Perioperative optimisation in low- and middle-income countries (LMICs): A systematic review and meta-analysis of enhanced recovery after surgery (ERAS).

Background: Enhanced recovery after surgery (ERAS) protocols have largely been incorporated into practice in high-income settings due to proven improvement in perioperative outcomes. We aimed to review the implementation of ERAS protocols and other perioperative optimisation strategies in low- and middle-income countries (LMICs) and their impact on length of hospital stay (LOS). Methods: We searched MEDLINE, PubMed, Global Health (CABI), WHO Global Index Medicus, Index Medicus, and Latin American and Caribbean Health Sciences Literature (LILACS) for studies incorporating ERAS or other prehabilitation approaches in LMICs. We conducted a pooled analysis of LOS using a random-effects model to evaluate the impact of such programs. This systematic review was pre-registered on PROSPERO. Results: We screened 1205 studies and included 70 for a full-text review; six were eligible for inclusion and five for quantitative analysis, two of which were randomised controlled trials. ERAS was compared to routine practice in all included studies, while none implemented prehabilitation or other preoperative optimisation strategies. Pooled analysis of 290 patients showed reduced LOS in the ERAS group with a standardised mean difference of -2.18 (95% confidence interval (CI) = -4.13, -.0.05, P < 0.01). The prediction interval was wide (95% CI = -7.85, 3.48) with substantial heterogeneity (I2 = 94%). Conclusions: Perioperative optimisation is feasible in LMICs and appears to reduce LOS, despite high levels of between-study heterogeneity. There is a need for high-quality data on perioperative practice in LMICs and supplementary qualitative analysis to further understand barriers to perioperative optimisation implementation. Registration: PROSPERO: CRD42021279053.

Prognostic models for surgical-site infection in gastrointestinal surgery: systematic review.

BACKGROUND: Identification of patients at high risk of surgical-site infection may allow clinicians to target interventions and monitoring to minimize associated morbidity. The aim of this systematic review was to identify and evaluate prognostic tools for the prediction of surgical-site infection in gastrointestinal surgery. METHODS: This systematic review sought to identify original studies describing the development and validation of prognostic models for 30-day SSI after gastrointestinal surgery (PROSPERO: CRD42022311019). MEDLINE, Embase, Global Health, and IEEE Xplore were searched from 1 January 2000 to 24 February 2022. Studies were excluded if prognostic models included postoperative parameters or were procedure specific. A narrative synthesis was performed, with sample-size sufficiency, discriminative ability (area under the receiver operating characteristic curve), and prognostic accuracy compared. RESULTS: Of 2249 records reviewed, 23 eligible prognostic models were identified. A total of 13 (57 per cent) reported no internal validation and only 4 (17 per cent) had undergone external validation. Most identified operative contamination (57 per cent, 13 of 23) and duration (52 per cent, 12 of 23) as important predictors; however, there remained substantial heterogeneity in other predictors identified (range 2-28). All models demonstrated a high risk of bias due to the analytic approach, with overall low applicability to an undifferentiated gastrointestinal surgical population. Model discrimination was reported in most studies (83 per cent, 19 of 23); however, calibration (22 per cent, 5 of 23) and prognostic accuracy (17 per cent, 4 of 23) were infrequently assessed. Of externally validated models (of which there were four), none displayed 'good' discrimination (area under the receiver operating characteristic curve greater than or equal to 0.7). CONCLUSION: The risk of surgical-site infection after gastrointestinal surgery is insufficiently described by existing risk-prediction tools, which are not suitable for routine use. Novel risk-stratification tools are required to target perioperative interventions and mitigate modifiable risk factors.

This study is about finding ways to predict if someone will get an infection after having surgery on their stomach and intestines. If doctors know who is at high risk of getting an infection, they can take steps to prevent it and help the patient recover faster. The researchers looked at all the recent studies that have tried to predict who might get an infection after surgery. They found 23 studies that were good enough to look at in more detail. The researchers found that the studies they looked at were not very good at predicting who might get an infection. Most of the studies did not even check if their predictions were accurate. The few studies that did check were not very good at it. This means that doctors cannot use these predictions to help their patients. This means that doctors need to find better ways to predict who might get an infection after surgery on their stomach and intestines. If they can do this, they can help their patients recover faster and avoid problems like infections.

Educational impact and recommendations from implementation of student-led clinical trial recruitment: a mixed-methods study.

Medical students have an essential role in medical research, yet often lack opportunities for involvement within randomised trials. This study aimed to understand the educational impact of clinical trial recruitment for medical students. Tracking wound infection with smartphone technology (TWIST) was a randomised controlled trial that included adult patients undergoing emergency abdominal surgery across two university teaching hospitals. All recruiters underwent prerecruitment training based on 'Generating Student Recruiters for Randomised Trials' principles, and completed prerecruitment and postrecruitment surveys. Respondent agreement with statements were assessed using 5-point Likert scales (from 1 ('strongly disagree') to 5 ('strongly agree')). Quantitative data were analysed using paired t-tests to compare differences pre-involvement and post-involvement. Thematic content analysis was performed on free-text data to generate recommendations for future student research involvement. Of 492 patients recruited to TWIST between 26 July 2016 and 4 March 2020, 86.0% (n=423) were recruited by medical students. Following introduction of student co-investigators (n=31), the overall monthly recruitment rate tripled (4.8-15.7 patients). 96.8% of recruiters (n=30/31) completed both surveys, and all respondents reported significant improvement in clinical and academic competencies. Three higher-level thematic domains emerged from the qualitative analysis: (1) engagement, (2) preparation and (3) ongoing support. Student recruitment in clinical trials is feasible and accelerates recruitment to clinical trials. Students demonstrated novel clinical research competencies and increased their likelihood of future involvement. Adequate training, support and selection of suitable trials are essential for future student involvement in randomised trials.

