Use and impact of virtual primary care on quality and safety: The public's perspectives during the COVID-19 pandemic

INTRODUCTION

With the onset of Coronavirus disease (COVID-19), primary care has swiftly transitioned from face-to-face to virtual care, yet it remains largely unknown how this has impacted the quality and safety of care. We aim to evaluate patient use of virtual primary care models during COVID-19, including change in uptake, perceived impact on the quality and safety of care and willingness of future use.

METHODOLOGY

An online cross-sectional survey was administered to the public across the United Kingdom, Sweden, Italy and Germany. McNemar tests were conducted to test pre- and post-pandemic differences in uptake for each technology. One-way analysis of variance was conducted to examine patient experience ratings and perceived impacts on healthcare quality and safety across demographic characteristics.

RESULTS

Respondents (n = 6326) reported an increased use of telephone consultations ( + 6.3%, p < .001), patient-initiated services ( + 1.5%, n = 98, p < 0.001), video consultations ( + 1.4%, p < .001), remote triage ( + 1.3, p < 0.001) and secure messaging systems ( + 0.9%, p = .019). Experience rates using virtual care technologies were higher for men (2.4  ±  1.0 vs. 2.3  ±  0.9, p < .001), those with higher literacy (2.8  ±  1.0 vs. 2.3  ±  0.9, p < .001), and participants from Germany (2.5  ±  0.9, p < .001). Healthcare timeliness and efficiency were the dimensions most often reported as being positively impacted by virtual technologies (60.2%, n = 2793 and 55.7%, n = 2,401, respectively), followed by effectiveness (46.5%, n = 1802), safety (45.5%, n = 1822), patient-centredness (45.2%, n = 45.2) and equity (42.9%, n = 1726). Interest in future use was highest for telephone consultations (55.9%), patient-initiated digital services (56.1%), secure messaging systems (43.4%), online triage (35.1%), video consultations (37.0%) and chat consultations (30.1%), although significant variation was observed between countries and patient characteristics.

DISCUSSION

Future work must examine the drivers and determinants of positive experiences using remote care to co-create a supportive environment that ensures equitable adoption and use. Comparative analysis between countries and health systems offers the opportunity for policymakers to learn from best practices internationally.

Summary Paper of the Updated 2023 European Association of Urology Guidelines on Urological Trauma

CONTEXT

The European Association of Urology (EAU) Guidelines Panel for Urological Trauma has produced guidelines in order to assist medical professionals in the management of urological trauma in adults for the past 20 yr. It must be emphasised that clinical guidelines present the best evidence available to the experts, but following guideline recommendations will not necessarily result in the best outcome. Guidelines can never replace clinical expertise when making treatment decisions for individual patients regarding other parameters such as experience and available facilities. Guidelines are not mandates and do not purport to be a legal standard of care.

OBJECTIVE

To present a summary of the 2023 version of the EAU guidelines on the management of urological trauma.

EVIDENCE ACQUISITION

A systematic literature search was conducted from 1966 to 2022, and articles with the highest certainty evidence were selected. It is important to note that due to its nature, genitourinary trauma literature still relies heavily on expert opinion and retrospective series.

EVIDENCE SYNTHESIS

Databases searched included Medline, EMBASE, and the Cochrane Libraries, covering a time frame between May 1, 2021 and April 29, 2022. A total of 1236 unique records were identified, retrieved, and screened for relevance.

CONCLUSIONS

The guidelines provide an evidence-based approach for the management of urological trauma.

PATIENT SUMMARY

Trauma is a serious public health problem with significant social and economic costs. Urological trauma is common; traffic accidents, falls, intrapersonal violence, and iatrogenic injuries are the main causes. Developments in technology, continuous training of medical professionals, and improved care of polytrauma patients reduce morbidity and maximise the opportunity for quick recovery.

Orthopaedic infections: what have we learned?

