Spectral Dynamics Prior to Motor Events Differ Between NREM Sleep Parasomnias and Healthy Sleepers.

STUDY OBJECTIVES: The umbrella term "Disorders of Arousal" (DoA), encompassing sleepwalking, confusional arousals, and sleep terrors, refers to parasomnias manifesting during non-rapid eye movement (NREM) sleep, commonly thought to arise from an aberrant arousal process. While previous studies have detailed EEG changes linked to DoA episodes, it remains uncertain how these alterations differ from a physiological arousal process. This study directly compared brain activity between DoA episodes and arousals associated with physiological movements (motor arousal) in individuals with DoA and healthy sleepers. METHODS: Fifty-three adult patients with DoA (25 males, 32.2±15.5years) and 33 control subjects (14 males, 31.4±11.4years) underwent one or more home-EEG recordings. A semiparametric regression model was employed to elucidate the complex relationship between EEG activity across channels, within and across different groups, including motor arousals in DoA (n=169), parasomnia episodes in DoA (n=361), and motor arousals in healthy sleepers (n=137). RESULTS: Parasomnia episodes and motor arousals in both groups were preceded by a diffuse increase in slow-wave activity (SWA) and beta power, and a widespread decrease in sigma power. However, motor arousals in DoA displayed lower beta and central sigma than in healthy sleepers. Within DoA patients, episodes were preceded by lower beta, frontal sigma, and higher SWA than motor arousals. CONCLUSIONS: Our findings suggest that the arousal process is altered in DOA patients, and that specific EEG patterns are required for DOA episodes to emerge. These insights will help guide future research into the underlying circuits and objective markers of DOA.

The longitudinal characterization of immune responses in COVID-19 patients reveals novel prognostic signatures for disease severity, patients' survival and long COVID.

Introduction: SARS-CoV-2 pandemic still poses a significant burden on global health and economy, especially for symptoms persisting beyond the acute disease. COVID-19 manifests with various degrees of severity and the identification of early biomarkers capable of stratifying patient based on risk of progression could allow tailored treatments. Methods: We longitudinally analyzed 67 patients, classified according to a WHO ordinal scale as having Mild, Moderate, or Severe COVID-19. Peripheral blood samples were prospectively collected at hospital admission and during a 6-month follow-up after discharge. Several subsets and markers of the innate and adaptive immunity were monitored as putative factors associated with COVID-19 symptoms. Results: More than 50 immunological parameters were associated with disease severity. A decision tree including the main clinical, laboratory, and biological variables at admission identified low NK-cell precursors and CD14+CD91+ monocytes, and high CD8+ Effector Memory T cell frequencies as the most robust immunological correlates of COVID-19 severity and reduced survival. Moreover, low regulatory B-cell frequency at one month was associated with the susceptibility to develop long COVID at six months, likely due to their immunomodulatory ability. Discussion: These results highlight the profound perturbation of the immune response during COVID-19. The evaluation of specific innate and adaptive immune-cell subsets allows to distinguish between different acute and persistent COVID-19 symptoms.

The Near-infrared Visualization and Pre-emptive Ligation of the Thoracic Duct Effectively Reduce the Chyle Leak Incidence After Minimally Invasive Esophagectomy.

OBJECTIVE: The aim of the present study is to assess the effectiveness of indocyanine-green (ICG)-guided lymphography (ICG-Lg) in reducing the incidence of chyle leak (CL) after esophagectomy. BACKGROUND: Chylothorax may severely impact esophageal cancer surgery, and the pre-emptive ligation of the thoracic duct (TD) is the most widespread control of this complication. Intraoperative ICG-Lg has been recently embedded in minimally invasive esophagectomy to facilitate TD detection and pre-emptive ligation. METHODS: This retrospective analysis included consecutive patients who underwent minimally invasive Ivor Lewis esophagectomy for cancer at a tertiary referral center between January 2018 and August 2023. Patients were routinely submitted to extended lymphadenectomy with TD ligation and removal. All patients treated after January 2021 underwent ICG-Lg for TD identification and ligation (ICG group) and compared to the previous series (no-ICG group). The primary outcome was the incidence of postoperative CL, while univariate and backward stepwise multivariate logistic regression models were performed to identify associated factors. RESULTS: After including 320 patients, 151 (ICG group) were submitted to ICG-Lg before the pre-emptive TD ligation. Both groups presented similar characteristics, except for neoadjuvant therapy (P=<0.001) and preoperative comorbidities (P=0.045). Intraoperative ICG-Lg significantly reduced the incidence of postoperative CL (11.8% vs 4.6%, P=0.026) and was significantly associated with shorter median length of hospital stay (13 vs 9 days, P=0.006). However, CL after ICG-Lg was more likely to require repairing reoperation (P=0.050). CONCLUSIONS: Intraoperative ICG-Lg demonstrated significantly lower rates of CL after total minimally invasive esophagectomy and, therefore, it should be routinely embedded in the standardized surgical technique of high-volume centers for esophageal cancer.

