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Background

IMCI guidelines for childhood pneumonia diagnosis have high sensitivity but low specificity. A digital stethoscope with an automated machine-learning algorithm for classifying lung sounds may improve diagnostic performance. We aimed to evaluate agreement between digital stethoscope recorded lung sound classifications generated from an automated machine learning algorithm with a paediatrician listening panel from children receiving care at community clinics in rural Bangladesh.

Methods

Government community health workers recorded lung sounds from four chest positions using a novel digital stethoscope in children under-5 with cough and/or difficult breathing at first-level community clinics in Bangladesh from November 2019 to December 2020. A trained paediatrician listening panel classified recorded lung sounds into normal, crackles, wheeze, crackles and wheeze, or uninterpretable. A machine learning algorithm classified recorded sounds into the same categories, which were compared with panel classifications.

Results

Of 2434 children screened, 990 were enrolled. Compared to paediatricians, the sensitivity, specificity, and positive and negative predictive values of detecting abnormal sounds (wheeze and/or crackles) by the machine learning algorithm were 61.8 (95%CI: 55.7, 67.6), 60.7 (56.6, 64.6), 41.8 (36.9, 46.8), and 77.6 (73.6, 81.3) among all enrolled children, and 63.5 (54.5, 71.9), 66.2 (60.1, 73.1), 52.7 (44.4, 60.8), and 75.9 (69.2, 81.8) among children with IMCI defined pneumonia.

Conclusions

This study shows an automated algorithm had moderate sensitivity and specificity for classifying lung sounds as either abnormal or normal when using a paediatric listening panel as the reference. Agreement between the machine learning algorithm and paediatric listening panel modestly increased among children with IMCI-defined pneumonia.

Background

Background: Worldwide, biggest killer of children under 5 years of age, is pneumonia. The clinicians use chest x=ray for diagnosing and following it up against the guidelines and consequent hazards. We collaborated with American Academy of Pediatrics initiative of Value in inpatient pediatrics (VIP) Improving Community Acquired Pneumonia (ICAP) Quality improvement project to change the paradigm.

Objectives: To decrease the use of chest x-ray to 10% for initial diagnosis and to decrease the use of follow up chest x-ray to less than 10% in inpatients in under 5 age group.

Methods

We implemented series of interventions including information dissemination, interactive discussions and webinars with all care providers. The rates of chest x-ray use were determined by individual chart review at baseline and then over 5 improvement cycles. The Baseline percentages were compared with the final cycle using Fisher’s exact test.

Results

Rates of chest x-ray use decreased for initial diagnosis from 100% to 50% and rate of follow up chest x-ray decreased more than the set goal.

Conclusions

This real time experience of practicality of implementation of guidelines with such approach can be an impetus for decreasing the use of chest x-ray for managing pediatric pneumonia by the clinicians.

Background

The main aim of this work was to assess if the mass spectra obtained by MALDI-TOF MS, was able to differentiate PCV-13 serotypes from NON-PCV13 serotypes. Therefore using this methodology as screening tool in order to minimize the use of the antisera.

Methods

The training set included PCV-13 isolates and the top 10 of the most prevalent NON-PCV13 isolates, which were selected according to the Argentina national epidemiology, all isolates were previously serotyped by Quellung reaction. Mass spectrum analysis was performed using a MicroFlex LT mass spectrometer (Bruker Daltonik GmbH) and the procedures were conducted according to the manufacturer’s instructions. Classification models were generated using the machine learning (ML) algorithms in ClinProTools, namely QuickClassifier (QC), Supervised Neural Network (SNN), and Genetic Algorithm (GA).

Results

In this first part of the pilot evaluation, we were able to discriminate two groups types, making it possible to differentiate PCV-13 from NON-PCV13 isolates. GA, showed the best cross-validation and recognition capacity values. (Fig1). In the second part, the best models were challenged with 100 isolates whose serotypes were unknown, in order to evaluated the real impact of this approach (Fig2).

Conclusions

A combination of MALDI-TOF MS analysis and ML models may be a potentially efficient screening tool for Streptococcus pneumoniae serotipification, although an external validation must be done in a second part of the pilot evaluation and more isolates whose serotypes are unknown should be challenged with all the algorithms in order to evaluate the real use of this methodology.

