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Scientific Reports Oct 2022Malaria and pneumonia are the leading causes of childhood mortality in children under 5 years of age. Nevertheless, the proportions and deaths of malaria co-infection... (Meta-Analysis)
Meta-Analysis
Malaria and pneumonia are the leading causes of childhood mortality in children under 5 years of age. Nevertheless, the proportions and deaths of malaria co-infection among patients with severe pneumonia, particularly in children under 5 years of age, and characteristics of co-infection remain poorly explored. Hence, the present study aimed to collate the evidence of malaria among patients with severe pneumonia, severe pneumonia among patients with malaria, and the proportion of deaths among patients with co-infections. Potentially relevant studies were searched in six databases including PubMed, Scopus, Web of Science, Embase, Ovid, and MEDLINE to identify studies on malaria and severe pneumonia co-infections that were published until 21 July 2022 with a restriction for the non-English language but no restriction for the publication year. The quality of the included studies was determined using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). The pooled estimates, including the pooled proportion of malaria among patients with severe pneumonia, and the proportion of deaths among patients with co-infections, were estimated by the random-effects model. Of the 4094 studies examined, 11 studies that met the eligibility criteria were included in the review. Meta-analysis results showed that the proportion of malaria (2162 cases) among patients with severe pneumonia (9738 cases) was 19% (95% CI 12-26%, I: 98.79%, 11 studies). The proportion of severe pneumonia (546 cases) among patients with malaria (10,325 cases) was 20% (95% CI 0-40%, I: 99.48%, 4 studies). The proportion of deaths among patients with co-infection was 13% (95% CI 2-23%, I: 85.1%, 3 studies). In conclusion, nearly one-fifth of patients with severe pneumonia have malaria, one-fifth of patients with malaria have severe pneumonia, and about 13% of co-infections lead to deaths. This information raised the clinical importance of diagnosis and management of concurrent infections. Patients with severe pneumonia should be investigated for malaria, and vice versa. Detection of co-infections might provide the information to inform the physician to manage and cure co-infected patients who live in areas where both diseases were endemic.
Topics: Child; Child, Preschool; Coinfection; Humans; Malaria; Pneumonia
PubMed: 36243777
DOI: 10.1038/s41598-022-22151-x -
Journal of Infection and Public Health Jul 2024Burkholderia pseudomallei, a Gram-negative pathogen, causes melioidosis. Although various clinical laboratory identification methods exist, culture-based techniques lack... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Burkholderia pseudomallei, a Gram-negative pathogen, causes melioidosis. Although various clinical laboratory identification methods exist, culture-based techniques lack comprehensive evaluation. Thus, this systematic review and meta-analysis aimed to assess the diagnostic accuracy of culture-based automation and non-automation methods.
METHODS
Data were collected via PubMed/MEDLINE, EMBASE, and Scopus using specific search strategies. Selected studies underwent bias assessment using QUADAS-2. Sensitivity and specificity were computed, generating pooled estimates. Heterogeneity was assessed using I statistics.
RESULTS
The review encompassed 20 studies with 2988 B. pseudomallei samples and 753 non-B. pseudomallei samples. Automation-based methods, particularly with updating databases, exhibited high pooled sensitivity (82.79%; 95% CI 64.44-95.85%) and specificity (99.94%; 95% CI 98.93-100.00%). Subgroup analysis highlighted superior sensitivity for updating-database automation (96.42%, 95% CI 90.01-99.87%) compared to non-updating (3.31%, 95% CI 0.00-10.28%), while specificity remained high at 99.94% (95% CI 98.93-100%). Non-automation methods displayed varying sensitivity and specificity. In-house latex agglutination demonstrated the highest sensitivity (100%; 95% CI 98.49-100%), followed by commercial latex agglutination (99.24%; 95% CI 96.64-100%). However, API 20E had the lowest sensitivity (19.42%; 95% CI 12.94-28.10%). Overall, non-automation tools showed sensitivity of 88.34% (95% CI 77.30-96.25%) and specificity of 90.76% (95% CI 78.45-98.57%).
CONCLUSION
The study underscores automation's crucial role in accurately identifying B. pseudomallei, supporting evidence-based melioidosis management decisions. Automation technologies, especially those with updating databases, provide reliable and efficient identification.
Topics: Burkholderia pseudomallei; Melioidosis; Humans; Sensitivity and Specificity; Automation, Laboratory; Bacteriological Techniques; Automation
PubMed: 38820898
DOI: 10.1016/j.jiph.2024.04.022