The changing epidemiology of human leishmaniasis in the non-endemic country of Austria between 2000 to 2021, including a congenital case.

BACKGROUND: Leishmaniasis is caused by infection with intracellular protozoans of the genus Leishmania. Transmission occurs predominantly by the bite of phlebotomine sandflies, other routes, including congenital transmission, are rare. The disease manifests as either cutaneous, visceral or mucosal/mucocutaneous leishmaniasis. In recent years, changes in the epidemiological pattern have been reported from Europe. PRINCIPAL FINDINGS: A total of 311 new and 29 published leishmaniasis cases occurring between 01/01/2000 and 12/31/2021 in Austria were collected and analyzed. These encompassed 146 cutaneous (CL), 14 visceral (VL), 4 mucosal, and 3 cases with concurrent VL and CL. In addition, asymptomatic infections, comprising 11 unspecified cases with Leishmania DNA detectable only in the blood and 162 cases with anti-Leishmania antibodies were reported. Particularly since 2016, the incidence of leishmaniasis has steadily risen, mainly attributable to increasing numbers of CL and cases with positive serology against Leishmania species, whereas the incidence of VL has slowly decreased. Analysis revealed that a shift in the causative species spectrum had occurred and that a substantial number of CL cases were caused by members of the Leishmania donovani/infantum complex. Simultaneous occurrence of VL and CL was identified in immunocompromised individuals, but also in a not yet reported case of an immunocompetent child after vertical transmission. CONCLUSIONS: The incidence of leishmaniasis has risen in the recent years. The numbers are anticipated to keep rising due to increasing human mobility, including travel and forced migration, growing reservoir host populations as well as expansion and dispersal of vector species caused by climate and habitat changes, urbanization and globalization. Hence, elevated awareness for the disease, including possible transmission in previously non-endemic regions and non-vector transmission modes, support of sandfly surveillance efforts and implementation and establishment of public health interventions in a One Health approach are pivotal in the global efforts to control and reduce leishmaniasis.

Comparison of humans versus mobile phone-powered artificial intelligence for the diagnosis and management of pigmented skin cancer in secondary care: a multicentre, prospective, diagnostic, clinical trial.

BACKGROUND: Diagnosis of skin cancer requires medical expertise, which is scarce. Mobile phone-powered artificial intelligence (AI) could aid diagnosis, but it is unclear how this technology performs in a clinical scenario. Our primary aim was to test in the clinic whether there was equivalence between AI algorithms and clinicians for the diagnosis and management of pigmented skin lesions. METHODS: In this multicentre, prospective, diagnostic, clinical trial, we included specialist and novice clinicians and patients from two tertiary referral centres in Australia and Austria. Specialists had a specialist medical qualification related to diagnosing and managing pigmented skin lesions, whereas novices were dermatology junior doctors or registrars in trainee positions who had experience in examining and managing these lesions. Eligible patients were aged 18-99 years and had a modified Fitzpatrick I-III skin type; those in the diagnostic trial were undergoing routine excision or biopsy of one or more suspicious pigmented skin lesions bigger than 3 mm in the longest diameter, and those in the management trial had baseline total-body photographs taken within 1-4 years. We used two mobile phone-powered AI instruments incorporating a simple optical attachment: a new 7-class AI algorithm and the International Skin Imaging Collaboration (ISIC) AI algorithm, which was previously tested in a large online reader study. The reference standard for excised lesions in the diagnostic trial was histopathological examination; in the management trial, the reference standard was a descending hierarchy based on histopathological examination, comparison of baseline total-body photographs, digital monitoring, and telediagnosis. The main outcome of this study was to compare the accuracy of expert and novice diagnostic and management decisions with the two AI instruments. Possible decisions in the management trial were dismissal, biopsy, or 3-month monitoring. Decisions to monitor were considered equivalent to dismissal (scenario A) or biopsy of malignant lesions (scenario B). The trial was registered at the Australian New Zealand Clinical Trials Registry ACTRN12620000695909 (Universal trial number U1111-1251-8995). FINDINGS: The diagnostic study included 172 suspicious pigmented lesions (84 malignant) from 124 patients and the management study included 5696 pigmented lesions (18 malignant) from the whole body of 66 high-risk patients. The diagnoses of the 7-class AI algorithm were equivalent to the specialists' diagnoses (absolute accuracy difference 1·2% [95% CI -6·9 to 9·2]) and significantly superior to the novices' ones (21·5% [13·1 to 30·0]). The diagnoses of the ISIC AI algorithm were significantly inferior to the specialists' diagnoses (-11·6% [-20·3 to -3·0]) but significantly superior to the novices' ones (8·7% [-0·5 to 18·0]). The best 7-class management AI was significantly inferior to specialists' management (absolute accuracy difference in correct management decision -0·5% [95% CI -0·7 to -0·2] in scenario A and -0·4% [-0·8 to -0·05] in scenario B). Compared with the novices' management, the 7-class management AI was significantly inferior (-0·4% [-0·6 to -0·2]) in scenario A but significantly superior (0·4% [0·0 to 0·9]) in scenario B. INTERPRETATION: The mobile phone-powered AI technology is simple, practical, and accurate for the diagnosis of suspicious pigmented skin cancer in patients presenting to a specialist setting, although its usage for management decisions requires more careful execution. An AI algorithm that was superior in experimental studies was significantly inferior to specialists in a real-world scenario, suggesting that caution is needed when extrapolating results of experimental studies to clinical practice. FUNDING: MetaOptima Technology.

Diagnostic difficulties in pediatric annular dermatoses.

The polymorphic presentation of annular dermatoses in the pediatric population renders them a diagnostic challenge to the clinician. They include various distinct disease entities that can be vaguely categorized according to the age of onset. Herein, we report on a young girl with clinical characteristics of Wells' syndrome, while histological findings favored the diagnosis of annular erythema of infancy (AEI). Although morphological and histological similarities do exist, AEI and eosinophilic annular erythema (EAE) of childhood are considered as distinct entities in the literature. Wells' syndrome (WS) is an eosinophilic dermatosis and histologically characterized by eosinophilic dermal infiltration with the hallmark feature of "flame figures." Based on this case, we discuss and review the differential diagnoses of annular dermatoses in children.