Background

Pleural empyema is a serious complication of pneumonia in children. Negative bacterial cultures commonly impede optimal antibiotic stewardship. To improve bacterial identification, we developed a multiplex-qPCR for empyema and evaluated its performance compared with bacterial culture.

Methods

Our multiplex-qPCR assay targeting Streptococcus pneumoniae, Streptococcus pyogenes, Staphylococcus aureus and Haemophilus influenzae was first validated using n=267 laboratory-prepared (spiked) samples. We are recruiting 150 hospitalised children (<18yrs) with empyema for a clinical study in Melbourne, Australia. Pleural fluid specimens are examined by multiplex-qPCR and culture, and clinical sensitivity and time-to-identity compared to assess the potential ability multiplex-qPCR to reduce duration of empiric untargeted antibiotic therapy.

Results

Our multiplex-qPCR demonstrated 99.1% sensitivity and 100% specificity using spiked samples. From the first 50 clinical study participants, a bacterial pathogen was identified in 45/50 (90%) specimens by multiplex-qPCR, compared with 9/50 (18%) by culture (P<0.0001). S. pneumoniae (n=36) was the most common bacterial species identified, followed by S. pyogenes (n=6), H. influenzae (n=2) and S. aureus (n=1). Of the specimens found to contain S. pneumoniae by multiplex-qPCR, only 3/36 (8%) were also culture positive. We estimate our multiplex-qPCR would have reduced the duration of untargeted antibiotic therapy in 35/50 (70%) cases by a median 20 days (IQR 17-23).

Conclusions

Our multiplex-qPCR significantly improved detection of bacterial causes of empyema compared with culture, particularly for S. pneumoniae, and demonstrated potential to improve antibiotic stewardship. Findings suggest that multiplex-qPCR might benefit epidemiological studies of empyema and public health surveillance in addition to its utility for clinical diagnostics.

Background

Studies have demonstrated the use of saliva for detection of pneumococcal carriage. However, isolating pneumococci from saliva is challenging due to the density and diversity of bacteria present in the oral cavity, and this is particularly challenging in individuals with colonized at a low density. Furthermore, co-colonisation with multiple pneumococcal serotypes is seldom detected by the gold standard culture-based methods, and often only the majority serotype is identified. We therefore developed a novel assay to enrich for pneumococcus in a serotype-specific manner from a complex sample such as saliva.

Methods

Serotype-specific antisera/antibodies were incubated in a mixed sample containing two pneumococcal serotypes (majority and minority concentrations), and in culture-enriched saliva spiked with varying concentrations of pneumococcus. Magnetic IgG microbeads (Miltenyi Biotech) were used to purify the antibody-bound target strain using a Kingfisher™ Flex, and the eluate were plated on blood agar for counting and isolation.

Results

For all serotypes investigated, the minority serotype was enriched from ~0.1% of the initial sample, to between 13% and 90% in the final sample (corresponding to a 100-to-900-fold enrichment). Even at concentrations as low as 50 CFU/mL pneumococcus can be enriched from a saliva sample, to an extent that allows easy isolation of individual colonies.

Conclusions

This method is an important development for isolation of pneumococci from clinical samples and may be particularly useful for isolation of minority serotypes in co-colonization studies. This technique will also be a useful in a laboratory setting where mixed samples need to be separated (e.g. transformation experiments).

Background

Invasive Pneumococcal Disease (IPD) is a cause of morbidity and mortality in children. Some Streptococcus pneumoniae isolates are resistant to antibiotics used for IPD, such as beta-lactams and macrolides.

Methods

Ambispective case series study in pediatric patients with IPD admitted in 10 hospitals of Bogotá in 2008-2021, and 4 hospitals of Cali, 2 of Medellin and 1 of Cartagena in 2017-2021(preliminary data).

