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

Introduction

Existing 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.

Methods

We 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.

Results

A 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).

Conclusions

The 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.

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

BACKGROUND

Existing scores to identify children at risk of hospitalized pneumonia-related mortality lack broad external validation. Our objective was to externally validate three such risk scores.

METHODS

We applied the Respiratory Index of Severity in Children (RISC) for HIV-negative children, the RISC-Malawi, and the Pneumonia Etiology Research for Child Health (PERCH) scores to hospitalized children in the Pneumonia REsearch Partnerships to Assess WHO REcommendations (PREPARE) data set. The PREPARE data set includes pooled data from 41 studies on pediatric pneumonia from across the world. We calculated test characteristics and the area under the curve (AUC) for each of these clinical prediction rules.

RESULTS

The RISC score for HIV-negative children was applied to 3574 children 0-24 months and demonstrated poor discriminatory ability (AUC = 0.66, 95% confidence interval (CI) = 0.58-0.73) in the identification of children at risk of hospitalized pneumonia-related mortality. The RISC-Malawi score had fair discriminatory value (AUC = 0.75, 95% CI = 0.74-0.77) among 17 864 children 2-59 months. The PERCH score was applied to 732 children 1-59 months and also demonstrated poor discriminatory value (AUC = 0.55, 95% CI = 0.37-0.73).

CONCLUSIONS

In a large external application of the RISC, RISC-Malawi, and PERCH scores, a substantial number of children were misclassified for their risk of hospitalized pneumonia-related mortality. Although pneumonia risk scores have performed well among the cohorts in which they were derived, their performance diminished when externally applied. A generalizable risk assessment tool with higher sensitivity and specificity to identify children at risk of hospitalized pneumonia-related mortality may be needed. Such a generalizable risk assessment tool would need context-specific validation prior to implementation in that setting.

Global Influenza Hospital-based Surveillance Network (GIHSN): results of surveillance of influenza and other respiratory viruses in hospitalised patients in Brazil, 2015

BACKGROUND

Influenza-like illness occurs annually worldwide, with peak timing and severity varying seasonally, resulting in significant annual mortality.

OBJECTIVES

There were three objectives: (1) to describe the epidemiological and clinical features of hospitalised patients with severe acute respiratory infection caused by influenza and other respiratory viruses (ORVs); (2) to report the influenza seasonality in the region and (3) to correlate findings of influenza circulation and immunisation time in Brazil.

PATIENTS/METHODS

This study took place in three Brazilian hospitals located in cities with different climatic conditions (Curitiba (south), Rio de Janeiro (south-east) and Fortaleza (north-east)). Patients presenting with an acute process with indication for admission consisting of a predefined set of conditions potentially associated with recent influenza infection were enrolled.

RESULTS

We screened 1666 patients, with 595 meeting the inclusion criteria. Influenza viruses and ORVs were detected in 6.5% and 59% of patients, respectively. Influenza-positive cases fell into the severe spectrum as compared with those with ORVs (30% vs 11%), but without any difference in mortality rates. Epidemiological results revealed variations in the peak time of influenza infections between north-east (Fortaleza) and south (Curitiba) Brazil, basically following the rain period of each region. In north-east Brazil, viral circulation was prevalent in the first 4 months of the year, indicating that the vaccination campaign occurred in a postseasonal period, possibly explaining the low effectiveness.

CONCLUSIONS

The active-surveillance model is a valuable tool for investigating respiratory virus impact on hospitalised patients, with influenza-infection monitoring enabling implementation of adequate preventive measures.

Direct injection/h.p.l.c. methods for the analysis of drugs in biological samples

1. Direct injection h.p.l.c. methods for zaprinast, and pantoprazole and its sulphone metabolite were developed. 2. Optimal recovery of pantoprazole and its sulphone metabolite was effected by the absence of transfer losses and the effective adjustment of sample pH on-line. 3. Acetonitrile reduced the recovery of pantoprazole and its sulphone metabolite at acetonitrile concentrations greater than 5% in serum. 4. Direct injection h.p.l.c. methods minimize sample handling losses, reduce human contact with biological samples and are sufficiently accurate and reproducible to be used to support pharmacodynamic and toxicokinetic studies.

Determination of temelastine and a hydroxymethyl-pyridyl metabolite in biological fluid by high-performance liquid chromatography

A high-performance liquid chromatographic method for the analysis of temelastine (1) and 2-[4-(5-bromo-3-methylpyrid-2-yl)-butylamino]-5-[6-hydroxymethy lpyrid-3- ylmethyl]-pyrimidin-4(1H)-one (1-A) in biological fluid is presented. The method combines the previously reported extraction procedure and new chromatography conditions capable of resolving 1, 1-A, and structurally similar compounds formed by the oxidation of 1. The modified method has been used to measure concentrations of 1 and 1-A in biological fluids taken from the rat and dog, and to look for the presence of 1-A in humans following administration of 1.

Two systems for the automated analysis of drugs in biological fluids using high-performance liquid chromatography

This paper describes two fully automated assays. One for zaprinast, a cGMP specific phosphodiesterase inhibitor, which uses the Gilson-Advanced Automated Sample Processor combination, and the other for an H+/K+ ATPase inhibitor and its sulphone metabolite, which uses direct injection. Both assays were developed to support pharmacokinetic studies at therapeutic doses in small animals as well as in man. Plasma or serum (20-200 microliters) is placed directly into an autosampler and all subsequent manipulations are performed mechanically.

Sample preparation for the HPLC analysis of drugs in biological fluids

Sample preparation for the analysis of drugs in biological fluids consists of a number of unit operations that are used for (i) release of the drug from a conjugate or biological matrix; (ii) removal of endogenous compounds that could interfere with the assay; and (iii) techniques for liquid handling. The trends in sample preparation that have occurred over the past 10 years in the authors' laboratory are discussed. In general, there has been a move from the traditional liquid-liquid extraction to methods using bonded-silica which permit rapid throughput and efficient extraction. Automation of sample preparation has seen further gains in productivity; however, the present generation of equipment lack the control and communication systems that are essential for the development of the automated integrated laboratory of the future.

Analysis of drugs from biological fluids using disposable solid phase columns

The traditional liquid-liquid extraction method for the removal of drug from biological matrix is being superseded by solid phase extraction. This involves the selection of an appropriate sorbent (normal-phase, reversed-phase, ion-exchange etc.), but once this has been achieved the method is quick and simple to operate. Most sample handling losses are avoided so recovery of drug is high and it is easily automated. Disposable columns have several advantages. Samples of 0.05-2.0 ml can be analysed routinely. Several wash stages can be included in a method to provide a specific extraction prior to a quick analysis by high-performance liquid chromatography (HPLC), radioimmunoassay, UV etc. A potential problem is that retention of the drug may involve more than one mechanism. Elution of drug may therefore require a stronger eluting solvent than analytical HPLC systems using the same stationary phase.