{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T20:17:53Z","timestamp":1792527473028,"version":"4.5.0"},"reference-count":85,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T00:00:00Z","timestamp":1773273600000},"content-version":"vor","delay-in-days":70,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["The Scientific World Journal"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Sickle cell disease is a human hemoglobinopathy associated with high hemolytic capacity. Hemoglobin S (HbS) polymerization is a primary pathophysiological event in sickle cell anemia. Despite numerous studies conducted to understand the pathophysiology of the disease, including oxidative imbalance and cardiovascular risk, questions still arise. This systematic review and meta\u2010analysis aimed to evaluate studies linking oxidative stress, lipid profile, and dyslipidemia in sickle cell patients, predisposing them to atherogenic risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      The systematic review of databases and search engines was conducted over 24 years (2000\u20132024) worldwide, according to the guidelines of PRISMA and the Cochrane Handbook. Research articles were searched in the PubMed and Web of Science databases. Only case\u2010control articles were retained. Data were extracted from the articles and analyzed using R version 4.3.2, with a common\u2010effect model for meta\u2010analyses. Heterogeneity was assessed using\n                      <jats:italic>I<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      statistics. The standardized mean difference (SMD) was used to assess the extent of the disease on the different parameters studied. Heterogeneity across individual studies was assessed using Higgins\u2019s inconsistency Q statistics and reported as\n                      <jats:italic>I<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      and\n                      <jats:italic>p<\/jats:italic>\n                      \u2010values. ROBINS\u2010E was used to assess the risk of bias in the included studies.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 405 studies were initially identified; after the elimination of duplicates and studies not meeting the objectives of the review, 25 studies were finally included in the meta\u2010analyses. The reported SMDs using a common\u2010effect model were 1.15 [0.96; 1.34] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01) for Lactate Dehydrogenase (LDH), 1.03 [0.48; 1.53] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01) for Myeloperoxidase (MPO), and 1.13 [0.96; 1.29] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01) for Malondialdehyde (MDA), reflecting the strong influence of sickle cell disease on hemolysis and the production of lipid peroxidation markers compared with normal controls. The antioxidant markers Glutathione Peroxidase (GPx), Reduced Glutathione (GSH), catalase, Superoxide Dismutase (SOD), and Total Antioxidant Capacity (TAC) reported respective SMDs of \u22121.97 [\u22122.32; \u22121.63] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01), \u22123.01 [\u22123.50; \u22122.52] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01), \u22121.39 [\u22121.58; \u22121.20] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01), \u22121.99 [\u22121.92; \u22121.47] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01), and\u22121.58 [\u22121.90; \u22121.25] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01), reflecting the strong negative influence of sickle cell disease on the activity of these enzymes. The evaluated lipid profiles reported dyslipidemia and an atherogenic risk characterized by a significant negative influence on plasma concentrations of Total Cholesterol (TC), High\u2010Density Lipoprotein cholesterol (HDLc), and Low\u2010Density Lipoprotein cholesterol (LDLc), with respective SMDs of \u22121.32 [\u22121.42; \u22121.21] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01), \u22120.84 [\u22120.94; \u22120.73] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01), and\u22122.54 [\u22123.15; \u22121.93]. Conversely, a significant influence of sickle cell disease was observed on the triglycerides\/HDL\u2010c ratio and triglycerides, characterized by respective SMDs of 1.58 [1.41; 1.75] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01) and 1.58 [1.41; 1.75] (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;0.01).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Analyses performed in these studies reported a large influence of sickle cell disease on oxidative stress, characterized by an imbalance of the oxidant\/antioxidant system in favor of oxidants, as well as lipid profile imbalance causing dyslipidemia and a high atherogenic risk compared with normal controls, as assessed by large SMDs. These results provide additional information on oxidative stress abnormalities in sickle cell disease and may serve as a basis for decision\u2010making aimed at improving patient care.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1155\/tswj\/8864775","type":"journal-article","created":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T06:34:10Z","timestamp":1773383650000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Oxidative Stress, Antioxidant Capacity, Dyslipidemia and Cardiovascular Risk in Sickle Cell Disease: A Systematic Review and Meta\u2010Analysis"],"prefix":"10.1155","volume":"2026","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0833-8167","authenticated-orcid":false,"given":"Josu\u00e9 Louokdom","family":"Simo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2867-0538","authenticated-orcid":false,"given":"Romaric De Manfouo","family":"Tuono","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maryline Seuko","family":"Njopwouo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2179-3105","authenticated-orcid":false,"given":"Claude Tagny","family":"Tayou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,3,12]]},"reference":[{"key":"e_1_2_15_1_2","doi-asserted-by":"publisher","DOI":"10.1002\/14651858.CD013590"},{"key":"e_1_2_15_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/biom13081262"},{"key":"e_1_2_15_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12291-017-0729-3"},{"key":"e_1_2_15_4_2","first-page":"1","volume-title":"Hematology","author":"Biswal S.","year":"2019"},{"key":"e_1_2_15_5_2","doi-asserted-by":"publisher","DOI":"10.1111\/bjh.12594"},{"key":"e_1_2_15_6_2","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-bioeng-070909-105339"},{"key":"e_1_2_15_7_2","doi-asserted-by":"publisher","DOI":"10.1684\/abc.2011.0633"},{"key":"e_1_2_15_8_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-90477-z"},{"key":"e_1_2_15_9_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2141.2011.08961.x"},{"key":"e_1_2_15_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.freeradbiomed.2019.07.004"},{"key":"e_1_2_15_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.freeradbiomed.2013.08.181"},{"key":"e_1_2_15_12_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12959-025-00804-x"},{"key":"e_1_2_15_13_2","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2020.00454"},{"key":"e_1_2_15_14_2","doi-asserted-by":"publisher","DOI":"10.1172\/JCI10726"},{"key":"e_1_2_15_15_2","doi-asserted-by":"publisher","DOI":"10.5315\/wjh.v11.i2.94171"},{"key":"e_1_2_15_16_2","doi-asserted-by":"publisher","DOI":"10.1002\/ajh.21475"},{"key":"e_1_2_15_17_2","doi-asserted-by":"publisher","DOI":"10.3390\/antiox10020296"},{"key":"e_1_2_15_18_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1440-1681.2007.04639.x"},{"key":"e_1_2_15_19_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12879-019-4221-y"},{"key":"e_1_2_15_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.hemonc.2021.11.003"},{"key":"e_1_2_15_21_2","doi-asserted-by":"publisher","DOI":"10.12692\/ijb\/3.7.188-194"},{"key":"e_1_2_15_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.freeradbiomed.2007.08.014"},{"key":"e_1_2_15_23_2","doi-asserted-by":"publisher","DOI":"10.11604\/pamj.2019.32.141.17166"},{"key":"e_1_2_15_24_2","doi-asserted-by":"crossref","unstructured":"EphraimR. 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