Self-Diagnosis of Surgical Site Infections: Lessons from a tertiary care centre in Karachi, Pakistan.

Low-and Middle-Income Countries Pakistan Patient Self-screening Surgical Site Infection

Journal

Pakistan journal of medical sciences
ISSN: 1682-024X
Titre abrégé: Pak J Med Sci
Pays: Pakistan
ID NLM: 100913117

Informations de publication

Date de publication:
Jan 2020
Historique:
entrez: 15 1 2020
pubmed: 15 1 2020
medline: 15 1 2020
Statut: ppublish

Résumé

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. 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 follow-ups were compared to surgeon evaluation. A total of 348 patients completed the study, among whom 18 (5.5%) developed a SSI. Patient self-screening 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%. 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.

Sections du résumé

BACKGROUND AND OBJECTIVE 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 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 follow-ups were compared to surgeon evaluation.
RESULTS RESULTS
A total of 348 patients completed the study, among whom 18 (5.5%) developed a SSI. Patient self-screening 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 CONCLUSIONS
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.

Identifiants

pubmed: 31933608
doi: 10.12669/pjms.36.ICON-Suppl.1716
pii: PJMS-36-S55
pmc: PMC6943118
doi:

Types de publication

Journal Article

Langues

eng

Pagination

S55-S60

Informations de copyright

Copyright: © Pakistan Journal of Medical Sciences.

Déclaration de conflit d'intérêts

Conflict Interests: None.

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Auteurs

Sana Z Sajun (SZ)

Sana Z Sajun, MSc. Interactive Research and Development, Karachi, Pakistan.

Katherine Albutt (K)

Katherine Albutt, MD MPH. Department of Surgery, Massachusetts General Hospital, Program in Global Surgery and Social Change, Harvard Medical School, Boston, USA.

Umme Salama Moosajee (US)

Umme Salama Moosajee, BSc. Center for Essential Surgery and Acute Care, Global Health Directorate, Indus Health Network, Karachi, Pakistan.

Gustaf Drevin (G)

Gustaf Drevin, Program in Global Surgery and Social Change, Harvard Medical School, Boston, USA.

Swagoto Mukhopadhyay (S)

Swagoto Mukhopadhyay, MD. Program in Global Surgery and Social Change, Harvard University, Department of Surgery, Boston, USA.

Lubna Samad (L)

Lubna Samad, MRCS FCPS. Center for Essential Surgery and Acute Care, Global Health Directorate, Indus Health Network, Karachi, Pakistan.

Classifications MeSH