Implementation of digital remote postoperative monitoring in routine practice: a qualitative study of barriers and facilitators.

INTRODUCTION: Remote monitoring can strengthen postoperative care in the community and minimise the burden of complications. However, implementation requires a clear understanding of how to sustainably integrate such complex interventions into existing care pathways. This study aimed to explore perceptions of potential facilitators and barriers to the implementation of digital remote postoperative monitoring from key stakeholders and derive recommendations for an implementable service. METHODS: A qualitative implementation study was conducted of digital remote postoperative wound monitoring across two UK tertiary care hospitals. All enrolled patients undergoing general surgery, and all staff involved in postoperative care were eligible. Criterion-based purposeful sampling was used to select stakeholders for semi-structured interviews on their perspectives and experiences of digital remote postoperative monitoring. A theory-informed deductive-inductive qualitative analysis was conducted; drawing on normalisation process theory (NPT) to determine facilitators for and barriers to implementation within routine care. RESULTS: There were 28 semi-structured interviews conducted with patients (n = 14) and healthcare professionals (n = 14). Remote postoperative monitoring was perceived to fulfil an unmet need in facilitating the diagnosis and treatment of postoperative complications. Participants perceived clear benefit to both the delivery of health services, and patient outcomes and experience, but some were concerned that this may not be equally shared due to potential issues with accessibility. The COVID-19 pandemic demonstrated telemedicine services are feasible to deliver and acceptable to participants, with examples of nurse-led remote postoperative monitoring currently supported within local care pathways. However, there was a discrepancy between patients' expectations regarding digital health to provide more personalised care, and the capacity of healthcare staff to deliver on these. Without further investment into IT infrastructure and allocation of staff, healthcare staff felt remote postoperative monitoring should be prioritised only for patients at the highest risk of complications. CONCLUSION: The COVID-19 pandemic has sparked the digital transformation of international health systems, yet the potential of digital health interventions has yet to be realised. The benefits to stakeholders are clear, and if health systems seek to meet governmental policy and patient expectations, there needs to be greater organisational strategy and investment to ensure appropriate deployment and adoption into routine care. TRIAL REGISTRATION: NCT05069103.

Is socioeconomic deprivation associated with worse quality of life, anxiety and depression in liver transplant recipients? A cross-sectional study in a national transplantation programme.

OBJECTIVE: To identify whether socioeconomic deprivation is associated with worse health-related quality of life (HR-QoL), anxiety and depression following liver transplantation. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: Liver transplant recipients within a national transplantation programme. METHODS: Participants completed the condition-specific 'Short Form of Liver Disease Quality of Life' Questionnaire, the Generalised Anxiety Disorder-7 (GAD-7) Questionnaire and the Patient Health Questionnaire-9 (PHQ-9). The aggregate HR-QoL Score (range 0-100) was derived, and multivariable linear regression was performed based on sociodemographic and clinical variables to estimate its independent association with Scottish Index of Multiple Deprivation (SIMD) quintiles. The GAD-7 Questionnaire and PHQ-9 were used to screen respondents for anxiety and depression, and multivariable logistic regression was performed to estimate their independent association with SIMD quintiles. RESULTS: Some 331 patients completed the questionnaires. Quintiles were equally distributed in the cohort, with no significant differences observed in underlying patient characteristics. Following multivariable adjustment, greater socioeconomic deprivation was associated with lower post-transplantation HR-QoL scores, with a difference of 9.7 points (95% CI: 4.6 to 14.9, p<0.001) between the most and least deprived quintiles. Recipients living in areas of least deprivation were less likely to suffer from anxiety (OR 0.05, 95% CI: 0.00 to 0.28, p=0.003) or depression (OR 0.13, 95% CI: 0.02 to 0.56, p=0.009). CONCLUSION: Despite the highly selected nature of liver transplant recipients, those living in the most deprived areas have a significantly lower HR-QoL and are more likely to suffer from anxiety and depression.

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.

Evaluation of remote digital postoperative wound monitoring in routine surgical practice.

