Self-Diagnosis of Surgical Site Infections: Lessons From a Tertiary Care Centre in Karachi, Pakistan

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Self-Diagnosis of Surgical Site Infections: Lessons From a Tertiary Care Centre in Karachi, Pakistan


JournalPakistan Journal of Medical Sciences
Publication date – Jan – 2020
Authors – Sana Z Sajun, Katherine Albutt, Umme Salama Moosajee, Gustaf Drevin, Swagoto Mukhopadhyay, and Lubna Samad
KeywordsLow-and middle-income countries, Pakistan, Patient Self-screening, Surgical site infection
Open access – Yes
SpecialityGeneral surgery, Other
World region Southern Africa
Country: Pakistan
Language – English
Submitted to the One Surgery Index on May 5, 2020 at 6:41 am
Abstract:

Background and Objective: Surgical site infections (SSIs) usually manifest post-discharge, rendering accurate diagnosis and treatment challenging, thereby catalyzing the development of alternate strategies like self-monitored SSI surveillance. This study aimed to evaluate the diagnostic accuracy of patients and Infection Control Monitors (ICMs) to develop a replicable method of SSI-detection.
Methods: A two-year prospective diagnostic accuracy study was conducted in Karachi, Pakistan between 2015 and 2017. Patients were educated about SSIs and provided with questionnaires to elicit symptoms of SSI during post-discharge self-screening. Results of patient’s self-screening and ICM evaluation at followups were compared to surgeon evaluation.
Results: A total of 348 patients completed the study, among whom 18 (5.5%) developed a SSI. Patient selfscreening had a sensitivity of 39%, specificity of 95%, positive predictive value (PPV) of 28%, and negative predictive value (NPV) of 97%. ICM evaluation had a sensitivity of 82%, specificity of 99%, PPV of 82%, and NPV of 99%.
Conclusion: Patients cannot self-diagnose a SSI reliably. However, diagnostic accuracy of ICMs is significantly higher and they may serve as a proxy for surgeons, thereby reducing the burden on specialized surgical workforce in LMICs. Regardless, supplementing post-discharge follow-up with patient self-screening could
increase SSI-detection and reduce burden on health systems.

OSI Number – 20304
PMID – 31933608

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