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than the controls (79.44+15.54 cm/sec) Similarly Keikhaei et al¹³⁸ in a study among Iranian children with HbSS (n=34) and HbAA( n=34) showed the TCD results as follows; HbSS had mean right TAMMV: 125+24.4cm and control had 92.8+ 11.99 cm/sec (p=0.001) while the HbSS also had left TAMMV as 107.5+ 28.2 cm/sec and control had 96.7+ 10.9 cm/sec (p=0.04). These may be comparable to this present study. However, in these various researches, the sample sizes used were small and thus may not be the true representation of the children with sickle cell anaemia in that population.^98,138,139

Bode and Wais⁷⁰ in a study of cerebral blood flow using TCD in normal children reported the mean velocities in the MCA as 94±10cm/sec. This is not in keeping with what was found in this study [87.27 ± 10.69 cm/sec].¹⁴⁰ Another transcranial Doppler study by Adams et al¹⁴⁰ on 64 children without haemoglobinopathy reported a mean velocity of 79±13cm/sec in the middle cerebral artery. This is lower than the mean velocity recorded in the Hb AA subjects in this study.

The reason for this may be related to the age differences in which the healthy children that participated in Adams study¹⁴⁰ had a mean age of 10±4years while the Hb AA subjects in this study were younger with a mean age of 6±4 years, although both studies included children with ages ranging between 2-16 years. It is known that velocities are higher in younger age groups.⁷⁰ The highest velocities in the HBSS group were recorded in the MCA and ICA while the lowest velocities were in the ACA. This is in keeping with existing knowledge about the pathophysiology of cerebral vasculopathy in sickle cell disease.⁵ The MCA and ICA are the vessels most frequently involved in stroke in SCA.¹⁴¹ Focal stenosis in sickle cell arteriopathy leads to a reduction in the vessel diameter and a consequent increase in blood flow velocity.¹⁴¹ The MCA and ICA seem to be high velocity vessels as the highest velocities in the children with HBAA genotype were also

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recorded in the MCA and ICA, this is also in keeping with findings by Bode and Wais⁷⁰ and Adams et al¹⁴⁰

The prevalence of elevated velocities in this study was 45% out of which 8.6% of the children had high risk velocities with 36.5% having conditional risk velocities. This differs from the report of Adams et al¹⁸ in African-American children. In their study, they reported 55 of the 315 children studied had abnormal velocities giving a prevalence of 17.5%. Eight percent had high risk velocities while 9.5% had velocities in the conditional risk range.¹⁸ The prevalence of conditional risk velocities in the present study (36.5%) is higher than the report by Hankins et al¹⁴² (19.7%) and Lagunju et al¹¹(19.7%). Children with conditional risk velocities have a lower risk (2-5% per year) for developing stroke compared to children with high risk velocities (9% per year).^16,29 In addition children with conditional risk velocities have a potential of converting to high risk velocities by a progressive increase in their flow velocities over time to a high risk range. ^18,19 This has been documented in previous studies with a reported conversion rate of 23% by Hankins et al¹⁴² and 29-55% in the STOP trial with a higher risk of conversion in younger children less than 10 years of age and those with velocities between 184 to 199cm/sec.¹⁸ Thus considering the high prevalence of conditional risk in this present study, finding of any child with conditional risk raises concern. More so, there is currently no established consensus on management of children with conditional risk velocities compared to children with high risk velocities where the evaluation and treatment algorithms are relatively well established. However locally, in LUTH, all children with conditional risk are commenced on hydroxyurea if the TCD ultrasound repeated after 6 months shows a second value indicating conditional risk. This will need further evaluation. Other findings from various studies by different authors reported conditional risk prevalence as: 11% by Melo et

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al⁹⁸ in 2008; 2% by Pavlakis et al¹⁴³ in 2010; 8.1% by Hokazonoi et al⁹⁹; 6.5% by Ann-Claudia et al;¹⁴⁴ 4.76% by Molavi et al¹⁴⁵; and 88% by Lakhkar et al¹⁴⁶ in 2012.

The prevalence of high risk velocities in this study was 8.6% which is comparable to earlier reports by Adams et al¹⁶ (8% out of 315 Children), Adams et al¹⁸ (9.7% of 1,934 children), Bernaudin et al⁶¹ (9.2% of 217) and Soyebi et al³⁵ (9.3% out of 2,331 children). On the other hand, the finding in this study differ from earlier reports from Africa where lower prevalence of high risk was reported by Lagunju et al¹¹( 4.7%), Oniyangi et al ¹⁴⁷(6.9%) and Makani et al³³(none) of the children had high risk velocities. The reason for this disparity is not clear, though the possibility of more awareness on need to screen with TCD may have contributed to the higher prevalence in the present study. Additionally, our report was lower than 12.3-34% reported from German and French SCD cohort studies.^61,148 Added to this explanation, the sample size of the 47 children from the Germany study was quite small and not properly powered.⁶¹

