ReviewAdvances in surgery2013
Improvement in the diagnosis of appendicitis.
Review in Advances in surgery, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05070000 (Value of Ultrasound and Computed Tomography in the Diagnosis of Acute Appendicitis With Histopathology as Gold Standard - Retrospective Cohort Study.), which is not on this map. Cited by 21 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.
Value of Ultrasound and Computed Tomography in the Diagnosis of Acute Appendicitis With Histopathology as Gold Standard - Retrospective Cohort Study.
Who cites it
21 citing papers in PubMed.
- Appendectomy Skin Closure Technique, Randomized Controlled Trial: Changing Paradigms (ASC).World journal of surgery · 2016Trial
- Large Language Model Automated Extraction of Clinical Signs and Symptoms From Emergency Department Reports for Machine Learning Prediction Models: Development and Validation Study.JMIR medical informatics · 2026Article
- Predictive Value of Clinical and CT Scan Findings for Complicated Appendicitis: A Retrospective Analysis.Cureus · 2025Article
- Assessment of negative appendectomy in acute appendicitis diagnoses.Surgery in practice and science · 2025Article
- Machine-learning based prediction of appendicitis for patients presenting with acute abdominal pain at the emergency department.World journal of emergency surgery : WJES · 2024Article
- A Novel Deep Learning Approach for the Automatic Diagnosis of Acute Appendicitis.Journal of clinical medicine · 2024Article
- Demonstration of a new entity of non-perforated appendicitis through studying cluster of appendicitis.Scientific reports · 2022Article
- Case series: Treatment outcome of late presentation of acute appendicitis.International journal of surgery case reports · 2022Article
- Hospitalization Trends for Acute Appendicitis in Spain, 1998 to 2017.International journal of environmental research and public health · 2021Observational
- Conditional CT Strategy-An Effective Tool to Reduce Negative Appendectomy Rate and the Overuse of the CT.Journal of clinical medicine · 2021Article
- Xanthogranulomatous appendicitis: A comprehensive literature review.World journal of gastrointestinal surgery · 2021Article
- Factors Associated With Potentially Missed Diagnosis of Appendicitis in the Emergency Department.JAMA network open · 2020Article
- [Acute abdomen : What the clinician wants to know from the radiologist].Der Radiologe · 2019Article
- Negative Appendectomy Rate and Risk Factors That Influence Improper Diagnosis at King Abdulaziz University Hospital.Materia socio-medica · 2018Article
- Does time of surgery influence the rate of false-negative appendectomies? A retrospective observational study of 274 patients.Patient safety in surgery · 2018Article
- Retrospective Multivariate Analysis of Data from Children with Suspected Appendicitis: A New Tool for Diagnosis.Emergency medicine international · 2018Article
- Observational
- CT guided appendicectomy incision: A prospective case series.International journal of surgery case reports · 2017Article
- Is there a need to standardize reporting terminology in appendicitis?Ultrasound quarterly · 2015Article
- A novel reporting system to improve accuracy in appendicitis imaging.AJR. American journal of roentgenology · 2015Article
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
Our attempts to systematically improve accuracy in the evaluation of patients with suspected appendicitis are, in some ways, hindered by the fact that the condition is so frequently straightforward to diagnose. Careful history-taking and physical examination are reliable in most patients. However, establishing the diagnosis with these skills alone remains vulnerable to conditions that masquerade as acute appendicitis. A substantial body of clinical research over the last quarter-century has shown that improved accuracy is possible. Strategies for improvement include the use of diagnostic scoring systems, laboratory makers such as CRP, diagnostic laparoscopy, and advanced imaging modalities such as CT, MRI, and US. How clinicians use these strategies depends on many factors related to practice setting, the population served, and clinical goals. In children, for instance, the desire to limit exposure to ionizing radiation competes with the greater anatomic detail that a CT scan can provide; at the same time, many hospitals that treat children do not have the resources to maintain the sort of full-time, highly sophisticated abdominal US programs that achieve the highest rates of diagnostic accuracy in clinical studies. Trade-offs have to be made, but improvement is possible in almost all groups of patients: the clinical community should no longer settle for a 15% NA rate when 5% is clearly possible without adverse consequences. Many clinicians will be faced with the task of evaluating patients suspected of having acute appendicitis. A deliberate, proactive, and, ideally, benchmarked strategy for improving diagnosis should be the standard to which we hold ourselves and the promise we deliver to our patients.
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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.