Skip to main content
Top
Published in: BMC Medicine 1/2017

Open Access 01-12-2017 | Research article

An exploration of mortality risk factors in non-severe pneumonia in children using clinical data from Kenya

Authors: Timothy Tuti, Ambrose Agweyu, Paul Mwaniki, Niels Peek, Mike English, on behalf of the Clinical Information Network Author Group

Published in: BMC Medicine | Issue 1/2017

Login to get access

Abstract

Background

Childhood pneumonia is the leading infectious cause of mortality in children younger than 5 years old. Recent updates to World Health Organization pneumonia guidelines recommend outpatient care for a population of children previously classified as high risk. This revision has been challenged by policymakers in Africa, where mortality related to pneumonia is higher than in other regions and often complicated by comorbidities.
This study aimed to identify factors that best discriminate inpatient mortality risk in non-severe pneumonia and explore whether these factors offer any added benefit over the current criteria used to identify children with pneumonia requiring inpatient care.

Methods

We undertook a retrospective cohort study of children aged 2–59 months admitted with a clinical diagnosis of pneumonia at 14 public hospitals in Kenya between February 2014 and February 2016. Using machine learning techniques, we analysed whether clinical characteristics and common comorbidities increased the risk of inpatient mortality for non-severe pneumonia. The topmost risk factors were subjected to decision curve analysis to explore if using them as admission criteria had any net benefit above the current criteria.

Results

Out of 16,162 children admitted with pneumonia during the study period, 10,687 were eligible for subsequent analysis. Inpatient mortality within this non-severe group was 252/10,687 (2.36%). Models demonstrated moderately good performance; the partial least squares discriminant analysis model had higher sensitivity for predicting mortality in comparison to logistic regression.
Elevated respiratory rate (≥70 bpm), age 2–11 months and weight-for-age Z-score (WAZ) < –3SD were highly discriminative of mortality. These factors ranked consistently across the different models. For a risk threshold probability of 7–14%, there is a net benefit to admitting the patient sub-populations with these features as additional criteria alongside those currently used to classify severe pneumonia. Of the population studied, 70.54% met at least one of these criteria. Sensitivity analyses indicated that the overall results were not significantly affected by variations in pneumonia severity classification criteria.

