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2. Predictive model for aminoglycoside induced ototoxicity.

Author

Adeyemo, Adebolajo A., Adeolu, Josephine, Akinyemi, Joshua O., Omotade, Olayemi O., and Oluwatosin, Odunayo M.

Subjects
RECEIVER operating characteristic curves, AKAIKE information criterion, LIKELIHOOD ratio tests, LOGISTIC regression analysis, OTOTOXICITY
Abstract

Background: Irreversible hearing loss is a well-known adverse effect of aminoglycosides, however, inability to accurately predict ototoxicity is a major limitation in clinical care. We addressed this limitation by developing a prediction model for aminoglycoside ototoxicity applicable to the general population. Methods: We employed a prospective non-drug-resistant tuberculosis (TB), non-HIV/AIDS cohort of 153 adults on Streptomycin based anti-TB therapy. High frequency pure-tone audiometry was done at regular intervals throughout the study. Clinical and audiological predictors of ototoxicity were collated and ototoxic threshold shift from the baseline audiogram computed. The prediction model was developed with logistic regression method by examining multiple predictors of ototoxicity. Series of models were fitted sequentially; the best model was identified using Akaike Information Criterion and likelihood ratio test. Key variables in the final model were used to develop a logit model for ototoxicity prediction. Results: Ototoxicity occurred in 35% of participants. Age, gender, weight, cumulative Streptomycin dosage, social class, baseline pure tone average (PTA) and prior hearing symptoms were explored as predictors. Multiple logistic regression showed that models with age, cumulative dosage and baseline PTA were best for predicting ototoxicity. Regression parameters for ototoxicity prediction showed that yearly age increment raised ototoxicity risk by 5% (AOR = 1.05; CI, 1.01–1.09), and a gram increase in cumulative dosage increased ototoxicity risk by 7% (AOR = 1.05; CI, 1.05–1.12) while a unit change in baseline log (PTA) was associated 254% higher risk of ototoxicity (AOR = 3.54, CI: 1.25, 10.01). Training and validation models had area under the receiver operating characteristic curve as 0.84 (CI, 0.76–0.92) and 0.79 (CI, 0.62–0.96) respectively, showing the model has discriminatory ability. Conclusion: This model can predict aminoglycoside ototoxicity in the general population. [ABSTRACT FROM AUTHOR]

Published
2024
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5. Re-telling the story of aminoglycoside ototoxicity: tales from sub-Saharan Africa.

Author

Adeyemo, Adebolajo A., Adedokun, Babatunde, Adeolu, Josephine, Akinyemi, Joshua O., Omotade, Olayemi O., and Oluwatosin, Odunayo M.

Subjects
OTOTOXICITY, AGE groups, CHI-squared test, LONGITUDINAL method, AUDIOMETRY, DESCRIPTIVE statistics
Abstract

Background: Aminoglycosides, such as Streptomycin, are cheap, potent antibiotics widely used Sub-Saharan Africa. However, aminoglycosides are the commonest cause of ototoxicity. The limited prospective epidemiological studies on aminoglycoside ototoxicity from Sub-Saharan Africa motivated this study to provide epidemiological information on Streptomycin-induced ototoxicity, identify risk factors and predictors of ototoxicity. Method: A longitudinal study of 153 adults receiving Streptomycin-based antituberculous drugs was done. All participants underwent extended frequency audiometry and had normal hearing thresholds at baseline. Hearing thresholds were assessed weekly for 2months, then monthly for the subsequent 6months. Ototoxicity was determined using the ASHA criteria. Descriptive statistics were used to analyze socio-demographic variables. Ototoxicity incidence rate was calculated, and Kaplan-Meier estimate used to determine cumulative probability of ototoxicity. Chi-square test was done to determine parameters associated with ototoxicity and Cox regression models were used to choose the predictors of ototoxicity. Results: Age of participants was 41.43 ± 12.66 years, with a male-to-female ratio of 1:0.6. Ototoxicity was found in 34.6% of the participants, giving an incidence of 17.26 per 1,000-person-week. The mean onset time to ototoxicity was 28.0 ± 0.47 weeks. By 28th week, risk of developing ototoxicity for respondents below 40 years of age was 0.29, and for those above 40 years was 0.77. At the end of the follow-up period, the overall probability of developing ototoxicity in the study population was 0.74. A significant difference in onset of ototoxicity was found between the age groups: the longest onset was seen in <40 years, followed by 40-49 years, and shortest onset in ≥50 years. Hazard of ototoxicity was significantly higher in participants aged ≥50 years compared to participants aged ≤40 years (HR = 3.76, 95% CI = 1.84-7.65). The probability of ototoxicity at 40 g, 60 g and 80 g cumulative dose of Streptomycin was 0.08, 0.43 and 2.34, respectively. Age and cumulative dose were significant predictors of ototoxicity. Conclusion: The mean onset time to Streptomycin-induced ototoxicity was 28 weeks after commencement of therapy. Age and cumulative dose can reliably predict the onset of Streptomycin-induced ototoxicity. Medium to long term monitoring of hearing is advised for patients on aminoglycoside therapy. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Human candidate gene polymorphisms and risk of severe malaria in children in Kilifi, Kenya: a case-control association study

