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Background and objective The diagnosis of rare diseases (RDs) is often challenging due to their rarity, variability and the high number of individual RDs, resulting in a delay in diagnosis with adverse effects for patients and healthcare systems. The development of computer assisted diagnostic decision support systems could help to improve these problems by supporting differential diagnosis and by prompting physicians to initiate the right diagnostic tests. Towards this end, we developed, trained and tested a machine learning model implemented as part of the software called Pain2D to classify four rare diseases (EDS, GBS, FSHD and PROMM), as well as a control group of unspecific chronic pain, from pen-and-paper pain drawings filled in by patients. Methods Pain drawings (PDs) were collected from patients suffering from one of the four RDs, or from unspecific chronic pain. The latter PDs were used as an outgroup in order to test how Pain2D handles more common pain causes. A total of 262 (59 EDS, 29 GBS, 35 FSHD, 89 PROMM, 50 unspecific chronic pain) PDs were collected and used to generate disease specific pain profiles. PDs were then classified by Pain2D in a leave-one-out-cross-validation approach. Results Pain2D was able to classify the four rare diseases with an accuracy of 61–77% with its binary classifier. EDS, GBS and FSHD were classified correctly by the Pain2D k-disease classifier with sensitivities between 63 and 86% and specificities between 81 and 89%. For PROMM, the k-disease classifier achieved a sensitivity of 51% and specificity of 90%. Conclusions Pain2D is a scalable, open-source tool that could potentially be trained for all diseases presenting with pain.

Many monogenic disorders cause a characteristic facial morphology. Artificial intelligence can support physicians in recognizing these patterns by associating facial phenotypes with the underlying syndrome through training on thousands of patient photographs. However, this ‘supervised’ approach means that diagnoses are only possible if the disorder was part of the training set. To improve recognition of ultra-rare disorders, we developed GestaltMatcher, an encoder for portraits that is based on a deep convolutional neural network. Photographs of 17,560 patients with 1,115 rare disorders were used to define a Clinical Face Phenotype Space, in which distances between cases define syndromic similarity. Here we show that patients can be matched to others with the same molecular diagnosis even when the disorder was not included in the training set. Together with mutation data, GestaltMatcher could not only accelerate the clinical diagnosis of patients with ultra-rare disorders and facial dysmorphism but also enable the delineation of new phenotypes. GestaltMatcher uses a deep convolutional neural network to improve recognition of rare disorders based on facial morphology. The framework detects similarities among patients with previously unseen syndromes, aiding discovery of new disease genes.

Background Rare diseases (RDs) affect less than 5/10,000 people in Europe and fewer than 200,000 individuals in the United States. In rheumatology, RDs are heterogeneous and lack systemic classification. Clinical courses involve a variety of diverse symptoms, and patients may be misdiagnosed and not receive appropriate treatment. The objective of this study was to identify and classify some of the most important RDs in rheumatology. We also attempted to determine their combined prevalence to more precisely define this area of rheumatology and increase awareness of RDs in healthcare systems. We conducted a comprehensive literature search and analyzed each disease for the specified criteria, such as clinical symptoms, treatment regimens, prognoses, and point prevalences. If no epidemiological data were available, we estimated the prevalence as 1/1,000,000. The total point prevalence for all RDs in rheumatology was estimated as the sum of the individually determined prevalences. Results A total of 76 syndromes and diseases were identified, including vasculitis/vasculopathy (n = 15), arthritis/arthropathy (n = 11), autoinflammatory syndromes (n = 11), myositis (n = 9), bone disorders (n = 11), connective tissue diseases (n = 8), overgrowth syndromes (n = 3), and others (n = 8). Out of the 76 diseases, 61 (80%) are classified as chronic, with a remitting-relapsing course in 27 cases (35%) upon adequate treatment. Another 34 (45%) diseases were predominantly progressive and difficult to control. Corticosteroids are a therapeutic option in 49 (64%) syndromes. Mortality is variable and could not be determined precisely. Epidemiological studies and prevalence data were available for 33 syndromes and diseases. For an additional eight diseases, only incidence data were accessible. The summed prevalence of all RDs was 28.8/10,000. Conclusions RDs in rheumatology are frequently chronic, progressive, and present variable symptoms. Treatment options are often restricted to corticosteroids, presumably because of the scarcity of randomized controlled trials. The estimated combined prevalence is significant and almost double that of ankylosing spondylitis (18/10,000). Thus, healthcare systems should assign RDs similar importance as any other common disease in rheumatology.

