The novel CFTR haplotype E583G/F508del in CFTR-related disorder.

BACKGROUND: CFTR-related disorder (CFTR-RD) is a clinical entity associated to complex diagnostic paths and newly upgraded standard of care. In CFTR-RD, CFTR genotyping represents a diagnostic surrogate marker. In case of novel haplotype, the diagnosis could represents an area of concern. We described the molecular evaluation of the rare CFTR variant E583G identified in trans with the F508del in a novel haplotype. METHODS AND RESULTS: An adult woman was referred to our pulmonary unit for persistent respiratory symptoms. CFTR Next Generation Sequencing was performed to evaluate full-gene mutational status. The variant identified was evaluated for its pathogenicity integrating clinical evidences with dedicated bioinformatics analyses. Clinical evaluation of patient matched with a mono-organ CFTR-RD diagnosis. Genotyping revealed the novel CFTR haplotype F508del/E583G. Multiple evidences of a deleterious effect of the CFTR E583G rare variant emerged from the bioinformatics analyses performed. CONCLUSIONS: Guidelines for CFTR-RD are available with the purpose of harmonizing clinical and molecular investigations. In such context, the identification of novel CFTR haplotype need to a deeper evaluation with a combination of skills. The novel E583G variant could be considered of clinical interest and overall a CFTR-RD Variants of Varying Clinical Consequences.

Reference Equations for Within-Breath Respiratory Oscillometry in White Adults.

BACKGROUND: Within-breath analysis of oscillometry parameters is a growing research area since it increases sensitivity and specificity to respiratory pathologies and conditions. However, reference equations for these parameters in White adults are lacking and devices using multiple sinusoids or pseudorandom forcing stimuli have been underrepresented in previous studies deriving reference equations. The current study aimed to establish reference ranges for oscillometry parameters, including also the within-breath ones in White adults using multi-sinusoidal oscillations. METHODS: White adults with normal spirometry, BMI ≤30 kg/m2, without a smoking history, respiratory symptoms, pulmonary or cardiac disease, neurological or neuromuscular disorders, and respiratory tract infections in the previous 4 weeks were eligible for the study. Study subjects underwent oscillometry (multifrequency waveform at 5-11-19 Hz, Resmon PRO FULL, RESTECH Srl, Italy) in 5 centers in Europe and the USA according to international standards. The within-breath and total resistance (R) and reactance (X), the resonance frequency, the area under the X curve, the frequency dependence of R (R5-19), and within-breath changes of X (ΔX) were submitted to lambda-mu-sigma models for deriving reference equations. For each output parameter, an AIC-based stepwise input variable selection procedure was applied. RESULTS: A total of 144 subjects (age 20.8-86.3 years; height 146-193 cm; BMI 17.42-29.98 kg/m2; 56% females) were included. We derived reference equations for 29 oscillatory parameters. Predicted values for inspiratory and expiratory parameters were similar, while differences were observed for their limits of normality. CONCLUSIONS: We derived reference equations with narrow confidence intervals for within-breath and whole-breath oscillatory parameters for White adults.

Lung Ultrasound Signs: The Beginning. Part 3-An Accademia di Ecografia Toracica Comprehensive Review on Ultrasonographic Signs and Real Needs.

Over the last 20 years, scientific literature and interest on chest/lung ultrasound (LUS) have exponentially increased. Interpreting mixed-anatomical and artifactual-pictures determined the need of a proposal of a new nomenclature of artifacts and signs to simplify learning, spread, and implementation of this technique. The aim of this review is to collect and analyze different signs and artifacts reported in the history of chest ultrasound regarding normal lung, pleural pathologies, and lung consolidations. By reviewing the possible physical and anatomical interpretation of these artifacts and signs reported in the literature, this work aims to present the AdET (Accademia di Ecografia Toracica) proposal of nomenclature and to bring order between published studies.

Microwave ablation followed by cTACE in 5-cm HCC lesions: does a single-session approach affect liver function?

