Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

INTRODUCTION: Rheumatoid factor (RF) and anti-cyclic citrullinated peptide antibody (ACPA) are used in the diagnosis and prognostication of rheumatoid arthritis (RA). We wanted to determine the specific contributions of RF and ACPA to the biological nature of RA and whether they act synergistically. METHODS: We identified 731 patients from our prospective multi-ethnic RA cohort and categorised them into four groups: ACPA-positive, RF-positive, doubly positive and doubly negative. We compared the demographics, Disease Activity Score-28, Health Assessment Questionnaire score, quality of life using Short Form 36 and the use of prednisolone and disease-modifying antirheumatic drugs (DMARDs) of these patient groups. RESULTS: Four hundred and ninety-one patients (67.2%) were ACPA+RF+, 54 (7.4%) were ACPA+RF-, 82 (11.2%) were ACPA-RF+ and 104 (14.2%) were ACPA-RF-. Mean disease duration before the study entry was not different in the four groups. Patients with older age of onset were less likely to be positive for RF and ACPA. Fewer ACPA+RF+ patients were in remission compared to those in the other groups ( P < 0.05). Erythrocyte sedimentation rate (ESR) was higher at study entry in the ACPA+RF+ group (40.4 mm/h vs. 30.6-30.9 mm/h, P < 0.05). Prednisolone and number of DMARDs used were higher in the ACPA+RF+ group compared to the doubly negative group. There were no differences in the functional status and quality of life. CONCLUSIONS RA patients who were positive for both ACPA and RF had lower remission rate, higher baseline ESR and required more corticosteroid and DMARD treatment compared to those who were singly positive or doubly negative. Being doubly positive confers a worse outcome to RA patients.
Humans ; Arthritis, Rheumatoid/diagnosis* ; Male ; Female ; Middle Aged ; Rheumatoid Factor/blood* ; Anti-Citrullinated Protein Antibodies/blood* ; Adult ; Quality of Life ; Prospective Studies ; Antirheumatic Agents/therapeutic use* ; Aged ; Peptides, Cyclic/immunology* ; Prednisolone/therapeutic use* ; Surveys and Questionnaires ; Severity of Illness Index ; Prognosis

INTRODUCTION: This review aims to provide evidence-based recommendations for an enhanced primary series (third dose) coronavirus disease 2019 (COVID-19) vaccination in people with rheumatic diseases (PRDs) in the local and regional context. METHODS: Literature reviews were performed regarding the necessity, efficacy, safety and strategies for enhanced primary series COVID-19 vaccination in PRDs. Recommendations were developed based on evidence according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. Evidence was synthesised by eight working group members, and the consensus was achieved by a Delphi method with nine members of an expert task force panel. RESULTS: Two graded recommendations and one ungraded position statement were developed. PRDs have impaired immunogenicity from the COVID-19 vaccine and are at an increased risk of postvaccine breakthrough severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and poor clinical outcomes, compared to the general population. We strongly recommend that PRDs on immunomodulatory drugs be offered a third dose of the messenger RNA (mRNA) vaccine as part of an enhanced primary series, after the standard two-dose regimen. We conditionally recommend that the third dose of mRNA vaccine against SARS-CoV-2 be given at least 4 weeks after the second dose or as soon as possible thereafter. There is insufficient data to inform whether the third mRNA vaccine should be homologous or heterologous in PRDs. CONCLUSION These recommendations that were developed through evidence synthesis and formal consensus process provide guidance for an enhanced primary series COVID-19 vaccination in PRDs.
Humans ; COVID-19/prevention & control* ; COVID-19 Vaccines/administration & dosage* ; Rheumatic Diseases/immunology* ; Singapore ; SARS-CoV-2 ; Vaccination/methods* ; Delphi Technique ; Immunization, Secondary

INTRODUCTION: The most recent local study on the incidence of histological subtypes of all brain and spinal tumours treated surgically was published in 2000. In view of the outdated data, we investigated the presenting characteristics, histological subtypes and outcomes of adult patients who underwent surgery for brain or spinal tumours at our institution. METHODS: A single-centre retrospective review of 501 patients who underwent surgery for brain or spinal tumours from 2016 to 2020 was conducted. The inclusion criteria were (a) patients who had a brain or spinal tumour that was histologically verified and (b) patients who were aged 18 years and above at the time of surgery. RESULTS: Four hundred and thirty-five patients (86.8%) had brain tumours and 66 patients (13.2%) had spinal tumours. Patients with brain tumours frequently presented with cranial nerve palsy, headache and weakness, while patients with spinal tumours frequently presented with weakness, numbness and back pain. Overall, the most common histological types of brain and spinal tumours were metastases, meningiomas and tumours of the sellar region. The most common complications after surgery were cerebrospinal fluid leak, diabetes insipidus and urinary tract infection. In addition, 15.2% of the brain tumours and 13.6% of the spinal tumours recurred, while 25.7% of patients with brain tumours and 18.2% of patients with spinal tumours died. High-grade gliomas and metastases had the poorest survival and highest recurrence rates. CONCLUSION This study serves as a comprehensive update of the epidemiology of brain and spinal tumours and could help guide further studies on brain and spinal tumours.
Humans ; Retrospective Studies ; Female ; Male ; Middle Aged ; Adult ; Aged ; Central Nervous System Neoplasms/pathology* ; Brain Neoplasms/pathology* ; Treatment Outcome ; Postoperative Complications ; Young Adult ; Spinal Neoplasms/pathology* ; Neoplasm Recurrence, Local ; Aged, 80 and over ; Adolescent

INTRODUCTION: Radiofrequency ablation (RFA) avoids the complications of general anaesthesia, reduces length of hospitalisation and reduces morbidity from surgery. As such, it is a strong alternative treatment for patients with comorbidities who are not surgical candidates. However, to our knowledge, there have only been 1 systematic review and 3 combined systematic review and meta-analyses on this topic to date. This systematic review and meta-analysis seeks to evaluate the efficacy and safety of RFA in the treatment of papillary thyroid carcinoma (PTC) with longer follow-up durations. METHOD: PubMed, Embase and Cochrane databases were searched for relevant studies published from 1990 to 2021; 13 studies with a total of 1366 patients were included. The Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines and Sandelowski et al.'s approach1 to "negotiated consensual validation" were used to achieve consensus on the final list of articles to be included. All authors then assessed each study using a rating scheme modified from the Oxford Centre for Evidence-Based Medicine. RESULTS: Pooled volume reduction rates (VRRs) from 1 to 48 months after RFA, complete disappearance rates (CDR) and complications were assessed. Pooled mean VRRs were 96.59 (95% confidence interval [CI] 91.05-102.13, I2=0%) at 12 months2-6 and 99.31 (95% CI 93.74-104.88, I2=not applicable) at 48 months.2,5 Five studies showed an eventual CDR of 100%.2,4,7-9 No life-threatening complications were recorded. The most common complications included pain, transient voice hoarseness, fever and less commonly, first-degree burn. CONCLUSION RFA may be an effective and safe alternative to treating PTC. Larger clinical trials with longer follow-up are needed to further evaluate the effectiveness of RFA in treating PTC.
Humans ; Radiofrequency Ablation/methods* ; Thyroid Cancer, Papillary/surgery* ; Thyroid Neoplasms/surgery* ; Treatment Outcome ; Postoperative Complications/etiology*