Results

739 cases of IPD were found. Susceptibility profile information was obtained for 649(87.8%) isolates; 581(78.6%) were non-meningeal (NM) and 68(9.2%) meningeal (M). Regarding to NM isolates, the penicillin-resistance, increased from 9.4% (13/138) in 2008-2011 to 19.7% (19/96) in 2012-2014 and to 22.1% (77/347) in 2015-2021, the resistant to ceftriaxone was 1.4% (2/138) in 2008-2011; 1.04% (1/96) in 2012-2014 and 9.2% (32/347) in 2015-2021. M showed 20% resistance to penicillin, 4.5% resistance to ceftriaxone, and 4.5% intermediate susceptibility. Resistance to macrolides was 33.9%, to clindamycin 24.7%, and to trimethoprim sulfa 30%. All isolates were susceptible to vancomycin. Only 40% of the isolates were susceptible to all antibiotics; 9% were multi-resistant. The serotype most resistant to penicillin was 19A (24.4%), which was associated with multiresistance.

Conclusions

An increase in antibiotic resistance to penicillin and ceftriaxone is observed over time in this study associated with emergence of multiresistant Streptococcus pneumoniae serotype 19A.

Background

The accuracy of molecular methods for the detection of Streptococcus pneumoniae carriage in vaccine impact studies is under debate. We propose a procedure for carriage surveillance studies that enhances the specificity of molecular methods and the sensitivity of culture.

Methods

Culture and qPCR methods were applied to nasopharyngeal samples collected in the Netherlands (n=972) and England (n=577) from 946 toddlers and 603 adults, and in paired oropharyngeal samples exclusively from 319 Dutch adults. Detection by qPCR was performed on culture-enriched samples using a dual-target approach with piaB and lytA. Samples with no live pneumococci isolated at primary culture yet generating signal for pneumococcus in qPCRs were re-examined with a qPCR-guided culture. C_q cut-offs for positivity in qPCRs were determined via receiver operating characteristic curve analysis using isolation of live pneumococci as reference.

Results

Implementation of qPCR-guided culturing significantly increased the proportion of nasopharyngeal and oropharyngeal samples from which live pneumococcus was recovered (p<0.0001). Detection of pneumococcus with qPCRs in n=1549 culture-enriched nasopharyngeal samples exhibited near-perfect agreement with conventional culture (κ: 0.95). For paired nasopharyngeal and oropharyngeal samples from n=319 adults, none of the methods applied to a single sample type exhibited good agreement with combined results for primary+qPCR-guided nasopharyngeal and oropharyngeal cultures (κ; 0.13 to 0.55). However, primary+qPCR-guided cultures and qPCRs on culture-enriched samples displayed increased sensitivity of oropharyngeal compared with nasopharyngeal samples (p<0.05).

Conclusions

The accuracy of pneumococcal carriage surveillance can be greatly improved by complementing conventional culture with qPCR and by using results of qPCR-guided cultures to interpret qPCR data.

Background

Streptococcus pneumoniae is a leading cause of pneumonia, the single biggest infectious killer of adults and children worldwide (pre-COVID-19), particularity in low- and middle-income countries. Lower cost vaccines and improved diagnostics can support disease management. We developed specific monoclonal antibodies targeting 29 common serotypes to support vaccine development and diagnostics and we developed a serotype-specific urine antigen detection (SSUAD) assay to detect the 29 pneumococcal polysaccharide (PnPS) antigens in urine.

Methods

Mice were immunized with serotype specific PnPS conjugates and hybridomas generated from splenic B-cell fusions. Optimal clones were selected by screening their antibodies on a multiplexed PnPS antigen array for sensitivity and specificity. The best candidates were printed in multiplex arrays and screened via checkerboard analysis to confirm their performance for capturing and detecting soluble PnPs. The optimal antibody pairs for each serotype were included in an immunoarray.

Results

We generated at least one clone for each of the PnPS serotypes selected. Checkboard analysis of antibodies enabled us to create a prototype multiplexed-immunoarray wherein each serotype could be detected. Initial performance demonstrated a limit of detection as low as 1pg/mL of PnPS and minimal to no cross-reactivity with other serotype PnPS, except for 6A/C and 15A/B. There was strong intra-and inter-assay precision at <10% and <20% CV respectively.

Conclusions

A subset of these antibodies (14) are commercially available now with the complete set on offer Q3 2022. The prototype SSUAD provides a high-performance multiplexed serotype-specific screen using a plate-based immunoassay protocol and equipment common in many laboratories.