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. Author manuscript; available in PMC: 2017 Jul 1.
Published in final edited form as: Br J Haematol. 2015 Oct 12;174(2):325–329. doi: 10.1111/bjh.13769

Establishing sickle cell diagnostics and characterizing a paediatric sickle cell disease cohort in Malawi

J Brett Heimlich 1,2,*, Godwin Chipoka 1,*, Portia Kamthunzi 1, Robert Krysiak 1, Yacinta Majawa 1, Pilirani Mafunga 1, Yuri Fedoriw 5, Ajib Phiri 4, Nigel S Key 5, Kenneth I Ataga 5,**, Satish Gopal 1,4,5,**
PMCID: PMC4829491  NIHMSID: NIHMS719033  PMID: 26455430

Sickle cell disease (SCD) is the most prevalent genetic disease in sub-Saharan Africa and an estimated 240,000 children are born with SCD each year (Piel et al., 2013). Similar to Africa as a whole, Malawi has a substantial SCD burden but scarce resources for diagnosis and treatment (Brabin et al., 2004; Piel et al., 2013). Neither neonatal screening nor standardized methods for SCD diagnosis currently exist, as haemoglobin electrophoresis and alternative diagnostic methods are typically absent; consequently, all patients with suspected SCD in Malawi have been diagnosed using clinical criteria alone in recent years. To begin addressing the diagnostics and care gap, we implemented haemoglobin electrophoresis testing in the capital city, Lilongwe, in January 2015. We report baseline clinical and laboratory characteristics of children with confirmed SCD. These data provide a foundation for future studies to understand the natural history of SCD in Malawi and develop intervention strategies appropriate for the setting to improve outcomes.

Study subjects were recruited from a paediatric chronic care clinic at Kamuzu Central Hospital (KCH) between January and May 2015. Haemoglobin electrophoresis was completed using whole blood preserved in EDTA-coated tubes, haemolysed in a saponin-based reagent and analysed using a Quickgel Chamber system and Titan Plus power source (both from Helena Laboratories, Beaumont, TX). Complete blood counts were performed on an Ac•T 5diff CP Hematology Analyzer (Beckman Coulter, Atlanta GA), blood serum chemistries using a Cobas c311 analyser (Roche Diagnostics, Basel, Switzerland) and urine dipsticks (Bayer Multistix 10 SG, Bayer AG, Leverkusen, Germany). The University of North Caolina-Chapel Hill institutional review board and Malawi National Health Science Review Committee approved the study. Written informed consent was obtained from parents of all enrolled children. Children aged 7-17 years also provided informed assent prior to study participation.

A total of 137 patients with clinically suspected SCD were enrolled between January and May 2015. Of those enrolled, 117 patients were confirmed to have HbSS, two were HbAS, 12 were HbAA and the diagnosis was uncertain in six patients. Of 125 children who were under long-term care for SCD prior to enrolment, 107 (86%) were confirmed to have HbSS. No patients were double heterozygous for HbS and HbC or β-thalassaemia. Baseline clinical parameters and historical complications are listed in Table I. A high proportion of the total population (79%) was receiving malaria prophylaxis with sulfadoxine/pyrimethamine (SP) at study enrolment. Prior malaria was reported by 39% of patients, and tended to be higher in the 0-5 years age group compared to the group aged over 5 years (46% vs. 31%, p=0.03). Seventy-two per cent reported prior anaemia, followed by joint pain (56%), jaundice (52%) and acute pain episodes (50%). Most patients reported a history of blood transfusions (74%). Nocturnal enuresis was reported by 21% and no patients reported haematuria. Baseline laboratory parameters are found in Table II. Urinalysis revealed the presence of blood in 26% of patients, although microscopy was not performed to assess the presence of red blood cells. Proteinuria was found in 7% of patients.

Table I.

Baseline clinical parameters and historical complications for ambulatory children with HbSS in Lilongwe.

