Evidence map›Paper›PMID 41361042›Full record

ArticleJournal of general internal medicine2026

Diagnostic Performance of Onset Characterization vs. Time-to-Peak Assessment in Acute Abdominal Pain.

Toshihiko Takada, Ryuji Suzuki, Hiroshi Honjo, Masayuki Miyajima, Tadao Kubota, Shunichi Fukuhara

Abstract readComparative Study
In one paragraph

Article in Journal of general internal medicine, 2026. 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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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Toshihiko TakadaDepartment of General Medicine, Shirakawa Satellite for Teaching and Research (STAR), Fukushima Medical University, Shirakawa, Fukushima, Japan. ttakada@water.ocn.ne.jp.ORCID 0000-0002-8032-6224
Ryuji SuzukiDepartment of General Medicine, Shirakawa Satellite for Teaching and Research (STAR), Fukushima Medical University, Shirakawa, Fukushima, Japan.
Hiroshi HonjoDepartment of Radiology, Shirakawa Kosei General Hospital, Shirakawa, Fukushima, Japan.
Masayuki MiyajimaDepartment of Radiology, Shirakawa Kosei General Hospital, Shirakawa, Fukushima, Japan.
Tadao KubotaDepartment of Surgery, Okinawa Chubu Hospital, Uruma, Okinawa, Japan.
Shunichi FukuharaDepartment of General Medicine, Shirakawa Satellite for Teaching and Research (STAR), Fukushima Medical University, Shirakawa, Fukushima, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate assessment of symptom onset is crucial for diagnosing acute abdominal pain, particularly to identify life-threatening conditions such as rupture, dissection, vascular occlusion, torsion, or perforation. However, the optimal method for evaluating pain onset remains unclear.

objectiveTo compare the diagnostic performance of two history-taking approaches for evaluating pain onset: sudden onset characterization, which asks whether the pain began suddenly, and time-to-peak assessment, which asks how long it took for the pain to reach maximum intensity, considering "instantaneous peak" responses as positive.

designProspective diagnostic study at a single acute care hospital in Japan between December 2022 and October 2024. PATIENTS: A consecutive sample of adult patients presenting with abdominal pain of 7 days' duration or less in the emergency department was assessed. MAIN MEASURES: The primary outcome was the presence of a target condition, defined as rupture, dissection, vascular occlusion, torsion, or perforation of an intra-abdominal organ, confirmed by contrast-enhanced computed tomography findings or clinical follow-up. Diagnostic measures including specificity, sensitivity, positive and negative predictive values, and likelihood and diagnostic odds ratios were calculated for each approach. KEY

resultsOf the 629 patients (median age, 58 years [interquartile range (IQR), 44-72 years]; 48.5% male), 20 (3.2%) were diagnosed with a target condition. Specificity improved from 86.7% (95% confidence interval [CI], 83.8%-89.2%) with sudden onset characterization to 94.3% (95% CI, 92.1%-95.8%) with time-to-peak assessment (P < .001). Sensitivity was 40.0% (95% CI, 21.9%-61.3%) for sudden onset characterization and 30.0% (95% CI, 14.5%-51.9%) for time-to-peak assessment (P = .48).

conclusionsTime-to-peak assessment demonstrated higher specificity without a significant loss of sensitivity compared with sudden onset characterization. This approach may assist in ruling-in critical intra-abdominal conditions in patients with acute abdominal pain. However, neither method alone is sufficient to rule-out life-threatening conditions.

Indexed as

Abdomen, AcuteAbdominal PainMedical History TakingPain MeasurementAgedFemaleHumansJapanMaleMiddle AgedProspective StudiesSensitivity and SpecificityTime Factorsacute abdomenclinical decision makinghistory taking

Identifiers

PMID41361042
PMCPMC13241358

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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.