Among the HbAA group there was a progressive decline in the flow velocities with increasing age category. Highest velocities were recorded in the 60-95 months (5-8 years) age group. This is similar to the findings in the study by Bode and Wais who recorded the highest velocities in the 5-6 year age group among the 25 healthy newborn and 112 healthy children studied, however this present study did involve neonates.⁷⁰ Adams et al¹⁴⁰ in a study of 64 normal children also reported the highest velocities in children aged 4-8 years. However in contrast, the velocities in the Hb SS group was not associated with age and is consistent with the findings by Adams et al¹⁴⁹ in a study of 124 children with sickle cell anaemia in which the authors reported no correlation between age and cerebral blood flow velocities. This study differed from most studies: A prospective study by Oniyangi et al¹⁴⁷, in Abuja over 4 years among 129 children with SCD also did not show any correlation between CBFV and age. However, Lagunju et al⁷¹, in a study of 237 children with Hb

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SS genotype reported a significant negative correlation between age and TAMMV. They reported that children less than 5 years of age had higher TAMMV than children older than 5 years. The sample size in the study by Lagunju et al⁷¹, was considerably lower than in this study and the children were followed up for a period of 2 years. This is not consistent with the present study. In addition Melo et al⁹⁸, established an inverse relationship between age and mean velocity and in their study, HbSS subjects were compared with controls. However, unlike this present study, the sample size was small (n = 34), the mean age for SCA was also higher (9.5+4.67 ) than ours (6.6 + 3) in years and internal carotid artery vessel was not insonated and thus was not captured in the analysis. This is also in agreement to a study by of Babikians et al¹⁰¹.

Gender was noted to be a determinant of velocities in the HbAA group as the females had higher flow velocities than the males across the 5 intracranial vessels (RT ICA,MCA,ACA and LT MCA, ACA) and also with the mean CBFV with the exception in the left ICA( P = 0.074). This suggests that female gender is independently associated with increased flow velocity. This observation conforms to what was reported by Adams et al¹⁴⁰ in a TCD study of 64 children, the number of males in the study were slightly higher than the females (36 and 28 respectively). However, the males had lower mean velocities in the MCA (76 compared to 82cm/sec, p-value was 0.03).

Vavilala et al⁷² also reported that the mean velocities in the MCA in females was higher than in males, they studied 26 children aged 10-16years who were in pubertal stages and reported higher mean velocities in the MCA and the basilar artery in them. Hormonal differences in males and females has been suggested as a possible reason for the observation as oestrogen levels has been shown to correlate directly with cerebral blood flow velocities. Gender differences in cerebral blood flow velocities in adults with females having higher mean velocities than males were also reported in the Rotterdam study.⁷³ The study was a prospective population based cohort study

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among 7983 participants aged 55 years and over and the possible explanation may be the difference in hormonal status compared to men.⁷³ This is supported by findings of others who found that pre-menopausal women had significantly higher CBF values compared to age-matched men.^150,151 Another possible contribution maybe gender differences found in cerebral metabolism, vessel lumen and haematocrit. ^62,152-154 Tontisirin et al¹⁵⁵, in a study of 48 children aged 4-8years also noted that females had higher velocities in the MCA than the males due to inherent difference in cerebral metabolic rate and estimated cerebrovascular resistance between gender. More studies are needed in this area to identify the factors that are responsible for this phenomenon. Furthermore, Melo et al⁹⁸ did not find any difference in flow mean flow velocity in their comparative study except for PCA in control group which is also similar to that by Babikians¹⁵⁶ , in a study with similar group of controls.

Those with lower socio-economics class in the HbAA group had higher cerebral blood flow velocities than with those with higher socioeconomic status (p < 0.001). There was no significant association between socioeconomic statuses cerebral blood flow velocities in the HbSS subjects.

The reason for this is unknown and further research would help to elucidate the cause. However this reaffirms the reliability of TCD as a screening tool in children with genotype HbSS. To the researcher’s knowledge, there is no published report available.

This study further, revealed a negative correlation between cerebral blood flow velocities and haematocrit in the children with HbSS. This is in agreement with earlier reports by Lagunju et al^11,71 and is in keeping with other studies.16,18,98,99. However, studies by Oniyangi et al¹⁴⁷, and Keikhaei et al¹³⁸, did not find any significant correlation. The reason for this discrepancy is unknown, although compared to this present study; both studies had smaller sample sizes.

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There was negative correlation between haemoglobin and cerebral velocities in HbAA group. This may be explained by the lower Hb by the HbAA. Adams et al¹⁴⁰ also concluded that haematocrit did not significantly influence cerebral blood flow velocities after age and sex were considered in children with HbAA genotype.