Background Rare diseases (RDs) in rheumatology as a group have a high prevalence, but randomized controlled trials are hampered by their heterogeneity and low individual prevalence. To survey the current evidence of pharmacotherapies for rare rheumatic diseases, we conducted a systematic review and meta-analysis. Randomized controlled trials (RCTs) of RDs in rheumatology for different pharmaco-interventions were included into this meta-analysis if there were two or more trials investigating the same RD and using the same assessment tools or outcome parameters. The Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PUBMED were searched up to April 2nd 2020. The overall objective of this study was to identify RCTs of RDs in rheumatology, evaluate the overall quality of these studies, outline the evidence of pharmacotherapy, and summarize recommended therapeutic regimens. Results We screened 187 publications, and 50 RCTs met our inclusion criteria. In total, we analyzed data of 13 different RDs. We identified several sources of potential bias, such as a lack of description of blinding methods and allocation concealment, as well as small size of the study population. Meta-analysis was possible for 26 studies covering six RDs: Hunter disease, Behçet’s disease, giant cell arteritis, ANCA-associated vasculitis, reactive arthritis, and systemic sclerosis. The pharmacotherapies tested in these studies consisted of immunosuppressants, such as corticosteroids, methotrexate and azathioprine, or biologicals. We found solid evidence for idursulfase as a treatment for Hunter syndrome. In Behçet’s disease, apremilast and IF-α showed promising results with regard to total and partial remission, and Tocilizumab with regard to relapse-free remission in giant cell arteritis. Rituximab, cyclophosphamide, and azathioprine were equally effective in ANCA-associated vasculitis, while mepolizumab improved the efficacy of glucocorticoids. The combination of rifampicin and azithromycin showed promising results in reactive arthritis, while there was no convincing evidence for the efficacy of pharmacotherapy in systemic sclerosis. Conclusion For some diseases such as systemic sclerosis, ANCA-associated vasculitis, or Behcet's disease, higher quality trials were available. These RCTs showed satisfactory efficacies for immunosuppressants or biological drugs, except for systemic sclerosis. More high quality RCTs are urgently warranted for a wide spectrum of RDs in rheumatology.

Introduction Rare diseases (RD) are characterized by chronicity and may be associated with reduced life expectancy and quality of life. Case series and reports regarding pregnancies in individuals with specific RD exist, but there is no data on the outcome of pregnancies in the overall group. Material and Methods A retrospective analysis was conducted of all pregnancies in women with RD who were managed at our center between January 2018 and July 2022. Maternal, fetal, and obstetric parameters were recorded. Results During the study period, 388 pregnant women with 434 RD were managed. Of these, 11.9% had more than one RD. The breakdown of conditions was as follows: 50.7% acquired diseases, 21% congenital diseases excluding malformations, 17.5% malformations, and 10.8% tumors. Disease‐specific complications occurred in 23.2% of women, and pregnancy‐specific complications in 25.1% of live births. Women with preconception stability experienced significantly fewer complications. The cesarean section rate was 50.6%. Preterm birth occurred in 15.3% of cases, and 20.4% of newborns required admission to the neonatal intensive care unit. Conclusions Women with RD experience a high rate of disease‐specific and pregnancy complications. Preconception stability is a key factor for an uncomplicated course of pregnancy and birth. Pregnancies in women with rare diseases carry substantial disease‐related (23.2%) and pregnancy‐specific (25.1%) risks. Complication rates drop markedly when conditions are stable before conception.

Background Patients with rare diseases often face prolonged diagnostic journeys due to the low prevalence and diverse clinical presentations of these conditions. In Germany, specialized centers for rare diseases, established at university hospitals, offer targeted diagnostic and therapeutic care to reduce diagnostic delays. Tools like “Isabel Healthcare” can support clinicians by streamlining the differential diagnosis process and aiding in the accurate identification of rare conditions. Results The study included 100 patients with a mean age of 44 years. “Isabel Healthcare DDx companion” and the interdisciplinary case conferences generated a total of 727 diagnosis suggestions. Among the top ten diagnoses suggested by “Isabel Healthcare DDx companion”, 28% matched at least one diagnosis identified during the interdisciplinary case conferences. The diagnoses suggested as “more likely” by “Isabel Healthcare DDx companion” showed a higher correlation with the differential diagnoses and procedures identified during the interdisciplinary case conferences, suggesting a potential alignment in clinical decision-making processes. Conclusion This study has demonstrated the potential of the differential diagnostic tool “Isabel Healthcare DDx companion” to assist in patient diagnosis. However, discrepancies between the tool’s findings and expert decisions suggest that, although it can support clinicians in decision-making, its independent effectiveness may be limited by accurately filtering and interpreting the essential medical history required for a precise diagnosis.

