ReviewCritical care medicine2013
Using existing data to address important clinical questions in critical care.
Review in Critical care medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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
32 citing papers in PubMed.
- De Novo Natural Language Processing Algorithm Accurately Identifies Myxofibrosarcoma From Pathology Reports.Clinical orthopaedics and related research · 2025Article
- Harnessing Big Data in Critical Care: Exploring a new European Dataset.Scientific data · 2024Article
- Observational Studies.Respiratory care · 2023Article
- Commentary: Characteristics and Outcomes of Children with Cerebral Sinus Venous Thrombosis.Neurocritical care · 2023Article
- Review
- The Blessing and the Curse of the Administrative Database.Annals of the American Thoracic Society · 2020Article
- Score performance of SAPS 2 and SAPS 3 in combination with biomarkers IL-6, PCT or CRP.PloS one · 2020Article
- Development and validation of delirium prediction model for critically ill adults parameterized to ICU admission acuity.PloS one · 2020Article
- The opportunities and shortcomings of using big data and national databases for sarcoma research.Cancer · 2019Review
- Patient-ventilator asynchronies during mechanical ventilation: current knowledge and research priorities.Intensive care medicine experimental · 2019Review
- Utilizing the Axon Registry® for quality improvement.Neurology. Clinical practice · 2018Article
- Assessment of the Accuracy of Disease Coding Among Patients Diagnosed With Sarcoma.JAMA oncology · 2018Article
- Validation of an ICD code for accurately identifying emergency department patients who suffer an out-of-hospital cardiac arrest.Resuscitation · 2018Observational
- New perspectives to improve critical care benchmarking.Annals of intensive care · 2018Review
- Hospital Variation in Renal Replacement Therapy for Sepsis in the United States.Critical care medicine · 2018Article
- Claims-Based ICU Research: Learning From Imperfect Data.Critical care medicine · 2017Article
- Development and Prospective Validation of Tools to Accurately Identify Neurosurgical and Critical Care Events in Children With Traumatic Brain Injury.Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies · 2017Observational
- Epidemiology of Pediatric Critical Illness in a Population-Based Birth Cohort in Olmsted County, MN.Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies · 2017Article
- Study of Cardiovascular Outcomes in Renal Transplantation: A Prospective, Multicenter Study to Determine the Incidence of Cardiovascular Events in Renal Transplant Recipients in Ontario, Canada.Canadian journal of kidney health and disease · 2017Article
- Epidemiology of Vasopressin Use for Adults with Septic Shock.Annals of the American Thoracic Society · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
objectiveWith important technological advances in healthcare delivery and the Internet, clinicians and scientists now have access to overwhelming number of available databases capturing patients with critical illness. Yet, investigators seeking to answer important clinical or research questions with existing data have few resources that adequately describe the available sources and the strengths and limitations of each. This article reviews an approach to selecting a database to address health services and outcomes research questions in critical care, examines several databases that are commonly used for this purpose, and briefly describes some strengths and limitations of each. DATA SOURCES: Narrative review of the medical literature. SUMMARY: The available databases that collect information on critically ill patients are numerous and vary in the types of questions they can optimally answer. Selection of a data source must consider not only accessibility but also the quality of the data contained within the database, and the extent to which it captures the necessary variables for the research question. Questions seeking causal associations (e.g., effect of treatment on mortality) usually either require secondary data that contain detailed information about demographics, laboratories, and physiology to best address nonrandom selection or sophisticated study design. Purely descriptive questions (e.g., incidence of respiratory failure) can often be addressed using secondary data with less detail such as administrative claims. Although each database has its own inherent limitations, all secondary analyses will be subject to the same challenges of appropriate study design and good observational research.
conclusionThe literature demonstrates that secondary analyses can have significant impact on critical care practice. While selection of the optimal database for a particular question is a necessary part of high-quality analyses, it is not sufficient to guarantee an unbiased study. Thoughtful and well-constructed study design and analysis approaches remain equally important pillars of robust science. Only through responsible use of existing data will investigators ensure that their study has the greatest impact on critical care practice and outcomes.
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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.