Literature DB >> 29123434

The prevalence of abnormal leukocyte count, and its predisposing factors, in patients with sickle cell disease in Saudi Arabia.

Anwar E Ahmed1, Yosra Z Ali2, Ahmad M Al-Suliman3, Jafar M Albagshi3, Majid Al Salamah1, Mohieldin Elsayid1, Wala R Alanazi4, Rayan A Ahmed5, Donna K McClish6, Hamdan Al-Jahdali1,2.   

Abstract

INTRODUCTION: High white blood cell (WBC) count is an indicator of sickle cell disease (SCD) severity, however, there are limited studies on WBC counts in Saudi Arabian patients with SCD. The aim of this study was to estimate the prevalence of abnormal leukocyte count (either low or high) and identify factors associated with high WBC counts in a sample of Saudi patients with SCD.
METHODS: A cross-sectional and retrospective chart review study was carried out on 290 SCD patients who were routinely treated at King Fahad Hospital in Hofuf, Saudi Arabia. An interview was conducted to assess clinical presentations, and we reviewed patient charts to collect data on blood test parameters for the previous 6 months.
RESULTS: Almost half (131 [45.2%]) of the sample had abnormal leukocyte counts: low WBC counts 15 (5.2%) and high 116 (40%). High WBC counts were associated with shortness of breath (P=0.022), tiredness (P=0.039), swelling in hands/feet (P=0.020), and back pain (P=0.007). The mean hemoglobin was higher in patients with normal WBC counts (P=0.024), while the mean hemoglobin S was high in patients with high WBC counts (P=0.003). After adjustment for potential confounders, predictors of high WBC counts were male gender (adjusted odds ratio [aOR]=3.63) and patients with cough (aOR=2.18), low hemoglobin (aOR=0.76), and low heart rate (aOR=0.97).
CONCLUSION: Abnormal leukocyte count was common: approximately five in ten Saudi SCD patients assessed in this sample. Male gender, cough, low hemoglobin, and low heart rate were associated with high WBC count. Strategies targeting high WBC count could prevent disease complication and thus could be beneficial for SCD patients.

Entities:  

Keywords:  SCD; Saudi; Saudi Arabia; hemoglobin; leukocyte; low heart rate; white blood cell

Year:  2017        PMID: 29123434      PMCID: PMC5661844          DOI: 10.2147/JBM.S148463

Source DB:  PubMed          Journal:  J Blood Med        ISSN: 1179-2736


Introduction

White blood cell (WBC) or leukocyte count is a blood test used to detect a range of blood disorders, evaluate the severity of various underlying diseases, and at times predict the risk of death.1–7 Several previous reports revealed a possible association between WBCs and severity of sickle cell disease (SCD).7–10 Buchanan and Glader11 reported that WBC counts were significantly increased during serious bacterial infection and vaso-occlusive crisis among children with SCD. Litos et al10 found that SCD patients who developed complications had higher WBC counts than asymptomatic SCD patients.10 WBC count was found to be an accurate test for detecting acute chest syndrome in SCD patients who attended an emergency department (ED) with pain crises.12 Castro et al13 noted that WBC count was associated with acute chest syndrome in patients with SCD. Liem et al14 reported SCD patients with acute chest syndrome had a higher WBC count compared to controls. Evidence was found that a high level of WBC count is recognized as a major risk factor for hospital admission and frequent ED visits.15,16 Olatunji and Davies15 documented that patients with particularly high levels of WBCs had frequent hospital admission. Recently, Curtis et al16 found that an elevated WBC count was associated with high risk of frequent ED visits. The evidence of the association between WBC and the severity of SCD mainly comes from epidemiological studies in Western countries; however, these findings may not be generalizable to SCD patients in non-Western countries. For better understanding, the role of WBCs in SCD severity should be assessed in various SCD populations worldwide, particularly in non-Western countries. Studies in the Eastern Province of Saudi Arabia reported high WBC counts in Saudi children with SCD and acute chest syndrome,17,18 and another study assessed SCD complications in Saudi adults with SCD, revealing high WBC levels with a mean of 12.7×109 cells/L.19 Despite clear evidence that WBC was found to be associated with complications and poor prognosis in SCD patients, no study in the Saudi SCD population has been found to assess the prevalence of high WBCs and SCD severity or complications. The purpose of the current study was to estimate the prevalence of abnormal WBCs (low or high) and identify the predictors of high WBCs in a sample of Saudis with SCD, and severity of SCD. We hypothesize that SCD symptoms and complications may be associated with high WBCs in Saudi patients with SCD.