Long-term and real-world safety and efficacy of retroviral gene therapy for adenosine deaminase deficiency.

Adenosine deaminase (ADA) deficiency leads to severe combined immunodeficiency (SCID). Previous clinical trials showed that autologous CD34+ cell gene therapy (GT) following busulfan reduced-intensity conditioning is a promising therapeutic approach for ADA-SCID, but long-term data are warranted. Here we report an analysis on long-term safety and efficacy data of 43 patients with ADA-SCID who received retroviral ex vivo bone marrow-derived hematopoietic stem cell GT. Twenty-two individuals (median follow-up 15.4 years) were treated in the context of clinical development or named patient program. Nineteen patients were treated post-marketing authorization (median follow-up 3.2 years), and two additional patients received mobilized peripheral blood CD34+ cell GT. At data cutoff, all 43 patients were alive, with a median follow-up of 5.0 years (interquartile range 2.4-15.4) and 2 years intervention-free survival (no need for long-term enzyme replacement therapy or allogeneic hematopoietic stem cell transplantation) of 88% (95% confidence interval 78.7-98.4%). Most adverse events/reactions were related to disease background, busulfan conditioning or immune reconstitution; the safety profile of the real world experience was in line with premarketing cohort. One patient from the named patient program developed a T cell leukemia related to treatment 4.7 years after GT and is currently in remission. Long-term persistence of multilineage gene-corrected cells, metabolic detoxification, immune reconstitution and decreased infection rates were observed. Estimated mixed-effects models showed that higher dose of CD34+ cells infused and younger age at GT affected positively the plateau of CD3+ transduced cells, lymphocytes and CD4+ CD45RA+ naive T cells, whereas the cell dose positively influenced the final plateau of CD15+ transduced cells. These long-term data suggest that the risk-benefit of GT in ADA remains favorable and warrant for continuing long-term safety monitoring. Clinical trial registration: NCT00598481 , NCT03478670 .

Optimizing CO2 field flooding during sternotomy: In vitro confirmation of the Karolinska studies.

Although CO2 field-flooding was first used during cardiac surgery more than 60 years ago, its efficacy is still disputed. The invisible nature of the gas and the difficulty in determining the "safe" quantity to protect the patient are two of the main obstacles to overcome for its validation. Moreover, CO2 concentration in the chest cavity is highly sensitive to procedural aspects, such suction and hand movements. Based on our review of the existing literature, we identified four major factors that influence the intra-cavity CO2 concentration during open-heart surgery: type of delivery device (diffuser), delivery CO2 flow rate, diffuser position around the wound cavity, and its orientation inside the cavity. In this initial study, only steady state conditions were considered to establish a basic understanding on the effect of the four above-mentioned factors. Transient factors, such as suction or hand movements, will be reported separately.

Differential impact of transfusion guidelines on blood transfusion practices within a health network.