All (n=117) Male (n= 62) Female (n=55) p value
Age years, median (IQR) 7.3 (2.7-10.4) 5.3 (2.3-9.4) 8.9 (4.2-11.9) 0.004
Height cm, median (IQR, n) 115 (88-131, 60) 111 (89-128, 36) 119.5 (93-140, 24) 0.21
Weight kg, median (IQR, n) 19 (13-27, 108) 16.5 (12-23.6, 58) 21 (14-30, 50) 0.01
Blood Pressure Systolic mmHg , median (IQR, n) 103 (98-110, 83) 101 (94-108, 43) 103 (99-110, 40) 0.37
Blood Pressure Diastolic mmHg, median (IQR, n) 60 (55-65, 83) 58 (53-65, 43) 61 (56-68, 40) 0.13
Heart Rate BPM, median (IQR, n) 104 (91-118, 114) 105 (94-123, 61) 104 (88-112, 53) 0.15
O2 Saturation % (room air), median (IQR, n) 93 (88-97, 108) 91 (85-96, 59) 95 (91-98, 49) 0.004
% Hypoxaemic (SPO2 < 90%), n (%) 36 (30.7) 26 (41.9) 10 (18.2) 0.005
Body Temperature, °C, median (IQR, n) 37 (36.7-37.4, 91) 37 (36.7-37, 46) 37 (36.4-37.2, 45) 0.22
Positive History of:
 Malaria, n (%) 45 (38.5) 22 23 0.34
  0-5 years, n (%) 25 (46.3) - - 0.03
  6-18 years, n (%) 20 (31.7) - -
 Pneumonia, n (%) 29 (24.8) 10 (16.1) 19 (34.5) 0.02
 TB, n (%) 7 (6.0) 4 (6.5) 3 (5.5) 0.82
 HIV, n (%) 0 0 0 -
Anaemia, n (%) 84 (71.8) 49 (79.0) 35 (63.6) 0.06
Pallor, n (%) 16 (13.7) 7 (11.3) 9 (16.4) 0.43
Jaundice, n (%) 61 (52.1) 33 (53.2) 28 (50.9) 0.82
Received blood transfusion, n (%) 87 (74.4) 47 (75.8) 40 (72.7) 0.47
 Median units received (range) 1.5 (1-10) 1 (1-8) 2 (1-10) 0.73
 Days since last transfusion, median (IQR) 316 (133-1144) 240 (111-410) 577 (180-1784) 0.03
Pain episodes, n (%) 58 (49.6) 27 (43.5) 31 (56.4) 0.16
Joint pain, n (%) 66 (56.4) 33 (53.2) 33 (60.0) 0.34
Dactylitis, n (%) 41 (35.0) 19 (30.6) 22 (40.0) 0.29
Leg ulcers, n (%) 5 (4.3) 5 (8.1) 0 0.03
Stroke, n (%) 10 (8.5) 5 (8.1) 5 (9.1) 0.84
Nocturnal Enuresis, n (%) 24 (20.5) 12 (19.4) 12 (21.8) 0.74
Haematuria, n (%) 0 0 0 -

IQR, interquartile range; BPM, beats/min; SPO2, peripheral capillary oxygen saturation; TB, tuberculosis; HIV, human immunodeficiency virus

Table II.

Baseline laboratory parameters for ambulatory children with HbSS in Lilongwe.

Complete Blood Count All (n=113) Males (n=58) Females (n=46) Unit p value
White blood cell count, median (IQR) 16 (12.2-19.2) 16.5 (12.8-19.6) 15.9 (11.9-18.9) ×109/l 0.18
Hb, mean (IQR) 73 (69-79) 72 (66-78) 75 (70-79) g/l 0.12
Haematocrit, mean (IQR) 22.6 (21-24.6) 22.2 (20-24.6) 22.9 (21.3-24.7) % 0.14
Mean Corpuscular Volume, mean (IQR) 88.2 (83-94) 88 (83-94) 88.3 (82.5-94) fl 0.88
Platelet Count 450 (351-586) 435.5 (364.5-565) 485 (323-588) ×109/l 0.97
Absolute Neutrophil Count 5.39 (4.3-6.7) 5.4 (4.5-6.5) 5.4 (4.0-6.7) ×109/l 0.98
Lymphocyte Count 7.9 (5.9-10.8) 8.6 (6.1-11.2) 6.3 (5.7-10.2) ×109/l 0.03
Serum Chemistries All (n=115) Males (n=62) Females (n=53)
Creatinine, median (IQR) 26.5 (17.6-26.5) 26.5 (17.6-26.5) 26.5 (17.6-35.6) μmol/l 0.15
Total Bilirubin, median (IQR) 29.1 (18.8-44.5) 29.1 (18.8-42.8) 29.1 (17.1-49.6) μmol/l 0.97
Direct Bilirubin, median (IQR) 10.3 (6.8-13.7) 10.3 (6.8-13.7) 10.3 (6.8-15.4) μmol/l 0.98
Lactate Dehydrogenase, median (IQR) 658 (527-773) 664 (544-773) 634 (517-772) iu/l 0.54
Urine Dipstick All (n=100) Males (n=51) Females (n=49)
Glucose, n (%) 3 (3) 0 3 (6.1) 0.06
Bilirubin, n (%) 12 (12) 7 (13.7) 5 (10.2) 0.69
Specific gravity, median (IQR) 1.015 (1.01-1.02) 1.015 (1.01-1.015) 0.82
Blood, n (%) 26 (26) 10 (19.5) 16 (32.7) 0.09
pH, median (IQR) 6 (5.5-6.3) 5.5 (5.5-6) 0.86
Protein, n( %) 7 (7) 3 (5.9) 4 (8.2) 0.57
Urobilinogen, median (IQR) 3.4 (3.4-17.1) 3.4 (3.4-17.1) μmol/l 0.64
Positive nirtrite, n(%) 7 (7) 5 (9.8) 2 (4.1) 0.31
Leucocytes, n( %) 19 (19) 0 19 (38.8) <0.001

