External validation of the RISC, RISC-Malawi, and PERCH clinical prediction rules to identify risk of death in children hospitalized with pneumonia

Rees, Chris A.; Hooli, Shubhada; King, Carina; McCollum, Eric D.; Colbourn, Tim; Lufesi, Norman; Mwansambo, Charles; Lazzerini, Marzia; Madhi, Shabir А.; Cutland, Clare; Nunes, Marta C; Gessner, Bradford D.; Basnet, Sudha; Kartasasmita, Cissy B.; Mathew, Joseph L; Zaman, Syed; Paranhos-Baccalà, Gláucia; Bhatnagar, Shinjini; Wadhwa, Nitya; Lodha, Rakesh; Aneja, Satinder; Santosham, Mathuram; Picot, Valentina; Sylla, Mariam; Awasthi, Sanjay; Bavdekar, Ashish; Pape, Jean-William; Rouzier, Vanessa; Chou, Monidarin; Rakoto-Andrianarivelo, Mala; Wang, Jianwei; Nymadawa, Pagbajabyn; Vanhems, Philippe; Russomando, Graciela; Asghar, Rai Muhammad; Banajeh, Salem; Iqbal, Imran; MacLeod, W. Bentley; Maulén-Radován, Irene; Miño, G; Saha, Samir K.; Singhi, Sunit; Thea, Donald M; Clara, Alexey; Campbell, Harry; Nair, Harish; Falconer, Jennifer; Williams, Linda; Horne, Margaret; Strand, Tor A.; Qazi, Shamim; Nisar, Yasir Bin; Neuman, Mark I.

doi:10.7189/jogh.11.04062

Cited by 13 publications

(19 citation statements)

References 42 publications

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“…Therefore, children with pneumonia of the same age as 2 years old who have a respiratory rate of 50 breaths per minute and 70 breaths per minute have the same prognosis, according to the revised WHO classification. Our finding indicates that an increase in respiratory rate contributes to the severity of pneumonia, and this finding has been replicated elsewhere [17,19,20,22,33]. For instance, Agweyu et al [18] find that a respiratory rate of 70 breaths per minute or more is independently associated with death.…”

Section: Discussionsupporting

confidence: 82%

“…In one study, an axillary temperature of ≥ 39 °C has an adjusted risk ratio of 1.9 for mortality in pediatric pneumonia [18]. Furthermore, the duration of illness, including fever, has been found as a factor that is associated with an adverse outcome in childhood pneumonia [19,20]. A study from Bangladesh finds that symptoms that last more than 3 days increase the risk of adverse outcomes in pediatric CAP [21].…”

Section: Discussionmentioning

confidence: 99%

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Factors associated with severe childhood community-acquired pneumonia: a retrospective study from two hospitals

Muljono

Halim

Heriyanto

et al. 2022

Egypt Pediatric Association Gaz

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Background Community-acquired pneumonia (CAP) is the leading cause of death in children globally. Indonesia is ranked 1st in South East Asia with the highest burden of pneumonia. Identification of risk factors is necessary for early intervention and better management. This study intended to describe CAP’s clinical signs and laboratory findings and explore the risk factors of severe CAP among children in Indonesia. Methods This was a retrospective study of childhood hospitalizations in Siloam General Hospitals and Siloam Hospitals Lippo Village from December 2015 to December 2019. Demographic data, clinical signs, and laboratory findings were collected and processed using IBM SPSS 26.0. Results This study included 217 participants with 66 (30.4%) severe pneumonia cases. Multivariate analysis shows that fever that lasts more than 7 days (ORadj = 4.95; 95%CI 1.61–15.21, Padj = 0.005) and increase in respiratory rate (ORadj = 1.05, 95%CI 1.01–1.08, Padj = 0.009) are two predictors of severe pneumonia. Meanwhile, a normal hematocrit level (ORadj = 0.9; 95%CI 0.83–0.98, Padj = 0.011) and children with normal BMI (ORadj = 0.7; 95%CI 0.57–0.84, Padj < 0.001) are significant independent predictors of severe pneumonia. The Hosmer-Lemeshow test shows that this model is a good fit with a P-value of 0.281. The AUC for this model is 0.819 (95%CI = 0.746–0.891, P-value < 0.001) which shows that this model has good discrimination. Conclusion Pediatric CAP hospitalizations with fever lasting > 7 days and tachypnea were at higher risk for progressing to severe pneumonia. A normal hematocrit level and a normal BMI are protective factors for severe pneumonia.

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Section: Discussionsupporting

confidence: 82%

Section: Discussionmentioning

confidence: 99%

Factors associated with severe childhood community-acquired pneumonia: a retrospective study from two hospitals

Muljono

Halim

Heriyanto

et al. 2022

Egypt Pediatric Association Gaz

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“…Prior clinical prediction models developed in single countries (ie, RISC, mRISC and RISC-Malawi) have demonstrated AUC from 0.80 to 0.92 when internally validated,4–6 while the PERCH score, derived from five countries in sub-Saharan Africa as well as Thailand and Bangladesh, had an AUC of 0.76 on internal validation 7. However, when externally applied to patients in various settings, only the RISC-Malawi score had fair discriminatory ability 9. The PREPARE risk assessment tool transcends region-specific issues, such as differing epidemiology of causative viruses or bacteria and variations in availability of measures such as chest radiography, supplemental oxygen, antibiotic availability and unmeasured variables that can contribute to morbidity, given its derivation and validation from a widely representative patient population.…”