Whether clinical practice guidelines have a significant impact on practice is unclear. The effect of guideline recommendations on clinical practice often a lags behind the date of publication. We evaluated by means of a data-driven approach if and when the guidelines on red blood cell transfusions (RBCTs) issued by Swiss Smarter Medicine in 2016 had an impact on RBCTs practice within a hospital network, where awareness of guidelines was promoted mainly among internal medicine specialties. Data on RBCTs performed in a Swiss hospital network from January 2014 to April 2021 were analyzed by hospital site and specialty to assess whether guidelines led to a decrease in inappropriate RBCTs. RBCTs were defined as "inappropriate" if patients had a hemoglobin level ≥ 70 g/L without or ≥ 80 g/L with significant cardiovascular comorbidities. Changes in the rate of inappropriate transfusions were analyzed with an advanced statistical approach that included generalized additive models. Overall prior to March 2017 there were more inappropriate than appropriate RBCTs, but after October 2017 the opposite could be observed. A change-point in the time trend was estimated from transfusion data to occur in the time interval between March and October 2017. This change was mainly driven by practice changes in the medical wards, while no significant change was observed in the critical care, surgical and oncology wards. Change in practice varied by hospital site. In conclusion, our results show that a significant change in the RBCTs practice at the hospital level occurred approximately 18 months after national guidelines were issued.

Profiling Covid-19 patients with respect to level of severity: an integrated statistical approach.

A full understanding of the characteristics of Covid-19 patients with a better chance of experiencing poor vital outcomes is critical for implementing accurate and precise treatments. In this paper, two different advanced data-driven statistical approaches along with standard statistical methods have been implemented to identify groups of patients most at-risk for death or severity of respiratory distress. First, the tree-based analysis allowed to identify profiles of patients with different risk of in-hospital death (by Survival Tree-ST analysis) and severity of respiratory distress (by Classification and Regression Tree-CART analysis), and to unravel the role on risk stratification of highly dependent covariates (i.e., demographic characteristics, admission values and comorbidities). The ST analysis identified as the most at-risk group for in-hospital death the patients with age > 65 years, creatinine [Formula: see text] 1.2 mg/dL, CRP [Formula: see text] 25 mg/L and anti-hypertensive treatment. Based on the CART analysis, the subgroups most at-risk of severity of respiratory distress were defined by patients with creatinine level [Formula: see text] 1.2 mg/dL. Furthermore, to investigate the multivariate dependence structure among the demographic characteristics, the admission values, the comorbidities and the severity of respiratory distress, the Bayesian Network analysis was applied. This analysis confirmed the influence of creatinine and CRP on the severity of respiratory distress.

Longitudinal single-cell profiling of chemotherapy response in acute myeloid leukemia.

Acute myeloid leukemia may be characterized by a fraction of leukemia stem cells (LSCs) that sustain disease propagation eventually leading to relapse. Yet, the contribution of LSCs to early therapy resistance and AML regeneration remains controversial. We prospectively identify LSCs in AML patients and xenografts by single-cell RNA sequencing coupled with functional validation by a microRNA-126 reporter enriching for LSCs. Through nucleophosmin 1 (NPM1) mutation calling or chromosomal monosomy detection in single-cell transcriptomes, we discriminate LSCs from regenerating hematopoiesis, and assess their longitudinal response to chemotherapy. Chemotherapy induced a generalized inflammatory and senescence-associated response. Moreover, we observe heterogeneity within progenitor AML cells, some of which proliferate and differentiate with expression of oxidative-phosphorylation (OxPhos) signatures, while others are OxPhos (low) miR-126 (high) and display enforced stemness and quiescence features. miR-126 (high) LSCs are enriched at diagnosis in chemotherapy-refractory AML and at relapse, and their transcriptional signature robustly stratifies patients for survival in large AML cohorts.

Modelling the impact of protein-kinase R allelic variant on HIV biomarkers trajectories by means of latent class mixed models.

This paper is based on a retrospective longitudinal study on people living with HIV under antiretroviral treatment (ART) where allelic variants (either heterozygous CT genotype or homozygous CC genotype) have been evaluated at position -168 of the promoter region of the protein kinase R (-168/PKR). In general, antiviral effects of interferon are partially mediated by a RNA-dependent protein kinase (PKR) that, once activated, inhibits protein synthesis. Indeed, activation of PKR response can inhibit HIV replication. To explore the role of allelic variants in shaping dynamics of commonly monitored HIV biomarkers, CD4 cells, CD8 cells and HIV-load were modelled within a latent class mixed model (LCMM) to account for participants' heterogeneity over time. The estimated models identified two sub-groups from CD4 and HIV-load dynamics, revealing better outcomes for subgroups of participants with the heterozygous CT genotype. Heterozygous CT subjects in one of the two identified subgroups exhibited higher increase of CD4 cells and more marked decrease of HIV-load, over time, with respect to the homozygous CC subjects assigned to the same group.