PURPOSE: Microwave ablation (MWA) and conventional transarterial chemoembolization (cTACE) are locoregional treatments commonly performed in very early, early and intermediate stages of hepatocellular carcinoma (HCC). Despite combined locoregional approaches have shown encouraging results in obtaining complete tumor necrosis, their application in a single session is poorly described. Our aim was to evaluate the safety and efficacy of single-session MWA and cTACE treatment in 5-cm HCCs and its influence on liver function. MATERIALS AND METHODS: All 5-cm HCCs treated by MWA and cTACE performed in a single-session in our Interventional Radiology unit between January 2020 and December 2022 were retrospectively recorded and analyzed. Patients with poor or missing pre- and post-treatment imaging were excluded. Technical success, clinical success, and complications rate were examined as primary endpoints. Pre- and post-treatment liver function laboratory parameters were also evaluated. RESULTS: A total of 15 lesions (mean lesion diameter, 5.0 ± 1.4 cm) in 15 patients (11 men; mean age, 67.1 ± 8.9 years) were retrospectively evaluated. Technical and clinical success were 100% and 73%, respectively. Four (27%) cases of partial response and no cases of progressive or stable disease were recorded. AST and ALT values have found to be significantly higher in post-treatment laboratory tests. No other significant differences between pre- and post-treatment laboratory values were registered. AST and ALT pre- and post-treatment higher differences (ΔAST and ΔALT) were significantly associated with a lower clinical success rate. CONCLUSION: MWA and cTACE single-session approach is safe and effective for 5-cm HCCs, without significant liver function impairment. A post-treatment increase in AST and ALT values may be a predictor for clinical failure.

Abelacimab in Cancer-Associated Thrombosis: The Right Drug at the Right Time for the Right Purpose. A Comprehensive Review.

Cancer-associated thrombosis (CAT) is a devastating complication of cancer that can significantly impact a patient's health and life. The incidence of CAT is approximately 20%, and 1 in 5 cancer patients will develop CAT annually. Indeed, CAT can promote pulmonary embolism and deep vein thrombosis, leading to increased morbidity and mortality that dramatically impact survival. CAT can also provoke delay or discontinuation of anticancer treatment, which may result in a lack of treatment efficacy and high costs for patients, institutions, and society. Current guidelines advocate direct oral anticoagulants (DOACs) as the first-line anticoagulant option in CAT. Compared to low-molecular-weight-heparins (LMWHs), DOACs are advantageous in that they typically have an oral route of administration, do not require laboratory monitoring, and have a more predictable anticoagulant effect. However, in patients with thrombocytopenia, renal failure, or those receiving anticancer regimens with potential for drug-drug interactions, LMWH is still the mainstay of care. The main limitation of current anticoagulant agents is related to bleeding risk (BR), both for DOACs and LMWHs. Specifically, DOACs have been associated with high BR in gastrointestinal and genitourinary cancers. In this challenging scenario, abelacimab, an anti-factor XI agent, could represent a viable option in the management of CAT due to its "hemostasis sparing" effect. The safe profile of abelacimab could be useful in patients with active malignancy and CAT, as long-term anticoagulant therapy is often required. Two ongoing international phase III trials (Aster and Magnolia) compare abelacimab with the standard of care (i.e., apixaban in patients with CAT and dalteparin in those with CAT and high BR, respectively). Abelacimab is a new and attractive anticoagulant for the management of CAT, especially in the insidious and critical scenario of active cancer patients with venous thromboembolism and high BR. The aim of this narrative review is to discuss the updated evidence on the performance of DOACs and LMWHs in the treatment of CAT and to focus on the potential role of abelacimab in CAT and its promising associated clinical trials.

Liver resection versus radiofrequency ablation in octogenarian patients for hepatocellular carcinoma: a propensity score multicenter analysis.

