This descriptive study was undertaken at a semi-urban tertiary care hospital in India from 1 February, 2018 to 31　July, 2018. The study was approved by the institutional ethics committee and informed consent from parents was taken prior to enrollment. Consecutive patients aged 1 month to 12 years, who visited the pediatric OPD and/or got admitted in the pediatric ward with a clinical diagnosis of pneumonia by the treating doctor, and which necessitated a chest radiograph to be taken, were enrolled for the study. Exclusion criteria were subjects with documented congenital heart disease, chronic respiratory illness, congenital lung problems, immunosuppressive conditions or known to have neuromuscular disorders with respiratory system involvement.

For calculation of sample size, prevalence of lower acute respiratory infection was taken as 28% [5]. At significance level of 5%, with 20% relative precision, and power of the study 80%, sample size was calculated as 240. To allow for potential recruitment failure rate, 285 children were assessed for eligibility for enrollment in the study.

A detailed history was taken and respiratory system examination done for all subjects, and RISC scoring for HIV non-infected children [1] was done by the principal investigator. Variables in the the RISC score represent known risk factors for severe outcomes of pneumonia in children, with a maximum score of 8 points.

CXR scoring was done by a single radiologist, as per the WHO interpretation of chest radiographs [2,4] .

A total of 285 children with physician-diagnosed pneumonia were assessed for eligibility to be enrolled in the study (Fig. 1). Out of these, 20 were excluded based on exclusion criteria and 18 were excluded as a CXR was not taken/available. A total of 241 children were finally included in the study.

Fig. 1 Study flow chart.

There are hardly any scoring systems which are validated for community-acquired pneumonia (CAP) in Indian children that would have high utility in resource-limited settings. We demonstrated a statistically signi-ficant correlation between RISC scoring system [1] and the WHO interpretation of chest radiographs [2].

Limitations of the study were that RISC score is not useful to differentiate between types of pneumonia based on etiology. RISC score is not useful to monitor resolution of symptoms. A negative score for wheeze (-2) may encourage false negatives. When developing detection tests, a balance must be chosen between risks of false negatives and false positives.

The major scoring systems designed to predict mortality risk and serve as guides for admission in community-acquired pneumonia (CAP) are for adults [6], and such scores for children are scarce [7,8]. Only the modified predisposition, insult, response and organ dysfunction (PIRO) score has so far been applied to children with CAP [6]. We used the RISC score for our study as it has six predictors for assessing the severity of pneumonia (hypoxia, chest indrawing, feed refusal, wheeze, malnutrition, age) and is easy to administer. Other risk models [9,10] are relatively cumbersome to administer.

The WHO introduced the Integrated Management of Childhood Illness (IMCI) to standardize and improve treatment and thus prevent major causes of death in children <5 years [10]. The first drawback of IMCI diagnostic criteria is of over-diagnosing pneumonia by including children with wheezing. In our study too, 36.5% of patients had a wheeze on presentation. However, the RISC scoring system overcomes this by giving a negative score for wheezing. The second drawback of IMCI is a missed diagnosis, as it has a low sensitivity [11,12].

Hooli, et al. [13] did an external validation of RISC by calculated classification performance measures at thresholds of 3 and 4. Using a RISC score of 3 had a sensitivity of 59% and specificity of 78%. With a score threshold of 4, the sensitivity was 32.6% and specificity was 93.1%. A median RISC score of 1 corresponded with a risk of mortality of 0% (95%CI: 0%-0.6%) in the study by Reed, et al. [1]. In our study, using a RISC score of >1 had a higher sensitivity and was a moderate screening test to predict pneumonia.

To conclude, we propose that RISC score may be used for diagnosing pneumonia in resource-constrained areas to supplement IMCI protocols. Assessment of a combination of the two in community-based studies may provide additional information on this aspect.

Ethics clearance: Amala Institute of Medical Sciences; No. AIMSIEC/05/2018 dated January 22, 2018.

Contributors: KP: concept and design of the study; ERS: analyzed and collected data; drafted the manuscript; TPL: analyzing data; VKP: supervised cognitive and behavioral assessments. All authors approved the final version of manuscript, and are accountable for all aspects related to the study.

Funding: None; Competing interest: None stated.

1. Reed C, Madhi SA, Klugman KP, et al. Development of the respiratory index of severity in children (RISC) score among young children with respiratory infections in South Africa. PLoS One. 2012;7:e27793.

2. Cherian T, Mulholland EK, Carlin JB, et al. Standardized interpretation of paediatric chest radiographs for the diagnosis of pneumonia in epidemiological studies. Bull WHO. 2005;83:353-9.

3. O’ Grady KA, Torzillo PJ, Ruben AR, et al. Identification of radiological alveolar pneumonia in children with high rates of hospitalized respiratory infections: comparison of WHO - defined and pediatric pulmonologist diagnosis in the clinical context. Pediatr Pulmonol. 2012;47:386-92.

4. Taylor E, Haven K, Reed P; SHIVERS Investigation Team. A chest radiograph scoring system in patients with severe acute respiratory infection: A validation study. BMC Med Imaging. 2015;15:61.

5. Prietsch Silvio OM, Fischer Gilberto B, César Juraci A, et al. Acute lower respiratory illness in under-five children in Rio Grande, Rio Grande do Sul State, Brazil: Prevalence and risk factors. Cad Saúde Pública.　 2008; 24:1429-438.

6. Uwaezuoke SN, Ayuk AC. Prognostic scores and bio-markers for pediatric community - acquired pneumonia: How far have we come? Pediatric Health Med Ther. 2017; 8:9-18.

7. Arbo A, Lovera D, Martínez – Cuellar C. Mortality predictive scores for community – acquired pneumonia in children. Curr Infect Dis Rep.　2019;21:10.

8. Moreno L, Krishnan JA, Duran P, Ferrero F. Development and validation of a clinical prediction rule to distinguish bacterial from viral pneumonia in children. Pediatr Pulmonol. 2006;41:331-7. Erratum in: Pediatr Pulmonol. 2006;41:494.

9. Williams DJ, Zhu Y, Grijalva CG, et al.　Predicting severe pneumonia outcomes in children. Pediatrics. 2016;138: e20161019.　

10. Emukule GO, McMorrow M, Ulloa C, et al. Predicting mortality among hospitalized children with respiratory illness in Western Kenya, 2009-2012. PLoS ONE. 2014; 9:e92968.

11. Deodari AK, Chellani H, Carlin JB, et al. Clinico-epidemiological profile and predictors of severe illness in young infants (<60 days) reporting to a hospital in North India. Indian Pediatr. 2007;44:739-48.

12. Uwemedimo OT, Lewis TP, Essien EA, et al. Distribution and determinants of pneumonia diagnosis using Integrated Management of Childhood Illness guidelines: A nationally representative study in Malawi. BMJ Glob Health. 2018;3:e000506.

13. Hooli S, Colbourn T, Lufesi N, et al. Predicting hospitalised paediatric pneumonia mortality risk: An external validation of risc and mrisc, and local tool development (RISCMalawi) from Malawi. PLoS One. 2016;11:e0168126.

14. Imilda I, Yani FF, Hariyanto D, Basir　D. Bacterial pneumonia score to identify bacterial pneumonia, Paediatr Indones. 2015;55:79-82.