Conclusions

Children with non-severe pneumonia aged 2–11 months or with respiratory rate ≥ 70 bpm or very low WAZ experience risks of inpatient mortality comparable to severe pneumonia. Inpatient care is warranted in these high-risk groups of children.
Appendix
Available only for authorised users
Literature
1.
go back to reference Liu L, et al. Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the Sustainable Development Goals. Lancet. 2017;388(10063):3027–35.CrossRef Liu L, et al. Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the Sustainable Development Goals. Lancet. 2017;388(10063):3027–35.CrossRef
4.
go back to reference Programme of Acute Respiratory Infections. Progress and current status of the ARI Programme at global level (1983 - 1984). Geneva: World Health Organization; 1985. Programme of Acute Respiratory Infections. Progress and current status of the ARI Programme at global level (1983 - 1984). Geneva: World Health Organization; 1985.
5.
go back to reference World Health Organization. Revised WHO classification and treatment of childhood pneumonia at health facilities. Geneva: World Health Organization; 2014. p. 6–14. World Health Organization. Revised WHO classification and treatment of childhood pneumonia at health facilities. Geneva: World Health Organization; 2014. p. 6–14.
6.
go back to reference Qazi SA, Fox MP, Thea DM. Editorial commentary: ambulatory management of chest-indrawing pneumonia. Clin Infect Dis. 2015;60(8):1225–7.CrossRefPubMed Qazi SA, Fox MP, Thea DM. Editorial commentary: ambulatory management of chest-indrawing pneumonia. Clin Infect Dis. 2015;60(8):1225–7.CrossRefPubMed
7.
go back to reference Agweyu A, Opiyo N, English M. Experience developing national evidence based clinical guidelines for childhood pneumonia in a low-income setting — making the GRADE? BMC Pediatr. 2012;12(1):1.CrossRefPubMedPubMedCentral Agweyu A, Opiyo N, English M. Experience developing national evidence based clinical guidelines for childhood pneumonia in a low-income setting — making the GRADE? BMC Pediatr. 2012;12(1):1.CrossRefPubMedPubMedCentral
8.
go back to reference Ayieko P, et al. Characteristics of admissions and variations in the use of basic investigations, treatments and outcomes in Kenyan hospitals within a new Clinical Information Network. Archives of disease in childhood. 2015. doi:10.1136/archdischild-2015-309269. Ayieko P, et al. Characteristics of admissions and variations in the use of basic investigations, treatments and outcomes in Kenyan hospitals within a new Clinical Information Network. Archives of disease in childhood. 2015. doi:10.​1136/​archdischild-2015-309269.
9.
go back to reference Enarson PM, et al. Potentially modifiable factors associated with death of infants and children with severe pneumonia routinely managed in district hospitals in Malawi. PLoS One. 2015;10(8):e0133365.CrossRefPubMedPubMedCentral Enarson PM, et al. Potentially modifiable factors associated with death of infants and children with severe pneumonia routinely managed in district hospitals in Malawi. PLoS One. 2015;10(8):e0133365.CrossRefPubMedPubMedCentral
10.
go back to reference Von Elm E, et al. The Strengthening the Reporting of Observational Studies in Epidemiology [STROBE] statement: guidelines for reporting observational studies. Gac Sanit. 2008;22(2):144–50.CrossRef Von Elm E, et al. The Strengthening the Reporting of Observational Studies in Epidemiology [STROBE] statement: guidelines for reporting observational studies. Gac Sanit. 2008;22(2):144–50.CrossRef
11.
go back to reference Tuti T, et al. Improving documentation of clinical care within a clinical information network: an essential initial step in efforts to understand and improve care in Kenyan hospitals. BMJ Global Health. 2016;1(1):e000028.CrossRefPubMedPubMedCentral Tuti T, et al. Improving documentation of clinical care within a clinical information network: an essential initial step in efforts to understand and improve care in Kenyan hospitals. BMJ Global Health. 2016;1(1):e000028.CrossRefPubMedPubMedCentral
12.
go back to reference Harris PA, et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.CrossRefPubMed Harris PA, et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.CrossRefPubMed
13.
go back to reference R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2016. R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2016.
14.
go back to reference World Health Organization. Management of the child with a serious infection or severe malnutrition: guidelines for care at the first-referral level in developing countries. Geneva: World Health Organization; 2000. World Health Organization. Management of the child with a serious infection or severe malnutrition: guidelines for care at the first-referral level in developing countries. Geneva: World Health Organization; 2000.
15.