BACKGROUND: Liver resection (LR) and radiofrequency ablation (RFA) are considered curative options for hepatocellular carcinoma (HCC). The aim of this study was to compare outcomes after LR and RFA in octogenarian patients with HCC. MATERIALS AND METHODS: This multicenter retrospective study included 102 elderly patients (> 80 years old) treated between January 2009 and January 2019, who underwent LR or RFA for HCC (65 and 37 with, respectively). RESULTS: After Propensity Score Matching, the postoperative course of LR was burdened by a higher rate of complications than RFA group (64% vs 14%, respectively, p: 0.001). The LR group had also significantly longer operative time (207 ± 85 min vs 33 ± 49 min, p < 0.001) and postoperative hospital stays than the RFA group (7 d vs 2 d, p = 0.019). Overall survival at 1-, 2-, and 3-year were 86%, 86%, and 70% for the LR group and 82%, 64%, and 52% for the RFA group (p = 0.380). Disease-free survival at 1-, 2-, and 3-year were 89%, 74%, and 56% for the LR group, and 51%, 40%, and 40% for the RFA group (p = 0.037). CONCLUSION: Despite a higher rate of Dindo-Clavien I-II post-operative complications, a longer operative time and length of hospital stay, LR in octogenarian patients can provide comparable 90d mortality than RFA and better long-term outcomes.

Vertical Artifacts as Lung Ultrasound Signs: Trick or Trap? Part 2- An Accademia di Ecografia Toracica Position Paper on B-Lines and Sonographic Interstitial Syndrome.

Although during the last few years the lung ultrasound (LUS) technique has progressed substantially, several artifacts, which are currently observed in clinical practice, still need a solid explanation of the physical phenomena involved in their origin. This is particularly true for vertical artifacts, conventionally known as B-lines, and for their use in clinical practice. A wider consensus and a deeper understanding of the nature of these artifactual phenomena will lead to a better classification and a shared nomenclature, and, ultimately, result in a more objective correlation between anatomo-pathological data and clinical scenarios. The objective of this review is to collect and document the different signs and artifacts described in the history of chest ultrasound, with a particular focus on vertical artifacts (B-lines) and sonographic interstitial syndrome (SIS). By reviewing the possible physical and anatomical interpretation of the signs and artifacts proposed in the literature, this work also aims to bring order to the available studies and to present the AdET (Accademia di Ecografia Toracica) viewpoint in terms of nomenclature and clinical approach to the SIS.

New International Guidelines and Consensus on the Use of Lung Ultrasound.

Following the innovations and new discoveries of the last 10 years in the field of lung ultrasound (LUS), a multidisciplinary panel of international LUS experts from six countries and from different fields (clinical and technical) reviewed and updated the original international consensus for point-of-care LUS, dated 2012. As a result, a total of 20 statements have been produced. Each statement is complemented by guidelines and future developments proposals. The statements are furthermore classified based on their nature as technical (5), clinical (11), educational (3), and safety (1) statements.

Antituberculosis drug-induced non-blistering systemic severe reactions: A 10-year (2012-2022) literature review.

Drug reaction with eosinophilia and systemic symptoms (DRESS) and drug-induced liver injury (DILI) can hamper therapeutic strategy, contribute to multiple drug resistance and serious public health burden. Diagnosis (including allergy assessment) and management of these two severe hypersensitivity reactions in clinical practice are somewhat difficult and published scientific evidence is rather weak and limited. The first step is always represented by stopping all anti-tuberculosis (TB) drugs, treating reaction with systemic corticosteroids, and identifying the offending drug, even if it is often complicated by the patient's simultaneous intake of antibiotics. Patch tests and in vitro tests, such as lymphocyte transformation test, could bridge this diagnostic gap, but the available data are scarce and their sensitivity low. The re-challenge test is often necessary but places patients at risk for serious adverse reactions. The desensitization protocols are quite varied and not universally accepted. In this narrative review, we provide an update to the literature data on the management of DRESS and DILI with particular attention to the allergological work-up in the last decade.

Multi-objective automatic analysis of lung ultrasound data from COVID-19 patients by means of deep learning and decision trees.

