ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2016
A Data Mining Approach to Determine Sepsis Guideline Impact on Inpatient Mortality and Complications.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- The Impact of Delayed Symptomatic Treatment Implementation in the Intensive Care Unit.Healthcare (Basel, Switzerland) · 2021Article
- Frequent Causal Pattern Mining: A Computationally Efficient Framework For Estimating Bias-Corrected Effects.Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data · 2019Article
- A Framework for Visualizing Data Quality for Predictive Models and Clinical Quality Measures.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- Delay Within the 3-Hour Surviving Sepsis Campaign Guideline on Mortality for Patients With Severe Sepsis and Septic Shock.Critical care medicine · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Sepsis incidents have doubled from 2000 through 2008, and hospitalizations for these diagnoses have increased by 70%. The use of the Surviving Sepsis Campaign (SSC) guidelines can lead to earlier diagnosis and treatment; however, the effectiveness of the SSC guidelines in preventing complications for this population is unclear. The overall purpose of this study was to apply SSC guideline recommendations to EHR data for patients with severe sepsis or septic shock and determine guideline compliance as well as its impact on inpatient mortality and sepsis complications. Propensity Score Matching in conjuction with Bootstrap Simulation were used to match patients with and without exposure to the SSC recommendations. Findings showed that EHR data could be used to estimate compliance with SSC recommendations as well as the effect of compliance on outcomes. Compliance with guideline recommendations ranged from 9% to 100%. For individual recommendations with sufficient data, association with outcomes varied. Checking lactate influenced four outcomes; however, two were negative and two positive. Use of a ventilator for patients with respiratory distress had a positive association with three outcomes.
Identifiers
27570669PMC5001751What 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.