go back to reference World Health Organization. Pocket book of hospital care for children: guidelines for the management of common childhood illnesses with limited resources. 2nd ed. Geneva: World Health Organization; 2013. World Health Organization. Pocket book of hospital care for children: guidelines for the management of common childhood illnesses with limited resources. 2nd ed. Geneva: World Health Organization; 2013.
17.
go back to reference Kuhn M. Building predictive models in R using the caret package. J Statistical Software. 2008;28(5):1–26.CrossRef Kuhn M. Building predictive models in R using the caret package. J Statistical Software. 2008;28(5):1–26.CrossRef
18.
go back to reference Guyon I, Elisseeff A. An introduction to variable and feature selection. J Mach Learn Res. 2003;3(Mar):1157–82. Guyon I, Elisseeff A. An introduction to variable and feature selection. J Mach Learn Res. 2003;3(Mar):1157–82.
20.
go back to reference Vickers AJ, Van Calster B, Steyerberg EW. Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests. BMJ. 2016;352:i6.CrossRefPubMedPubMedCentral Vickers AJ, Van Calster B, Steyerberg EW. Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests. BMJ. 2016;352:i6.CrossRefPubMedPubMedCentral
21.
go back to reference Saeys Y, Inza I, Larrañaga P. A review of feature selection techniques in bioinformatics. Bioinformatics. 2007;23(19):2507–17.CrossRefPubMed Saeys Y, Inza I, Larrañaga P. A review of feature selection techniques in bioinformatics. Bioinformatics. 2007;23(19):2507–17.CrossRefPubMed
22.
go back to reference Barker M, Rayens W. Partial least squares for discrimination. J Chemom. 2003;17(3):166–73.CrossRef Barker M, Rayens W. Partial least squares for discrimination. J Chemom. 2003;17(3):166–73.CrossRef
24.
go back to reference Cortes C, Vapnik V. Support-vector networks. Mach Learn. 1995;20(3):273–97. Cortes C, Vapnik V. Support-vector networks. Mach Learn. 1995;20(3):273–97.
25.
go back to reference Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Stat Soc Ser B (Stat Methodol). 2005;67(2):301–20.CrossRef Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Stat Soc Ser B (Stat Methodol). 2005;67(2):301–20.CrossRef
27.
go back to reference Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Mak. 2006;26(6):565–74.CrossRef Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Mak. 2006;26(6):565–74.CrossRef
28.
go back to reference Chawla NV. Data mining for imbalanced datasets: an overview. In: Maimon O, Rokach L, editors. Data mining and knowledge discovery handbook. New York: Springer; 2005. p. 853–67.CrossRef Chawla NV. Data mining for imbalanced datasets: an overview. In: Maimon O, Rokach L, editors. Data mining and knowledge discovery handbook. New York: Springer; 2005. p. 853–67.CrossRef
29.
go back to reference Chawla NV, et al. SMOTE: synthetic minority over-sampling technique. J Artif Intell Res. 2002;16:321–57. Chawla NV, et al. SMOTE: synthetic minority over-sampling technique. J Artif Intell Res. 2002;16:321–57.
31.
go back to reference Fawcett T. An introduction to ROC analysis. Pattern Recogn Lett. 2006;27(8):861–74.CrossRef Fawcett T. An introduction to ROC analysis. Pattern Recogn Lett. 2006;27(8):861–74.CrossRef
32.
go back to reference DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837–45.CrossRefPubMed DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837–45.CrossRefPubMed
33.
go back to reference Agweyu A, et al. Prevalence and correlates of treatment failure among Kenyan children hospitalised with severe community‐acquired pneumonia: a prospective study of the clinical effectiveness of WHO pneumonia case management guidelines. Tropical Med Int Health. 2014;19(11):1310–20.CrossRef Agweyu A, et al. Prevalence and correlates of treatment failure among Kenyan children hospitalised with severe community‐acquired pneumonia: a prospective study of the clinical effectiveness of WHO pneumonia case management guidelines. Tropical Med Int Health. 2014;19(11):1310–20.CrossRef
34.
go back to reference English M, et al. Assessment of inpatient paediatric care in first referral level hospitals in 13 districts in Kenya. Lancet. 2004;363(9425):1948–53.CrossRefPubMed English M, et al. Assessment of inpatient paediatric care in first referral level hospitals in 13 districts in Kenya. Lancet. 2004;363(9425):1948–53.CrossRefPubMed
35.
go back to reference Druetz T, et al. The community case management of pneumonia in Africa: a review of the evidence. Health Policy Plan. 2015;30(2):253–66.CrossRefPubMed Druetz T, et al. The community case management of pneumonia in Africa: a review of the evidence. Health Policy Plan. 2015;30(2):253–66.CrossRefPubMed
36.
go back to reference Scott JAG, et al. The definition of pneumonia, the assessment of severity, and clinical standardization in the Pneumonia Etiology Research for Child Health study. Clin Infect Dis. 2012;54 suppl 2:S109–16.CrossRefPubMedPubMedCentral Scott JAG, et al. The definition of pneumonia, the assessment of severity, and clinical standardization in the Pneumonia Etiology Research for Child Health study. Clin Infect Dis. 2012;54 suppl 2:S109–16.CrossRefPubMedPubMedCentral