Author

Abathina, Amadou, Abubakar, Ismaela, Achidi, Eric, Agbenyega, Tsiri, Aiyegbo, Mohammed, Akoto, Alex, Allen, Angela, Allen, Stephen, Amenga-Etego, Lucas, Amodu, Folakemi, Amodu, Olukemi, Anchang-Kimbi, Judith, Ansah, Nana, Ansah, Patrick, Ansong, Daniel, Antwi, Sampson, Anyorigiya, Thomas, Apinjoh, Tobias, Asafo-Agyei, Emmanuel, Asoala, Victor, Atuguba, Frank, Auburn, Sarah, Bah, Abdou, Bamba, Kariatou, Bancone, Germana, Band, Gavin, Barnwell, David, Barry, Abdoulaye, Bauni, Evasius, Besingi, Richard, Bojang, Kalifa, Bougouma, Edith, Bull, Susan, Busby, George, Camara, Abdoulie, Camara, Landing, Campino, Susana, Carter, Richard, Carucci, Dan, Casals-Pascual, Climent, Ceesay, Ndey, Ceesay, Pa, Chau, Tran, Chuong, Ly, Clark, Taane, Clarke, Geraldine, Cole-Ceesay, Ramou, Conway, David, Cook, Katharine, Cook, Olivia, Cornelius, Victoria, Corran, Patrick, Correa, Simon, Cox, Sharon, Craik, Rachel, Danso, Bakary, Davis, Timothy, Day, Nicholas, Deloukas, Panos, Dembele, Awa, deVries, Jantina, Dewasurendra, Rajika, Diakite, Mahamadou, Diarra, Elizabeth, Dibba, Yaya, Diss, Andrea, Djimdé, Abdoulaye, Dolo, Amagana, Doumbo, Ogobara, Doyle, Alan, Drakeley, Chris, Drury, Eleanor, Duffy, Patrick, Dunstan, Sarah, Ebonyi, Augustine, Elhassan, Ahmed, Elhassan, Ibrahim, Elzein, Abier, Enimil, Anthony, Esangbedo, Pamela, Evans, Jennifer, Evans, Julie, Farrar, Jeremy, Fernando, Deepika, Fitzpatrick, Kathryn, Fullah, Janet, Garcia, Jacob, Ghansah, Anita, Gottleib, Michael, Green, Angie, Hart, Lee, Hennsman, Meike, Hien, Tran, Hieu, Nguyen, Hilton, Eliza, Hodgson, Abraham, Horstmann, Rolf, Hubbart, Christina, Hughes, Catherine, Hussein, Ayman, Hutton, Robert, Ibrahim, Muntaser, Ishengoma, Deus, Jaiteh, Jula, Jallow, Mariatou, Jallow, Muminatou, Jammeh, Kebba, Jasseh, Momodou, Jeffreys, Anna, Jobarteh, Amie, Johnson, Kimberly, Joseph, Sarah, Jyothi, Dushyanth, Kachala, David, Kamuya, Dorcas, Kanyi, Haddy, Karunajeewa, Harin, Karunaweera, Nadira, Keita, Momodou, Kerasidou, Angeliki, Khan, Aja, Kivinen, Katja, Kokwaro, Gilbert, Konate, Amadou, Konate, Salimata, Koram, Kwadwo, Kwiatkowski, Dominic, Laman, Moses, Le, Si, Leffler, Ellen, Lemnge, Martha, Lin, Enmoore, Ly, Alioune, Macharia, Alexander, MacInnis, Bronwyn, Mai, Nguyen, Makani, Julie, Malangone, Cinzia, Mangano, Valentina, Manjurano, Alphaxard, Manneh, Lamin, Manning, Laurens, Manske, Magnus, Marsh, Kevin, Marsh, Vicki, Maslen, Gareth, Maxwell, Caroline, Mbunwe, Eric, McCreight, Marilyn, Mead, Daniel, Mendy, Alieu, Mendy, Anthony, Mensah, Nathan, Michon, Pascal, Miles, Alistair, Miotto, Olivo, Modiano, David, Mohamed, Hiba, Molloy, Sile, Molyneux, Malcolm, Molyneux, Sassy, Moore, Mike, Moyes, Catherine, Mtei, Frank, Mtove, George, Mueller, Ivo, Mugri, Regina, Munthali, Annie, Mutabingwa, Theonest, Nadjm, Behzad, Ndi, Andre, Ndila, Carolyne, Newton, Charles, Niangaly, Amadou, Njie, Haddy, Njie, Jalimory, Njie, Madi, Njie, Malick, Njie, Sophie, Njiragoma, Labes, Nkrumah, Francis, Ntunthama, Neema, Nyika, Aceme, Nyirongo, Vysaul, O'Brien, John, Obu, Herbert, Oduro, Abraham, Ofori, Alex, Olaniyan, Subulade, Olaosebikan, Rasaq, Oluoch, Tom, Omotade, Olayemi, Oni, Olajumoke, Onykwelu, Emmanuel, Opi, Daniel, Orimadegun, Adebola, O'Riordan, Sean, Ouedraogo, Issa, Oyola, Samuel, Parker, Michael, Pearson, Richard, Pensulo, Paul, Peshu, Norbert, Phiri, Ajib, Phu, Nguyen, Pinder, Margaret, Pirinen, Matti, Plowe, Chris, Potter, Claire, Poudiougou, Belco, Puijalon, Odile, Quyen, Nguyen, Ragoussis, Ioannis, Ragoussis, Jiannis, Rasheed, Oba, Reeder, John, Reyburn, Hugh, Riley, Eleanor, Risley, Paul, Rockett, Kirk, Rodford, Joanne, Rogers, Jane, Rogers, William, Rowlands, Kate, Ruano-Rubio, Valentín, Sabally-Ceesay, Kumba, Sadiq, Abubacar, Saidy-Khan, Momodou, Saine, Horeja, Sakuntabhai, Anavaj, Sall, Abdourahmane, Sambian, David, Sambou, Idrissa, SanJoaquin, Miguel, Sepúlveda, Nuno, Shah, Shivang, Shelton, Jennifer, Siba, Peter, Silva, Nilupa, Simmons, Cameron, Simpore, Jaques, Singhasivanon, Pratap, Sinh, Dinh, Sirima, Sodiomon, Sirugo, Giorgio, Sisay-Joof, Fatoumatta, Sissoko, Sibiry, Small, Kerrin, Somaskantharajah, Elilan, Spencer, Chris, Stalker, Jim, Stevens, Marryat, Suriyaphol, Prapat, Sylverken, Justice, Taal, Bintou, Tall, Adama, Taylor, Terrie, Teo, Yik, Thai, Cao, Thera, Mahamadou, Titanji, Vincent, Toure, Ousmane, Troye-Blomberg, Marita, Usen, Stanley, Uyoga, Sophie, Vanderwal, Aaron, Wangai, Hannah, Watson, Renee, Williams, Thomas, Wilson, Michael, Wrigley, Rebecca, Yafi, Clarisse, Yamoah, Lawrence, Ndila, Carolyne M, Macharia, Alexander W, Nyutu, Gideon, Ojal, John, Shebe, Mohammed, Awuondo, Kennedy O, Mturi, Neema, Tsofa, Benjamin, Clark, Taane G, Kariuki, Silvia, Mackinnon, Margaret, Maitland, Kathryn, Kwiatkowski, Dominic P, Rockett, Kirk A, and Williams, Thomas N

