ReviewAnnals of translational medicine2017
Predictors of treatment failure and clinical stability in patients with community acquired pneumonia.
Review in Annals of translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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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.
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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.
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Who cites it
16 citing papers in PubMed, 41 citations in OpenAlex.
- Role of hepatocyte-derived fibrinogen-related protein 1 as a serum biomarker in the diagnosis of community-acquired pneumonia and sepsis: A cross-sectional study.The Journal of international medical research · 2026Observational
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- Proteome signature for differential diagnosis of patients with bilateral lung infiltrates.ERJ open research · 2025Article
- Childhood Pneumonia: What's Unchanged, and What's New?Indian journal of pediatrics · 2023Review
- Evaluation of Plasma Lipocalin-2 as a Predictor of Etiology and Severity in Adult Patients with Community-Acquired Pneumonia.Microorganisms · 2023Article
- Calprotectin: An Ignored Biomarker of Neutrophilia in Pediatric Respiratory Diseases.Children (Basel, Switzerland) · 2021Review
- Utility of procalcitonin as a predictor of bloodstream infections and supportive modality requirements in critically ill cancer patients.Clinica chimica acta; international journal of clinical chemistry · 2020Article
- Observational
- Diagnostic markers for community-acquired pneumonia.Annals of translational medicine · 2020Review
- Lactate dehydrogenase as a prognostic marker of renal transplant recipients with severe community-acquired pneumonia: a 10-year retrospective study.Annals of translational medicine · 2019Article
- Biomarkers in Pneumonia-Beyond Procalcitonin.International journal of molecular sciences · 2019Review
- Plasma Soluble Urokinase-Type Plasminogen Activator Receptor Level as a Predictor of the Severity of Community-Acquired Pneumonia.International journal of environmental research and public health · 2019Article
- Budget Impact of Omadacycline for the Treatment of Patients with Community-Acquired Bacterial Pneumonia in the United States from the Hospital Perspective.American health & drug benefits · 2019Article
- Future Research Directions in Pneumonia. NHLBI Working Group Report.American journal of respiratory and critical care medicine · 2018Article
- Time to Clinical Stability Among Pediatric Patients With Severe Pneumonia: Southwest Ethiopia: Prospective Follow-Up Study.Sage open pediatricsArticle
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Community acquired pneumonia (CAP) is the leading infectious cause of mortality worldwide with approximately 10% of patients hospitalized requiring intensive care unit (ICU) admission. The ability to predict clinical stability (CS) and treatment failure (TF) enables the clinician to alter antibiotics appropriately, facilitate a timely ICU admission, or arrange a suitable discharge. The detection of CS and TF can be difficult and changes in clinical signs may be subtle or delayed. Thus clinical scores and biomarkers are routinely used to identify severity and monitor clinical progression. The evidence, however, is vast and the definitive role of these systems is at times difficult to elucidate. The aim of this review is to analyse the current literature and to provide a rational and clinically focused view of the predictive utility of various systems used to identify CS and TF in CAP.
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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.