COVID-19 raised the need for automatic medical diagnosis, to increase the physicians' efficiency in managing the pandemic. Among all the techniques for evaluating the status of the lungs of a patient with COVID-19, lung ultrasound (LUS) offers several advantages: portability, cost-effectiveness, safety. Several works approached the automatic detection of LUS imaging patterns related COVID-19 by using deep neural networks (DNNs). However, the decision processes based on DNNs are not fully explainable, which generally results in a lack of trust from physicians. This, in turn, slows down the adoption of such systems. In this work, we use two previously built DNNs as feature extractors at the frame level, and automatically synthesize, by means of an evolutionary algorithm, a decision tree (DT) that aggregates in an interpretable way the predictions made by the DNNs, returning the severity of the patients' conditions according to a LUS score of prognostic value. Our results show that our approach performs comparably or better than previously reported aggregation techniques based on an empiric combination of frame-level predictions made by DNNs. Furthermore, when we analyze the evolved DTs, we discover properties about the DNNs used as feature extractors. We make our data publicly available for further development and reproducibility.

Lung Ultrasound in COVID-19 and Post-COVID-19 Patients, an Evidence-Based Approach.

OBJECTIVES: Worldwide, lung ultrasound (LUS) was utilized to assess coronavirus disease 2019 (COVID-19) patients. Often, imaging protocols were however defined arbitrarily and not following an evidence-based approach. Moreover, extensive studies on LUS in post-COVID-19 patients are currently lacking. This study analyses the impact of different LUS imaging protocols on the evaluation of COVID-19 and post-COVID-19 LUS data. METHODS: LUS data from 220 patients were collected, 100 COVID-19 positive and 120 post-COVID-19. A validated and standardized imaging protocol based on 14 scanning areas and a 4-level scoring system was implemented. We utilized this dataset to compare the capability of 5 imaging protocols, respectively based on 4, 8, 10, 12, and 14 scanning areas, to intercept the most important LUS findings. This to evaluate the optimal trade-off between a time-efficient imaging protocol and an accurate LUS examination. We also performed a longitudinal study, aimed at investigating how to eventually simplify the protocol during follow-up. Additionally, we present results on the agreement between AI models and LUS experts with respect to LUS data evaluation. RESULTS: A 12-areas protocol emerges as the optimal trade-off, for both COVID-19 and post-COVID-19 patients. For what concerns follow-up studies, it appears not to be possible to reduce the number of scanning areas. Finally, COVID-19 and post-COVID-19 LUS data seem to show differences capable to confuse AI models that were not trained on post-COVID-19 data, supporting the hypothesis of the existence of LUS patterns specific to post-COVID-19 patients. CONCLUSIONS: A 12-areas acquisition protocol is recommended for both COVID-19 and post-COVID-19 patients, also during follow-up.

The Role of Laparoscopic Surgery in Localized Pancreatic Neuroendocrine Tumours.

OPINION STATEMENT: Pancreatic neuroendocrine tumours (PNETs) are a rare and heterogeneous group of tumours with various clinical manifestations and biological behaviours. They represent approximately 2-4% of all pancreatic tumours, with an incidence of 2-3 cases per million people. PNETs are classified clinically as non-functional or functional, and pancreatic resection is recommended for lesions greater than 2 cm. The surgical approach can involve "typical" and "atypical" resections depending on the number, size and location of the tumour. Typical resections include pancreaticoduodenectomy, distal pancreatectomy enucleation and, rarely, total pancreatectomy. Atypical resections comprise central pancreatectomies or enucleations. Minimally invasive pancreatic resection has been proven to be technically feasible and safe in high-volume and specialized centres with highly skilled laparoscopic surgeons, with consolidated benefits for patients in the postoperative course. However, open and minimally invasive pancreatic surgery remains to have a high rate of complications; there is no specific technical contraindication to minimally invasive pancreatic surgery, but an appropriate patient selection is crucial to obtain satisfactory clinical and oncological outcomes.

On the Impact of Different Lung Ultrasound Imaging Protocols in the Evaluation of Patients Affected by Coronavirus Disease 2019: How Many Acquisitions Are Needed?

Lung ultrasound (LUS) is currently being extensively used for the evaluation of patients affected by coronavirus disease 2019. In the past months, several imaging protocols have been proposed in the literature. However, how the different protocols would compare when applied to the same patients had not been investigated yet. To this end, in this multicenter study, we analyzed the outcomes of 4 different LUS imaging protocols, respectively based on 4, 8, 12, and 14 LUS acquisitions, on data from 88 patients. Results show how a 12-area acquisition system seems to be a good tradeoff between the acquisition time and accuracy.