EUS-guided ablation with the HybridTherm Probe as second-line treatment in patients with locally advanced pancreatic ductal adenocarcinoma: A case-control study.

Background and Objectives: Data on the clinical efficacy of EUS-guided ablation using the HybridTherm-Probe (EUS-HTP) in locally advanced pancreatic ductal adenocarcinoma (LA-PDAC) are lacking. The aim of the study was to assess the impact of EUS-HTP added to chemotherapy (CT) on overall survival (OS) and progression-free survival (PFS) of LA-PDAC patients with local disease progression (DP) after first-line therapy, compared to CT alone in controls. Methods: LA-PDAC cases, prospectively treated by EUS-HTP, were retrospectively compared to matched controls (1:2) receiving standard treatment. Study endpoints were the OS and PFS from local DP after first-line therapy, compared through log-rank test calculating hazard ratios and differences in restricted mean OS/PFS time (RMOST/RMPFST) within prespecified time points (4, 6, and 12 months). Results: Thirteen cases and 26 controls were included. Clinical, tumor, and therapy features before and after first-line therapy were case-control balanced. The median OS and PFS were not significantly improved in cases over controls (months: 7 vs. 5 and 5 vs. 3, respectively). At 4 and 6 months, the RMPFST difference was in favor of cases (P = 0.0001 and P = 0.003, respectively). In cases and controls not candidate to further CT (N = 5 and N = 9), the median OS and PFS were not significantly improved in cases over controls (months: 6 vs. 3 and 4 vs. 2, respectively), but the RMPFST difference was in favor of cases at 4 months (P = 0.002). Conclusions: In locally progressive PDAC patients experiencing failure of first-line therapy, EUS-HTP achieves a significantly better RMPFST up to 6 months compared to standard treatment, although without a significant impact on OS.

AI-SCoRE (artificial intelligence-SARS CoV2 risk evaluation): a fast, objective and fully automated platform to predict the outcome in COVID-19 patients.

PURPOSE: To develop and validate an effective and user-friendly AI platform based on a few unbiased clinical variables integrated with advanced CT automatic analysis for COVID-19 patients' risk stratification. MATERIAL AND METHODS: In total, 1575 consecutive COVID-19 adults admitted to 16 hospitals during wave 1 (February 16-April 29, 2020), submitted to chest CT within 72 h from admission, were retrospectively enrolled. In total, 107 variables were initially collected; 64 extracted from CT. The outcome was survival. A rigorous AI model selection framework was adopted for models selection and automatic CT data extraction. Model performances were compared in terms of AUC. A web-mobile interface was developed using Microsoft PowerApps environment. The platform was externally validated on 213 COVID-19 adults prospectively enrolled during wave 2 (October 14-December 31, 2020). RESULTS: The final cohort included 1125 patients (292 non-survivors, 26%) and 24 variables. Logistic showed the best performance on the complete set of variables (AUC = 0.839 ± 0.009) as in models including a limited set of 13 and 5 variables (AUC = 0.840 ± 0.0093 and AUC = 0.834 ± 0.007). For non-inferior performance, the 5 variables model (age, sex, saturation, well-aerated lung parenchyma and cardiothoracic vascular calcium) was selected as the final model and the extraction of CT-derived parameters was fully automatized. The fully automatic model showed AUC = 0.842 (95% CI: 0.816-0.867) on wave 1 and was used to build a 0-100 scale risk score (AI-SCoRE). The predictive performance was confirmed on wave 2 (AUC 0.808; 95% CI: 0.7402-0.8766). CONCLUSIONS: AI-SCoRE is an effective and reliable platform for automatic risk stratification of COVID-19 patients based on a few unbiased clinical data and CT automatic analysis.

The role of statisticians in the response to COVID-19 in Israel: a holistic point of view.