Orthopaedic infections remain challenging complications to treat, with profound economic impact in addition to patient morbidity. The overall estimates of infection after orthopaedic surgery with internal devices has been estimated at 5%, with hospital costs eight times that of those without fracture-related infections and with significantly poorer functional and pain interference PROMIS scores. Orthopaedic infection interventions have been focused on prevention and treatment options. The creation of new modalities for orthopaedic infection treatment can benefit from the understanding of the temporal relationship between bacterial colonization and host-cell integration, a concept referred to as "the race for the surface." Regarding prevention, host modulation and antibiotic powder use have been explored as viable options to lower infection rates. Orthopaedic infection treatment has additionally continued to evolve, with PO antibiotics demonstrating equivalent efficacy to IV antibiotics for the treatment of orthopaedic infections in recent studies. In conclusion, orthopaedic infections remain difficult clinical dilemmas, although evolving prevention and treatment modalities continue to emerge.

Increase in hypoglycaemia and hyperglycaemia in people with diabetes admitted to hospital during COVID-19 pandemic

BACKGROUND

We used detailed information on patients with diabetes admitted to hospital to determine differences in clinical outcomes before and during the COVID-19 pandemic in the UK.

METHODS

The study used electronic patient record data from Imperial College Healthcare NHS Trust. Hospital admission data for patients coded for diabetes was analysed over three time periods: pre-pandemic (31st January 2019-31st January 2020), Wave 1 (1st February 2020-30th June 2020), and Wave 2 (1st September 2020-30th April 2021). We compared clinical outcomes including glycaemia and length of stay.

RESULTS

We analysed data obtained from 12,878, 4008 and 7189 hospital admissions during the three pre-specified time periods. The incidence of Level 1 and Level 2 hypoglycaemia was significantly higher during Waves 1 and 2 compared to the pre-pandemic period (25 % and 25.1 % vs. 22.9 % for Level 1 and 11.7 % and 11.5 % vs. 10.3 % for Level 2). The incidence of hyperglycaemia was also significantly higher during the two waves. The median hospital length of stay increased significantly (4.1[1.6, 9.8] and 4.0[1.4, 9.4] vs. 3.5[1.2, 9.2] days).

CONCLUSIONS

During the COVID-19 pandemic in the UK, hospital in-patients with diabetes had a greater number of hypoglycaemic/hyperglycaemic episodes and an increased length of stay when compared to the pre-pandemic period. This highlights the necessity for a focus on improved diabetes care during further significant disruptions to healthcare systems and ensuring minimisation of the impact on in-patient diabetes services.

SUMMARY

Diabetes is associated with poorer outcomes from COVID-19. However the glycaemic control of inpatients before and during the COVID-19 pandemic is unknown. We found the incidence of hypoglycaemia and hyperglycaemia was significantly higher during the pandemic highlighting the necessity for a focus on improved diabetes care during further pandemics.

How do hospital inpatients conceptualise patient safety? A qualitative interview study using constructivist grounded theory

BACKGROUND

Efforts to involve patients in patient safety continue to revolve around professionally derived notions of minimising clinical risk, yet evidence suggests that patients hold perspectives on patient safety that are distinct from clinicians and academics. This study aims to understand how hospital inpatients across three different specialties conceptualise patient safety and develop a conceptual model that reflects their perspectives.

METHODS

A qualitative semi-structured interview study was conducted with 24 inpatients across three clinical specialties (medicine for the elderly, elective surgery and maternity) at a large central London teaching hospital. An abbreviated form of constructivist grounded theory was employed to analyse interview transcripts. Constant comparative analysis and memo-writing using the clustering technique were used to develop a model of how patients conceptualise patient safety.

RESULTS

While some patients described patient safety using terms consistent with clinical/academic definitions, patients predominantly conceptualised patient safety in the context of what made them 'feel safe'. Patients' feelings of safety arose from a range of care experiences involving specific actors: hospital staff, the patient, their friends/family/carers, and the healthcare organisation. Four types of experiences contributed to how patients conceptualise safety: actions observed by patients; actions received by patients; actions performed by patients themselves; and shared actions involving patients and other actors in their care.

CONCLUSIONS

Our findings support the need for a patient safety paradigm that is meaningful to all stakeholders, incorporating what matters to patients to feel safe in hospital. Additional work should explore and test how the proposed conceptual model can be practically applied and implemented to incorporate the patient conceptualisation of patient safety into everyday clinical practice.

Remote COVID-19 Assessment in Primary Care (RECAP) risk prediction tool: derivation and real-world validation studies

BACKGROUND

Accurate assessment of COVID-19 severity in the community is essential for patient care and requires COVID-19-specific risk prediction scores adequately validated in a community setting. Following a qualitative phase to identify signs, symptoms, and risk factors, we aimed to develop and validate two COVID-19-specific risk prediction scores. Remote COVID-19 Assessment in Primary Care-General Practice score (RECAP-GP; without peripheral oxygen saturation [SpO2]) and RECAP-oxygen saturation score (RECAP-O2; with SpO2).

METHODS

RECAP was a prospective cohort study that used multivariable logistic regression. Data on signs and symptoms (predictors) of disease were collected from community-based patients with suspected COVID-19 via primary care electronic health records and linked with secondary data on hospital admission (outcome) within 28 days of symptom onset. Data sources for RECAP-GP were Oxford-Royal College of General Practitioners Research and Surveillance Centre (RCGP-RSC) primary care practices (development set), northwest London primary care practices (validation set), and the NHS COVID-19 Clinical Assessment Service (CCAS; validation set). The data source for RECAP-O2 was the Doctaly Assist platform (development set and validation set in subsequent sample). The two probabilistic risk prediction models were built by backwards elimination using the development sets and validated by application to the validation datasets. Estimated sample size per model, including the development and validation sets was 2880 people.

FINDINGS

Data were available from 8311 individuals. Observations, such as SpO2, were mostly missing in the northwest London, RCGP-RSC, and CCAS data; however, SpO2 was available for 1364 (70·0%) of 1948 patients who used Doctaly. In the final predictive models, RECAP-GP (n=1863) included sex (male and female), age (years), degree of breathlessness (three point scale), temperature symptoms (two point scale), and presence of hypertension (yes or no); the area under the curve was 0·80 (95% CI 0·76-0·85) and on validation the negative predictive value of a low risk designation was 99% (95% CI 98·1-99·2; 1435 of 1453). RECAP-O2 included age (years), degree of breathlessness (two point scale), fatigue (two point scale), and SpO2 at rest (as a percentage); the area under the curve was 0·84 (0·78-0·90) and on validation the negative predictive value of low risk designation was 99% (95% CI 98·9-99·7; 1176 of 1183).

INTERPRETATION

Both RECAP models are valid tools to assess COVID-19 patients in the community. RECAP-GP can be used initially, without need for observations, to identify patients who require monitoring. If the patient is monitored and SpO2 is available, RECAP-O2 is useful to assess the need for treatment escalation.

FUNDING

Community Jameel and the Imperial College President's Excellence Fund, the Economic and Social Research Council, UK Research and Innovation, and Health Data Research UK.

Differences in Clinical Presentation With Long COVID After Community and Hospital Infection and Associations With All-Cause Mortality: English Sentinel Network Database Study

BACKGROUND

Most studies of long COVID (symptoms of COVID-19 infection beyond 4 weeks) have focused on people hospitalized in their initial illness. Long COVID is thought to be underrecorded in UK primary care electronic records.

OBJECTIVE

We sought to determine which symptoms people present to primary care after COVID-19 infection and whether presentation differs in people who were not hospitalized, as well as post-long COVID mortality rates.

METHODS

We used routine data from the nationally representative primary care sentinel cohort of the Oxford-Royal College of General Practitioners Research and Surveillance Centre (N=7,396,702), applying a predefined long COVID phenotype and grouped by whether the index infection occurred in hospital or in the community. We included COVID-19 infection cases from March 1, 2020, to April 1, 2021. We conducted a before-and-after analysis of long COVID symptoms prespecified by the Office of National Statistics, comparing symptoms presented between 1 and 6 months after the index infection matched with the same months 1 year previously. We conducted logistic regression analysis, quoting odds ratios (ORs) with 95% CIs.

