Evidence map›Paper›PMID 39521983›Full record

ArticleBMC emergency medicine2024

Predictive score for diagnosing acute colonic diverticulitis in the emergency department: a retrospective study.

Siriwimon Tantarattanapong, Choasita Glawsongkram, Wasuntaraporn Pethyabarn

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Article in BMC emergency medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Siriwimon TantarattanapongDepartment of Emergency Medicine, Songklanagarind Hospital, Faculty of Medicine, Prince of Songkla University, Hat Yai, 90110, Songkhla, Thailand.
Choasita GlawsongkramDepartment of Emergency Medicine, Songklanagarind Hospital, Faculty of Medicine, Prince of Songkla University, Hat Yai, 90110, Songkhla, Thailand.
Wasuntaraporn PethyabarnDepartment of Emergency Medicine, Songklanagarind Hospital, Faculty of Medicine, Prince of Songkla University, Hat Yai, 90110, Songkhla, Thailand. kwang.wsp@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute diverticulitis is commonly misdiagnosed among patients with acute abdominal pain in the emergency department (ED). There are predictive scores that assist in the diagnosis of acute left-sided diverticulitis, but no scoring system is available for diagnosing acute diverticulitis without regard to the affected side. Therefore, developing a predictive score for diagnosing acute diverticulitis that is not limited to the left side will guide physicians in making a diagnosis and increase the appropriateness of computed tomography. This study aimed to establish a predictive score for diagnosing acute diverticulitis.

methodThis single-centre retrospective study included adult patients (≥ 18 years) who presented to the ED with acute abdominal pain. Multivariate logistic regression analysis was used to identify essential factors for diagnosing acute diverticulitis, and the Akaike information criterion was calculated to identify significant predictive factors for diagnosing acute diverticulitis using a clinical scoring system.

resultsOf 424 patients who fulfilled the inclusion criteria, 72 (17%) were diagnosed with acute diverticulitis. The significant factors associated with acute diverticulitis were age ≥ 60 years (adjusted odds ratio (adj.OR) 2.23, 95% confidence interval (CI): 1.20 - 4.14, p = 0.01), duration of abdominal pain ≥ 48 h (adj.OR 2.64, 95% CI: 1.28 - 5.45, p = 0.017), history of a diverticulum (adj.OR 7.77, 95% CI: 3.27 - 18.45, p < 0.001), absence of nausea and vomiting (adj.OR 3.42, 95% CI: 1.65 - 7.10, p < 0.001), absence of anorexia (adj.OR 3.33, 95% CI: 1.34 - 8.33, p = 0.026), absence of tachycardia (adj.OR 3.51, 95% CI: 1.39 - 8.87, p = 0.003), and abdominal guarding (adj.OR 2.99, 95% CI: 1.52 - 5.91, p = 0.002). These predictive factors were converted into predictive scores for diagnosing acute diverticulitis. For the score of ≥ 4, the sensitivity and specificity were 73.24% (95% CI: 0.61-0.83) and 80.40% (95% CI: 0.76-0.84), respectively, and the negative predictive value was 93.71% (95% CI: 0.90-0.96). No significant signs, symptoms, or laboratory findings were associated with complicated diverticulitis.

conclusionPredictive factors for diagnosing acute diverticulitis included age ≥ 60 years, duration of abdominal pain ≥ 48 h, history of a diverticulum, abdominal guarding, and absence of nausea and vomiting, anorexia, and tachycardia. A predictive score ≥ 4 suggested the presence of acute diverticulitis.

Indexed as

Diverticulitis, ColonicEmergency Service, HospitalAbdominal PainAcute DiseaseAdultAgedAge FactorsFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesTomography, X-Ray ComputedAcute abdominal painAcute diverticulitisDiagnosisPredictive score

Identifiers

PMID39521983
PMCPMC11550550

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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.