The COVID-19 pandemic cast a dramatic spotlight on the use of data as a fundamental component of good decision-making. Evaluating and comparing alternative policies required information on concurrent infection rates and insightful analysis to project them into the future. Statisticians in Israel were involved in these processes early in the pandemic in some silos as an ad-hoc unorganized effort. Informal discussions within the statistical community culminated in a roundtable, organized by three past presidents of the Israel Statistical Association, and hosted by the Samuel Neaman Institute in April 2021. The meeting was designed to provide a forum for exchange of views on the profession's role during the COVID-19 pandemic, and more generally, on its influence in promoting evidence-based public policy. This paper builds on the insights and discussions that emerged during the roundtable meeting and presents a general framework, with recommendations, for involving statisticians and statistics in decision-making.

Lentiviral haematopoietic stem-cell gene therapy for early-onset metachromatic leukodystrophy: long-term results from a non-randomised, open-label, phase 1/2 trial and expanded access.

BACKGROUND: Effective treatment for metachromatic leukodystrophy (MLD) remains a substantial unmet medical need. In this study we investigated the safety and efficacy of atidarsagene autotemcel (arsa-cel) in patients with MLD. METHODS: This study is an integrated analysis of results from a prospective, non-randomised, phase 1/2 clinical study and expanded-access frameworks. 29 paediatric patients with pre-symptomatic or early-symptomatic early-onset MLD with biochemical and molecular confirmation of diagnosis were treated with arsa-cel, a gene therapy containing an autologous haematopoietic stem and progenitor cell (HSPC) population transduced ex vivo with a lentiviral vector encoding human arylsulfatase A (ARSA) cDNA, and compared with an untreated natural history (NHx) cohort of 31 patients with early-onset MLD, matched by age and disease subtype. Patients were treated and followed up at Ospedale San Raffaele, Milan, Italy. The coprimary efficacy endpoints were an improvement of more than 10% in total gross motor function measure score at 2 years after treatment in treated patients compared with controls, and change from baseline of total peripheral blood mononuclear cell (PBMC) ARSA activity at 2 years after treatment compared with values before treatment. This phase 1/2 study is registered with ClinicalTrials.gov, NCT01560182. FINDINGS: At the time of analyses, 26 patients treated with arsa-cel were alive with median follow-up of 3·16 years (range 0·64-7·51). Two patients died due to disease progression and one due to a sudden event deemed unlikely to be related to treatment. After busulfan conditioning, all arsa-cel treated patients showed sustained multilineage engraftment of genetically modified HSPCs. ARSA activity in PBMCs was significantly increased above baseline 2 years after treatment by a mean 18·7-fold (95% CI 8·3-42·2; p<0·0001) in patients with the late-infantile variant and 5·7-fold (2·6-12·4; p<0·0001) in patients with the early-juvenile variant. Mean differences in total scores for gross motor function measure between treated patients and age-matched and disease subtype-matched NHx patients 2 years after treatment were significant for both patients with late-infantile MLD (66% [95% CI 48·9-82·3]) and early-juvenile MLD (42% [12·3-71·8]). Most treated patients progressively acquired motor skills within the predicted range of healthy children or had stabilised motor performance (maintaining the ability to walk). Further, most displayed normal cognitive development and prevention or delay of central and peripheral demyelination and brain atrophy throughout follow-up; treatment benefits were particularly apparent in patients treated before symptom onset. The infusion was well tolerated and there was no evidence of abnormal clonal proliferation or replication-competent lentivirus. All patients had at least one grade 3 or higher adverse event; most were related to conditioning or to background disease. The only adverse event related to arsa-cel was the transient development of anti-ARSA antibodies in four patients, which did not affect clinical outcomes. INTERPRETATION: Treatment with arsa-cel resulted in sustained, clinically relevant benefits in children with early-onset MLD by preserving cognitive function and motor development in most patients, and slowing demyelination and brain atrophy. FUNDING: Orchard Therapeutics, Fondazione Telethon, and GlaxoSmithKline.

Profiling Antibody Response Patterns in COVID-19: Spike S1-Reactive IgA Signature in the Evolution of SARS-CoV-2 Infection.