Published
2018
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15. Human candidate gene polymorphisms and risk of severe malaria in children in Kilifi, Kenya: a case-control association study

Author

Ndila, Carolyne M, Uyoga, Sophie, Macharia, Alexander W, Nyutu, Gideon, Peshu, Norbert, Ojal, John, Shebe, Mohammed, Awuondo, Kennedy O, Mturi, Neema, Tsofa, Benjamin, Sepúlveda, Nuno, Clark, Taane G, Band, Gavin, Clarke, Geraldine, Rowlands, Kate, Hubbart, Christina, Jeffreys, Anna, Kariuki, Silvia, Marsh, Kevin, Mackinnon, Margaret, Maitland, Kathryn, Kwiatkowski, Dominic P, Rockett, Kirk A, Williams, Thomas N, Abathina, Amadou, Abubakar, Ismaela, Achidi, Eric, Agbenyega, Tsiri, Aiyegbo, Mohammed, Akoto, Alex, Allen, Angela, Allen, Stephen, Amenga-Etego, Lucas, Amodu, Folakemi, Amodu, Olukemi, Anchang-Kimbi, Judith, Ansah, Nana, Ansah, Patrick, Ansong, Daniel, Antwi, Sampson, Anyorigiya, Thomas, Apinjoh, Tobias, Asafo-Agyei, Emmanuel, Asoala, Victor, Atuguba, Frank, Auburn, Sarah, Bah, Abdou, Bamba, Kariatou, Bancone, Germana, Barnwell, David, Barry, Abdoulaye, Bauni, Evasius, Besingi, Richard, Bojang, Kalifa, Bougouma, Edith, Bull, Susan, Busby, George, Camara, Abdoulie, Camara, Landing, Campino, Susana, Carter, Richard, Carucci, Dan, Casals-Pascual, Climent, Ceesay, Ndey, Ceesay, Pa, Chau, Tran, Chuong, Ly, Clark, Taane, Cole-Ceesay, Ramou, Conway, David, Cook, Katharine, Cook, Olivia, Cornelius, Victoria, Corran, Patrick, Correa, Simon, Cox, Sharon, Craik, Rachel, Danso, Bakary, Davis, Timothy, Day, Nicholas, Deloukas, Panos, Dembele, Awa, Devries, Jantina, Dewasurendra, Rajika, Diakite, Mahamadou, Diarra, Elizabeth, Dibba, Yaya, Diss, Andrea, Djimdé, Abdoulaye, Dolo, Amagana, Doumbo, Ogobara, Doyle, Alan, Drakeley, Chris, Drury, Eleanor, Duffy, Patrick, Dunstan, Sarah, Ebonyi, Augustine, Elhassan, Ahmed, Elhassan, Ibrahim, Elzein, Abier, Enimil, Anthony, Esangbedo, Pamela, Evans, Jennifer, Evans, Julie, Farrar, Jeremy, Fernando, Deepika, Fitzpatrick, Kathryn, Fullah, Janet, Garcia, Jacob, Ghansah, Anita, Gottleib, Michael, Green, Angie, Hart, Lee, Hennsman, Meike, Hien, Tran, Hieu, Nguyen, Hilton, Eliza, Hodgson, Abraham, Horstmann, Rolf, Hughes, Catherine, Hussein, Ayman, Hutton, Robert, Ibrahim, Muntaser, Ishengoma, Deus, Jaiteh, Jula, Jallow, Mariatou, Jallow, Muminatou, Jammeh, Kebba, Jasseh, Momodou, Jobarteh, Amie, Johnson, Kimberly, Joseph, Sarah, Jyothi, Dushyanth, Kachala, David, Kamuya, Dorcas, Kanyi, Haddy, Karunajeewa, Harin, Karunaweera, Nadira, Keita, Momodou, Kerasidou, Angeliki, Khan, Aja, Kivinen, Katja, Kokwaro, Gilbert, Konate, Amadou, Konate, Salimata, Koram, Kwadwo, Kwiatkowski, Dominic, Laman, Moses, Si, Le, Leffler, Ellen, Lemnge, Martha, Lin, Enmoore, Alioune, Ly, Macharia, Alexander, Macinnis, Bronwyn, Mai, Nguyen, Makani, Julie, Malangone, Cinzia, Mangano, Valentina, Manjurano, Alphaxard, Manneh, Lamin, Manning, Laurens, Manske, Magnus, Marsh, Vicki, Maslen, Gareth, Maxwell, Caroline, Mbunwe, Eric, Mccreight, Marilyn, Mead, Daniel, Mendy, Alieu, Mendy, Anthony, Mensah, Nathan, Michon, Pascal, Miles, Alistair, Miotto, Olivo, Modiano, David, Mohamed, Hiba, Molloy, Sile, Molyneux, Malcolm, Molyneux, Sassy, Moore, Mike, Moyes, Catherine, Mtei, Frank, Mtove, George, Mueller, Ivo, Mugri, Regina, Munthali, Annie, Mutabingwa, Theonest, Nadjm, Behzad, Ndi, Andre, Ndila, Carolyne, Newton, Charles, Niangaly, Amadou, Njie, Haddy, Njie, Jalimory, Njie, Madi, Njie, Malick, Njie, Sophie, Njiragoma, Labes, Nkrumah, Francis, Ntunthama, Neema, Nyika, Aceme, Nyirongo, Vysaul, O'Brien, John, Obu, Herbert, Oduro, Abraham, Ofori, Alex, Olaniyan, Subulade, Olaosebikan, Rasaq, Oluoch, Tom, Omotade, Olayemi, Oni, Olajumoke, Onykwelu, Emmanuel, Opi, Daniel, Orimadegun, Adebola, O'Riordan, Sean, Ouedraogo, Issa, Oyola, Samuel, Parker, Michael, Pearson, Richard, Pensulo, Paul, Phiri, Ajib, Phu, Nguyen, Pinder, Margaret, Pirinen, Matti, Plowe, Chris, Potter, Claire, Poudiougou, Belco, Puijalon, Odile, Quyen, Nguyen, Ragoussis, Ioannis, Ragoussis, Jiannis, Rasheed, Oba, Reeder, John, Reyburn, Hugh, Riley, Eleanor, Risley, Paul, Rockett, Kirk, Rodford, Joanne, Rogers, Jane, Rogers, William, Ruano-Rubio, Valentín, Sabally-Ceesay, Kumba, Sadiq, Abubacar, Saidy-Khan, Momodou, Saine, Horeja, Sakuntabhai, Anavaj, Sall, Abdourahmane, Sambian, David, Sambou, Idrissa, Sanjoaquin, Miguel, Shah, Shivang, Shelton, Jennifer, Siba, Peter, Silva, Nilupa, Simmons, Cameron, Simpore, Jaques, Singhasivanon, Pratap, Sinh, Dinh, Sirima, Sodiomon, Sirugo, Giorgio, Sisay-Joof, Fatoumatta, Sissoko, Sibiry, Small, Kerrin, Somaskantharajah, Elilan, Spencer, Chris, Stalker, Jim, Stevens, Marryat, Suriyaphol, Prapat, Sylverken, Justice, Taal, Bintou, Tall, Adama, Taylor, Terrie, Teo, Yik, Thai, Cao, Thera, Mahamadou, Titanji, Vincent, Toure, Ousmane, Troye-Blomberg, Marita, Usen, Stanley, Vanderwal, Aaron, Wangai, Hannah, Watson, Renee, Williams, Thomas, Wilson, Michael, Wrigley, Rebecca, Yafi, Clarisse, Yamoah, Lawrence, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford, London School of Hygiene and Tropical Medicine (LSHTM), The Wellcome Trust Sanger Institute [Cambridge], St Mary's Hospital, Imperial College, TNW and MM are funded through awards from the Wellcome Trust (grants 091758 and 202800 [to TNW] and grant 088634 [to MM]) and DPK and TGC receive support from the Medical Research Council (grant G19/9 [to DPK] and grants MR/K000551/1, MR/M01360X/1, MR/N010469/1, and MC_PC_15103 [to TGC]). The research leading to these results received funding from the European Community's Seventh Framework Programme (FP7/2007-2013, under grant agreement 242095) and from the Medical Research Council (grant G0600718). MalariaGEN is supported by the Wellcome Trust (WT077383/Z/05/Z) and by the Foundation for the National Institutes of Health (grant 566) as part of the Bill & Melinda Gates' Grand Challenges in Global Health Initiative. The Resource Centre for Genomic Epidemiology of Malaria is supported by the Wellcome Trust (grant 090770/Z/09/Z). Support was also provided by the Medical Research Council (grant G0600718). The Wellcome Trust also provides core awards to the Wellcome Trust Centre for Human Genetics (grant 090532/Z/09/Z) and to the Wellcome Trust Sanger Institute (grant 098051). This work forms part of a larger collaboration with the MalariaGEN Consortium, whose members are listed at http://www.malariagen.net/projects/host/consortium-members. This paper is published with permission from the Director of the Kenya Medical Research Institute (KEMRI)., MalariaGEN Consortium (Anavaj Sakuntabhai), and European Project: 242095,EC:FP7:HEALTH,FP7-HEALTH-2009-single-stage,EVIMALAR(2009)

