
Raymond Mpanjilwa Musowoya
University of Zambia, ZambiaTitle: Predictors of musculoskeletal manifestations in paediatric patients presenting with sickle cell disease at a tertiary teaching hospital in Lusaka, Zambia
Abstract
Aims: 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.