This contribution explores in a new statistical perspective the antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 141 coronavirus disease 2019 (COVID-19) patients exhibiting a broad range of clinical manifestations. This cohort accurately reflects the characteristics of the first wave of the SARS-CoV-2 pandemic in Italy. We determined the IgM, IgA, and IgG levels towards SARS-CoV-2 S1, S2, and NP antigens, evaluating their neutralizing activity and relationship with clinical signatures. Moreover, we longitudinally followed 72 patients up to 9 months postsymptoms onset to study the persistence of the levels of antibodies. Our results showed that the majority of COVID-19 patients developed an early virus-specific antibody response. The magnitude and the neutralizing properties of the response were heterogeneous regardless of the severity of the disease. Antibody levels dropped over time, even though spike reactive IgG and IgA were still detectable up to 9 months. Early baseline antibody levels were key drivers of the subsequent antibody production and the long-lasting protection against SARS-CoV-2. Importantly, we identified anti-S1 IgA as a good surrogate marker to predict the clinical course of COVID-19. Characterizing the antibody response after SARS-CoV-2 infection is relevant for the early clinical management of patients as soon as they are diagnosed and for implementing the current vaccination strategies.

Altered Frequency and Phenotype of HLA-G-Expressing DC-10 in Type 1 Diabetes Patients at Onset and in Subjects at Risk to Develop the Disease.

Type 1 diabetes (T1D) is a chronic autoimmune disease resulting in progressive destruction of ß-cells. Several factors affecting lymphocyte and antigen-presenting cells, including dendritic cells (DCs), contribute to defective maintenance of tolerance in T1D. DC-10 are a subset of human DCs involved in IL-10-mediated tolerance. A precise monitoring of DC-10 in the peripheral blood is possible thanks to the discovery of specific biomarkers. DC-10, being cells that naturally express HLA-G, may be used for the appropriate staging of the disease. By enumerating and phenotypically characterizing DC-10 in the peripheral blood of subjects at different stages of T1D development-first-degree relatives (FDRs) of T1D patients, without (Abneg) or with (Abpos) autoantibodies, T1D patients at onset, and age-matched healthy controls (HCs)-we showed that DC-10 contain a high proportion of HLA-G-expressing cells as compared with monocytes. We reported that a low frequency of DC-10 during disease development is paralleled with the increased proportion of pro-inflammatory cDC2 cells. Moreover, DC-10 number and phenotype differ from Abneg FDRs, Abpos FDRs, and T1D patients compared with HCs, and DC-10 from T1D patients express low levels of CD83. Finally, multiple regression analysis, considering DC-10 and HLA-G-related parameters, showed that Abneg FDRs are more similar to subjects with autoimmunity than to HCs. This is the first demonstration that impairment in DC-10 number and phenotype, specifically CD83 expression, is associated with risk of developing T1D, suggesting a possible use of CD83+ DC-10 to stratify individuals at risk of T1D in conjunction with classical prognostic factors.

CXCL10 levels at hospital admission predict COVID-19 outcome: hierarchical assessment of 53 putative inflammatory biomarkers in an observational study.

BACKGROUND: Host inflammation contributes to determine whether SARS-CoV-2 infection causes mild or life-threatening disease. Tools are needed for early risk assessment. METHODS: We studied in 111 COVID-19 patients prospectively followed at a single reference Hospital fifty-three potential biomarkers including alarmins, cytokines, adipocytokines and growth factors, humoral innate immune and neuroendocrine molecules and regulators of iron metabolism. Biomarkers at hospital admission together with age, degree of hypoxia, neutrophil to lymphocyte ratio (NLR), lactate dehydrogenase (LDH), C-reactive protein (CRP) and creatinine were analysed within a data-driven approach to classify patients with respect to survival and ICU outcomes. Classification and regression tree (CART) models were used to identify prognostic biomarkers. RESULTS: Among the fifty-three potential biomarkers, the classification tree analysis selected CXCL10 at hospital admission, in combination with NLR and time from onset, as the best predictor of ICU transfer (AUC [95% CI] = 0.8374 [0.6233-0.8435]), while it was selected alone to predict death (AUC [95% CI] = 0.7334 [0.7547-0.9201]). CXCL10 concentration abated in COVID-19 survivors after healing and discharge from the hospital. CONCLUSIONS: CXCL10 results from a data-driven analysis, that accounts for presence of confounding factors, as the most robust predictive biomarker of patient outcome in COVID-19.