Methods

Cross-sectional and retrospective designs were used to recruit and review medical charts of Saudi patients with SCD (age ≥2 years) who attended the outpatient clinic at King Fahad Hospital in Hofuf, Eastern Region, Saudi Arabia, for routine health assessment. Four hundred SCD patients attended King Fahad Hospital in Hofuf for routine assessment during the study period between October 1, 2016 and March 31, 2017. Of those, 290 consented and enrolled in the study, with a response rate of 72.5%. The study included two stages: structured interview by a hematologist, and a chart review covering the previous 6 months for each patient. The interview took 10 to 15 min and the patients were asked to report whether they had fever, shortness of breath, cough, tiredness, wheezing, skin redness, swelling in hands/feet, blood transfusion, itching, and frequent (≥3) ED visits during the previous 6 months. Participants were asked whether they experienced frequent pain in the previous 6 months. Those who responded that they “experienced frequent pain” were asked to specify the pain site: back, arm, leg, and/or chest. Participants were allowed to select more than one pain site. If the participants were aged between 2 and 17 years, pain history was assessed by the child and/or the parents. The medical chart of each patient was reviewed for the previous 6 months. We collected data on heart rate and blood tests. The blood tests included: hemoglobin, hemoglobin F, hemoglobin A2, hemoglobin S, and the WBC count. In case of multiple readings, the most recent reading was extracted. The WBC counts were assessed by automated blood cell counters (Beckman Coulter, Brea, CA, USA) and cell counts were expressed in 109 cells/L. In order to estimate the prevalence of abnormal leukocyte count, we categorized leukocyte count into three groups: low <4×109 cells/L (low WBC count referred to a leukopenia), normal 4–11×109 cells/L, and high >11×109 cells/L (high WBC count referred to a leukocytosis). The normal WBC range (4–11×109 cells/L) was applied to all age groups. For the purpose of multivariate analysis, patients with low WBC counts were excluded to identify the independent predictors of high WBC counts.

Statistical analysis

The analyses were performed using IBM SPSS Statistics for Windows, version 24 (IBM Corporation, Armonk, NY, USA). The sample characteristics were presented as percentages for non-numerical variables (Table 1) and counts and means and SDs for numerical variables (Table 2). We estimated the prevalence of abnormal leukocyte count (either low or high) using the percentage and 95% CIs. For subgroup analyses we used a chi-square test to assess the association between WBC groups and non-numerical variables (Table 1). For subgroup analyses we used the ANOVA test to assess the association between WBC groups and numerical variables (Table 2). In the adjusted analysis, we only considered high vs. normal WBC counts. Multiple-binary logistic regression was used to identify the independent factors associated with high WBC counts (Table 3). The aOR and 95% CIs were used to assess the strength of the relationship. The significant levels criterion was P<0.05 in all analyses.
Table 1

WBC count and its relation to sample characteristics in SCD patients

CharacteristicsLevelsOverall N=290
Low <4 15 (5.2%)
Normal 4–11 159 (54.8%)
P-value
n%n%n%
GenderFemale13145.275.38161.80.073
Male15954.885.07849.1
Age, years<259935.155.15757.60.397
25–3612343.664.96653.7
>366021.323.33253.3
FeverNo13346.764.57858.60.573
Yes15253.395.98052.6
CoughNo15252.495.99159.90.105
Yes13847.664.36849.3
Shortness of breathNo15252.463.99562.50.022*
Yes13847.696.56446.4
WheezingNo23282.6156.512654.30.186
Yes4917.400.02857.1
TirednessNo8429.122.45666.70.029*
Yes20570.9136.310350.2
Swelling in hands/feetNo20069.973.511959.50.020*
Yes8630.189.33844.2
RednessNo25387.5124.714055.30.661
Yes3612.538.31952.8
ItchingNo20872.7125.811856.70.292
Yes7827.333.83848.7
Blood transfusionNo19667.6105.110453.10.651
Yes9432.455.35558.5
Back painNo10435.976.76865.40.007*
Yes18664.184.39148.9
Leg painNo7224.834.23244.40.075
Yes21875.2125.512758.3
Arm painNo18062.195.09854.40.962
Yes11037.965.56155.5
Chest painNo17660.774.010157.40.372
Yes11439.387.05850.9
Frequent ED visitsNo19976.8115.511055.30.626
Yes6023.223.33151.7

Note:

Significant at α=0.05.

