly developed algorithm, we evaluated the accuracy of the estimated arousal index and HSAT-derived surrogates for the AHI. Results: The agreement between the autonomic and cortical arousal index was moderate to good with an intraclass correlation coefficient of 0.73. When using thresholds of 5, 15, and 30 to categorize SDB into none, mild, moderate, and severe, the addition of sleep and arousal information significantly improved the classification accuracy from 70.2% (Cohen's κ = 0.58) to 80.4% (κ = 0.72), with a significant reduction of patients where the severity category was underestimated from 18.8% to 7.3%. Discussion: Extracting sleep and arousal information from autonomic nervous system activity can improve the diagnostic accuracy of HSATs by significantly reducing the probability of underestimating SDB severity without compromising specificity.