Patient-Oriented Questionnaires and Machine Learning for Rare Disease Diagnosis: A Systematic Review.

A major challenge faced by patients with rare diseases (RDs) often stems from delays in diagnosis, typically due to nonspecific clinical symptoms or doctors' limited experience in connecting symptoms to the underlying RD. Using patient-oriented questionnaires (POQs) as a data source for machine learning (ML) techniques can serve as a potential solution. These questionnaires enable patients to portray their day-to-day experiences living with their condition, irrespective of clinical symptoms.

Impact of virtual reality on peri-interventional pain, anxiety and distress in a pediatric oncology outpatient clinic: a randomized controlled trial.

Purpose: Pain and anxiety-inducing interventions have a major impact on pediatric patients. Pain reduction by virtual reality (VR) during port and vein punctures is well studied. This study investigates peri-interventional reduction of pain, anxiety and distress using VR compared to the standard of care (SOC) in a pediatric oncology outpatient clinic.

Exploring different stakeholders' perspectives on ward rounds in paediatric oncology: a qualitative study.

Rational/aims And Objectives: Ward rounds are a core routine for interprofessional communication and clinical care planning: Health care professionals and patients meet regularly and it encourages patients to actively participate. In paediatric oncology, the long treatment process, the serious diagnosis, and involvement of both patients and their parents in shared-decision-making require specific ward round skills. Despite its high value for patient-centred care, a universal definition of ward round is lacking.

A diagnostic support system based on pain drawings: binary and k-disease classification of EDS, GBS, FSHD, PROMM, and a control group with Pain2D.

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.

[Rare diseases in the differential diagnosis of myalgia].

Myalgia describes pain in the skeletal muscles. According to the current German clinical guidelines from 2020 (AWMF register number: 030/051), the initial diagnostic assessment consists of the anamnesis, clinical examination, electrophysiological examination and standard laboratory tests. Additional special examinations, such as molecular genetic investigations, special laboratory tests, medical imaging and muscle biopsy are only needed in certain cases.

Predictors of growth patterns in children with mucopolysaccharidosis I after haematopoietic stem cell transplantation.

Mucopolysaccharidosis type I (MPS I) is an autosomal-recessive metabolic disorder caused by an enzyme deficiency of lysosomal alpha-l-iduronidase (IDUA). Haematopoietic stem cell transplantation (HSCT) is the therapeutic option of choice in MPS I patients younger than 2.5 years, which has a positive impact on neurocognitive development.

Infants and Newborns with Atypical Teratoid Rhabdoid Tumors (ATRT) and Extracranial Malignant Rhabdoid Tumors (eMRT) in the EU-RHAB Registry: A Unique and Challenging Population.

Malignant rhabdoid tumors (MRT) predominantly affect infants and young children. Patients below six months of age represent a particularly therapeutically challenging group. Toxicity to developing organ sites limits intensity of treatment.

[Rare diseases in the differential diagnosis of myalgia].

Myalgia describes pain in the skeletal muscles. According to the current German clinical guidelines from 2020 (AWMF register number: 030/051), the initial diagnostic assessment consists of the anamnesis, clinical examination, electrophysiological examination and standard laboratory tests. Additional special examinations, such as molecular genetic investigations, special laboratory tests, medical imaging and muscle biopsy are only needed in certain cases.

Trigger finger in children with hurler syndrome - distribution pattern and treatment options.

Mucopolysaccharidosis is a rare and congenital autosomal recessive lysosomal storage disorder of glycosaminoglycans. An enzyme defect leads to cell, tissue and organ dysfunction. Carpal tunnel syndrome and trigger finger are the results of mucopolysaccharid deposition.

Rapid development of a digital module during the Covid 19 pandemic in undergraduate medical education of pediatrics by teachers and students.

During the early Covid 19 pandemic, undergraduate medical teaching of pediatric medicine had to be switched to online teaching at the Hanover Medical School (MHH). The aim was to develop an online module together with students. In a multi-stage process, a working group consisting of lecturers and students developed the concept and implemented it.

Clinical and genetic risk factors define two risk groups of extracranial malignant rhabdoid tumours (eMRT/RTK).

Introduction: Extracranial rhabdoid tumours are rare, highly aggressive malignancies primarily affecting young children. The EU-RHAB registry was initiated in 2009 to prospectively collect data of rhabdoid tumour patients treated according to the EU-RHAB therapeutic framework.

Methods: We evaluated 100 patients recruited within EU-RHAB (2009-2018).

Development of a Social Network for People Without a Diagnosis (RarePairs): Evaluation Study.

Background: Diagnostic delay in rare disease (RD) is common, occasionally lasting up to more than 20 years. In attempting to reduce it, diagnostic support tools have been studied extensively. However, social platforms have not yet been used for systematic diagnostic support.

Hematopoietic stem cell transplantation in mucopolysaccharidosis type IIIA: A case description and comparison with a genotype-matched control group.

Background: Mucopolysaccharidosis type IIIA (MPS IIIA, Sanfilippo A syndrome) is a chronic progressive neurodegenerative storage disorder caused by a deficiency of lysosomal sulfamidase. The clinical hallmarks are sleep disturbances, behavioral abnormalities and loss of cognitive, speech and motor abilities. Affected children show developmental slowing from the second year of life, dementia occurs by the age of 5 years followed by death in the second decade of life.

Common pre-diagnostic features in individuals with different rare diseases represent a key for diagnostic support with computerized pattern recognition?

Background: Rare diseases (RD) result in a wide variety of clinical presentations, and this creates a significant diagnostic challenge for health care professionals. We hypothesized that there exist a set of consistent and shared phenomena among all individuals affected by (different) RD during the time before diagnosis is established.

Objective: We aimed to identify commonalities between different RD and developed a machine learning diagnostic support tool for RD.

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Background: Diagnosing a rare metabolic disease challenges physicians and affected individuals and their families. To support the diagnostic pathway, a diagnostic tool was developed using the experiences of the affected individuals gained in interviews.

Methods: 17 interviews with parents or individuals with a selected rare metabolic disease (Mucopolysaccharidosis (MPS), M.

SICKO. Development of a Multi-Disciplinary Training-Concept for Paediatric Oncology.

Treating children with cancer requires multiple different skills. For the healthcare personnel (HCP) in Germany the practice of ongoing training to improve professional skills is almost non-existent. Therefore, we developed a programme called 'SICKO' to support HCPs skills and attitudes by means of a multidisciplinary workshop.

Patient's Experience in Pediatric Primary Immunodeficiency Disorders: Computerized Classification of Questionnaires.

Introduction: Primary immunodeficiency disorders (PIDs) are a heterogeneous group of more than 200 rare diseases. Timely diagnosis is of uttermost importance. Therefore, we aimed to develop a diagnostic questionnaire with computerized pattern-recognition in order to support physicians to identify suspicious patient histories.

[On the fast track to diagnosis : Recommendations for patients without a diagnosis].

Background: Patients, who have spent many years without a proper diagnosis present an extraordinary problem to health care providers and to the healthcare system as a whole. A long 'diagnostic journey' increases the risk of disease chronification, as well as the number of therapy attempts, which could lead to iatrogenic impairment. New resources and specialized health care departments are being developed to help and support this patient group.

Diagnostic needs for rare diseases and shared prediagnostic phenomena: Results of a German-wide expert Delphi survey.

Background: Worldwide approximately 7,000 rare diseases have been identified. Accordingly, 4 million individuals live with a rare disease in Germany. The mean time to diagnosis is about 6 years and patients receive several incorrect diagnoses during this time.

Diagnostic support for selected neuromuscular diseases using answer-pattern recognition and data mining techniques: a proof of concept multicenter prospective trial.

Background: Diagnosis of neuromuscular diseases in primary care is often challenging. Rare diseases such as Pompe disease are easily overlooked by the general practitioner. We therefore aimed to develop a diagnostic support tool using patient-oriented questions and combined data mining algorithms recognizing answer patterns in individuals with selected neuromuscular diseases.

Diagnostic Support for Selected Paediatric Pulmonary Diseases Using Answer-Pattern Recognition in Questionnaires Based on Combined Data Mining Applications--A Monocentric Observational Pilot Study.

Background: Clinical symptoms in children with pulmonary diseases are frequently non-specific. Rare diseases such as primary ciliary dyskinesia (PCD), cystic fibrosis (CF) or protracted bacterial bronchitis (PBB) can be easily missed at the general practitioner (GP).

Objective: To develop and test a questionnaire-based and data mining-supported tool providing diagnostic support for selected pulmonary diseases.

Supporting diagnostic decisions using hybrid and complementary data mining applications: a pilot study in the pediatric emergency department.

Introduction: This article demonstrates the capacity of a combination of different data mining (DM) methods to support diagnosis in pediatric emergency patients. By using a novel combination of these DM procedures, a computer-based diagnosis was created.

Methods: A support vector machine (SVM), artificial neural networks (ANNs), fuzzy logics, and a voting algorithm were simultaneously used to allocate a patient to one of 18 diagnoses (e.

[Carpal tunnel syndrome in children with mucopolysaccharidosis type 1H: diagnosis and therapy in an interdisciplinary centre].

Carpal tunnel syndrome is common in children with mucopolysaccharidosis type 1H (MPS type 1H). Clinical signs of carpal tunnel syndrome are frequently absent in these children and it is often very difficult to perform and interpret neurophysiological investigations. In this article we wish to present our experience and results regarding the diagnosis and postoperative results after decompression of the median nerve.