Conectar
Being on a waiting list for elective (planned) cardiac surgery can be physically and psychologically challenging for patients. Research suggests that stress associated with waiting for surgery is dependent on different individual and contextual factors. However, most data on patients’ experiences of waiting for surgery and preferences for waiting list management derives from non-cardiac clinical populations. The aim of the current study is to explore patients’ experiences of being on a waiting list for elective cardiac surgery, and their views on how the waiting experience could be improved in the future. This work will inform the patient management strategy during the waiting period for surgery across the four major hospitals in London directly involved in this study, and potentially beyond by transferring learning to other services.
This is a mixed-methods study that will collect quantitative and qualitative data using a cross-sectional online survey. Patients who are on waiting lists for elective surgery across four major cardiac surgery departments in London hospitals, and are at least 18 years old, will be invited by their healthcare team via text message or letter to complete the survey. The target sample size of non-randomly selected participants will be 268. Bivariable and multivariable regression models will be used to assess associations between survey items measuring the impact of the cardiac condition on specific life domains (eg, daily activities, social and family relationships, hobbies, sexual life), anxiety and depression symptoms as measured by the Patient Health Questionnaire-4 and survey items evaluating experiences of health services. Data on experience and preferences for improvements to the waiting experience will be analysed with qualitative content analysis using an inductive approach.
This study was reviewed and granted ethical approval by the East of England—East Cambridge Research Ethics Committee. Findings from this study will be disseminated through peer-reviewed journals, a research website and social media and with an online event engaging patients, members of the public, healthcare professionals and other relevant stakeholders.
The present systematic review and meta-analysis aimed to determine the prevalence of surgical site infection (SSI) and related factors in patients after foot and ankle surgery. A comprehensive, systematic search was conducted in different international electronic databases, such as Scopus, PubMed, Web of Science and Persian electronic databases such as Iranmedex and Scientific Information Database (SID) using keywords extracted from Medical Subject Headings such as ‘Prevalence’, ‘Surgical wound infection’, ‘Surgical site infection’ and ‘Orthopaedics’ from the earliest to 1 June 2023. The appraisal tool for cross-sectional studies (AXIS tool) evaluates the quality of the included studies. A total of 10 447 patients undergoing foot and ankle surgery participated in nine studies. The pooled prevalence of SSI in patients who underwent foot and ankle surgery was reported in nine studies was 4.2% (95% CI: 2.4%–7.2%; I2 = 96.793%; p < 0.001). The odds ratio of SSI prevalence in men was higher than that of women and was significant (OR: 1.335; 95% CI: 1.106–1.612; Z = 3.009; p = 0.003). The pooled prevalence of SSI in patients with hindfoot fracture sites reported in five studies was 4.9% (95% CI: 2.6%–8.9%; I2 = 90.768%; p < 0.001). The pooled prevalence of SSI in patients with diabetes mellitus (DM) reported in six studies was 9.1% (95% CI: 5.6%–14.6%; I2 = 73.957%; p = 0.002). The pooled prevalence of SSI in patients with hypertension (HTN) reported in five studies was 5.5% (95% CI: 2.5%–11.6%; I2 = 91.346%; p < 0.001). The pooled prevalence of SSI in patients with tobacco use reported in eight studies was 6.6% (95% CI: 4.1%–10.4%; I2 = 85.379%; p < 0.001). In general, the existing differences in the prevalence of SSI after foot and ankle surgery in different studies can be based on different risk factors such as comorbidities and gender. Therefore, it is suggested to design appropriate interventions to reduce SSI in these patients.
The goal of this systematic review and meta-analysis is to provide an overview of the prevalence of surgical wound infection and related factors in patients after long bone surgery. A comprehensive, systematic search was conducted in different international electronic databases, such as Scopus, PubMed, Web of Science and Persian electronic databases such as Iranmedex and Scientific Information Database using keywords extracted from Medical Subject Headings such as “Prevalence”, “Surgical wound infection”, “Surgical site infection” and “Orthopedics” from the earliest to the May 1, 2023. The appraisal tool for cross-sectional studies (AXIS tool) evaluates the quality of the included studies. A total of 71 854 patients undergoing long bone surgery participated in 12 studies. The pooled prevalence of surgical wound infection in patients who underwent long bone surgery reported in the 12 studies was 3.3% (95% CI: 1.5%–7.2%; I 2 = 99.39%; p < 0.001). The pooled prevalence of surgical wound infection in male and female patients who underwent long bone surgery was 4.6% (95% CI: 1.7%–11.7%; p < 0.001; I 2 = 99.34%) and 2.6% (95% CI: 1.0%–6.3%; I 2 = 98.84%; p < 0.001), respectively. The pooled prevalence of surgical wound infection in patients with femur surgery sites reported in nine studies was 3.7% (95% CI: 2.1–6.4%; I 2 = 93.43%; p < 0.001). The pooled prevalence of surgical wound infection in open and close fractures was 16.4% (95% CI: 8.2%–30.2%; I 2 = 95.83%; p < 0.001) and 2.9% (95% CI: 1.5%–5.5%; I 2 = 96.40%; p < 0.001), respectively. The pooled prevalence of surgical wound infection in patients with diabetes mellitus (DM), hypertension (HTN) and cardiovascular disease (CVD) was 4.6% (95% CI: 2.3%–8.9%; I 2 = 81.50%; p < 0.001), 2.7% (95% CI: 1.2%–6.0%; I 2 = 83.82%; p < 0.001) and 3.0% (95% CI: 1.4%–6.4%; I 2 = 69.12%; p = 0.006), respectively. In general, the different prevalence of surgical wound infection in patients undergoing surgical treatment after long bone fracture may be caused by underlying factors (gender and co-morbidity) and fracture-related factors (surgery site and type of fracture).
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