Dataset Information

Clinical features of severe malaria associated with death: a 13-year observational study in the Gambia.

ABSTRACT:

Background

Severe malaria (SM) is a major cause of death in sub-Saharan Africa. Identification of both specific and sensitive clinical features to predict death is needed to improve clinical management.

Methods

A 13-year observational study was conducted from 1997 through 2009 of 2,901 children with SM enrolled at the Royal Victoria Teaching Hospital in The Gambia to identify sensitive and specific predictors of poor outcome in Gambian children with severe malaria between the ages 4 months to 14 years. We have measured the sensitivity and specificity of clinical features that predict death or development of neurological sequelae.

Findings

Impaired consciousness (odds ratio {OR} 4.4 [95% confidence interval {CI}, 2.7-7.3]), respiratory distress (OR 2.4 [95%CI, 1.7-3.2]), hypoglycemia (OR 1.7 [95%CI, 1.2-2.3]), jaundice (OR 1.9 [95%CI, 1.2-2.9]) and renal failure (OR 11.1 [95%CI, 3.3-36.5]) were independently associated with death in children with SM. The clinical features that showed the highest sensitivity and specificity to predict death were respiratory distress (area under the curve 0.63 [95%CI, 0.60-0.65]) and impaired consciousness (AUC 0.61[95%CI, 0.59-0.63]), which were comparable to the ability of hyperlactatemia (blood lactate>5 mM) to predict death (AUC 0.64 [95%CI, 0.55-0.72]). A Blantyre coma score (BCS) of 2 or less had a sensitivity of 74% and specificity of 67% to predict death (AUC 0.70 [95% C.I. 0.68-0.72]), and sensitivity and specificity of 74% and 69%, respectively to predict development of neurological sequelae (AUC 0.72 [95% CI, 0.67-0.76]).The specificity of this BCS threshold to identify children at risk of dying improved in children less than 3 years of age (AUC 0.74, [95% C.I 0.71-0.76]).

Conclusion

The BCS is a quantitative predictor of death. A BCS of 2 or less is the most sensitive and specific clinical feature to predict death or development of neurological sequelae in children with SM.

SUBMITTER: Jallow M

PROVIDER: S-EPMC3460946 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Clinical features of severe malaria associated with death: a 13-year observational study in the Gambia.

Jallow Muminatou M Casals-Pascual Climent C Ackerman Hans H Walther Brigitte B Walther Michael M Pinder Margaret M Sisay-Joof Fatou F Usen Stanley S Jallow Mariatou M Abubakar Ismaela I Olaosebikan Rasaq R Jobarteh Aminata A Conway David J DJ Bojang Kalifa K Kwiatkowski Dominic D

PloS one 20120928 9

<h4>Background</h4>Severe malaria (SM) is a major cause of death in sub-Saharan Africa. Identification of both specific and sensitive clinical features to predict death is needed to improve clinical management.<h4>Methods</h4>A 13-year observational study was conducted from 1997 through 2009 of 2,901 children with SM enrolled at the Royal Victoria Teaching Hospital in The Gambia to identify sensitive and specific predictors of poor outcome in Gambian children with severe malaria between the ages ...[more]

PMID: 23029157

Similar Datasets

Project description:BackgroundThe criteria for defining severe malaria have evolved over the last 20 years. We aimed to assess the strength of association of death with features currently characterizing severe malaria through a systematic review and meta-analysis.MethodElectronic databases (Medline, Embase, Cochrane Database of Systematic Reviews, Thomson Reuters Web of Knowledge) were searched to identify publications including African children with severe malaria. PRISMA guidelines were followed. Selection was based on design (epidemiological, clinical and treatment studies), setting (Africa), participants (children < 15 years old with severe malaria), outcome (survival/death rate), and prognostic indicators (clinical and laboratory features). Quality assessment was performed following the criteria of the 2011 Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Odds ratios (ORs) were calculated for each study and prognostic indicator, and, when a test was assessed in at least two studies, pooled estimates of ORs were computed using fixed- or random-effects meta-analysis.ResultsA total of 601 articles were identified and screened and 30 publications were retained. Features with the highest pooled ORs were renal failure (5.96, 95% CI 2.93-12.11), coma score (4.83, 95% CI 3.11-7.5), hypoglycemia (4.59, 95% CI 2.68-7.89), shock (4.31, 95% CI 2.15-8.64), and deep breathing (3.8, 95% CI 3.29-4.39). Only half of the criteria had an OR > 2. Features with the lowest pooled ORs were impaired consciousness (0.58, 95% CI 0.25-1.37), severe anemia (0.76, 95% CI 0.5- 1.13), and prostration (1.12, 95% CI 0.45-2.82).ConclusionThe findings of this meta-analysis show that the strength of association between the criteria defining severe malaria and death is quite variable for each clinical and/or laboratory feature (OR ranging from 0.58 to 5.96). This ranking allowed the identification of features weakly associated with death, such as impaired consciousness and prostration, which could assist to improve case definition, and thus optimize antimalarial treatment.

Project description:Patients with advanced stomach adenocarcinoma (STAD) commonly show high mortality and poor prognosis. Increasing evidence has suggested that basic metabolic changes may promote the growth and aggressiveness of STAD; therefore, identification of metabolic prognostic signatures in STAD would be meaningful. An integrative analysis was performed with 407 samples from The Cancer Genome Atlas (TCGA) and 433 samples from Gene Expression Omnibus (GEO) to develop a metabolic prognostic signature associated with clinical and immune features in STAD using Cox regression analysis and least absolute shrinkage and selection operator (LASSO). The different proportions of immune cells and differentially expressed immune-related genes (DEIRGs) between high- and low-risk score groups based on the metabolic prognostic signature were evaluated to describe the association of cancer metabolism and immune response in STAD. A total of 883 metabolism-related genes in both TCGA and GEO databases were analyzed to obtain 184 differentially expressed metabolism-related genes (DEMRGs) between tumor and normal tissues. A 13-gene metabolic signature (GSTA2, POLD3, GLA, GGT5, DCK, CKMT2, ASAH1, OPLAH, ME1, ACYP1, NNMT, POLR1A, and RDH12) was constructed for prognostic prediction of STAD. Sixteen survival-related DEMRGs were significantly related to the overall survival of STAD and the immune landscape in the tumor microenvironment. Univariate and multiple Cox regression analyses and the nomogram proved that a metabolism-based prognostic risk score (MPRS) could be an independent risk factor. More importantly, the results were mutually verified using TCGA and GEO data. This study provided a metabolism-related gene signature for prognostic prediction of STAD and explored the association between metabolism and the immune microenvironment for future research, thereby furthering the understanding of the crosstalk between different molecular mechanisms in human STAD. Some prognosis-related metabolic pathways have been revealed, and the survival of STAD patients could be predicted by a risk model based on these pathways, which could serve as prognostic markers in clinical practice.

Dataset Information

Clinical features of severe malaria associated with death: a 13-year observational study in the Gambia.

Background

Methods

Findings

Conclusion

Publications

Clinical features of severe malaria associated with death: a 13-year observational study in the Gambia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets