The effect of weight gain and metabolic dysfunction-associated steatotic liver disease on liver fibrosis progression and regression in people with HIV.

OBJECTIVE: People with HIV (PWH) have high risk of liver fibrosis. We investigated the effect of weight gain and metabolic dysfunction-associated steatotic liver disease (MASLD) on liver fibrosis dynamics. DESIGN: Multicenter cohort study. METHODS: Fibrosis progression was defined as development of significant fibrosis (liver stiffness measurement [LSM]≥8 kPa), or transition to cirrhosis (LSM≥13 kPa), for those with significant fibrosis at baseline. Fibrosis regression was defined as transition to LSM<8 kPa, or to LSM<13 kPa for those with cirrhosis at baseline. MASLD was defined as hepatic steatosis (controlled attenuation parameter >248 dB/m) with at least one metabolic abnormality. A continuous-time multi-state Markov model was used to describe transitions across fibrosis states. RESULTS: Among 1183 PWH included from three centres (25.2% with viral hepatitis coinfection), baseline prevalence of significant fibrosis and MASLD was 14.4% and 46.8%, respectively. During a median follow-up of 2.5 years (interquartile range 1.9-3.5) the incidence rate of fibrosis progression and regression was 2.8 (95% CI, 2.3-3.4) and 2.2 (95% CI, 1.9-2.6) per 100 person-years, respectively. In Markov model, weight gain increased the odds of fibrosis progression (odds ratio [OR] 3.11, 95% CI 1.59-6.08), whereas weight gain (OR 0.30, 95% CI 0.10-0.84) and male sex (OR 0.32, 95% CI 0.14-0.75) decreased the odds of fibrosis regression. On multivariable Cox regression analysis, predictors of fibrosis progression were weight gain (adjusted hazard ratio [aHR] 3.12, 95% CI 1.41-6.90) and MASLD (aHR 2.72, 95% CI 1.05-7.02). CONCLUSIONS: Fibrosis transitions are driven by metabolic health variables in PWH, independently of viral hepatitis coinfection and antiretroviral class therapy.

Association between Second-Hand Exposure to E-Cigarettes at Home and Exacerbations in Children with Asthma.

Several studies have shown the effects of e-cigarettes in adults. Nowadays, few data are available in the pediatric population. This study aims to assess the relationship between asthma exacerbations and home exposure to e-cigarettes. We conducted a pilot, retrospective, monocenter, observational study. Demographic and clinical data were collected, including number of asthma exacerbations, need for rescue therapy and/or therapeutic step-up, and Asthma Control Test (ACT) and children-Asthma Control Test (c-ACT) scores. The cohort consisted of 54 patients (5-17 years old), divided into two groups: A, including patients exposed to e-cigarette aerosols; B, including unexposed patients. The statistical analysis showed no relevant variation in the number of asthma symptomatic days and need for rescue therapy in group A versus group B (p = 0.27 and 0.19, respectively). There were no statistically significant variations when also considering the number of patients who needed a therapeutic step-up (p = 0.3). The mean values of ACT and c-ACT were, respectively, 17.2 ± 7.6 and 18.3 ± 5.6 in group A and 19.6 ± 3.8 and 14.6 ± 5.8 in group B (p = 0.3 and 0.4, respectively). Although we did not find a statistically significant correlation between second-hand e-cigarette exposure and asthma exacerbations, our findings suggest that asthmatic children exposed second-hand to e-cigarettes may have increased risk of asthma symptomatic days. Future research is warranted.

Bone Mineral Density and Trabecular Bone Score Changes throughout Menopause in Women with HIV.

OBJECTIVE: The objectives of this study were to describe the trajectories of bone mineral density (BMD) and trabecular bone score (TBS) changes throughout pre-menopause (reproductive phase and menopausal transition) and post-menopause (early and late menopause) in women with HIV (WWH) undergoing different antiretroviral therapies (ARTs) and explore the risk factors associated with those changes. METHODS: This was an observational longitudinal retrospective study in WWH with a minimum of two DEXA evaluations comprising BMD and TBS measurements, both in the pre-menopausal and post-menopausal periods. Menopause was determined according to the STRAW+10 criteria, comprising four periods: the reproductive period, menopausal transition, and early- and late-menopausal periods. Mixed-effects models were fitted to estimate the trajectories of the two outcomes (BMD and TBS) over time. Annualized lumbar BMD and TBS absolute and percentage changes were calculated in each STRAW+10 time window. A backward elimination procedure was applied to obtain the final model, including the predictors that affected the trajectories of BMD or TBS over time. RESULTS: A total of 202 WWH, all Caucasian, were included. In detail, 1954 BMD and 195 TBS data were analyzed. The median number of DEXA evaluations per woman was 10 (IQR: 7, 12). The median observation periods per patient were 12.0 years (IQR = 8.9-14.4) for BMD and 6.0 years (IQR: 4.3, 7.9) for TBS. The prevalence of osteopenia (63% vs. 76%; p < 0.001) and osteoporosis (16% vs. 36%; p < 0.001) increased significantly between the pre-menopausal and post-menopausal periods. Both BMD (1.03 (±0.14) vs. 0.92 (±0.12) g/cm2; p < 0.001) and TBS (1.41 (IQR: 1.35, 1.45) vs. 1.32 (IQR: 1.28, 1.39); p < 0.001) decreased significantly between the two periods. The trend in BMD decreased across the four STRAW+10 periods, with a slight attenuation only in the late-menopausal period when compared with the other intervals. The TBS slope did not significantly change throughout menopause. The delta mean values of TBS in WWH were lower between the menopausal transition and reproductive period compared with the difference between menopause and menopausal transition. CONCLUSIONS: Both BMD and TBS significantly decreased over time. The slope of the change in BMD and TBS significantly decreased in the menopausal transition, suggesting that this period should be considered by clinicians as a key time during which to assess bone health and modifiable risk factors in WWH.

