Predicting elevated transcranial doppler velocity among patients with sickle cell anemia in Uganda: A cross-sectional study

PLOS ONE

卷:21

Research Article

Doreen Nayiga¹  David Mukunya²  Simon Odoch¹  Faith Oguttu²  Ian Munabi³  Milton W. Musaba⁴  Charles Kimbugwe⁵  Brian Tonny Makoko²  Jonathan Babuya²  Joshua Mugabi²  Alain Nyalihama¹  Martin Chebet¹  Lisa Rynn¹  Samuel Kizito⁶  Vincent Ssentumbwe⁷  Sarah Kiguli⁸  Peter Olupot Olupot² 

[1] Department of Anatomy, Makerere University, Kampala, Uganda

[2] Mbale regional referral hospital, Mbale, Uganda

[3] Department of Pediatrics and Child Health, Busitema University, Mbale, Uganda

[4] Division of Computational and Data Science, Washington University, St. Louis, Missouri, United States of America

[5] Department of Pediatrics and Child Health, Makerere University, Kampala, Uganda

[6] Department of Obstetrics and Gynecology, Busitema University, Mbale, Uganda

[7] Silver School of Social Work, New York University, New York, New York, United States of America

[8] Department of Community and Public Health, Busitema University, Mbale, Uganda

关键词: Sickle cell disease;    Medical risk factors;    Stroke;    Neuropathy;    Blood transfusion;    Heart rate;    Forecasting;    Screening guidelines;   

DOI  :  10.1371/journal.pone.0351700

 received in 2025-09-22, accepted in 2026-05-29,  发布年份 2026

来源: PLOS

【 摘 要 】

BackgroundSickle cell anemia (SCA) is an autosomal recessive blood disorder resulting from a specific point mutation in the β-globin gene. Over half a million children are born with sickle cell anemia annually. Transcranial Doppler (TCD) velocity is an accurate predictor of the risk of stroke among children with sickle cell anemia. Unfortunately, TCD screening is not routinely done in developing countries due to limited resources. There is a need to develop a model that predicts elevated TCD velocity, utilizing routinely collected data to guide management of children with sickle cell anemia.MethodsWe conducted a cross-sectional study from 1st July 2024–30th August 2024 among children with SCA attending the Sickle Cell Clinic. We developed a risk-prediction model for elevated TCD (≥ 170 cm/s) using sociodemographic, hematological, and clinical factors.We used the least absolute shrinkage and selection operator (LASSO) penalized regression to select the best subset of predictors of increased TCD velocity. Model performance was assessed by determining the discrimination using the area under the curve and calibration by drawing a calibration plot.ResultsWe enrolled 385 children; the mean age was 10.3 (SD 3.8) years. The prevalence of elevated TCD, defined as ≥170 cm/s was 8.3% (95% CI: 5.8, 11.5; n = 32/385). Using a lambda of 0.008, the final model had 12 predictors. The predictors included neuropathy, red blood cell count, heart rate, age, adherence to hydroxyurea, headache, hematocrit, serum lactate dehydrogenase, gender, malnutrition, blood transfusion, and neutrophils. The model predicted elevated TCD with an AUC of 84.7% (95%CI: 74.7, 90.8).ConclusionWe developed and validated a model to predict elevated TCD among children living with SCA in Uganda. Further exploration is needed to assess whether this model predicts stroke.

【 授权许可】

CC BY   
Nayiga et al 2026

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