In our experience, local clinicians were generally accurate in identifying children with SCD on clinical grounds alone. However, many children without SCD were being treated as such, and children with non-classical presentations and younger ages are probably not receiving appropriate diagnosis and treatment in settings where suitable diagnostic methods are lacking (Grosse et al., 2011). Children with confirmed SCD in Lilongwe had substantial morbidity, and commonly reported histories of anaemia, jaundice, joint pain and pain episodes. Nearly 10% of our population reported a history of stroke, similar to other African SCD cohorts in which prevalence of prior stroke is 7-13% in adolescent SCD populations (Njamnshi et al., 2006).

Seventy-four per cent of SCD patients had a history of blood transfusion despite an erratic local blood supply in Malawi, with most having been transfused within the last year. A history of repeated blood transfusion was independently associated with mortality among children with SCD in Kenya (Makani et al., 2009). Defining optimal approaches to transfusion therapy for children with SCD in sub-Saharan Africa is important, where limited supply may impair wide-scale applicability of chronic transfusion to prevent severe complications, such as stroke (Adams et al., 1998). Malaria is also a significant cause of morbidity and mortality for SCD patients in endemic regions (McAuley et al., 2010). Approximately 80% of children with SCD in our cohort were receiving malaria prophylaxis. Despite high rates of prophylaxis, 39% of patients reported a history of malaria. A history of malaria was significantly more common in our cohort among children aged <5 years, and earlier SCD diagnosis using haemoglobin electrophoresis may allow earlier initiation of chemoprophylaxis at younger ages. Patients exhibited moderate anaemia and leucocytosis, with elevated bilirubin and lactate dehydrogenase (LDH) levels, as expected with the haemolytic process in SCD. In addition to reflecting active haemolysis, LDH is associated with microalbuminuria, a biomarker for renal damage in paediatric SCD patients (Gurkan et al., 2010). Renal disease in SCD is a significant cause of morbidity and mortality in the United States and a recent study in West Africa suggests that renal involvement is under-recognized in sub-Saharan Africa (Ranque et al., 2014). In our population, 26% of patients had haematuria by urine dipstick assessment, possibly reflecting haemoglobinuria, which is associated with chronic kidney disease in SCD (Saraf et al., 2014). Twenty-one per cent of the population also reported nocturnal enuresis, a symptom of hyposthenuria secondary to a medullary concentrating defect. Additionally, 7% of the cohort had proteinuria, a particularly high prevalence in this young patient cohort. Taken together, these findings suggest that a significant proportion of children with SCD in Malawi exhibit renal involvement, and may be at risk for worsening nephropathy and end-stage renal disease as they grow older.

In conclusion, haemoglobin electrophoresis implementation in Lilongwe provides a foundation for detailed cross-sectional description of paediatric SCD patients in Malawi. Children had substantial clinical and laboratory evidence of SCD-related morbidity. Earlier diagnosis can substantially improve care for this population by facilitating earlier therapeutic interventions, as well as providing a basis for research to better understand SCD-related morbidity in sub-Saharan Africa. These baseline data can inform management strategies to improve outcomes and increase life expectancy among children with SCD in Malawi.

Acknowledgements

We wish to acknowledge Mr. Wiza Kumwenda for assistance developing the study database. We additionally acknowledge leadership of Kamuzu Central Hospital (Dr. Jonathan Ngoma) and UNC Project-Malawi (Profs. Irving Hoffman, Francis Martinson, Mina Hosseinipour and Mr. Innocent Mofolo) for their support of this study, as well as the paediatrics department and laboratory staff. Finally, we wish to thank participating children and their families. This project was supported by the UJMT Fogarty Global Health Fellows Program (grant #R25TW009340), The Medical College of Georgia at Georgia Regents University and the National Heart, Lung, Blood Institute (grant #U01HL117659). SG is supported by grants from the National Institutes of Health (K01TW009488, R21CA180815 and U54CA190152). The funding sources had no involvement in any aspect of the study, decision to write or submit this manuscript.

