Raymond Mpanjilwa MusowoyaUniversity Teaching Hospital, Zambia
Title: Predictors of musculoskeletal manifestations in paediatric patients presenting with sickle cell disease at a tertiary teaching hospital in Lusaka, Zambia
Aim: Sickle cell disease (SCD) is an autosomal recessive inherited condition that presents with a number of clinical manifestations that include musculoskeletal manifestations (MM). MM may present differently in different individuals and settings and the predictors are not well known. Herein, we aimed at determining the predictors of MM in patients with SCD at the University Teaching Hospital, Lusaka, Zambia.
Methods: An unmatched case-control study was conducted between January and May 2019 in children below the age of 16 years. In all, 57 cases and 114 controls were obtained by systematic sampling method. A structured questionnaire was used to collect data. The different MM were identified, staged, and classified according to the Standard Orthopaedic Classification Systems using radiological and laboratory investigations. The data was entered in Epidata version 3.1 and exported to STATA 15 for analysis. Multiple logistic regression was used to determine predictors and predictive margins were used to determine the probability of MM.
Results: The cases were older median age 9.5 (interquartile range (IQR) 7 to 12) years compared to controls 7 (IQR 4 to 11) years; p = 0.003. After multivariate logistic regression, increase in age (adjusted odds ratio (AOR) = 1.2, 95% confidence interval (CI) 1.04 to 1.45; p = 0.043), increase in the frequency of vaso-occlusive crisis (VOC) (AOR = 1.3, 95% CI 1.09 to 1.52; p = 0.009) and increase in percentage of haemoglobin S (HbS) (AOR = 1.18, 95% CI 1.09 to 1.29; p < 0.001) were significant predictors of MM. Predictive margins showed that for a 16-year-old the average probability of having MM would be 51 percentage points higher than that of a two-year-old.
Conclusion: Increase in age, frequency of VOC, and an increase in the percentage of HbS were significant predictors of MM. These predictors maybe useful to clinicians in determining children who are at risk.