Defining the optimal time to appendectomy: A step toward precision surgery

Kabir, Tousif; Syn, Nicholas; Shaw, Vera; Tan, Yong Hui; Chua, Hui Wen; Ong, Lester Wei Lin; Koh, Frederick H; Ladlad, Jasmine; Barco, Jason Bae; Wang, Peter; You, Kui; Blasiak, Agata; Zhao, Joseph J; Ho, Dean; Kam, Juinn Huar; Ngaserin, Sabrina

doi:10.1016/j.surg.2022.04.021

Cited by 4 publications

(3 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Kabir et al . also found that the optimal window for appendicectomy was less than 25 h after admission and that after this period, patients had a significantly longer length of stay and higher 30‐day re‐admission rates compared to those who had surgery within 24 h of admission 18 …”

Section: Discussionmentioning

confidence: 91%

“…17 Kabir et al also found that the optimal window for appendicectomy was less than 25 h after admission and that after this period, patients had a significantly longer length of stay and higher 30-day re-admission rates compared to those who had surgery within 24 h of admission. 18 The literature also provides strong support for using IV contrast alone in CT diagnosis of acute appendicitis. Randomized control trials have demonstrated that CT has sensitivity 87%-100% and specificity 89%-100% for diagnosing appendicitis.…”

Section: Discussionmentioning

confidence: 92%

See 1 more Smart Citation

Use of oral contrast for CT scanning and time to diagnosis and treatment of acute appendicitis

Wright

Giddings

Rahman

et al. 2022

ANZ Journal of Surgery

View full text Add to dashboard Cite

Background The aim of this study was to investigate whether there is a delay in treatment for patients having pre‐operative CT imaging with both intravenous and oral contrast (CTIVO) compared to intravenous contrast alone (CTIV). Methods A retrospective review of patients who underwent emergency appendicectomy at a single hospital during a two‐year period (1/1/2019–31/12/2020) was performed. Demographic details, imaging timing/modality; biochemical markers; American Society of Anaesthesiologists (ASA) physical status classification, anaesthetic induction time; operative report findings; histopathology, peri‐operative complications, admission/discharge times were recorded. The Sunshine Appendicitis Grading System (SAGS) score was used for severity of appendicitis. Results Pre‐operative CT was performed in 294 patients; CTIVO: 159 (54%), CTIV: 135 (46%). Both groups were comparable for age, sex, ASA status and inflammatory markers. The median time from CT request to scanning was longer with CTIVO (CTIVO: 170 min, CTIV: 65 min, P < 0.0001). The median time from CT request to induction of anaesthesia was also longer with CTIVO (CTIVO: 780 minutes, CTIV: 406 min, P < 0.0001). A delay to theatre was not significantly associated with severity of appendicitis (SAGS score). The diagnostic accuracy was not reduced in the CTIV group compared to the CTIVO group. Conclusion CTIVO scans significantly delay CT diagnosis and surgical treatment of appendicitis compared to CTIV. Omitting oral contrast does not result in a reduction in diagnostic accuracy for appendicitis.

show abstract

Section: Discussionmentioning

confidence: 91%

Section: Discussionmentioning

confidence: 92%

Use of oral contrast for CT scanning and time to diagnosis and treatment of acute appendicitis

Wright

Giddings

Rahman

et al. 2022

ANZ Journal of Surgery

View full text Add to dashboard Cite

show abstract

“…As these fields undergo continued clinical validation, there has been a major increase in how data at population scale are used to develop models for image analysis in pathology, dermatology and hospital operations (e.g., readmission prediction, triage, etc). [ 31 32 33 34 35 ] Deep learning is also being increasingly used for drug discovery to design novel drug candidates or identify repurposing opportunities for a wide array of disorders. [ 36 ] Additional advances include the use of small data-based optimisation platforms to design patient-specific combination regimens.…”

Section: Introductionmentioning

confidence: 99%

N-of-1 medicine

Wang,

Leong,

Lau

et al. 2024

Singapore Medical Journal

Self Cite

View full text Add to dashboard Cite

The fields of precision and personalised medicine have led to promising advances in tailoring treatment to individual patients. Examples include genome/molecular alteration-guided drug selection, single-patient gene therapy design and synergy-based drug combination development, and these approaches can yield substantially diverse recommendations. Therefore, it is important to define each domain and delineate their commonalities and differences in an effort to develop novel clinical trial designs, streamline workflow development, rethink regulatory considerations, create value in healthcare and economics assessments, and other factors. These and other segments are essential to recognise the diversity within these domains to accelerate their respective workflows towards practice-changing healthcare. To emphasise these points, this article elaborates on the concept of digital health and digital medicine-enabled N-of-1 medicine, which individualises combination regimen and dosing using a patient’s own data. We will conclude with recommendations for consideration when developing novel workflows based on emerging digital-based platforms.

show abstract

Artificial intelligence in emergency medicine. A systematic literature review

Piliuk,

Tomforde

2023

International Journal of Medical Informatics

View full text Add to dashboard Cite

Defining the optimal time to appendectomy: A step toward precision surgery

Cited by 4 publications

References 37 publications

Use of oral contrast for CT scanning and time to diagnosis and treatment of acute appendicitis

Use of oral contrast for CT scanning and time to diagnosis and treatment of acute appendicitis

N-of-1 medicine

Artificial intelligence in emergency medicine. A systematic literature review

Contact Info

Product

Resources

About