Remote diagnosis of surgical-site infection using a mobile digital intervention: a randomised controlled trial in emergency surgery patients.

Surgical site infections (SSI) cause substantial morbidity and pose a burden to acute healthcare services after surgery. We aimed to investigate whether a smartphone-delivered wound assessment tool can expedite diagnosis and treatment of SSI after emergency abdominal surgery. This single-blinded randomised control trial (NCT02704897) enroled adult emergency abdominal surgery patients in two tertiary care hospitals. Patients were randomised (1:1) to routine postoperative care or additional access to a smartphone-delivered wound assessment tool for 30-days postoperatively. Patient-reported SSI symptoms and wound photographs were requested on postoperative days 3, 7, and 15. The primary outcome was time-to-diagnosis of SSI (Centers for Disease Control definition). 492 patients were randomised (smartphone intervention: 223; routine care: 269). There was no significant difference in the 30-day SSI rate between trial arms: 21 (9.4%) in smartphone vs 20 (7.4%, p = 0.513) in routine care. Among the smartphone group, 32.3% (n = 72) did not utilise the tool. There was no significant difference in time-to-diagnosis of SSI for patients receiving the intervention (-2.5 days, 95% CI: -6.6-1.6, p = 0.225). However, patients in the smartphone group had 3.7-times higher odds of diagnosis within 7 postoperative days (95% CI: 1.02-13.51, p = 0.043). The smartphone group had significantly reduced community care attendance (OR: 0.57, 95% CI: 0.34-0.94, p = 0.030), similar hospital attendance (OR: 0.76, 95% CI: 0.28-1.96, p = 0.577), and significantly better experiences in accessing care (OR: 2.02, 95% CI: 1.17-3.53, p = 0.013). Smartphone-delivered wound follow-up is feasible following emergency abdominal surgery. This can facilitate triage to the appropriate level of assessment required, allowing earlier postoperative diagnosis of SSI.

Characterisation of in-hospital complications associated with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol UK: a prospective, multicentre cohort study.

BACKGROUND: COVID-19 is a multisystem disease and patients who survive might have in-hospital complications. These complications are likely to have important short-term and long-term consequences for patients, health-care utilisation, health-care system preparedness, and society amidst the ongoing COVID-19 pandemic. Our aim was to characterise the extent and effect of COVID-19 complications, particularly in those who survive, using the International Severe Acute Respiratory and Emerging Infections Consortium WHO Clinical Characterisation Protocol UK. METHODS: We did a prospective, multicentre cohort study in 302 UK health-care facilities. Adult patients aged 19 years or older, with confirmed or highly suspected SARS-CoV-2 infection leading to COVID-19 were included in the study. The primary outcome of this study was the incidence of in-hospital complications, defined as organ-specific diagnoses occurring alone or in addition to any hallmarks of COVID-19 illness. We used multilevel logistic regression and survival models to explore associations between these outcomes and in-hospital complications, age, and pre-existing comorbidities. FINDINGS: Between Jan 17 and Aug 4, 2020, 80 388 patients were included in the study. Of the patients admitted to hospital for management of COVID-19, 49·7% (36 367 of 73 197) had at least one complication. The mean age of our cohort was 71·1 years (SD 18·7), with 56·0% (41 025 of 73 197) being male and 81·0% (59 289 of 73 197) having at least one comorbidity. Males and those aged older than 60 years were most likely to have a complication (aged ≥60 years: 54·5% [16 579 of 30 416] in males and 48·2% [11 707 of 24 288] in females; aged <60 years: 48·8% [5179 of 10 609] in males and 36·6% [2814 of 7689] in females). Renal (24·3%, 17 752 of 73 197), complex respiratory (18·4%, 13 486 of 73 197), and systemic (16·3%, 11 895 of 73 197) complications were the most frequent. Cardiovascular (12·3%, 8973 of 73 197), neurological (4·3%, 3115 of 73 197), and gastrointestinal or liver (0·8%, 7901 of 73 197) complications were also reported. INTERPRETATION: Complications and worse functional outcomes in patients admitted to hospital with COVID-19 are high, even in young, previously healthy individuals. Acute complications are associated with reduced ability to self-care at discharge, with neurological complications being associated with the worst functional outcomes. COVID-19 complications are likely to cause a substantial strain on health and social care in the coming years. These data will help in the design and provision of services aimed at the post-hospitalisation care of patients with COVID-19. FUNDING: National Institute for Health Research and the UK Medical Research Council.