Footnotes

Author Contributions:

JBH, NSK, KIA, AP and SG designed the study. JBH, GC, PK, RK, YM and PM collected the data. JBH, YF and SG analysed the data. JBH and SG wrote the first draft while NSK, KIA and YF contributed to subsequent drafts.

Conflicts of Interest:

We declare no conflicts of interest.

REFERENCES

  1. Adams RJ, McKie VC, Hsu L, Files B, Vichinsky E, Pegelow C, Abboud M, Gallagher D, Kutlar A, Nichols FT, Bonds DR, Brambilla D. Prevention of a first stroke by transfusions in children with sickle cell anemia and abnormal results on transcranial Doppler ultrasonography. The New England journal of medicine. 1998;339:5–11. doi: 10.1056/NEJM199807023390102. [DOI] [PubMed] [Google Scholar]
  2. Brabin BJ, Prinsen-Geerligs PD, Verhoeff FH, Fletcher KA, Chimsuku LH, Ngwira BM, Leich OJ, Broadhead RL. Haematological profiles of the people of rural southern Malawi: an overview. Annals of tropical medicine and parasitology. 2004;98:71–83. doi: 10.1179/000349804225003055. [DOI] [PubMed] [Google Scholar]
  3. Grosse SD, Odame I, Atrash HK, Amendah DD, Piel FB, Williams TN. Sickle cell disease in Africa: a neglected cause of early childhood mortality. American journal of preventive medicine. 2011;41:S398–405. doi: 10.1016/j.amepre.2011.09.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Gurkan S, Scarponi KJ, Hotchkiss H, Savage B, Drachtman R. Lactate dehydrogenase as a predictor of kidney involvement in patients with sickle cell anemia. Pediatric nephrology. 2010;25:2123–2127. doi: 10.1007/s00467-010-1560-8. [DOI] [PubMed] [Google Scholar]
  5. Makani J, Kirkham FJ, Komba A, Ajala-Agbo T, Otieno G, Fegan G, Williams TN, Marsh K, Newton CR. Risk factors for high cerebral blood flow velocity and death in Kenyan children with Sickle Cell Anaemia: role of haemoglobin oxygen saturation and febrile illness. British journal of haematology. 2009;145:529–532. doi: 10.1111/j.1365-2141.2009.07660.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. McAuley CF, Webb C, Makani J, Macharia A, Uyoga S, Opi DH, Ndila C, Ngatia A, Scott JA, Marsh K, Williams TN. High mortality from Plasmodium falciparum malaria in children living with sickle cell anemia on the coast of Kenya. Blood. 2010;116:1663–1668. doi: 10.1182/blood-2010-01-265249. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Njamnshi AK, Mbong EN, Wonkam A, Ongolo-Zogo P, Djientcheu VD, Sunjoh FL, Wiysonge CS, Sztajzel R, Mbanya D, Blackett KN, Dongmo L, Muna WF. The epidemiology of stroke in sickle cell patients in Yaounde, Cameroon. J Neurol Sci. 2006;250:79–84. doi: 10.1016/j.jns.2006.07.003. [DOI] [PubMed] [Google Scholar]
  8. Piel FB, Patil AP, Howes RE, Nyangiri OA, Gething PW, Dewi M, Temperley WH, Williams TN, Weatherall DJ, Hay SI. Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates. Lancet. 2013;381:142–151. doi: 10.1016/S0140-6736(12)61229-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Ranque B, Menet A, Diop IB, Thiam MM, Diallo D, Diop S, Diagne I, Sanogo I, Kingue S, Chelo D, Wamba G, Diarra M, Anzouan JB, N’Guetta R, Diakite CO, Traore Y, Legueun G, Deme-Ly I, Belinga S, Boidy K, Kamara I, Tharaux P-L, Jouven X. Early renal damage in patients with sickle cell disease in sub-Saharan Africa: a multinational, prospective, cross-sectional study. The Lancet Haematology. 2014;1:e64–e73. doi: 10.1016/S2352-3026(14)00007-6. [DOI] [PubMed] [Google Scholar]
  10. Saraf SL, Zhang X, Kanias T, Lash JP, Molokie RE, Oza B, Lai C, Rowe JH, Gowhari M, Hassan J, Desimone J, Machado RF, Gladwin MT, Little JA, Gordeuk VR. Haemoglobinuria is associated with chronic kidney disease and its progression in patients with sickle cell anaemia. British journal of haematology. 2014;164:729–739. doi: 10.1111/bjh.12690. [DOI] [PMC free article] [PubMed] [Google Scholar]

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