Subjects
Case-Control Studies, Child, Child, Preschool, Female, Gene Frequency, Genetic Predisposition to Disease, Humans, Kenya, Malaria, Male, Polymorphism, Genetic, Hematology, macromolecular substances, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Article, Genetic, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, parasitic diseases, [SDV.MP.PAR]Life Sciences [q-bio]/Microbiology and Parasitology/Parasitology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Polymorphism, Preschool
Abstract

Summary Background Human genetic factors are important determinants of malaria risk. We investigated associations between multiple candidate polymorphisms—many related to the structure or function of red blood cells—and risk for severe Plasmodium falciparum malaria and its specific phenotypes, including cerebral malaria, severe malaria anaemia, and respiratory distress. Methods We did a case-control study in Kilifi County, Kenya. We recruited as cases children presenting with severe malaria to the high-dependency ward of Kilifi County Hospital. We included as controls infants born in the local community between Aug 1, 2006, and Sept 30, 2010, who were part of a genetics study. We tested for associations between a range of candidate malaria-protective genes and risk for severe malaria and its specific phenotypes. We used a permutation approach to account for multiple comparisons between polymorphisms and severe malaria. We judged p values less than 0·005 significant for the primary analysis of the association between candidate genes and severe malaria. Findings Between June 11, 1995, and June 12, 2008, 2244 children with severe malaria were recruited to the study, and 3949 infants were included as controls. Overall, 263 (12%) of 2244 children with severe malaria died in hospital, including 196 (16%) of 1233 with cerebral malaria. We investigated 121 polymorphisms in 70 candidate severe malaria-associated genes. We found significant associations between risk for severe malaria overall and polymorphisms in 15 genes or locations, of which most were related to red blood cells: ABO, ATP2B4, ARL14, CD40LG, FREM3, INPP4B, G6PD, HBA (both HBA1 and HBA2), HBB, IL10, LPHN2 (also known as ADGRL2), LOC727982, RPS6KL1, CAND1, and GNAS. Combined, these genetic associations accounted for 5·2% of the variance in risk for developing severe malaria among individuals in the general population. We confirmed established associations between severe malaria and sickle-cell trait (odds ratio [OR] 0·15, 95% CI 0·11–0·20; p=2·61 × 10−58), blood group O (0·74, 0·66–0·82; p=6·26 × 10−8), and –α3·7-thalassaemia (0·83, 0·76–0·90; p=2·06 × 10−6). We also found strong associations between overall risk of severe malaria and polymorphisms in both ATP2B4 (OR 0·76, 95% CI 0·63–0·92; p=0·001) and FREM3 (0·64, 0·53–0·79; p=3·18 × 10−14). The association with FREM3 could be accounted for by linkage disequilibrium with a complex structural mutation within the glycophorin gene region (comprising GYPA, GYPB, and GYPE) that encodes for the rare Dantu blood group antigen. Heterozygosity for Dantu was associated with risk for severe malaria (OR 0·57, 95% CI 0·49–0·68; p=3·22 × 10−11), as was homozygosity (0·26, 0·11–0·62; p=0·002). Interpretation Both ATP2B4 and the Dantu blood group antigen are associated with the structure and function of red blood cells. ATP2B4 codes for plasma membrane calcium-transporting ATPase 4 (the major calcium pump on red blood cells) and the glycophorins are ligands for parasites to invade red blood cells. Future work should aim at uncovering the mechanisms by which these polymorphisms can result in severe malaria protection and investigate the implications of these associations for wider health. Funding Wellcome Trust, UK Medical Research Council, European Union, and Foundation for the National Institutes of Health as part of the Bill & Melinda Gates Grand Challenges in Global Health Initiative.