Lung Ultrasound for COVID-19 Patchy Pneumonia: Extended or Limited Evaluations?

OBJECTIVES: The 2019 novel coronavirus (severe acute respiratory syndrome coronavirus 2) is causing cases of severe pneumonia. Lung ultrasound (LUS) could be a useful tool for physicians detecting a bilateral heterogeneous patchy distribution of pathologic findings in a symptomatic suggestive context. The aim of this study was to focus on the implications of limiting LUS examinations to specific regions of the chest. METHODS: Patients were evaluated with a standard sequence of LUS scans in 14 anatomic areas. A scoring system of LUS findings was reported, ranging from 0 to 3 (worst score, 3). The scores reported on anterior, lateral, and posterior landmarks were analyzed separately and compared with each other and with the global findings. RESULTS: Thirty-eight patients were enrolled. A higher prevalence of score 0 was observed in the anterior region (44.08%). On the contrary, 21.05% of posterior regions and 13.62% of lateral regions were evaluated as score 3, whereas only 5.92% of anterior regions were classified as score 3. Findings from chest computed tomography performed in 16 patients with coronavirus disease 2019 correlated with and matched the distribution of findings from LUS. CONCLUSIONS: To assess the quantity and severity of lung disease, a comprehensive LUS examination is recommended. Omitting areas of the chest misses involved lung.

A New Lung Ultrasound Protocol Able to Predict Worsening in Patients Affected by Severe Acute Respiratory Syndrome Coronavirus 2 Pneumonia.

OBJECTIVES: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can generate severe pneumonia associated with high mortality. A bedside lung ultrasound (LUS) examination has been shown to have a potential role in this setting. The purpose of this study was to evaluate the potential prognostic value of a new LUS protocol (evaluation of 14 anatomic landmarks, with graded scores of 0-3) in patients with SARS-CoV-2 pneumonia and the association of LUS patterns with clinical or laboratory findings. METHODS: A cohort of 52 consecutive patients with laboratory-confirmed SARS-CoV-2 underwent LUS examinations on admission in an internal medicine ward and before their discharge. A total LUS score as the sum of the scores at each explored area was computed. We investigated the association between the LUS score and clinical worsening, defined as a combination of high-flow oxygen support, intensive care unit admission, or 30-day mortality as the primary end point. RESULTS: Twenty (39%) patients showed a worse outcome during the observation period; the mean LUS scores ± SDs were 20.4 ± 8.5 and 29.2 ± 7.3 in patients without and with worsening, respectively (P < .001). In a multivariable analysis, adjusted for comorbidities (>2), age (>65 years), sex (male), and body mass index (≥25 kg/m2 ), the association between the LUS score and worsening (odds ratio, 1.17; 95% confidence interval, 1.05 to 1.29; P = .003) was confirmed, with good discrimination of the model (area under the receiver operating characteristic curve, 0.82). A median LUS score higher than 24 was associated with an almost 6-fold increase in the odds of worsening (odds ratio, 5.67; 95% confidence interval, 1.29 to 24.8; P = .021). CONCLUSIONS: Lung ultrasound can represent an effective tool for monitoring and stratifying the prognosis of patients with SARS-CoV-2 pulmonary involvement.

Deep learning applied to lung ultrasound videos for scoring COVID-19 patients: A multicenter study.

In the current pandemic, lung ultrasound (LUS) played a useful role in evaluating patients affected by COVID-19. However, LUS remains limited to the visual inspection of ultrasound data, thus negatively affecting the reliability and reproducibility of the findings. Moreover, many different imaging protocols have been proposed, most of which lacked proper clinical validation. To address these problems, we were the first to propose a standardized imaging protocol and scoring system. Next, we developed the first deep learning (DL) algorithms capable of evaluating LUS videos providing, for each video-frame, the score as well as semantic segmentation. Moreover, we have analyzed the impact of different imaging protocols and demonstrated the prognostic value of our approach. In this work, we report on the level of agreement between the DL and LUS experts, when evaluating LUS data. The results show a percentage of agreement between DL and LUS experts of 85.96% in the stratification between patients at high risk of clinical worsening and patients at low risk. These encouraging results demonstrate the potential of DL models for the automatic scoring of LUS data, when applied to high quality data acquired accordingly to a standardized imaging protocol.