Remote digital postoperative wound monitoring provides an opportunity to strengthen postoperative community care and minimise the burden of surgical-site infection (SSI). This study aimed to pilot a remote digital postoperative wound monitoring service and evaluate the readiness for implementation in routine clinical practice. This was a single-arm pilot implementational study of remote digital postoperative wound monitoring across two tertiary care hospitals in the UK (IDEAL stage 2b, clinicaltrials.gov: NCT05069103). Adults undergoing abdominal surgery were recruited and received a smartphone-delivered wound assessment tool for 30-days postoperatively. Patients received 30-day postoperative follow-up, including the Telehealth Usability Questionnaire (TUQ). A thematic mixed-methods approach was used, according to the WHO framework for monitoring and evaluating digital health interventions. 200 patients were enroled, of whom 115 (57.5%) underwent emergency surgical procedures. Overall, the 30-day SSI rate was 16.5% (n = 33/200), with 72.7% (n = 24) diagnosed post-discharge. Usage of the intervention was 83.0% (n = 166/200), with subsequently 74.1% (n = 123/166) TUQ completion. There were no issues reported with feasibility of the technology, with the reliability (3.87, 95% CI: 3.73-4.00) and quality of the interface rated highly (4.18, 95%: 4.06-4.30). Patient acceptance was similarly high with regards to ease of use (4.51, 95% CI: 4.41-4.62), satisfaction (4.27, 95% CI: 4.13-4.41), and usefulness (4.07, 95% CI: 3.92-4.23). Despite the desire for more frequent and personalised interactions, the majority viewed the intervention as providing meaningful benefit over routine postoperative care. Remote digital postoperative wound monitoring successfully demonstrated readiness for implementation with regards to the technology, usability, and healthcare process improvement.

Readiness for implementation of novel digital health interventions for postoperative monitoring: a systematic review and clinical innovation network analysis.

An increasing number of digital health interventions (DHIs) for remote postoperative monitoring have been developed and evaluated. This systematic review identifies DHIs for postoperative monitoring and evaluates their readiness for implementation into routine health care. Studies were defined according to idea, development, exploration, assessment, and long-term follow-up (IDEAL) stages of innovation. A novel clinical innovation network analysis used coauthorship and citations to examine collaboration and progression within the field. 126 DHIs were identified, with 101 (80%) being early stage innovations (IDEAL stage 1 and 2a). None of the DHIs identified had large-scale routine implementation. There is little evidence of collaboration, and there are clear omissions in the evaluation of feasibility, accessibility, and the health-care impact. Use of DHIs for postoperative monitoring remains at an early stage of innovation, with promising but generally low-quality supporting evidence. Comprehensive evaluation within high-quality, large-scale trials and real-world data are required to definitively establish readiness for routine implementation.

Development stage of novel digital health interventions for postoperative monitoring: protocol of a systematic review.

Introduction: The postoperative period represents a time where patients are at a high-risk of morbidity, which warrants effective surveillance. While digital health interventions (DHIs) for postoperative monitoring are promising, a coordinated, standardized and evidence-based approach regarding their implementation and evaluation is currently lacking. This study aimed to identify DHIs implemented and evaluated in postoperative care to highlight research gaps and assess the readiness for routine implementation. Methods: A systematic review will be conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify studies describing the implementation and evaluation of DHIs for postoperative monitoring published since 2000 (PROSPERO ID: CRD42021264289). This will encompass the Embase, Cumulative Index to Nursing and Allied Health Literature, Cochrane Library, Web of Science and ClinicalTrials.gov databases, and manual search of bibliographies for relevant studies and gray literature. Methodological reporting quality will be evaluated using the Idea, Development, Exploration, Assessment and Long-term Follow-up (IDEAL) reporting guideline relevant to the IDEAL stage of the study, and risk of bias will be assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework. Data will be extracted according to the WHO framework for monitoring and evaluating DHIs, and a narrative synthesis will be performed. Discussion: This review will assess the readiness for implementation of DHIs for routine postoperative monitoring and will include studies describing best practice from service changes already being piloted out of necessity during the COVID-19 pandemic. This will identify interventions with sufficient evidence to progress to the next IDEAL stage, and promote standardized and comprehensive evaluation of future implementational studies.

Prospective validation of the 4C prognostic models for adults hospitalised with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol.

PURPOSE: To prospectively validate two risk scores to predict mortality (4C Mortality) and in-hospital deterioration (4C Deterioration) among adults hospitalised with COVID-19. METHODS: Prospective observational cohort study of adults (age ≥18 years) with confirmed or highly suspected COVID-19 recruited into the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study in 306 hospitals across England, Scotland and Wales. Patients were recruited between 27 August 2020 and 17 February 2021, with at least 4 weeks follow-up before final data extraction. The main outcome measures were discrimination and calibration of models for in-hospital deterioration (defined as any requirement of ventilatory support or critical care, or death) and mortality, incorporating predefined subgroups. RESULTS: 76 588 participants were included, of whom 27 352 (37.4%) deteriorated and 12 581 (17.4%) died. Both the 4C Mortality (0.78 (0.77 to 0.78)) and 4C Deterioration scores (pooled C-statistic 0.76 (95% CI 0.75 to 0.77)) demonstrated consistent discrimination across all nine National Health Service regions, with similar performance metrics to the original validation cohorts. Calibration remained stable (4C Mortality: pooled slope 1.09, pooled calibration-in-the-large 0.12; 4C Deterioration: 1.00, -0.04), with no need for temporal recalibration during the second UK pandemic wave of hospital admissions. CONCLUSION: Both 4C risk stratification models demonstrate consistent performance to predict clinical deterioration and mortality in a large prospective second wave validation cohort of UK patients. Despite recent advances in the treatment and management of adults hospitalised with COVID-19, both scores can continue to inform clinical decision making. TRIAL REGISTRATION NUMBER: ISRCTN66726260.