SARS-CoV-2 Antibody Rapid Tests: Valuable Epidemiological Tools in Challenging Settings.

During the last year, mass screening campaigns have been carried out to identify immunological response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and establish a possible seroprevalence. The obtained results gained new importance with the beginning of the SARS-CoV-2 vaccination campaign, as the lack of doses has persuaded several countries to introduce different policies for individuals who had a history of COVID-19. Lateral flow assays (LFAs) may represent an affordable tool to support population screening in low-middle-income countries, where diagnostic tests are lacking and epidemiology is still widely unknown. However, LFAs have demonstrated a wide range of performance, and the question of which one could be more valuable in these settings still remains. We evaluated the performance of 11 LFAs in detecting SARS-CoV-2 infection, analyzing samples collected from 350 subjects. In addition, samples from 57 health care workers collected at 21 to 24 days after the first dose of the Pfizer-BioNTech vaccine were also evaluated. LFAs demonstrated a wide range of specificity (92.31% to 100%) and sensitivity (50% to 100%). The analysis of postvaccination samples was used to describe the most suitable tests to detect IgG response against S protein receptor binding domain (RBD). Tuberculosis (TB) therapy was identified as a potential factor affecting the specificity of LFAs. This analysis identified which LFAs represent a valuable tool not only for the detection of prior SARS-CoV-2 infection but also for the detection of IgG elicited in response to vaccination. These results demonstrated that different LFAs may have different applications and the possible risks of their use in high-TB-burden settings. IMPORTANCE Our study provides a fresh perspective on the possible employment of SARS-CoV-2 LFA antibody tests. We developed an in-depth, large-scale analysis comparing LFA performance to enzyme-linked immunosorbent assay (ELISA) and electrochemiluminescence immunoassay (ECLIA) and evaluating their sensitivity and specificity in identifying COVID-19 patients at different time points from symptom onset. Moreover, for the first time, we analyzed samples of patients undergoing treatment for endemic poverty-related diseases, especially tuberculosis, and we evaluated the impact of this therapy on test specificity in order to assess possible performance in TB high-burden countries.

Quantitative assessment of lung involvement on chest CT at admission: Impact on hypoxia and outcome in COVID-19 patients.

BACKGROUND: The aim of this study was to quantify COVID-19 pneumonia features using CT performed at time of admission to emergency department in order to predict patients' hypoxia during the hospitalization and outcome. METHODS: Consecutive chest CT performed in the emergency department between March 1st and April 7th 2020 for COVID-19 pneumonia were analyzed. The three features of pneumonia (GGO, semi-consolidation and consolidation) and the percentage of well-aerated lung were quantified using a HU threshold based software. ROC curves identified the optimal cut-off values of CT parameters to predict hypoxia worsening and hospital discharge. Multiple Cox proportional hazards regression was used to analyze the capability of CT quantitative features, demographic and clinical variables to predict the time to hospital discharge. RESULTS: Seventy-seven patients (median age 56-years-old, 51 men) with COVID-19 pneumonia at CT were enrolled. The quantitative features of COVID-19 pneumonia were not associated to age, sex and time-from-symptoms onset, whereas higher number of comorbidities was correlated to lower well-aerated parenchyma ratio (rho = -0.234, p = 0.04) and increased semi-consolidation ratio (rho = -0.303, p = 0.008). Well-aerated lung (≤57%), semi-consolidation (≥17%) and consolidation (≥9%) predicted worst hypoxemia during hospitalization, with moderate areas under curves (AUC 0.76, 0.75, 0.77, respectively). Multiple Cox regression identified younger age (p < 0.01), female sex (p < 0.001), longer time-from-symptoms onset (p = 0.049), semi-consolidation ≤17% (p < 0.01) and consolidation ≤13% (p = 0.03) as independent predictors of shorter time to hospital discharge. CONCLUSION: Quantification of pneumonia features on admitting chest CT predicted hypoxia worsening during hospitalization and time to hospital discharge in COVID-19 patients.