Published
2018
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16. Early home treatment of childhood fevers with ineffective antimalarials is deleterious in the outcome of severe malaria

Author

Olumese Peter E, Amodu Olukemi K, Orimadegun Adebola E, and Omotade Olayemi O

Subjects
Arctic medicine. Tropical medicine, RC955-962, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Background Early diagnosis and prompt treatment including appropriate home-based treatment of malaria is a major strategy for malaria control. A major determinant of clinical outcome in case management is compliance and adherence to effective antimalarial regimen. Home-based malaria treatment with inappropriate medicines is ineffective and there is insufficient evidence on how this contributes to the outcome of severe malaria. This study evaluated the effects of pre-hospital antimalarial drugs use on the presentation and outcome of severe malaria in children in Ibadan, Nigeria. Methods Two hundred and sixty-eight children with a median age of 30 months comprising 114 children with cerebral malaria and 154 with severe malarial anaemia (as defined by WHO) were prospectively enrolled. Data on socio-demographic data, treatments given at home, clinical course and outcome of admission were collected and analysed. Results A total of 168 children had treatment with an antimalarial treatment at home before presenting at the hospital when there was no improvement. There were no significant differences in the haematocrit levels, parasite counts and nutritional status of the pre-hospital treated and untreated groups. The most commonly used antimalarial medicine was chloroquine. Treatment policy was revised to Artemesinin-based Combination Therapy (ACT) in 2005 as a response to unacceptable levels of therapeutic failures with chloroquine, however chloroquine use remains high. The risk of presenting as cerebral malaria was 1.63 times higher with pre-hospital use of chloroquine for treatment of malaria, with a four-fold increase in the risk of mortality. Controlling for other confounding factors including age and clinical severity, pre-hospital treatment with chloroquine was an independent predictor of mortality. Conclusion This study showed that, home treatment with chloroquine significantly impacts on the outcome of severe malaria. This finding underscores the need for wide-scale monitoring to withdraw chloroquine from circulation in Nigeria and efforts intensified at promoting prompt treatment with effective medicines in the community.

Published
2008
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30. Energy Expenditure and Adiposity in Nigerian and African-American Women

Author

Ebersole, Kara E., primary, Dugas, Lara R., additional, Durazo-Arvizu, Ramon A., additional, Adeyemo, Adebowale A., additional, Tayo, Bamidele O., additional, Omotade, Olayemi O., additional, Brieger, William R., additional, Schoeller, Dale A., additional, Cooper, Richard S., additional, and Luke, Amy H., additional

Published
2008
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35. Integrating Clinical Research into Epidemic Response: The Ebola Experience Summary

Author

Keusch, Gerald T., Mcadam, Keith, Cuff, Patricia A., Mancher, Michelle, Busta, Emily R., Babiker, Abdel, Barrie, Mohamed Bailor, Cooper, Janice, Davis, Sheila, Edwards, Kathryn, Ellenberg, Susan, Lewis, Roger, London, Alex John, Jens Lundgren, Mello, Michelle M., Omotade, Olayemi, Peters, David H., Wabwire-Mangen, Fred, Wells, Charles D., Darbyshire, Janet, and Forstag, Erin Hammers

36. Facilitating International Coordination and Collaboration

Author

Keusch, Gerald T., Mcadam, Keith, Cuff, Patricia A., Mancher, Michelle, Busta, Emily R., Babiker, Abdel, Barrie, Mohamed Bailor, Cooper, Janice, Davis, Sheila, Edwards, Kathryn, Ellenberg, Susan, Lewis, Roger, London, Alex John, Jens Lundgren, Mello, Michelle M., Omotade, Olayemi, Peters, David H., Wabwire-Mangen, Fred, Wells, Charles D., Darbyshire, Janet, and Forstag, Erin Hammers