The study showed significant correlation between flow velocities and total white cell count in both groups. The total white blood cell count was higher in the HbSS group than in the HbAA group and the difference were statistically significant. Lagunju et al¹⁵⁷ reported no correlation between total white blood cell count and TAMMV. The extent to which polymorphonuclear leukocytes and monocytes /macrophages contribute to pathobiology of cerebral ischemia.¹⁵⁸ Leukocytes by adhering to the blood vessel walls and obstructing the lumen, aggregating with other blood cells with more effective blockage of the lumen, stimulating the vascular endothelium to increase its expression of the ligands for adhesion molecules on blood cells, produce capillary plugging with subsequent parenchyma infiltration thus, causing tissue damage and inflammatory reaction which result to cytotoxic neuronal injury.^159,160

Platelet count showed a positive correlation with TAMMV in the HbSS group and this correlation was still maintained after regression. However, Lagunju et al¹⁵⁷ also reported no correlation between platelet count and cerebral blood flow velocities. Platelet might affect plasma blood viscosity which is correlated to cerebral blood flow and cardiac output and increased viscosity may increase the risk of thromboembolic events.^161,162

We observed that SaO2 correlated significantly and inversely with TAMMV in the HbSS group and this implies that the lower the oxygen desaturation, the higher the TAMMV. This is in agreement with Quinn et al²⁶ who observed similar findings. Haemoglobin oxygen desaturation may be related to the rightward shift of the oxy hemoglobin dissociation curve due to decreased

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affinity of sickle haemoglobin which is caused by an increased content of erythrocyte 2,3-bisphosphoglycerate.¹⁶³ Growing evidence also suggests that haemoglobin oxygen at rest is independently associated with anaemia and haemolysis.^164-167 It has been proposed that chronic haemolysis could promote pulmonary vasculopathy that could cause ventilation-perfusion mismatching and limit oxygen uptake by haemoglobin.¹⁶⁴ This includes elevated cerebral blood flow velocities and an increased risk of stroke.

Majority of the children in the present study had normal blood pressure and this comparable to Imuetiinyan et al¹⁶⁸ where 69 Saudi Arabian children with SCD aged 1-16 years old had normal blood pressure measurement. However this is unlike the study by Ekure et al¹⁶⁹ in children with HbSS where 74% of the subjects had systolic blood pressure below the 50^th percentile for general population. The reason for this unclear but may be attributed to inability to blood pressure measurement which was done only once in this study. There was also increased in blood pressure as the age increases in both subjects and controls and this was similar to that reported by Ekure et al¹⁶⁹. Both systolic and diastolic blood pressures were not statistical significant among the subjects and controls as observed by George et al¹⁷⁰ and Adeodu et al¹⁷¹. Previous studies have demonstrated that the arterial blood pressure in steady state patients with SCA is significantly lower than that of age, sex and race matched controls.^83,172 These findings are in view of the well known vascular and renal abnormalities associated with SCA. Added to this explanation, higher systolic blood pressure is associated with increased risk of a silent infarction.¹⁷³ In addition, SCA may have deleterious effect on myocardium, which contributes to abnormal rates of change in left ventricular cavity size and systolic/diastolic function in SCA patients. The risk for occlusive stroke increased with systolic but not diastolic pressure as shown by Pegelow et al⁸³. Eleven (3.5%) children and 14 (4.4%) children with HbSS had elevated systolic and diastolic blood pressure

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respectively greater than 95^th percentile in this study and this comparable to the study George et al¹⁷⁰ where 11(22%) children with HbSS had hypertension and lower than that by Ekure et al¹⁶⁹ where 3(2.4%) children with HbSS had hypertension. However the sample size was smaller in both studies. Ekure et al¹⁶⁹ in their study used Doppler to measure the systolic blood pressure unlike mercury sphygmomanometer that was used in this study could have attributed to the difference. Lagunju et al¹⁴ demonstrated systolic hypertension to be a risk factor for overt stroke in Nigerian children with SCA. It was observed that both the systolic and diastolic blood pressure positively correlated with TAMMV in the HbSS group. This implies that the higher blood pressures, the greater the cerebral blood flow and the higher the cerebral blood flow velocities.

Furthermore, as the blood pressure increases, the cerebral blood flow velocities increased in both male and female and also across the different age groups except for the age group of 167-196 months in the subjects in this study.

The study has shown that children with HbSS genotype had higher cerebral flow velocities than those with HbAA genotypes. Furthermore among the Nigerian children with SCA, there is high risk for stroke as reflected by the observations of conditional and high risk TAMMV in 45.1% of the patients studied. Additionally, other risk factors were associated with abnormal TAMMV in HbSS. Thus with 100% of the studied population acceptance of TCD as an investigative screening tool for assessment of primary stroke risk and other selective risk factors, there is need for its’

widespread implementation on regular basis in all children with SCA to identify those at risk for primary stroke irrespective of their socio-economic status.

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