RESULTS

In total, 5.63% (416,505/7,396,702) and 1.83% (7623/416,505) of the patients had received a coded diagnosis of COVID-19 infection and diagnosis of, or referral for, long COVID, respectively. People with diagnosis or referral of long COVID had higher odds of presenting the prespecified symptoms after versus before COVID-19 infection (OR 2.66, 95% CI 2.46-2.88, for those with index community infection and OR 2.42, 95% CI 2.03-2.89, for those hospitalized). After an index community infection, patients were more likely to present with nonspecific symptoms (OR 3.44, 95% CI 3.00-3.95; P<.001) compared with after a hospital admission (OR 2.09, 95% CI 1.56-2.80; P<.001). Mental health sequelae were more strongly associated with index hospital infections (OR 2.21, 95% CI 1.64-2.96) than with index community infections (OR 1.36, 95% CI 1.21-1.53; P<.001). People presenting to primary care after hospital infection were more likely to be men (OR 1.43, 95% CI 1.25-1.64; P<.001), more socioeconomically deprived (OR 1.42, 95% CI 1.24-1.63; P<.001), and with higher multimorbidity scores (OR 1.41, 95% CI 1.26-1.57; P<.001) than those presenting after an index community infection. All-cause mortality in people with long COVID was associated with increasing age, male sex (OR 3.32, 95% CI 1.34-9.24; P=.01), and higher multimorbidity score (OR 2.11, 95% CI 1.34-3.29; P<.001). Vaccination was associated with reduced odds of mortality (OR 0.10, 95% CI 0.03-0.35; P<.001).

CONCLUSIONS

The low percentage of people recorded as having long COVID after COVID-19 infection reflects either low prevalence or underrecording. The characteristics and comorbidities of those presenting with long COVID after a community infection are different from those hospitalized. This study provides insights into the presentation of long COVID in primary care and implications for workload.

Reflection on modern methods: constructing directed acyclic graphs (DAGs) with domain experts for health services research

Directed acyclic graphs (DAGs) are a useful tool to represent, in a graphical format, researchers’ assumptions about the causal structure among variables while providing a rationale for the choice of confounding variables to adjust for. With origins in the field of probabilistic graphical modelling, DAGs are yet to be widely adopted in applied health research, where causal assumptions are frequently made for the purpose of evaluating health services initiatives. In this context, there is still limited practical guidance on how to construct and use DAGs. Some progress has recently been made in terms of building DAGs based on studies from the literature, but an area that has received less attention is how to create DAGs from information provided by domain experts, an approach of particular importance when there is limited published information about the intervention under study. This approach offers the opportunity for findings to be more robust and relevant to patients, carers and the public, and more likely to inform policy and clinical practice. This article draws lessons from a stakeholder workshop involving patients, health care professionals, researchers, commissioners and representatives from industry, whose objective was to draw DAGs for a complex intervention—online consultation, i.e. written exchange between the patient and health care professional using an online system—in the context of the English National Health Service. We provide some initial, practical guidance to those interested in engaging with domain experts to develop DAGs.

Establishing a colorectal cancer research database from routinely collected health data: the process and potential from a pilot study

Objective

Colorectal cancer is a common cause of death and morbidity. A significant amount of data are routinely collected during patient treatment, but they are not generally available for research. The National Institute for Health Research Health Informatics Collaborative in the UK is developing infrastructure to enable routinely collected data to be used for collaborative, cross-centre research. This paper presents an overview of the process for collating colorectal cancer data and explores the potential of using this data source.

Methods

Clinical data were collected from three pilot Trusts, standardised and collated. Not all data were collected in a readily extractable format for research. Natural language processing (NLP) was used to extract relevant information from pseudonymised imaging and histopathology reports. Combining data from many sources allowed reconstruction of longitudinal histories for each patient that could be presented graphically.

Results

Three pilot Trusts submitted data, covering 12 903 patients with a diagnosis of colorectal cancer since 2012, with NLP implemented for 4150 patients. Timelines showing individual patient longitudinal history can be grouped into common treatment patterns, visually presenting clusters and outliers for analysis. Difficulties and gaps in data sources have been identified and addressed.

Discussion

Algorithms for analysing routinely collected data from a wide range of sites and sources have been developed and refined to provide a rich data set that will be used to better understand the natural history, treatment variation and optimal management of colorectal cancer.

Conclusion

The data set has great potential to facilitate research into colorectal cancer.

LOng COvid Multidisciplinary consortium Optimising Treatments and servIces acrOss the NHS (LOCOMOTION): protocol for a mixed-methods study in the UK

INTRODUCTION

Long COVID, a new condition whose origins and natural history are not yet fully established, currently affects 1.5 million people in the UK. Most do not have access to specialist long COVID services. We seek to optimise long COVID care both within and outside specialist clinics, including improving access, reducing inequalities, helping self-management and providing guidance and decision support for primary care. We aim to establish a 'gold standard' of care by systematically analysing current practices, iteratively improving pathways and systems of care.

METHODS AND ANALYSIS

This mixed-methods, multisite study is informed by the principles of applied health services research, quality improvement, co-design, outcome measurement and learning health systems. It was developed in close partnership with patients (whose stated priorities are prompt clinical assessment; evidence-based advice and treatment and help with returning to work and other roles) and with front-line clinicians. Workstreams and tasks to optimise assessment, treatment and monitoring are based in three contrasting settings: workstream 1 (qualitative research, up to 100 participants), specialist management in 10 long COVID clinics across the UK, via a quality improvement collaborative, experience-based co-design and targeted efforts to reduce inequalities of access, return to work and peer support; workstream 2 (quantitative research, up to 5000 participants), patient self-management at home, technology-supported monitoring and validation of condition-specific outcome measures and workstream 3 (quantitative research, up to 5000 participants), generalist management in primary care, harnessing electronic record data to study population phenotypes and develop evidence-based decision support, referral pathways and analysis of costs. Study governance includes an active patient advisory group.

ETHICS AND DISSEMINATION

LOng COvid Multidisciplinary consortium Optimising Treatments and servIces acrOss the NHS study is sponsored by the University of Leeds and approved by Yorkshire & The Humber-Bradford Leeds Research Ethics Committee (ref: 21/YH/0276). Participants will provide informed consent. Dissemination plans include academic and lay publications, and partnerships with national and regional policymakers.

TRIAL REGISTRATION NUMBER

NCT05057260, ISRCTN15022307.

Simultaneous Depth Estimation and Surgical Tool Segmentation in Laparoscopic Images

Surgical instrument segmentation and depth estimation are crucial steps to improve autonomy in robotic surgery. Most recent works treat these problems separately, making the deployment challenging. In this paper, we propose a unified framework for depth estimation and surgical tool segmentation in laparoscopic images. The network has an encoder-decoder architecture and comprises two branches for simultaneously performing depth estimation and segmentation. To train the network end to end, we propose a new multi-task loss function that effectively learns to estimate depth in an unsupervised manner, while requiring only semi-ground truth for surgical tool segmentation. We conducted extensive experiments on different datasets to validate these findings. The results showed that the end-to-end network successfully improved the state-of-the-art for both tasks while reducing the complexity during their deployment.

Comparing the longer-term effectiveness of a single dose of the Pfizer-BioNTech and Oxford-AstraZeneca COVID-19 vaccines across the age spectrum

BACKGROUND

A single dose strategy may be adequate to confer population level immunity and protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, especially in low- and middle-income countries where vaccine supply remains limited. We compared the effectiveness of a single dose strategy of the Oxford-AstraZeneca or Pfizer-BioNTech vaccines against SARS-CoV-2 infection across all age groups and over an extended follow-up period.

METHODS

Individuals vaccinated in North-West London, UK, with either the first dose of the Oxford-AstraZeneca or Pfizer-BioNTech vaccines between January 12, 2021 and March 09, 2021, were matched to each other by demographic and clinical characteristics. Each vaccinated individual was additionally matched to an unvaccinated control. Study outcomes included SARS-CoV-2 infection of any severity, COVID-19 hospitalisation, COVID-19 death, and all-cause mortality.