Abbreviations: WBC, white blood cell; SCD, sickle cell disease; ED, emergency department.

Table 2

Differences in hemoglobin electrophoresis by WBC count

MeasureOverall N=290
Low <4 15 (5.2%)
Normal 4–11 159 (54.8%)
High >11 116 (40%)
P-value
MeanSDMeanSDMeanSDMeanSD
Hemoglobin9.21.58.71.39.41.58.91.60.024*
Heart rate84.311.185.610.385.111.483.210.80.383
Hemoglobin F16.36.918.87.417.37.114.56.30.001*
Hemoglobin A23.31.33.11.23.31.53.31.10.917
Hemoglobin S79.47.476.96.478.37.481.17.20.003*

Note:

Significant at α=0.05.

Abbreviation: WBC, white blood cell.

Table 3

Factors associated with high WBC count in SCD patients, N=275 (116 high and 159 normal)

FactorBSEP-valueaOR95% CI for OR
LowerUpper
Male1.2890.3630.001*3.631.7837.384
Age 25–36 years−0.4180.3890.2830.660.3071.412
Age >36 years−0.2490.4350.5670.780.3321.829
Fever0.1590.3390.6381.170.6042.277
Cough0.7790.3560.029*2.181.0844.378
Shortness of breath0.0250.3950.9491.030.4732.222
Wheezing−0.8160.4230.0540.440.1931.013
Tiredness0.2200.3960.5791.250.5732.708
Swelling in hands/feet0.6410.3980.1071.900.8704.138
Redness−0.2980.5030.5540.740.2771.989
Itching0.3240.3660.3751.380.6762.832
Blood transfusion−0.4260.3860.2700.650.3071.392
Back pain0.6620.3610.0661.940.9563.930
Leg pain−0.9340.3830.015*0.390.1850.833
Arm pain−0.0570.3360.8650.940.4891.825
Chest pain−0.1100.3480.7510.900.4531.770
Frequent ED visits0.1850.4080.6511.200.5412.674
Hemoglobin−0.2740.1240.027*0.760.5960.969
Heart rate−0.0340.0160.032*0.970.9360.997
Hemoglobin F0.0090.0370.8141.010.9381.084
Hemoglobin A2−0.0220.1280.8630.980.7621.256
Hemoglobin S0.0340.0310.2731.030.9731.100

Note:

Significant at α=0.05.

Abbreviations: aOR, adjusted odds ratio; CI, confidence interval; WBC, white blood cell; SCD, sickle cell disease; ED, emergency department.

Ethics approval

The Ethics Committee at the Saudi Ministry of Health approved this study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee, and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all patients included in the study. The study received ethical approval from the Saudi Ministry of Health (SMOH), Institutional Review Board Log No 15-247E. Verbal informed consent was approved by SMOH. The study research team obtained verbal consent from adult patients (age ≥18 years), while verbal consent was obtained from children’s parents.

Results

A total of 290 SCD patients were included in the analysis. The average age of the sample was 29.1 years (±SD=10.2) and the average WBC count was 10.7 (±SD=6.3). Slightly more than half of the patients, 159 (54.8%), were within the normal range of the leukocyte count. Abnormal leukocyte count was found in 131/290 (45.2%; 95% CI: 39.35%-51.10%), low WBC in 15/290 (5.2%; 95% CI: 2.92%-8.39%), and high in 116/290 (40%; 95% CI: 34.32%-45.89%). Of the sample, 53.3% had fever, 52.4% had shortness of breath, and 23.2% had frequent ED visits during the previous 6 months. Table 1 presents more details on the sample characteristics. In the subgroup analyses (Table 1), the percentage of high WBC count was higher in SCD patients with shortness of breath (47.1% vs. 33.6%, P=0.022), tiredness (43.4% vs. 31.0%, P=0.039), swelling in hands/feet (46.5% vs. 37.0%, P=0.020), and back pain (46.8% vs. 27.9%, P=0.007). Subgroup analyses in Table 2 show that the mean hemoglobin was higher in patients with normal WBC (low 8.7, normal 9.4, and high 8.9, P=0.024). The mean hemoglobin F was higher in patients with low WBC counts (low 18.8, normal 17.3, and high 14.5, P=0.001) (Figure 1). The mean hemoglobin S was higher in patients with high WBC counts (low 76.9, normal 78.3, and high 81.1, P=0.003) (Figure 2).
Figure 1

Hemoglobin F by WBC groups.

