ArticleIranian journal of medical sciences2024
The Use of Platelet Count and Indices as Prognostic Factors for Mortality in Children with Sepsis.
Article in Iranian journal of medical sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Platelet parameters as potential biomarkers for sepsis: a systematic review and meta-analysis.Systematic reviews · 2025Pooled it
- Clinical Characteristics, Microbiological Profile, and Mortality Predictors in Pediatric Community-Acquired Sepsis: A Single-Center Study.Turkish archives of pediatrics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Sepsis is still one of the leading causes of mortality and morbidity in children worldwide. Consumptive coagulopathy and suppression of thrombopoiesis in the bone marrow resulting from immune dysregulation are pathological mechanisms that cause thrombocytopenia in sepsis. Platelet count (PLT) and indices, such as mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT) are markers of platelet activation and are strongly influenced by platelet morphology and proliferation kinetics. We aimed to study the use of platelet count and indices as predictors of mortality in children with sepsis. Methods: This is a cross-sectional study of 45 children diagnosed with sepsis on admission at Haji Adam Malik Hospital, Medan, North Sumatra, Indonesia, between October and November 2022. Blood samples were drawn upon admission, and platelet count and indices were then determined for all children. Subjects were followed up till discharge from hospital or death. Receiver Operating Characteristic (ROC) curve analysis of platelet parameters was done to determine the area under the curve (AUC), optimal cut-off value, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) in predicting mortality in children with sepsis. Using the cut-off values from ROC curve analysis, the odds ratio with 95% confidence interval was calculated using multiple logistic regression analyses. A P value less than 0.05 was considered statistically significant. Results: MPV, PDW, and PDW/PLT were significantly higher in non-survivors than survivors (P=0.04, P=0.02, and P=0.04, respectively). ROC curve analysis showed that PDW had the largest AUC (0.708 [95% CI=0.549-0.866]) with a cut-off value of 14.1%, sensitivity of 63.6%, and specificity of 82.6%. PDW was also the only parameter that significantly affected the outcome of children with sepsis. PDW≥14.1% at admission increases the risk of mortality by 5.7 times. Conclusion: Admission PDW is a fast and specific tool to predict the outcome of children with sepsis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.