FINDINGS

Amongst matched individuals, 63,608 were in each of the vaccine groups and 127,216 were unvaccinated. Between 14 and 84 days of follow-up after matching, there were 534 SARS-CoV-2 infections, 65 COVID-19 hospitalisations, and 190 deaths, of which 29 were categorized as due to COVID-19. The incidence rate ratio (IRR) for SARS-CoV-2 infection was 0.85 (95% confidence interval [CI], 0.69 to 1.05) for Oxford-Astra-Zeneca, and 0.69 (0.55 to 0.86) for Pfizer-BioNTech. The IRR for both vaccines was the same at 0.25 (0.09 to 0.55) and 0.14 (0.02 to 0.58) for reducing COVID-19 hospitalization and COVID-19 mortality, respectively. The IRR for all-cause mortality was 0.25 (0.15 to 0.39) and 0.18 (0.10 to 0.30) for the Oxford-Astra-Zeneca and Pfizer-BioNTech vaccines, respectively. Age was an effect modifier of the association between vaccination and SARS-CoV-2 infection of any severity; lower hazard ratios for increasing age.

INTERPRETATION

A single dose strategy, for both vaccines, was effective at reducing COVID-19 mortality and hospitalization rates. The magnitude of vaccine effectiveness was comparatively lower for SARS-CoV-2 infection, although this was variable across the age range, with higher effectiveness seen with older adults. Our results have important implications for health system planning -especially in low resource settings where vaccine supply remains constrained.

Enriching the Value of Patient Experience Feedback: Web-Based Dashboard Development Using Co-design and Heuristic Evaluation

Background

There is an abundance of patient experience data held within health care organizations, but stakeholders and staff are often unable to use the output in a meaningful and timely way to improve care delivery. Dashboards, which use visualized data to summarize key patient experience feedback, have the potential to address these issues.

Objective

The aim of this study is to develop a patient experience dashboard with an emphasis on Friends and Family Test (FFT) reporting, as per the national policy drive.

Methods

A 2-stage approach was used—participatory co-design involving 20 co-designers to develop a dashboard prototype, followed by iterative dashboard testing. Language analysis was performed on free-text patient experience data from the FFT, and the themes and sentiments generated were used to populate the dashboard with associated FFT metrics. Heuristic evaluation and usability testing were conducted to refine the dashboard and assess user satisfaction using the system usability score.

Results

The qualitative analysis from the co-design process informed the development of the dashboard prototype with key dashboard requirements and a significant preference for bubble chart display. The heuristic evaluation revealed that most cumulative scores had no usability problems (18/20, 90%), had cosmetic problems only (7/20, 35%), or had minor usability problems (5/20, 25%). The mean System Usability Scale score was 89.7 (SD 7.9), suggesting an excellent rating.

Conclusions

The growing capacity to collect and process patient experience data suggests that data visualization will be increasingly important in turning feedback into improvements to care. Through heuristic usability, we demonstrated that very large FFT data can be presented in a thematically driven, simple visual display without the loss of the nuances and still allow for the exploration of the original free-text comments. This study establishes guidance for optimizing the design of patient experience dashboards that health care providers find meaningful, which in turn drives patient-centered care.

Identifying factors that promote and limit the effective use of real-time patient experience feedback: a mixed-methods study in secondary care

OBJECTIVES

The Friends and Family Test (FFT) is commissioned by the National Health Service (NHS) in England to capture patient experience as a real-time feedback initiative for patient-centred quality improvement (QI). The aim of this study was to create a process map in order to identify the factors that promote and limit the effective use of FFT as a real-time feedback initiative for patient-centred QI.

SETTING

This study was conducted at a large London NHS Trust. Services include accident and emergency, inpatient, outpatient and maternity, which routinely collect FFT patient experience data.

PARTICIPANTS

Healthcare staff and key stakeholders involved in FFT.

INTERVENTIONS

Semi-structured interviews were conducted on 15 participants from a broad range of professional groups to evaluate their engagement with the FFT. Interview data were recorded, transcribed and analysed for using deductive thematic analysis.

RESULTS

Concerns related to inefficiency in the flow of FFT data, lack of time to analyse FFT reports (with emphasis on high level reporting rather than QI), insufficient access to FFT reports and limited training provided to understand FFT reports for frontline staff. The sheer volume of data received was not amenable to manual thematic analysis resulting in inability to acquire insight from the free text. This resulted in staff ambivalence towards FFT as a near real-time feedback initiative.

