FindZebra online search delving into rare disease case reports using natural language processing

Obstacles to Early Diagnosis of Gaucher Disease

Gaucher disease (GD) is a rare lysosomal storage disorder resulting from a deficiency of the lysosomal enzyme glucocerebrosidase caused by biallelic variants in the GBA1 gene. Patients may present with a wide spectrum of disease manifestations, including hepatosplenomegaly, thrombocytopenia, bone manifestations, and in the case of GD types 2 and 3, neurodegeneration, cognitive delay, and/or oculomotor abnormalities. While there is no treatment for neuronopathic GD, non-neuronopathic manifestations can be efficiently managed with enzyme replacement therapy or substrate reduction therapy. However, many patients with GD experience a lengthy diagnostic odyssey, which can negatively affect their access to care and clinical outcomes. The cause of this diagnostic delay is multifaceted. Since genotype/phenotype correlations in GD are not always clear, it is difficult to predict the presence, severity, and onset of clinical manifestations. This heterogeneity, combined with the molecular complexity of the GBA1 locus, low disease prevalence, and limited knowledge of GD among providers serves as a barrier to early diagnosis of GD. In this review, we discuss such obstacles and challenges, considerations, and future steps toward improving the diagnostic journey for patients with GD.

"Crying in the Wilderness"-The Use of Web-Based Support in Telomere Biology Disorders: Thematic Analysis

BACKGROUND

Web-based information and social support are commonly used in rare disease communities where geographic dispersion and limited provider expertise complicate in-person support. We examined web-based resource use among caregivers of individuals with telomere biology disorders (TBDs), which are rare genetic conditions with long diagnostic odysseys and uncertain prognoses including multiorgan system cancer risk.

OBJECTIVE

This study explored internet-based information-seeking and social support practices and perspectives of patients with TBDs and their caregivers.

METHODS

Our qualitative descriptive study used semistructured interviews of patients with TBDs and caregivers. Data were transcribed verbatim and thematically analyzed by an interdisciplinary team.

RESULTS

A total of 32 adults completed interviews. Participant ages ranged from 27 to 74 years. The majority (n=28, 88%) were female, occupied multiple TBD roles (eg, patient and parent), and had undergone genetic testing. Most engaged in web-based information-seeking (n=29, 91%) and TBD-specific social media (n=26, 81%). Participants found web-based resources useful for information-seeking but reported privacy concerns and frustration with forming supportive relationships. Most participants described ambivalence toward web-based resource use, citing tensions between hunger for information versus distrust, empowerment versus overwhelm, disclosure versus privacy, and accessibility versus connection. Fluctuations in web-based support use arose from perceived harms, information saturation, or decreased relevance over the course of TBD illness experience.

CONCLUSIONS

Individuals with TBDs and their caregivers reported frequent use of web-based informational and emotional support. However, ambivalence about the benefits and liabilities of web-based resources and persistent medical uncertainty may impact the adoption of and adherence to web-based support among patients with TBD and caregivers. Our findings suggest web-based psychosocial support should target long-term and multifaceted informational and emotional needs, be user-initiated, be offered alongside in-person formats, provide expert-informed information, and be attentive to personal privacy and evolving support needs of the TBD community. This study suggests web-based resources will be most effective in the TBD context when they achieve the following features: (1) offer a variety of ways to engage (eg, active and passive), (2) provide privacy protections in moderated "safe spaces" designed for personal disclosure, (3) offer separate venues for informational versus emotional support, (4) combine web-based relationship formation with opportunities for in-person gathering, (5) provide information that is reliable, easy to access, and informed by medical professionals, (6) remain mindful of user distress, and (7) are responsive to variations in levels and types of engagement. Additionally, advocacy organizations may wish to avoid traditional social media platforms when designing safe spaces for web-based emotional support, instead pivoting to internet-based tools that minimize privacy threats and limit the perpetual public availability of shared information.

Opportunities and challenges for identifying undiagnosed Rare Disease patients through analysis of primary care records: long QT syndrome as a test case

BACKGROUND

Patients with rare genetic diseases frequently experience significant diagnostic delays. Routinely collected data in the electronic health record (EHR) may be used to help identify patients at risk of undiagnosed conditions. Long QT syndrome (LQTS) is a rare inherited cardiac condition associated with significant morbidity and premature mortality. In this study, we examine LQTS as an exemplar disease to assess if clinical features recorded in the primary care EHR can be used to develop and validate a predictive model to aid earlier detection.

METHODS

1495 patients with an LQTS diagnostic code and 7475 propensity-score matched controls were identified from 10.5 million patients' electronic primary care records in the UK's Clinical Practice Research Datalink (CPRD). Associated clinical features recorded before diagnosis (with p < 0.05) were incorporated into a multivariable logistic regression model, the final model was determined by backwards regression and validated by bootstrapping to determine model optimism.

RESULTS

The mean age at LQTS diagnosis was 58.4 (SD 19.41). 18 features were included in the final model. Discriminative accuracy, assessed by area under the curve (AUC), was 0.74, (95% CI 0.73, 0.75) (optimism 6%). Features occurring at significantly greater frequency before diagnosis included: epilepsy, palpitations, syncope, collapse, mitral valve disease and irritable bowel syndrome.

CONCLUSION

This study demonstrates the potential to develop primary care prediction models for rare conditions, like LQTS, in routine primary care records and highlights key considerations including disease suitability, finding an appropriate linked dataset, the need for accurate case ascertainment and utilising an approach to modelling suitable for rare events.

[Short paths to diagnosis with artificial intelligence: systematic literature review on diagnostic decision support systems]

BACKGROUND

Rare diseases are often recognized late. Their diagnosis is particularly challenging due to the diversity, complexity and heterogeneity of clinical symptoms. Computer-aided diagnostic aids, often referred to as diagnostic decision support systems (DDSS), are promising tools for shortening the time to diagnosis. Despite initial positive evaluations, DDSS are not yet widely used, partly due to a lack of integration with existing clinical or practice information systems.

OBJECTIVE

This article provides an insight into currently existing diagnostic support systems that function without access to electronic patient records and only require information that is easily obtainable.

MATERIALS AND METHODS

A systematic literature search identified eight articles on DDSS that can assist in the diagnosis of rare diseases with no need for access to electronic patient records or other information systems in practices and hospitals. The main advantages and disadvantages of the identified rare disease diagnostic support systems were extracted and summarized.

RESULTS

Symptom checkers and DDSS based on portrait photos and pain drawings already exist. The degree of maturity of these applications varies.

CONCLUSION

DDSS currently still face a number of challenges, such as concerns about data protection and accuracy, and acceptance and awareness continue to be rather low. On the other hand, there is great potential for faster diagnosis, especially for rare diseases, which are easily overlooked due to their large number and the low awareness of them. The use of DDSS should therefore be carefully considered by doctors on a case-by-case basis.