Abbreviation: WBC, white blood cell.

Figure 2

Hemoglobin S by WBC groups.

Abbreviation: WBC, white blood cell.

We identified multiple factors associated with high WBC counts compared to normal WBC counts (excluding low WBC counts) in Table 3. Male gender (aOR=3.63, 95% CI, 1.783−7.384) and patients with cough (aOR=2.18, 95% CI, 1.084−4.378) increased the odds of high WBCs. However, the odds of high WBCs tended to decrease by 24% for every unit increase in hemoglobin (aOR=0.76, 95% CI, 0.596–0.969), and by 3% for every unit increase in high heart rate (aOR=0.97, 95% CI, 0.936–0.997).

Discussion

This epidemiological study was conducted to estimate the prevalence of abnormal leukocyte count (low or high) in a sample of Saudi patients with SCD, who were recruited from routine visits at King Fahad Hospital in Hofuf in the Eastern Province of Saudi Arabia where the prevalence of SCD was reported to be high.20,21 The study documented that high prevalence of abnormal leukocyte count was found in 131 (45.2%) of our total sample: low in 15 (5.2%), and high in 116 (40%). The study estimated the mean WBC counts of 10.7±6.3 (range =2.5–61) ×109 cells/L. This finding was consistent with a study conducted on Saudi adults with SCD from the Eastern Province 12.7±7.6 (range =2.6–52.5) ×109 cells/L.19 However, their typical WBC value was higher than the average normal range (4–11×109 cells/L). The high WBC counts in the SCD population could be as a result from infections or reactions to medications.22,23 Evaluation of WBCs should be performed periodically in primary health care clinics to identify patients with lower or higher values than the normal WBC range. This may enable hematologists to assess the current medications, underlying etiology, or impending SCD crisis and initiate treatment to mitigate symptoms and modifiable factors that are associated with high WBCs. The male gender was independently associated with high WBC counts. The odds of high WBC counts were 3.6 times higher in males compared to females (aOR =3.63). As per the authors’ knowledge, gender’s effect on high WBC counts has not been documented in SCD patients. Influence of gender on WBC counts in SCD patients should be investigated in various SCD populations. The prevalence of high WBC counts differs significantly between SCD patients with a cough and those with no cough. The odds of high WBC counts were 2 times higher in SCD patients with a cough than SCD patients with no cough. This finding is consistent with several studies.24,25 Eisenbrown et al25 reported that a higher WBC level in SCD patients with a cough should prompt a chest X-ray. According to subgroup analyses, there was a significant association between swelling in hands/feet and high WBC counts. Patients with swelling in hands/feet tend to have 2 times increased odds of high WBC compared to patients with no swelling in hands/feet. Several studies have shown that the presence of swelling in hands/feet in SCD patients was common, but they have not investigated its link with high WBC counts.26,27 The high prevalence of cough and swelling in hands/feet in the SCD population could be targeted in future research to identify whether they are risk factors or symptoms of high WBCs. The current study has demonstrated that hemoglobin and heart rate are negatively associated with high risk of high WBC counts. Routine examination of hemoglobin and heart rate to monitor WBC counts may help control SCD and its symptoms.

Limitations

Several limitations can be highlighted in this study. The findings of the study result from cross-sectional and retrospective chart review, thus relationships may not represent causation. The study recruited SCD patients who attended a single hospital in Saudi Arabia for routine medical check-ups, thus the population may not be a good representation of the SCD population in Saudi Arabia. Despite several limitations, the study has findings that may serve as novel evidence in identifying the potential predictors of high WBCs.

Conclusion

Abnormal leukocyte count was common: approximately five in ten Saudi SCD patients who were treated routinely at King Fahad Hospital in Hofuf. Male gender, cough, low hemoglobin, and low heart rate were associated with high WBC count. Strategies targeting high WBC count could prevent disease complication and thus be beneficial for SCD patients.
  24 in total

1.  White blood cell count as a predictor of the severity of sickle cell disease during pregnancy.

Authors:  Michail Litos; Ippokratis Sarris; Susan Bewley; Paul Seed; Iheanyi Okpala; Eugene Oteng-Ntim
Journal:  Eur J Obstet Gynecol Reprod Biol       Date:  2006-09-29       Impact factor: 2.435

2.  Diurnal variations in serum biochemical and haematological measurements.

Authors:  S J Pocock; D Ashby; A G Shaper; M Walker; P M Broughton
Journal:  J Clin Pathol       Date:  1989-02       Impact factor: 3.411

3.  The predictive value of white cell count in assessing clinical severity of sickle cell anaemia in Afro-Caribbeans patients.

