Background: As a result of the COVID‐19 outbreak, hygiene regulations have been revised and hand sanitation has been intensified.Objective: To investigate the onset of hand eczema during the COVID‐19 pandemic in healthcare workers (HCWs) directly involved in intensive care of COVID‐19 patients and HCWs without direct contact with COVID‐19 patients. Hereby, we aim at increasing awareness about occupational hand eczema and preventive measures that can be adopted.Method: A survey was distributed amongst 114 HCWs at a single surgical centre and at a COVID‐19 intensive care unit of the university hospital Ludwig Maximilian University Munich, Germany. Participants were questioned about the daily frequency of hand hygiene prior to and during the pandemic. Participants self‐reported the onset of hand eczema and associated symptoms.Results: Our study revealed a significant increase in hand washing, disinfection, and use of hand cream across all participants (P‐value <.001), regardless of having direct contact with COVID‐19 patients. A high prevalence of symptoms associated with acute hand dermatitis of 90.4% was found across all HCWs, whereas hand eczema itself was underreported (14.9%).Conclusion: The increase in hand sanitation during the COVID‐19 pandemic impairs the skin of the hands across all HCWs, independent of direct intensive care of affected patients.

Background Basal cell carcinoma (BCC) is the most common skin cancer in the general population. Treatments vary from Mohs surgery to topical therapy, depending on the subtype. Dermoscopy, reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) have gained a foothold in daily clinical practice to optimize diagnosis and subtype-oriented treatment. The new device Line-field confocal OCT (LC-OCT) allows imaging at high resolution and depth but its use is not yet been investigated in larger studies. Objectives To evaluate the main LC-OCT criteria for the diagnosis and subtyping of BCC in comparison to histopathology, OCT and RCM. Methods Fifty-two histopathologically confirmed BCCs were evaluated for imaging criteria. Their frequency, predictive values and ROC curves were calculated. A multinominal regression with stepwise variables selection to distinguish BCC subtypes was performed. Results Nodular BCCs were mainly characterized by atypical keratinocytes, altered DEJ, tumour nests in the dermis, dark clefting, prominent vascularisation and white hyperreflective stroma. Superficial BCCs showed a thickening of the epidermis due to a series of tumour lobules with clear connection to the DEJ (string of pearls pattern). Infiltrative BCCs were characterized by elongated hyporeflective tumour strands, surrounded by bright collagen (shoal of fish). The overall BCC subtype agreement between LC-OCT and conventional histology was 90.4 % (95% CI: 79.0, 96.8). Conclusion LC-OCT allows the non-invasive, real time identification of BCCs and their subtypes in vertical, horizontal and 3D mode compared to histology, RCM and OCT. Further larger studies are needed to better explore the clinical applications of this promising device.

Background: The treatment of keratinocyte cancers (KC) strictly depends on their differentiation and invasiveness. Non‐invasive diagnostic techniques can support the diagnosis in real time, avoiding unnecessary biopsies. This study aimed to preliminarily define main imaging criteria and histological correlations of actinic keratosis (AK), Bowen’s disease (BD) and squamous cell carcinoma (SCC) using the novel device line‐field confocal optical coherence tomography (LC‐OCT).Methods: Dermoscopy and LC‐OCT images of 73 histopathologically confirmed lesions (46 AKs, 11 BD and 16 SCCs) were included in the study. Exemplary lesions (10 AKs, 5 BD and 5 SCCs) were additionally investigated with optical coherence tomography and reflectance confocal microscopy.Results: Most common LC‐OCT findings of KC in the descriptive statistics were hyperkeratosis/parakeratosis, disruption of stratum corneum, broadened epidermis, basal and suprabasal keratinocyte atypia, dilated vessels/neoangiogenesis and elastosis/collagen alterations. In the univariate multinomial logistic regression, a preserved DEJ was less common in SCC compared with AK and BD, BD displayed marked keratinocyte atypia involving all epidermal layers (bowenoid pattern), while SCC showed ulceration, increased epidermal thickness, keratin plugs, acantholysis, not visible/interrupted DEJ and epidermal bright particles. LC‐OCT increased the diagnostic confidence by 24.7% compared with dermoscopy alone.Conclusions: Our study describes for the first time specific LC‐OCT features of different stages of KC and their histopathological correlates, focusing on keratinocyte morphology and architecture of the epidermis and DEJ. LC‐OCT may open new scenarios in the bedside diagnosis, treatment planning and follow‐up of KC.

