ArticleClinicoEconomics and outcomes research : CEOR2020
Development of a Severity Classification System for Sickle Cell Disease.
Article in ClinicoEconomics and outcomes research : CEOR, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 3 of them syntheses that pooled it.
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Who cites it
25 citing papers in PubMed, 3 syntheses or guidelines pooled it, 41 citations in OpenAlex.
- AI-assisted decision support for sickle cell disease severity stratification using routine blood tests: a systematic review and meta-analysis.BMC medical informatics and decision making · 2026Pooled it
- Measurement of fatigue in sickle cell disease: a systematic review of fatigue measures.Orphanet journal of rare diseases · 2025Pooled it
- A systematic literature review of frequency of vaso-occlusive crises in sickle cell disease.Orphanet journal of rare diseases · 2021Pooled it
- Brain MRI and cognitive outcomes in adults with sickle cell disease treated with crizanlizumab.Blood red cells & iron · 2026Article
- Blood Transfusion and ABO Blood Groups in Sickle Cell Disease.Medicina (Kaunas, Lithuania) · 2026Article
- Article
- A new method for augmenting short time series, with application to pain events in sickle cell disease.PLoS computational biology · 2026Article
- Hematopoietic Cell Transplantation for Sickle Cell Disease.Children (Basel, Switzerland) · 2026Review
- Nutritional status and clinical severity in children with sickle cell disease and confirmed asthma: a multicentre observational study.BMC pediatrics · 2026Observational
- Weather-Related Exposures and Emergency Department Visits for Pediatric Sickle Cell Complications.Pediatric emergency care · 2026Article
- Can pre-transplant sickle cell disease characteristics predict early post-transplant complications?Bone marrow transplantation · 2026Article
- Analgesic Utilization Pattern and Cost of Managing Children with Sickle Cell Diseases: a Retrospective Single-site Audit.Journal of racial and ethnic health disparities · 2026Article
- Optimizing the "right" patient selection for treatment for sickle cell disease.Hematology. American Society of Hematology. Education Program · 2025Article
- Association of depression and hydroxyurea use with neuropathic pain in hemoglobinopathies.Scientific reports · 2025Article
- Predictors and health impacts of Ramadan intermittent fasting among patients with sickle cell disease.Frontiers in medicine · 2025Article
- Disease severity drives risk of venous thrombotic events in women with sickle cell disease in a single-center retrospective study.Research and practice in thrombosis and haemostasis · 2024Article
- Predictors of Developing a Complex Course of Osteomyelitis in Patients with Sickle Cell Anaemia.Sultan Qaboos University medical journal · 2024Article
- Society for Maternal-Fetal Medicine Consult Series #68: Sickle cell disease in pregnancy.American journal of obstetrics and gynecology · 2024Article
- Laboratory predictors of sickle cell disease severity: a cross-sectional study.Journal of medicine and life · 2024Article
- Preferences for potential benefits and risks for gene therapy in the treatment of sickle cell disease.Blood advances · 2023Article
Corrections and comments
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Authors and funding
14 authors at 10 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThere is no well-accepted classification system of overall sickle cell disease (SCD) severity. We sought to develop a system that could be tested as a clinical outcome predictor. PATIENTS AND
methodsUsing validated methodology (RAND/UCLA modified Delphi panel), 10 multi-disciplinary expert clinicians collaboratively developed 180 simplified patient histories and rated each on multiple axes (estimated clinician follow-up frequency, risk of complications or death, quality of life, overall disease severity). Using ratings on overall disease severity, we developed a 3-level severity classification system ranging from Class I (least severe) to Class III (most severe).
resultsThe system defines patients as Class I who are 8-40 years with no end organ damage, no chronic pain, and ≤4 unscheduled acute care visits due to vaso-occlusive crises (VOC) in the last year. Patients <8 or >40 years with no end organ damage, no chronic pain, and <2 unscheduled acute care visits are also considered Class I. Patients any age with ≥5 unscheduled acute care visits and/or with severe damage to bone, retina, heart, lung, kidney, or brain are classified as Class III (except patients ≥25 years with severe retinopathy, no chronic pain, and 0-1 unscheduled acute care visits, who are considered Class II). Patients not meeting these Class I or III definitions are classified as Class II.
conclusionThis system consolidates patient characteristics into homogenous groups with respect to disease state to support clinical decision-making. The system is consistent with existing literature that increased unscheduled acute care visits and organ damage translate into clinically significant patient morbidity. Studies to further validate this system are planned.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.