Background The diagnosis of rare diseases poses a particular challenge to clinicians. This study analyzes whether patients’ pain drawings (PDs) help in the differentiation of two pain-associated rare diseases, Ehlers-Danlos Syndrome (EDS) and Guillain-Barré Syndrome (GBS). Method The study was designed as a prospective, observational, single-center study. The sample comprised 60 patients with EDS (3 male, 52 female, 5 without gender information; 39.2 ± 11.4 years) and 32 patients with GBS (10 male, 20 female, 2 without gender information; 50.5 ± 13.7 years). Patients marked areas afflicted by pain on a sketch of a human body with anterior, posterior, and lateral views. PDs were electronically scanned and processed. Each PD was classified based on the Ružička similarity to the EDS and the GBS averaged image (pain profile) in a leave-one-out cross validation approach. A receiver operating characteristic (ROC) curve was plotted. Results 60–80% of EDS patients marked the vertebral column with the neck and the tailbone and the knee joints as pain areas, 40–50% the shoulder-region, the elbows and the thumb saddle joint. 60–70% of GBS patients marked the dorsal and plantar side of the feet as pain areas, 40–50% the palmar side of the fingertips, the dorsal side of the left palm and the tailbone. 86% of the EDS patients and 96% of the GBS patients were correctly identified by computing the Ružička similarity. The ROC curve yielded an excellent area under the curve value of 0.95. Conclusion PDs are a useful and economic tool to differentiate between GBS and EDS. Further studies should investigate its usefulness in the diagnosis of other pain-associated rare diseases. This study was registered in the German Clinical Trials Register, No. DRKS00014777 (Deutsches Register klinischer Studien, DRKS), on 01.06.2018.

: This case study illustrates the difficulties in diagnosing rare diseases, specifically familial mediterranean fever. Familial mediterranean fever classically presents with recurrent episodes of fever. It is often associated with peritonitis, pleuritis or arthritis. The diagnosis can be made clinically, although genetic diagnostics should always be performed. Early diagnosis is important, as the symptoms can usually be treated well with consistent colchicine therapy and the risk of life-threatening amyloidosis can be reduced.

Competency-based education is used in several healthcare profession educational programs. Competency-based education has been at the forefront of dietetics education for several years and continues to this day. It is used in the undergraduate programs as well as in dietetic internships. The mastery of these competencies reflects the skillset a student or intern has achieved to be ready to advance to the next level. For an undergraduate student, mastery of all undergraduate competencies would indicate the ability to graduate the program and be eligible to apply to a dietetic internship. For a dietetic intern, mastery of all competencies would indicate that the intern would be eligible to complete the internship and would possess the skillsets to be ready for entry-level practice as a registered dietitian nutritionist. Mastering these competencies by an undergraduate student takes place in the classroom through education, assignments and experiences. The best-case scenario of the mastery of these competencies as an intern is in the supervised practice field experience with a preceptor. A preceptor is an individual who is considered a professional in their field of expertise. At times, a competency cannot be met in the field and is then met through alternative means. An internship director is responsible for devising strategies to assist the intern in meeting competencies. The purpose of this study was to compare the perceptions of directors of onsite (traditional) and distance internships regarding any challenges they may face in implementing strategies to meet core competencies. This study was based on a non-experimental quantitative and qualitative data collection design utilizing descriptive survey research. During the first phase of the study a pilot study was conducted, given that there were no previously developed surveys available. The second phase of the study included sending out a survey to 35 distance internship directors and 35 to onsite (traditional) internship directors. The results of the study showed that there were three core competencies among 41 core competencies with significant differences between onsite (traditional) and distance internship directors’ perceptions of challenges. The results of this study also showed the many challenges that are faced by distance and onsite (traditional) internship directors who are devising strategies to meet the core competencies. The results of this study also showed no significant differences in the success of graduates of onsite (traditional) and distance internships on the national registration examination for dietitians. The results of this study also showed that many of the onsite (traditional) and distance internship directors perceive that the mastery of core competencies during an internship does not have much influence on first-time pass rates on the national registration examination. This study informs dietetic internship directors or any other healthcare profession educational program that uses competency-based practices as to the challenges that are faced in devising strategies to meet these competencies. This study also informs internship directors of possible strategies to overcome these challenges. This study compliments past research studies as it showed that there are quality experiences and successes of graduates of both onsite (traditional) and distance internships.