Background: Anti-IL-5 antibodies represent an established therapy for severe eosinophilic asthma (SEA), but some patients show inadequate response. The objective of this study was to assess the effects of a switch to anti-IL-5Rα therapy in patients with inadequate response to anti-IL-5 therapy. Methods: In this retrospective multi-centre, real-life study, we analysed all SEA patients switched from anti-IL-5 to anti-IL-5Rα therapy due to inadequate response or intolerability. Pulmonary function tests, blood gas analyses, asthma control tests (ACT) and oral corticosteroid (OCS) usage were analysed and compared at three timepoints: baseline (BL, before anti-IL-5 therapy), timepoint 1 (T1, under anti-IL-5 therapy) and timepoint 2 (T2, under anti-IL-5Rα therapy). Results: Of 665 patients treated with anti-IL-5 antibodies, 70 were switched to anti-IL-5Rα and 60 were included in the analysis. Median treatment duration was 8 months [IQR 5; 15] for anti-IL-5 and 5 months [IQR 4; 6] for anti-IL-5Rα therapy. FEV₁ was 61% of predicted at BL [IQR 41; 74], 61% [IQR 43; 79] at T1 and 68% [IQR 49; 87] at T2 (p_T1-T2=0.011). ACT score was 10 [IQR 8; 13], 16 [IQR 10; 19] and 19 [IQR 14; 22], respectively (both p< 0.001). The number of patients requiring OCS was reduced from 41 (BL) to 32 (T1) and 19 (T2) (both p< 0.001). Ten patients discontinued anti-IL-5Rα therapy due to insufficient efficacy (n=7) and adverse events (n=3). Conclusion: Switching from anti-IL-5 to anti-IL-5Rα therapy in patients with inadequate response was associated with significantly improved FEV₁, asthma control and OCS reduction.

Background Food anaphylaxis is commonly elicited by unintentional ingestion of foods containing the allergen above the tolerance threshold level of the individual. While labelling the 14 main allergens used as ingredients in food products is mandatory in the EU, there is no legal definition of declaring potential contaminants. Precautionary allergen labelling such as “may contain traces of” is often used. However, this is unsatisfactory for consumers as they get no information if the contamination is below their personal threshold. In discussions with the food industry and technologists, it was suggested to use a voluntary declaration indicating that all declared contaminants are below a threshold of 0.5 mg protein per 100 g of food. This concentration is known to be below the threshold of most patients, and it can be technically guaranteed in most food production. However, it was also important to assess that in case of accidental ingestion of contaminants below this threshold by highly allergic patients, no fatal anaphylactic reaction could occur. Therefore, we performed a systematic review to assess whether a fatal reaction to 5mg of protein or less has been reported, assuming that a maximum portion size of 1kg of a processed food exceeds any meal and thus gives a sufficient safety margin. Methods MEDLINE and EMBASE were searched until 24^th January 2021 for provocation studies and case reports in which one of the 14 major food allergens was reported to elicit fatal or life-threatening anaphylactic reactions and assessed if these occurred below the ingestion of 5mg of protein. A Delphi process was performed to obtain an expert consensus on the results. Results In the 210 studies included, in our search no reports of fatal anaphylactic reactions reported below 5 mg protein ingested were identified. However, in provocation studies and case reports, severe reactions below 5mg were reported for the following allergens: eggs, fish, lupin, milk, nuts, peanuts, soy, and sesame seeds. Conclusion Based on the literature studied for this review it can be stated that cross-contamination of the 14 major food allergens below 0.5 mg/100 g is likely not to endanger most food allergic patients when a standard portion of food is consumed. We propose to use the statement “this product contains the named allergens in the list of ingredients, it may contain traces of other contaminations (to be named, e.g. nut) at concentrations less than 0.5 mg per 100 g of this product” for a voluntary declaration on processed food packages. This level of avoidance of cross-contaminations can be achieved technically for most processed foods, and the statement would be a clear and helpful message to the consumers. However it is clearly acknowledged that a voluntary declaration is only a first step to a legally binding solution. For this, further research on threshold levels is encouraged.

Image classification with convolutional neural networks (CNN) offers an unprecedented opportunity to medical imaging. Regulatory agencies in the USA and Europe have already cleared numerous deep learning/machine learning based medical devices and algorithms. While the field of radiology is on the forefront of artificial intelligence (AI) revolution, conventional pathology, which commonly relies on examination of tissue samples on a glass slide, is falling behind in leveraging this technology. On the other hand, ex vivo confocal laser scanning microscopy (ex vivo CLSM), owing to its digital workflow features, has a high potential to benefit from integrating AI tools into the assessment and decision-making process. Aim of this work was to explore a preliminary application of CNN in digitally stained ex vivo CLSM images of cutaneous squamous cell carcinoma (cSCC) for automated detection of tumor tissue. Thirty-four freshly excised tissue samples were prospectively collected and examined immediately after resection. After the histologically confirmed ex vivo CLSM diagnosis, the tumor tissue was annotated for segmentation by experts, in order to train the MobileNet CNN. The model was then trained and evaluated using cross validation. The overall sensitivity and specificity of the deep neural network for detecting cSCC and tumor free areas on ex vivo CLSM slides compared to expert evaluation were 0.76 and 0.91, respectively. The area under the ROC curve was equal to 0.90 and the area under the precision-recall curve was 0.85. The results demonstrate a high potential of deep learning models to detect cSCC regions on digitally stained ex vivo CLSM slides and to distinguish them from tumor-free skin.