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Chatbot on the Prevention of Postoperative Complications

Comparison of Traditional Nurse-led Education and Chatbot on the Prevention of Postoperative Complications After Major Visceral Surgery: a Randomized Controlled Trial

Status
Not yet recruiting
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT06624995
Enrollment
214
Registered
2024-10-03
Start date
2024-11-30
Completion date
2025-04-30
Last updated
2024-10-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Visceral Surgery Complications

Brief summary

Major visceral surgery encompasses a broad range of operations with a wide variety of procedures that fall under this category. The majority of patients undergoing major visceral surgery often present with cancer and other medical comorbidities and are put at an elevated risk of a large number of medical and surgical postoperative complications

Detailed description

Complications following major visceral surgery are relatively common and are estimated to occur in 18-23% of patients . The management of complications is challenging for both the elderly patient and the perioperative team, and adds considerably to the cost of care particularly when further interventions involve readmission, unplanned admission to an intensive care unit, interventional radiology and/or an unplanned return to theatre. With the advancement of online patient portals, the use of internet to seek for health information is already a common phenomenon; Chatbot may become a more significant source of information for patients.

Interventions

OTHERchatbot education

elderly patients interacted with Chatbot to discuss general postoperative complication related inquiries

Sponsors

Mansoura University
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION
Masking
DOUBLE (Caregiver, Outcomes Assessor)

Eligibility

Sex/Gender
ALL
Age
60 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Patients aged 60 years old and above, both sex, scheduled for elective major visceral surgery, able to communicate in the local language, and without any cognitive impairment.

Exclusion criteria

* Elderly patients with a history of major psychiatric disorders, patients with a history of previous major visceral surgery, and patients who were unable to provide informed consent will be excluded from the study.

Design outcomes

Primary

MeasureTime frameDescription
postoperative morbiditypatient will be evaluated at three time points: 24 hour postoperative; 48 hours postoperative , and 30 days postoperative.using the postoperative morbidity survey , Patients are assessed for diagnostic features in nine domains (pulmonary, infectious, renal, gastrointestinal, cardiovascular, neurological, haematological, wound and pain). For each of the nine domains morbidity is recorded on the presence or absence of preset criteria and it appears to accurately describe the pattern and prevalence of morbidity in the postoperative setting. I

Secondary

MeasureTime frameDescription
Geriatric anxietywill be measured at three time points: 90 to 120 minutes before the preoperative consultation (baseline ); after 7 days postoperative, and after 30 days postoperativequestionnaire comprising 30 items, called the GAS was created to evaluate, screen for, and quantify the intensity of anxiety symptoms in older persons
quality of lifewill be measured at two time points : at baseline (preoperative ) and after 30 days postoperativeThis short version of the SF-36 tool consists of 12 items and eight scales: physical functioning (PF), role limitations due to physical problems (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role limitations due to emotional problems (RE), and perceived mental health (MH).
usability of using chatbots4 weeks postoperativelyThis scale was composed of 16 validated items aimed to assess the personality, onboarding, navigation, understanding, responses, error handling and intelligence of a chatbot.

Contacts

Primary Contactmohamed hamed elzeky, phd
mohamadelzeky@mans.edu.eg+201040627871
Backup Contactnoha fathy shahine, phd
nohafathy@mans.edu.eg+201098375398

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026