A Machine Learning Approach to Predict Weight Change in ART-Experienced People Living With HIV.

INTRODUCTION: The objective of the study was to develop machine learning (ML) models that predict the percentage weight change in each interval of time in antiretroviral therapy-experienced people living with HIV. METHODS: This was an observational study that comprised consecutive people living with HIV attending Modena HIV Metabolic Clinic with at least 2 visits. Data were partitioned in an 80/20 training/test set to generate 10 progressively parsimonious predictive ML models. Weight gain was defined as any weight change >5%, at the next visit. SHapley Additive exPlanations values were used to quantify the positive or negative impact of any single variable included in each model on the predicted weight changes. RESULTS: A total of 3,321 patients generated 18,322 observations. At the last observation, the median age was 50 years and 69% patients were male. Model 1 (the only 1 including body composition assessed with dual-energy x-ray absorptiometry) had an accuracy greater than 90%. This model could predict weight at the next visit with an error of <5%. CONCLUSIONS: ML models with the inclusion of body composition and metabolic and endocrinological variables had an excellent performance. The parsimonious models available in standard clinical evaluation are insufficient to obtain reliable prediction, but are good enough to predict who will not experience weight gain.

Sarcopenic Obesity Phenotypes in Patients With HIV: Implications for Cardiovascular Prevention and Rehabilitation.

BACKGROUND: We aimed to describe prevalence, incidence, and risk factors for sarcopenic obesity (SO) phenotypes in people living with HIV (PWH) and their association with subclinical cardiovascular disease (CVD). METHODS: Observational, longitudinal study of PWH. A minimum of 1 criterion was necessary to diagnose sarcopenia: weak hand grip (HG), low appendicular skeletal muscle index (ASMI), short physical performance battery (SPPB < 11). Obesity was defined as body mass index (BMI) ≥ 30 kg/m2 or visceral adipose tissue (VAT) ≥ 160 cm2. These variables combined generated 5 SO phenotypes: severe SO: low HG + low ASMI + low SPPB + high BMI; SO1: weak HG + high VAT; SO2: weak HG + high BMI; SO3: low ASMI + high VAT; SO4: low ASMI + high BMI. Subclinical CVD was defined as carotid intima-media thickness (IMT) ≥ 1 mm, presence of carotid plaque, or coronary artery calcification (CAC) score > 10. RESULTS: Among 2379 male PWH 72%, median age was 52 years, median HIV vintage 21 years, and median BMI 24 kg/m2. Two PWH had severe SO. The prevalence of SO1-SO4 was 19.7%, 3.6%, 20.8% and 0.8%, respectively. Incidence of SO1-SO4 was 6.90, 1.2, 5.6, and 0.29 × 100 person-years, respectively. SO1 was associated with risk of IMT ≥ 1, and SO3 with risk of CAC score > 10. CONCLUSIONS: There was a large variability in incidence and prevalence of SO phenotypes. The presence of SO may have important implications for cardiovascular prevention and cardiac rehabilitation of PWH who suffered events.

Quality of life and intrinsic capacity in patients with post-acute COVID-19 syndrome is in relation to frailty and resilience phenotypes.