37. Integrating Clinical Research into Epidemic Response: The Ebola Experience Preface

Author

Keusch, Gerald T., Mcadam, Keith, Cuff, Patricia A., Mancher, Michelle, Busta, Emily R., Babiker, Abdel, Barrie, Mohamed Bailor, Cooper, Janice, Davis, Sheila, Edwards, Kathryn, Ellenberg, Susan, Lewis, Roger, London, Alex John, Jens Lundgren, Mello, Michelle M., Omotade, Olayemi, Peters, David H., Wabwire-Mangen, Fred, Wells, Charles D., Darbyshire, Janet, and Forstag, Erin Hammers

38. Strengthening Capacity for Response and Research

Author

Keusch, Gerald T., Mcadam, Keith, Cuff, Patricia A., Mancher, Michelle, Busta, Emily R., Babiker, Abdel, Barrie, Mohamed Bailor, Cooper, Janice, Davis, Sheila, Edwards, Kathryn, Ellenberg, Susan, Lewis, Roger, London, Alex John, Jens Lundgren, Mello, Michelle M., Omotade, Olayemi, Peters, David H., Wabwire-Mangen, Fred, Wells, Charles D., Darbyshire, Janet, and Forstag, Erin Hammers

39. Engaging Communities in Research and Response

Author

Keusch, Gerald T., Mcadam, Keith, Cuff, Patricia A., Mancher, Michelle, Busta, Emily R., Babiker, Abdel, Barrie, Mohamed Bailor, Cooper, Janice, Davis, Sheila, Edwards, Kathryn, Ellenberg, Susan, Lewis, Roger, London, Alex John, Jens Lundgren, Mello, Michelle M., Omotade, Olayemi, Peters, David H., Wabwire-Mangen, Fred, Wells, Charles D., Darbyshire, Janet, and Forstag, Erin Hammers

40. Conducting Clinical Research During an Epidemic

Author

Keusch, Gerald T., Mcadam, Keith, Cuff, Patricia A., Mancher, Michelle, Busta, Emily R., Babiker, Abdel, Barrie, Mohamed Bailor, Cooper, Janice, Davis, Sheila, Edwards, Kathryn, Ellenberg, Susan, Lewis, Roger, London, Alex John, Jens Lundgren, Mello, Michelle M., Omotade, Olayemi, Peters, David H., Wabwire-Mangen, Fred, Wells, Charles D., Darbyshire, Janet, and Forstag, Erin Hammers

41. Assessment of Vaccine Trials

Author

Keusch, Gerald T., Mcadam, Keith, Cuff, Patricia A., Mancher, Michelle, Busta, Emily R., Babiker, Abdel, Barrie, Mohamed Bailor, Cooper, Janice, Davis, Sheila, Edwards, Kathryn, Ellenberg, Susan, Lewis, Roger, London, Alex John, Jens Lundgren, Mello, Michelle M., Omotade, Olayemi, Peters, David H., Wabwire-Mangen, Fred, Wells, Charles D., Darbyshire, Janet, and Forstag, Erin Hammers

42. Assessment of Therapeutic Trials

Author

Keusch, Gerald T., Mcadam, Keith, Cuff, Patricia A., Mancher, Michelle, Busta, Emily R., Babiker, Abdel, Barrie, Mohamed Bailor, Cooper, Janice, Davis, Sheila, Edwards, Kathryn, Ellenberg, Susan, Lewis, Roger, London, Alex John, Jens Lundgren, Mello, Michelle M., Omotade, Olayemi, Peters, David H., Wabwire-Mangen, Fred, Wells, Charles D., Darbyshire, Janet, and Forstag, Erin Hammers

43. Integrating Clinical Research into Epidemic Response: The Ebola Experience Introduction

Author

Keusch, Gerald T., Mcadam, Keith, Cuff, Patricia A., Mancher, Michelle, Busta, Emily R., Babiker, Abdel, Barrie, Mohamed Bailor, Cooper, Janice, Davis, Sheila, Edwards, Kathryn, Ellenberg, Susan, Lewis, Roger, London, Alex John, Jens Lundgren, Mello, Michelle M., Omotade, Olayemi, Peters, David H., Wabwire-Mangen, Fred, Wells, Charles D., Darbyshire, Janet, and Forstag, Erin Hammers

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