Investigating training-test data splitting strategies for automated segmentation and scoring of COVID-19 lung ultrasound images.

Ultrasound in point-of-care lung assessment is becoming increasingly relevant. This is further reinforced in the context of the COVID-19 pandemic, where rapid decisions on the lung state must be made for staging and monitoring purposes. The lung structural changes due to severe COVID-19 modify the way ultrasound propagates in the parenchyma. This is reflected by changes in the appearance of the lung ultrasound images. In abnormal lungs, vertical artifacts known as B-lines appear and can evolve into white lung patterns in the more severe cases. Currently, these artifacts are assessed by trained physicians, and the diagnosis is qualitative and operator dependent. In this article, an automatic segmentation method using a convolutional neural network is proposed to automatically stage the progression of the disease. 1863 B-mode images from 203 videos obtained from 14 asymptomatic individual,14 confirmed COVID-19 cases, and 4 suspected COVID-19 cases were used. Signs of lung damage, such as the presence and extent of B-lines and white lung areas, are manually segmented and scored from zero to three (most severe). These manually scored images are considered as ground truth. Different test-training strategies are evaluated in this study. The results shed light on the efficient approaches and common challenges associated with automatic segmentation methods.

Immediate allergic reaction to thiocolchicoside confirmed by skin testing and basophil activation test: A case report and literature review.

BACKGROUND: Thiocolchicoside is a muscle relaxant, anti-inflammatory, and analgesic. Administered orally, intramuscularly, or topically, this drug is used in the symptomatic treatment of muscular spasms and rheumatologic disorders. Despite its extensive use, thiocolchicoside is a very rare sensitizer. OBJECTIVE: To evaluate IgE-mediated reaction to thiocolchicoside by basophil activation test. METHODS: Allergological work-up with skin prick tests, intradermal tests and basophil activation test with thiocolchicoside. RESULTS: We report the first case of immediate reaction to thiocolchicoside confirmed by basophil activation test in addition to positive skin tests. CONCLUSIONS: BAT can be considered a complementary diagnostic tool to demonstrate an IgE-mediated reaction also for muscle relaxant drugs.

Occupational hand dermatitis web survey in a university hospital during COVID-19 pandemic: the SHIELD study.

BACKGROUND: Occupational hand dermatitis (OHD) is a skin disease occurring on employees' hands in certain jobs. Little is known about prevalence, incidence and characteristics of this adverse skin reaction and its associated risk factors during COVID-19 pandemic. To evaluate both prevalence and incidence of OHD and associated risk factors in Italian clinicians. METHODS: A cross-sectional study was performed using a self-report questionnaire. RESULTS: Two hundred and thirty clinicians responded to the survey and 82% of responders did not report previous OHD history before the COVID-19 pandemic. Daily use of gloves was reported by 80% of responders. OHD prevalence was 18%, while incidence was 80%. We found a protective effect on symptom occurrence for vinyl/nitrile gloves if the time with gloves was ≥ 6 hours per day. CONCLUSIONS: This survey reveals a high OHD incidence in an Italian population of clinicians. Furthermore, wearing vinyl/nitrile gloves for at least 6 hours a day had a protective effect on symptom onset.

The diagnosis of pneumonia in a pregnant woman with coronavirus disease 2019 using maternal lung ultrasound.

Lung ultrasound examination has been demonstrated to be an accurate imaging method to detect pulmonary and pleural conditions. During pregnancy, there is a need for rapid assessment of the maternal lung in patients with suspected coronavirus disease 2019. We report our experience on lung ultrasound examination in the diagnosis of coronavirus disease 2019 pneumonia in a pregnant woman. Typical ultrasound features of this pulmonary pathology, including diffuse hyperechoic vertical artifacts with thickened pleural line and "white lung" with patchy distribution, were observed. We suggest point-of-care lung ultrasound examination as a diagnostic imaging tool in pregnant women with suspected coronavirus disease 2019.