Authors:  P O Olatunji; S C Davies
Journal:  Afr J Med Med Sci       Date:  2000-03

Review 4.  Leukocytosis: basics of clinical assessment.

Authors:  N Abramson; B Melton
Journal:  Am Fam Physician       Date:  2000-11-01       Impact factor: 3.292

5.  Acute chest syndrome in sickle cell disease in Saudi Arab Children in the Eastern Province.

Authors:  Ibrahim A Al-Dabbous
Journal:  Ann Saudi Med       Date:  2002 May-Jul       Impact factor: 1.526

Review 6.  The intriguing contribution of white blood cells to sickle cell disease - a red cell disorder.

Authors:  Iheanyi Okpala
Journal:  Blood Rev       Date:  2004-03       Impact factor: 8.250

7.  Comparative Evaluation of C-Reactive Protein and WBC Count in Fascial Space Infections of Odontogenic Origin.

Authors:  Ravikiran Bagul; Sanjay Chandan; Vikrant Dilip Sane; Sujay Patil; Dinesh Yadav
Journal:  J Maxillofac Oral Surg       Date:  2016-09-01

Review 8.  Leukocytes and coronary heart disease.

Authors:  Michael Hoffman; Arnon Blum; Roni Baruch; Eli Kaplan; Moshe Benjamin
Journal:  Atherosclerosis       Date:  2004-01       Impact factor: 5.162

9.  Sickle cell disease in children: differentiating osteomyelitis from vaso-occlusive crisis.

Authors:  Elizabeth Berger; Natasha Saunders; Lisa Wang; Jeremy N Friedman
Journal:  Arch Pediatr Adolesc Med       Date:  2009-03

Review 10.  Epidemiology of sickle cell disease in Saudi Arabia.

Authors:  Wasil Jastaniah
Journal:  Ann Saudi Med       Date:  2011 May-Jun       Impact factor: 1.526

View more
  6 in total

Review 1.  A comprehensive review of hydroxyurea for β-haemoglobinopathies: the role revisited during COVID-19 pandemic.

Authors:  Nirmani Yasara; Anuja Premawardhena; Sachith Mettananda
Journal:  Orphanet J Rare Dis       Date:  2021-03-01       Impact factor: 4.123

2.  Hematological parameters in Ghanaian sickle cell disease patients.

Authors:  Charles Antwi-Boasiako; Ivy Ekem; Mubarak Abdul-Rahman; Frederika Sey; Alfred Doku; Bartholomew Dzudzor; Gifty B Dankwah; Kate Hagar Otu; John Ahenkorah; Robert Aryee
Journal:  J Blood Med       Date:  2018-10-31

3.  Biochemical and Molecular analysis of the beta-globin gene on Saudi sickle cell anemia.

Authors:  Faris Q Alenzi; Dalal S AlShaya
Journal:  Saudi J Biol Sci       Date:  2019-03-15       Impact factor: 4.219

4.  Patterns and patient factors associated with loss to follow-up in the Muhimbili sickle cell cohort, Tanzania.

Authors:  Upendo Masamu; Raphael Z Sangeda; Daniel Kandonga; Jesca Ondengo; Flora Ndobho; Bruno Mmbando; Siana Nkya; Khadija Msami; Julie Makani
Journal:  BMC Health Serv Res       Date:  2020-12-14       Impact factor: 2.655

5.  Paediatric sickle cell disease at a tertiary hospital in Malawi: a retrospective cross-sectional study.

Authors:  Chikondi Sharon Chimbatata; Master Ro Chisale; Alfred Bornwell Kayira; Frank Watson Sinyiza; Balwani Chingatichifwe Mbakaya; Paul Uchizi Kaseka; Pocha Kamudumuli; Tsung-Shu Joseph Wu
Journal:  BMJ Paediatr Open       Date:  2021-09-08

6.  Neutrophils remain detrimentally active in hydroxyurea-treated patients with sickle cell disease.

Authors:  Emilia Alina Barbu; Venina M Dominical; Laurel Mendelsohn; Swee Lay Thein
Journal:  PLoS One       Date:  2019-12-23       Impact factor: 3.240

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.