Aetiology and severity of childhood pneumonia in primary care in Malawi: a cohort study

Abstract

ObjectiveTo determine the aetiology of community acquired pneumonia in children presenting to primary care in Northern Malawi, and to ascertain predictors for identification of children requiring hospitalisation.DesignThe BIOmarkers TO diagnose PnEumonia study was a prospective cohort study conducted from March to June 2016.SettingPrimary care in Northern Malawi.Patients494 children aged 2 –59 months with WHO defined pneumonia.Main outcome(s) and measure(s)Number of children with bacterial infection identified and the sensitivity/specificity of WHO markers of severity for need for hospitalisation.Results13 (2.6%) children had a bacterium consistent with pneumonia identified. A virus consistent with pneumonia was identified in in 448 (90.7%) of children. 56 children were admitted to hospital and two children died within 30 days. 442 (89.5%) received antibiotic therapy. Eleven children (2.6%) had HIV. WHO severity markers at baseline demonstrated poor sensitivity for the need for hospitalisation with a sensitivity of 0.303 (95% CI 0.188 to 0.441) and a specificity 0.9 (95% CI 0.868 to 0.926). A prediction rule to indicate the need for hospitalisation was developed.Conclusions and relevanceThe low rate of bacterial infection and high use of antibiotics in the setting of high immunisation rates highlights the changing profile of childhood pneumonia. Similarly, the markers of need for hospitalisation may have changed in the setting of extended immunisation. Further studies are required to examine this.

A systematic review of clinical prediction rules to predict hospitalisation in children with lower respiratory infection in primary care and their validation in a new cohort

“…However, even with this, there will also be a need to identify those at risk of severe disease so that they can be appropriately referred to hospital. The BIOTOPE study showed that WHO severity criteria were present in a minority (30.4%) of children hospitalised with pneumonia, consistent with recent work in the Lancet Global Health, showing that 39% of fatal cases of pneumonia were defined as having non-severe pneumonia, requiring only home treatment by the 2013 revision [11,17]. The fact that the WHO criteria would have discharged these children with oral antibiotics accentuates the need for new markers of severity, the STARWAVe rule may serve as a useful tool in this regard [13].…”

“…Validation of the STARWAVe rule was undertaken in the BIOTOPE cohort as described previously [11] . In brief, the BIOTOPE cohort consisted of 494 children with WHO clinically defined pneumonia presenting to primary care in Malawi.…”

“…Asthma was one of the predictor parameters associated with hospital admission and further work is required to determine the accuracy of this rule in a population of non-asthmatic patients. In BIOTOPE, no child was on medication for wheeze at home, nor had any child a previous diagnosis of asthma -this demonstrates the broad applicability of this rule in a non-asthmatic population also [11] The statistical model used to develop the checklist (STARWAVe) involved the inclusion of children who received antibiotics (37% of the study sample). This limits the value of the checklist as it is not representative of the risk of hospitalisation in those patients not receiving antibiotic therapy.…”

“…Rules were validated in the BIOTOPE cohort (BIOmarkers TO diagnose PnEumonia) which recruited children aged 2 months to 59 months with World Health Organisation defined pneumonia from two primary care facilities in Mzuzu, Northern Malawi [ 11 , 12 ]. The WHO algorithm indicates that all these children should have antibiotics.…”

426 A systematic review of clinical prediction rules to diagnose bacterial lower respiratory infection in children in primary care and their validation in a new cohort

“…6 The BIOTOPE cohort (BIOmarkers TO diagnose PnEumonia) recruited children aged 2-59 months with WHO defined pneumonia from two primary care facilities in Mzuzu, Malawi. 7 Validation of STARWAVe in BIOTOPE employed derivation and internal validation using bootstrapping.…”