Caecal diverticulitis can be misdiagnosed as acute appendicitis: a systematic review of the literature.
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ABSTRACT: Aim
Caecal diverticulitis (CD) is an uncommon condition which can be misdiagnosed as acute appendicitis due to similar clinical presentations. Further, its management varies among medical centres. The aim of this study was to review cases of patients with CD, to identify the factors differentiating CD from acute appendicitis and to provide a summary of existing diagnostic methods and therapeutic alternatives regarding its management.Methods
This systematic review was conducted in accordance with the PRISMA guidelines and the AMSTAR2 checklist. We searched MEDLINE and Embase from inception until 1 October 2018 for original publications reporting cases of CD.Results
Out of the 560 identified studies, 146 publications (988 patients) were included in the qualitative synthesis. Most frequent symptoms of CD were right iliac fossa pain (93.2%), nausea and/or vomiting (35.4%) and fever (26.9%). A total of 443 patients (44.8%) underwent radiological imaging, which reported CD in 225 patients (22.8%). For the other patients, the diagnosis was obtained by surgical exploration (73.9%). Among patients diagnosed with CD by imaging, 67 (29.8%) underwent surgery and 158 (70.2%) were treated conservatively. Among patients who underwent surgical exploration, treatment consisted most frequently of right hemi-colectomy (33%), appendectomy (18.8%) and diverticulectomy with appendectomy (16.3%).Conclusion
CD can be misdiagnosed as acute appendicitis, therefore resulting in unnecessary surgical exploration. The review of the literature starting from 1930 highlights the critical role of medical imaging in supporting the clinician to diagnose this condition and administer adequate treatment.
SUBMITTER: Uhe I
PROVIDER: S-EPMC9292704 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Introduction and importanceTubo-ovarian abscesses (TOA) is presented with multiple clinical manifestations including gastrointestinal findings.Case presentationHerein, we present a case of complicated diverticulitis that was misdiagnosed as TOA, owing to overlapping genital involvement.Clinical discussionImaging could be misleading in these patients as a result of severe inflammation of intestines and surrounding organs.ConclusionPatients who do not respond to antibiotic treatment should be suspected of other gastrointestinal pathologies such as diverticulitis and should be evaluated accordingly.
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| S-EPMC5315733 | biostudies-literature
Project description:BackgroundAcute colonic diverticulitis (ACD) complications arise in approximately 8% to 35% patients and the most common ones are represented by phlegmon or abscess, followed by perforation, peritonitis, obstruction, and fistula. In accordance with current guidelines, patients affected by generalized peritonitis should undergo emergency surgery. However, decisions on whether and when to operate ACD patients remain a substantially debated topic while algorithm for the best treatment has not yet been determined. Damage control surgery (DCS) represents a well-established method in treating critically ill patients with traumatic abdomen injuries. At present, such surgical approach is also finding application in non-traumatic emergencies such as perforated ACD. Thanks to a thorough systematic review of the literature, we aimed at achieving deeper knowledge of both indications and short- and long-term outcomes related to DCS in perforated ACD.MethodsWe performed a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) guidelines. Pubmed/MEDLINE, Embase, Scopus, Cochrane Library, and Web of Science databases were used to search all related literature.ResultsThe 8 included articles covered an approximately 13 years study period (2006-2018), with a total 359 patient population. At presentation, most patients showed III and IV American Society of Anesthesiologists (ASA) score (81.6%) while having Hinchey III perforated ACD (69.9%). Most patients received a limited resection plus vacuum-assisted closure at first-look while about half entire population underwent primary resection anastomosis (PRA) at a second-look. Overall morbidity rate, 30-day mortality rate and overall mortality rate at follow-up were between 23% and 74%, 0% and 20%, 7% and 33%, respectively. Patients had a 100% definitive abdominal wall closure rate and a definitive stoma rate at follow-up ranging between 0% and 33%.ConclusionDCS application to ACD patients seems to offer good outcomes with a lower percentage of patients with definitive ostomy, if compared to Hartmann's procedure. However, correct definition of DCS eligible patients is paramount in avoiding overtreatment. In accordance to 2016 WSES (World Society of Emergency Surgery) Guidelines, DCS remains an effective surgical strategy in critically ill patients affected by sepsis/septic shock and hemodynamical unstability.
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Project description:BackgroundTo assess the efficacy of artificial intelligence (AI) models in diagnosing and prognosticating acute appendicitis (AA) in adult patients compared to traditional methods. AA is a common cause of emergency department visits and abdominal surgeries. It is typically diagnosed through clinical assessments, laboratory tests, and imaging studies. However, traditional diagnostic methods can be time-consuming and inaccurate. Machine learning models have shown promise in improving diagnostic accuracy and predicting outcomes.Main bodyA systematic review following the PRISMA guidelines was conducted, searching PubMed, Embase, Scopus, and Web of Science databases. Studies were evaluated for risk of bias using the Prediction Model Risk of Bias Assessment Tool. Data points extracted included model type, input features, validation strategies, and key performance metrics.ResultsIn total, 29 studies were analyzed, out of which 21 focused on diagnosis, seven on prognosis, and one on both. Artificial neural networks (ANNs) were the most commonly employed algorithm for diagnosis. Both ANN and logistic regression were also widely used for categorizing types of AA. ANNs showed high performance in most cases, with accuracy rates often exceeding 80% and AUC values peaking at 0.985. The models also demonstrated promising results in predicting postoperative outcomes such as sepsis risk and ICU admission. Risk of bias was identified in a majority of studies, with selection bias and lack of internal validation being the most common issues.ConclusionAI algorithms demonstrate significant promise in diagnosing and prognosticating AA, often surpassing traditional methods and clinical scores such as the Alvarado scoring system in terms of speed and accuracy.
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