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.

Mobile devices and wearable technology for measuring patient outcomes after surgery: a systematic review.

Complications following surgery are common and frequently occur the following discharge. Mobile and wearable digital health interventions (DHI) provide an opportunity to monitor and support patients during their postoperative recovery. Lack of high-quality evidence is often cited as a barrier to DHI implementation. This review captures and appraises the current use, evidence base and reporting quality of mobile and wearable DHI following surgery. Keyword searches were performed within Embase, Cochrane Library, Web of Science and WHO Global Index Medicus databases, together with clinical trial registries and Google scholar. Studies involving patients undergoing any surgery requiring skin incision where postoperative outcomes were measured using a DHI following hospital discharge were included, with DHI defined as mobile and wireless technologies for health to improve health system efficiency and health outcomes. Methodological reporting quality was determined using the validated mobile health evidence reporting and assessment (mERA) guidelines. Bias was assessed using the Cochrane Collaboration tool for randomised studies or MINORS depending on study type. Overall, 6969 articles were screened, with 44 articles included. The majority (n = 34) described small prospective study designs, with a high risk of bias demonstrated. Reporting standards were suboptimal across all domains, particularly in relation to data security, prior patient engagement and cost analysis. Despite the potential of DHI to improve postoperative patient care, current progress is severely restricted by limitations in methodological reporting. There is an urgent need to improve reporting for DHI following surgery to identify patient benefit, promote reproducibility and encourage sustainability.

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.

Global burden of acute lower respiratory infection associated with human parainfluenza virus in children younger than 5 years for 2018: a systematic review and meta-analysis.

BACKGROUND: Human parainfluenza virus (hPIV) is a common virus in childhood acute lower respiratory infections (ALRI). However, no estimates have been made to quantify the global burden of hPIV in childhood ALRI. We aimed to estimate the global and regional hPIV-associated and hPIV-attributable ALRI incidence, hospital admissions, and mortality for children younger than 5 years and stratified by 0-5 months, 6-11 months, and 12-59 months of age. METHODS: We did a systematic review of hPIV-associated ALRI burden studies published between Jan 1, 1995, and Dec 31, 2020, found in MEDLINE, Embase, Global Health, Cumulative Index to Nursing and Allied Health Literature, Web of Science, Global Health Library, three Chinese databases, and Google search, and also identified a further 41 high-quality unpublished studies through an international research network. We included studies reporting community incidence of ALRI with laboratory-confirmed hPIV; hospital admission rates of ALRI or ALRI with hypoxaemia in children with laboratory-confirmed hPIV; proportions of patients with ALRI admitted to hospital with laboratory-confirmed hPIV; or in-hospital case-fatality ratios (hCFRs) of ALRI with laboratory-confirmed hPIV. We used a modified Newcastle-Ottawa Scale to assess risk of bias. We analysed incidence, hospital admission rates, and hCFRs of hPIV-associated ALRI using a generalised linear mixed model. Adjustment was made to account for the non-detection of hPIV-4. We estimated hPIV-associated ALRI cases, hospital admissions, and in-hospital deaths using adjusted incidence, hospital admission rates, and hCFRs. We estimated the overall hPIV-associated ALRI mortality (both in-hospital and out-hospital mortality) on the basis of the number of in-hospital deaths and care-seeking for child pneumonia. We estimated hPIV-attributable ALRI burden by accounting for attributable fractions for hPIV in laboratory-confirmed hPIV cases and deaths. Sensitivity analyses were done to validate the estimates of overall hPIV-associated ALRI mortality and hPIV-attributable ALRI mortality. The systematic review protocol was registered on PROSPERO (CRD42019148570). FINDINGS: 203 studies were identified, including 162 hPIV-associated ALRI burden studies and a further 41 high-quality unpublished studies. Globally in 2018, an estimated 18·8 million (uncertainty range 12·8-28·9) ALRI cases, 725 000 (433 000-1 260 000) ALRI hospital admissions, and 34 400 (16 400-73 800) ALRI deaths were attributable to hPIVs among children younger than 5 years. The age-stratified and region-stratified analyses suggested that about 61% (35% for infants aged 0-5 months and 26% for 6-11 months) of the hospital admissions and 66% (42% for infants aged 0-5 months and 24% for 6-11 months) of the in-hospital deaths were in infants, and 70% of the in-hospital deaths were in low-income and lower-middle-income countries. Between 73% and 100% (varying by outcome) of the data had a low risk in study design; the proportion was 46-65% for the adjustment for health-care use, 59-77% for patient groups excluded, 54-93% for case definition, 42-93% for sampling strategy, and 67-77% for test methods. Heterogeneity in estimates was found between studies for each outcome. INTERPRETATION: We report the first global burden estimates of hPIV-associated and hPIV-attributable ALRI in young children. Globally, approximately 13% of ALRI cases, 4-14% of ALRI hospital admissions, and 4% of childhood ALRI mortality were attributable to hPIV. These numbers indicate a potentially notable burden of hPIV in ALRI morbidity and mortality in young children. These estimates should encourage and inform investment to accelerate the development of targeted interventions. FUNDING: Bill & Melinda Gates Foundation.

Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study.

BACKGROUND: Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions. METHODS: We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal-external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London). FINDINGS: 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal-external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [-0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model. INTERPRETATION: The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19. FUNDING: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London.

Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score.

OBJECTIVE: To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). DESIGN: Prospective observational cohort study. SETTING: International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium-ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020. PARTICIPANTS: Adults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction. MAIN OUTCOME MEASURE: In-hospital mortality. RESULTS: 35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). CONCLUSIONS: An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations. STUDY REGISTRATION: ISRCTN66726260.

Can a smartphone-delivered tool facilitate the assessment of surgical site infection and result in earlier treatment? Tracking wound infection with smartphone technology (TWIST): protocol for a randomised controlled trial in emergency surgery patients.

INTRODUCTION: National data suggest that surgical site infection (SSI) complicates 2%-10% of general surgery cases, although the patient-reported incidence is much higher. SSIs cause significant patient morbidity and represent a significant burden on acute healthcare services, in a cohort predominantly suitable for outpatient management. Over three-quarters of UK adults now own smartphones, which could be harnessed to improve access to care. We aim to investigate if a smartphone-delivered wound assessment tool results in earlier treatment. METHODS AND ANALYSIS: This is a randomised controlled trial aiming to recruit 500 patients across National Health Service (NHS) hospitals. All emergency abdominal surgery patients over the age of 16 who own smartphones will be considered eligible, with the exclusion of those with significant visual impairment. Participants will be randomised in a 1:1 ratio between standard postoperative care and the intervention - use of the smartphone tool in addition to standard postoperative care. The main outcome measure will be time-to-diagnosis of SSI with secondary outcome measures considering use of emergency department and general practitioner services and patient experience. Follow-up will be conducted by clinicians blinded to group allocation. Analysis of time-to-diagnosis will be by comparison of means using an independent two sample t-test. ETHICS AND DISSEMINATION: This is the first randomised controlled trial on the use of a smartphone-delivered wound assessment tool to facilitate the assessment of SSI and the impact on time-to-diagnosis. The intervention is being used in addition to standard postoperative care. The study design and protocol were reviewed and approved by Southeast Scotland Research and Ethics Committee (REC Ref: 16/SS/0072 24/05/2016). Study findings will be presented at academic conferences, published in peer-reviewed journals and are expected in 2020. A written lay summary will be available to study participants on request. TRIAL REGISTRATION NUMBER: NCT02704897; Pre-results.

The effect of liver transplantation on patient-centred outcomes: a propensity-score matched analysis.

It is unclear whether liver transplantation confers an increase in health-related quality of life (HR-QoL) across all dimensions of health. This study aimed to estimate the effect of liver transplantation on HR-QoL. Pre- and post-transplantation patients attending an outpatient clinic were invited to complete the condition-specific 'Short form of liver disease QOL' questionnaire. Mixed-effect linear regression and propensity-score matching (PSM) on pretransplantation characteristics were used to estimate the difference in overall HR-QoL associated with transplantation. Of 454/609 (74.5%) eligible patients who were included in the analysis, 102 (22.5%) patients fall under pretransplantation category, and 352 (77.5%) were under post-transplantation category. Overall HR-QoL post-transplantation significantly increased in patients without hepatocellular carcinoma (HCC) (ß = 16.84, 95% CI: 13.33 to 20.35, P < 0.001), but not with HCC (ß = 1.25, 95% CI: -5.09 to 7.60, P = 0.704). Donation after circulatory death (DCD) organ recipients had a significantly lower HR-QoL (ß = -4.61, 95% CI: -8.95 to -0.24, P = 0.043). Following PSM, transplantation was associated with a significant increase in overall HR-QoL (average treatment effect: 6.3, 95% CI: 2.1-10.9). There is a significant improvement in HR-QoL attributable to transplantation in this cohort. Post-transplantation HR-QoL was affected by several factors, including HCC status and DCD transplantation, which has important implications for counselling prior to liver transplantation.