37.
go back to reference Ling, CX, Huang J, Zhang H. AUC: a statistically consistent and more discriminating measure than accuracy. In: Proceedings of IJCAI. 2003. p. 519–24. Ling, CX, Huang J, Zhang H. AUC: a statistically consistent and more discriminating measure than accuracy. In: Proceedings of IJCAI. 2003. p. 519–24.
38.
go back to reference Onyango D, et al. Risk factors of severe pneumonia among children aged 2-59 months in western Kenya: a case control study. Pan African Medical J. 2012;13(1):45. Onyango D, et al. Risk factors of severe pneumonia among children aged 2-59 months in western Kenya: a case control study. Pan African Medical J. 2012;13(1):45.
39.
go back to reference Black RE, et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet. 2013;382(9890):427–51.CrossRefPubMed Black RE, et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet. 2013;382(9890):427–51.CrossRefPubMed
40.
go back to reference English M, et al. Deep breathing in children with severe malaria: indicator of metabolic acidosis and poor outcome. Am J Trop Med Hyg. 1996;55(5):521–4.CrossRefPubMed English M, et al. Deep breathing in children with severe malaria: indicator of metabolic acidosis and poor outcome. Am J Trop Med Hyg. 1996;55(5):521–4.CrossRefPubMed
41.
go back to reference Chisti MJ, et al. Clinical predictors and outcome of metabolic acidosis in under-five children admitted to an urban hospital in Bangladesh with diarrhea and pneumonia. PLoS One. 2012;7(6):e39164.CrossRefPubMedPubMedCentral Chisti MJ, et al. Clinical predictors and outcome of metabolic acidosis in under-five children admitted to an urban hospital in Bangladesh with diarrhea and pneumonia. PLoS One. 2012;7(6):e39164.CrossRefPubMedPubMedCentral
42.
go back to reference Chisti MJ, et al. Pneumonia in severely malnourished children in developing countries — mortality risk, aetiology and validity of WHO clinical signs: a systematic review. Trop Med Int Health. 2009;14(10):1173–89.CrossRefPubMed Chisti MJ, et al. Pneumonia in severely malnourished children in developing countries — mortality risk, aetiology and validity of WHO clinical signs: a systematic review. Trop Med Int Health. 2009;14(10):1173–89.CrossRefPubMed
43.
go back to reference da Fonseca Lima EJ, et al. Risk factors for community-acquired pneumonia in children under five years of age in the post-pneumococcal conjugate vaccine era in Brazil: a case control study. BMC Pediatr. 2016;16(1):157.CrossRefPubMedPubMedCentral da Fonseca Lima EJ, et al. Risk factors for community-acquired pneumonia in children under five years of age in the post-pneumococcal conjugate vaccine era in Brazil: a case control study. BMC Pediatr. 2016;16(1):157.CrossRefPubMedPubMedCentral
44.
go back to reference Wonodi CB, et al. Evaluation of risk factors for severe pneumonia in children: the Pneumonia Etiology Research for Child Health study. Clin Infect Dis. 2012;54(suppl 2):S124–31.CrossRefPubMedPubMedCentral Wonodi CB, et al. Evaluation of risk factors for severe pneumonia in children: the Pneumonia Etiology Research for Child Health study. Clin Infect Dis. 2012;54(suppl 2):S124–31.CrossRefPubMedPubMedCentral
45.
go back to reference Caruana, R, et al. Intelligible models for healthcare: predicting pneumonia risk and hospital 30-day readmission. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Sydney, Australia. 2015. Association for Computing Machinery. Caruana, R, et al. Intelligible models for healthcare: predicting pneumonia risk and hospital 30-day readmission. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Sydney, Australia. 2015. Association for Computing Machinery.
46.
47.
go back to reference Pillonetto G, et al. Kernel methods in system identification, machine learning and function estimation: a survey. Automatica. 2014;50(3):657–82.CrossRef Pillonetto G, et al. Kernel methods in system identification, machine learning and function estimation: a survey. Automatica. 2014;50(3):657–82.CrossRef
48.
go back to reference World Health Organization. Dept. of Child and Adolescent Health and Development, Pocket book of hospital care for children: guidelines for the management of common illnesses with limited resources. 2nd ed. Geneva: World Health Organization; 2013. p. 378. World Health Organization. Dept. of Child and Adolescent Health and Development, Pocket book of hospital care for children: guidelines for the management of common illnesses with limited resources. 2nd ed. Geneva: World Health Organization; 2013. p. 378.
49.
go back to reference Mtove G, et al. Effect of context on respiratory rate measurement in identifying non‐severe pneumonia in African children. Tropical Med Int Health. 2015;20(6):757–65.CrossRef Mtove G, et al. Effect of context on respiratory rate measurement in identifying non‐severe pneumonia in African children. Tropical Med Int Health. 2015;20(6):757–65.CrossRef
51.