The objective of this study was to characterize frailty and resilience in people evaluated for Post-Acute COVID-19 Syndrome (PACS), in relation to quality of life (QoL) and Intrinsic Capacity (IC). This cross-sectional, observational, study included consecutive people previously hospitalized for severe COVID-19 pneumonia attending Modena (Italy) PACS Clinic from July 2020 to April 2021. Four frailty-resilience phenotypes were built: "fit/resilient", "fit/non-resilient", "frail/resilient" and "frail/non-resilient". Frailty and resilience were defined according to frailty phenotype and Connor Davidson resilience scale (CD-RISC-25) respectively. Study outcomes were: QoL assessed by means of Symptoms Short form health survey (SF-36) and health-related quality of life (EQ-5D-5L) and IC by means of a dedicated questionnaire. Their predictors including frailty-resilience phenotypes were explored in logistic regressions. 232 patients were evaluated, median age was 58.0 years. PACS was diagnosed in 173 (74.6%) patients. Scarce resilience was documented in 114 (49.1%) and frailty in 72 (31.0%) individuals. Predictors for SF-36 score < 61.60 were the phenotypes "frail/non-resilient" (OR = 4.69, CI 2.08-10.55), "fit/non-resilient" (OR = 2.79, CI 1.00-7.73). Predictors for EQ-5D-5L < 89.7% were the phenotypes "frail/non-resilient" (OR = 5.93, CI 2.64-13.33) and "frail/resilient" (OR = 5.66, CI 1.93-16.54). Predictors of impaired IC (below the mean score value) were "frail/non-resilient" (OR = 7.39, CI 3.20-17.07), and "fit/non-resilient" (OR = 4.34, CI 2.16-8.71) phenotypes. Resilience and frailty phenotypes may have a different impact on wellness and QoL and may be evaluated in people with PACS to identify vulnerable individuals that require suitable interventions.

Real-world data mining meets clinical practice: Research challenges and perspective.

As Big Data Analysis meets healthcare applications, domain-specific challenges and opportunities materialize in all aspects of data science. Advanced statistical methods and Artificial Intelligence (AI) on Electronic Health Records (EHRs) are used both for knowledge discovery purposes and clinical decision support. Such techniques enable the emerging Predictive, Preventative, Personalized, and Participatory Medicine (P4M) paradigm. Working with the Infectious Disease Clinic of the University Hospital of Modena, Italy, we have developed a range of Data-Driven (DD) approaches to solve critical clinical applications using statistics, Machine Learning (ML) and Big Data Analytics on real-world EHR. Here, we describe our perspective on the challenges we encountered. Some are connected to medical data and their sparse, scarce, and unbalanced nature. Others are bound to the application environment, as medical AI tools can affect people's health and life. For each of these problems, we report some available techniques to tackle them, present examples drawn from our experience, and propose which approaches, in our opinion, could lead to successful real-world, end-to-end implementations. DESY report number: DESY-22-153.

Possible Use of Minocycline in Adjunction to Intranasal Esketamine for the Management of Difficult to Treat Depression following Extensive Pharmacogenomic Testing: Two Case Reports.

The advent of intra-nasal esketamine (ESK), one of the first so called fast-acting antidepressant, promises to revolutionize the management of treatment resistant depression (TRD). This NMDA receptor antagonist has proven to be rapidly effective in the short- and medium-term course of the illness, revealing its potential in targeting response in TRD. Although many TRD ESK responders are able to achieve remission, a considerable portion of them undergo a metamorphosis of their depression into different clinical presentations, characterized by instable responses and high recurrence rates that can be considered closer to the concept of Difficult to Treat Depression (DTD) than to TRD. The management of these DTD patients usually requires a further complex multidisciplinary approach and can benefit from the valuable contribution of new personalized medicine tools such as therapeutic drug monitoring and pharmacogenetics. Despite this, these patients usually come with long and complex previous treatments history and, often, advanced and sophisticated ongoing pharmacological schemes that can make the finding of new alternative options to face the current recurrences extremely challenging. In this paper, we describe two DTD patients-already receiving intranasal ESK but showing an instable course-who were clinically stabilized by the association with minocycline, a semisynthetic second-generation tetracycline with known and promising antidepressant properties.

The interplay of post-acute COVID-19 syndrome and aging: a biological, clinical and public health approach.

The post-acute COVID-19 syndrome (PACS) is characterized by the persistence of fluctuating symptoms over three months from the onset of the possible or confirmed COVID-19 acute phase. Current data suggests that at least 10% of people with previously documented infection may develop PACS, and up to 50-80% of prevalence is reported among survivors after hospital discharge. This viewpoint will discuss various aspects of PACS, particularly in older adults, with a specific hypothesis to describe PACS as the expression of a modified aging trajectory induced by SARS CoV-2. This hypothesis will be argued from biological, clinical and public health view, addressing three main questions: (i) does SARS-CoV-2-induced alterations in aging trajectories play a role in PACS?; (ii) do people with PACS face immuno-metabolic derangements that lead to increased susceptibility to age-related diseases?; (iii) is it possible to restore the healthy aging trajectory followed by the individual before pre-COVID?. A particular focus will be given to the well-being of people with PACS that could be assessed by the intrinsic capacity model and support the definition of the healthy aging trajectory.