Section: Discussionmentioning

confidence: 99%

“… 7 However, when externally applied to patients in various settings, only the RISC-Malawi score had fair discriminatory ability. 9 The PREPARE risk assessment tool transcends region-specific issues, such as differing epidemiology of causative viruses or bacteria and variations in availability of measures such as chest radiography, supplemental oxygen, antibiotic availability and unmeasured variables that can contribute to morbidity, given its derivation and validation from a widely representative patient population. However, the PREPARE risk assessment tool must be externally validated prior to implementation.…”

Section: Discussionmentioning

confidence: 99%

“…We recently validated three of these risk assessment tools in a large, globally representative dataset using the demographic and clinical features of children at the time of admission. 9 In that external validation, only the Respiratory Index of Severity in Children–Malawi (RISC-Malawi) score demonstrated fair discriminatory value (area under the curve (AUC) 0.75, 95% CI 0.74 to 0.77), while the Respiratory Index of Severity in Children (RISC) score and a modified Pneumonia Etiology Research for Child Health (PERCH) score had limited discriminatory value in identifying hospitalised children at risk of pneumonia-related mortality (AUC 0.66, 95% CI 0.58 to 0.73%, and AUC 0.55, 95% CI 0.37 to 0.73, respectively). The suboptimal performance of these prediction rules when applied externally raises questions on whether a novel tool incorporating different combinations of widely available clinical indicators could perform better across broad settings.…”

Section: Introductionmentioning

confidence: 99%

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Derivation and validation of a novel risk assessment tool to identify children aged 2–59 months at risk of hospitalised pneumonia-related mortality in 20 countries

et al. 2022

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IntroductionExisting risk assessment tools to identify children at risk of hospitalised pneumonia-related mortality have shown suboptimal discriminatory value during external validation. Our objective was to derive and validate a novel risk assessment tool to identify children aged 2–59 months at risk of hospitalised pneumonia-related mortality across various settings.MethodsWe used primary, baseline, patient-level data from 11 studies, including children evaluated for pneumonia in 20 low-income and middle-income countries. Patients with complete data were included in a logistic regression model to assess the association of candidate variables with the outcome hospitalised pneumonia-related mortality. Adjusted log coefficients were calculated for each candidate variable and assigned weighted points to derive the Pneumonia Research Partnership to Assess WHO Recommendations (PREPARE) risk assessment tool. We used bootstrapped selection with 200 repetitions to internally validate the PREPARE risk assessment tool.ResultsA total of 27 388 children were included in the analysis (mean age 14.0 months, pneumonia-related case fatality ratio 3.1%). The PREPARE risk assessment tool included patient age, sex, weight-for-age z-score, body temperature, respiratory rate, unconsciousness or decreased level of consciousness, convulsions, cyanosis and hypoxaemia at baseline. The PREPARE risk assessment tool had good discriminatory value when internally validated (area under the curve 0.83, 95% CI 0.81 to 0.84).ConclusionsThe PREPARE risk assessment tool had good discriminatory ability for identifying children at risk of hospitalised pneumonia-related mortality in a large, geographically diverse dataset. After external validation, this tool may be implemented in various settings to identify children at risk of hospitalised pneumonia-related mortality.

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Pediatric prognostic models predicting inhospital child mortality in resource‐limited settings: An external validation study

Ogero,

Ndiritu,

Sarguta

et al. 2023

Health Science Reports

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Background and AimsPrognostic models provide evidence‐based predictions and estimates of future outcomes, facilitating decision‐making, patient care, and research. A few of these models have been externally validated, leading to uncertain reliability and generalizability. This study aims to externally validate four models to assess their transferability and usefulness in clinical practice. The models include the respiratory index of severity in children (RISC)‐Malawi model and three other models by Lowlavaar et al.MethodsThe study used data from the Clinical Information Network (CIN) to validate the four models where the primary outcome was in‐hospital mortality. 163,329 patients met eligibility criteria. Missing data were imputed, and the logistic function was used to compute predicted risk of in‐hospital mortality. Models' discriminatory ability and calibration were determined using area under the curve (AUC), calibration slope, and intercept.ResultsThe RISC‐Malawi model had 50,669 pneumonia patients who met the eligibility criteria, of which the case‐fatality ratio was 4406 (8.7%). Its AUC was 0.77 (95% CI: 0.77−0.78), whereas the calibration slope was 1.04 (95% CI: 1.00 −1.06), and calibration intercept was 0.81 (95% CI: 0.77−0.84). Regarding the external validation of Lowlavaar et al. models, 10,782 eligible patients were included, with an in‐hospital mortality rate of 5.3%. The primary model's AUC was 0.75 (95% CI: 0.72−0.77), the calibration slope was 0.78 (95% CI: 0.71−0.84), and the calibration intercept was 0.37 (95% CI: 0.28−0.46). All models markedly underestimated the risk of mortality.ConclusionAll externally validated models exhibited either underestimation or overestimation of the risk as judged from calibration statistics. Hence, applying these models with confidence in settings other than their original development context may not be advisable. Our findings strongly suggest the need for recalibrating these model to enhance their generalizability.

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External validation of the RISC, RISC-Malawi, and PERCH clinical prediction rules to identify risk of death in children hospitalized with pneumonia

Cited by 13 publications

References 42 publications

Factors associated with severe childhood community-acquired pneumonia: a retrospective study from two hospitals

Factors associated with severe childhood community-acquired pneumonia: a retrospective study from two hospitals

Derivation and validation of a novel risk assessment tool to identify children aged 2–59 months at risk of hospitalised pneumonia-related mortality in 20 countries

Pediatric prognostic models predicting inhospital child mortality in resource‐limited settings: An external validation study

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