go back to reference Bassat Q, et al. Distinguishing malaria from severe pneumonia among hospitalized children who fulfilled integrated management of childhood illness criteria for both diseases: a hospital-based study in Mozambique. Am J Trop Med Hyg. 2011;85(4):626–34.CrossRefPubMedPubMedCentral Bassat Q, et al. Distinguishing malaria from severe pneumonia among hospitalized children who fulfilled integrated management of childhood illness criteria for both diseases: a hospital-based study in Mozambique. Am J Trop Med Hyg. 2011;85(4):626–34.CrossRefPubMedPubMedCentral
52.
go back to reference English M, et al. Clinical overlap between malaria and severe pneumonia in African children in hospital. Trans R Soc Trop Med Hyg. 1996;90(6):658–62.CrossRefPubMed English M, et al. Clinical overlap between malaria and severe pneumonia in African children in hospital. Trans R Soc Trop Med Hyg. 1996;90(6):658–62.CrossRefPubMed
53.
go back to reference Agweyu A, et al. Oral amoxicillin versus benzyl penicillin for severe pneumonia among Kenyan children: a pragmatic randomized controlled noninferiority trial. Clin Infect Dis. 2015;60(8):1216–24.CrossRefPubMed Agweyu A, et al. Oral amoxicillin versus benzyl penicillin for severe pneumonia among Kenyan children: a pragmatic randomized controlled noninferiority trial. Clin Infect Dis. 2015;60(8):1216–24.CrossRefPubMed
54.
go back to reference Acácio S, et al. Under treatment of pneumonia among children under 5 years of age in a malaria-endemic area: population-based surveillance study conducted in Manhica district-rural, Mozambique. Int J Infect Dis. 2015;36:39–45.CrossRefPubMed Acácio S, et al. Under treatment of pneumonia among children under 5 years of age in a malaria-endemic area: population-based surveillance study conducted in Manhica district-rural, Mozambique. Int J Infect Dis. 2015;36:39–45.CrossRefPubMed
55.
go back to reference Mulholland K, et al. The challenges of trials of antibiotics for pneumonia in low-income countries. Lancet Respir Med. 2014;2(12):952–4.CrossRefPubMed Mulholland K, et al. The challenges of trials of antibiotics for pneumonia in low-income countries. Lancet Respir Med. 2014;2(12):952–4.CrossRefPubMed
56.
go back to reference Sonego M, et al. Risk factors for mortality from acute lower respiratory infections (ALRI) in children under five years of age in low and middle-income countries: a systematic review and meta-analysis of observational studies. PLoS One. 2015;10(1):e0116380.CrossRefPubMedPubMedCentral Sonego M, et al. Risk factors for mortality from acute lower respiratory infections (ALRI) in children under five years of age in low and middle-income countries: a systematic review and meta-analysis of observational studies. PLoS One. 2015;10(1):e0116380.CrossRefPubMedPubMedCentral
57.
go back to reference Simon AK, Hollander GA, McMichael A. Evolution of the immune system in humans from infancy to old age. In: Proc R Soc B. 2015;282:20143085. Simon AK, Hollander GA, McMichael A. Evolution of the immune system in humans from infancy to old age. In: Proc R Soc B. 2015;282:20143085.
58.
go back to reference Najnin N, Bennett CM, Luby SP. Inequalities in care-seeking for febrile illness of under-five children in urban Dhaka, Bangladesh. J Health Popul Nutr. 2011;29(5):523.CrossRefPubMedPubMedCentral Najnin N, Bennett CM, Luby SP. Inequalities in care-seeking for febrile illness of under-five children in urban Dhaka, Bangladesh. J Health Popul Nutr. 2011;29(5):523.CrossRefPubMedPubMedCentral
59.
go back to reference Willis JR, et al. Gender differences in perception and care-seeking for illness of newborns in rural Uttar Pradesh, India. J Health Popul Nutr. 2009;27:62–71.CrossRefPubMedPubMedCentral Willis JR, et al. Gender differences in perception and care-seeking for illness of newborns in rural Uttar Pradesh, India. J Health Popul Nutr. 2009;27:62–71.CrossRefPubMedPubMedCentral
60.
go back to reference World Health Organization. Guideline: Updates on the management of severe acute malnutrition in infants and children. Geneva: World Health Organization; 2013. p. 55–9. World Health Organization. Guideline: Updates on the management of severe acute malnutrition in infants and children. Geneva: World Health Organization; 2013. p. 55–9.
61.
go back to reference Ampofo K, et al. Seasonal invasive pneumococcal disease in children: role of preceding respiratory viral infection. Pediatrics. 2008;122(2):229–37.CrossRefPubMed Ampofo K, et al. Seasonal invasive pneumococcal disease in children: role of preceding respiratory viral infection. Pediatrics. 2008;122(2):229–37.CrossRefPubMed
Metadata
Title
An exploration of mortality risk factors in non-severe pneumonia in children using clinical data from Kenya
Authors
Timothy Tuti
Ambrose Agweyu
Paul Mwaniki
Niels Peek
Mike English
on behalf of the Clinical Information Network Author Group
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Medicine / Issue 1/2017
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/s12916-017-0963-9

Other articles of this Issue 1/2017

BMC Medicine 1/2017 Go to the issue