CONCLUSIONS

The results state that there is too much FFT free text for meaningful analysis, and the output is limited to the provision of sufficient capacity and resource to analyse the data, without consideration of other options, such as text analytics and amending the data collection tool.

Development of a Structured Query Language and Natural Language Processing Algorithm to Identify Lung Nodules in a Cancer Centre

Importance: The stratification of indeterminate lung nodules is a growing problem, but the burden of lung nodules on healthcare services is not well-described. Manual service evaluation and research cohort curation can be time-consuming and potentially improved by automation.

Objective: To automate lung nodule identification in a tertiary cancer centre.

Methods: This retrospective cohort study used Electronic Healthcare Records to identify CT reports generated between 31st October 2011 and 24th July 2020. A structured query language/natural language processing tool was developed to classify reports according to lung nodule status. Performance was externally validated. Sentences were used to train machine-learning classifiers to predict concerning nodule features in 2,000 patients.

Results: 14,586 patients with lung nodules were identified. The cancer types most commonly associated with lung nodules were lung (39%), neuro-endocrine (38%), skin (35%), colorectal (33%) and sarcoma (33%). Lung nodule patients had a greater proportion of metastatic diagnoses (45 vs. 23%, p < 0.001), a higher mean post-baseline scan number (6.56 vs. 1.93, p < 0.001), and a shorter mean scan interval (4.1 vs. 5.9 months, p < 0.001) than those without nodules. Inter-observer agreement for sentence classification was 0.94 internally and 0.98 externally. Sensitivity and specificity for nodule identification were 93 and 99% internally, and 100 and 100% at external validation, respectively. A linear-support vector machine model predicted concerning sentence features with 94% accuracy.

Conclusion: We have developed and validated an accurate tool for automated lung nodule identification that is valuable for service evaluation and research data acquisition.

Using natural language processing to understand, facilitate and maintain continuity in patient experience across transitions of care

BACKGROUND

Patient centred care necessitates that healthcare experiences and perceived outcomes be considered across all transitions of care. Information encoded within free-text patient experience comments relating to transitions of care are not captured in a systematic way due to the manual resource required. We demonstrate the use of natural language processing (NLP) to extract meaningful information from the Friends and Family Test (FFT).

METHODS

Free-text fields identifying favourable service ("What did we do well?") and areas requiring improvement ("What could we do better?") were extracted from 69,285 FFT reports across four care settings at a secondary care National Health Service (NHS) hospital. Sentiment and patient experience themes were coded by three independent coders to produce a training dataset. The textual data was standardised with a series of pre-processing techniques and the performance of six machine learning (ML) models was obtained. The best performing ML model was applied to predict the themes and sentiment from the remaining reports. Comments relating to transitions of care were extracted, categorised by sentiment, and care setting to identify the most frequent words/combinations presented as tri-grams and word clouds.

RESULTS

The support vector machine (SVM) ML model produced the highest accuracy in predicting themes and sentiment. The most frequent single words relating to transition and continuity with a negative sentiment were "discharge" in inpatients and Accident and Emergency, "appointment" in outpatients, and "home' in maternity. Tri-grams identified from the negative sentiments such as 'seeing different doctor', 'information aftercare lacking', 'improve discharge process' and 'timing discharge letter' have highlighted some of the problems with care transitions. None of this information was available from the quantitative data.

CONCLUSIONS

NLP can be used to identify themes and sentiment from patient experience survey comments relating to transitions of care in all four healthcare settings. With the help of a quality improvement framework, findings from our analysis may be used to guide patient-centred interventions to improve transitional care processes.

Outcomes of Postchemotherapy Retroperitoneal Lymph Node Dissection from a High-volume UK Centre Compared with a National Data Set

Background

Retroperitoneal lymph node dissection (RPLND) is essential for the treatment of metastatic germ cell tumours of the testis. Recommendations on the referral and management of complex urological cancers in the UK includes centralisation of services to regional centres.

Objective

To review contemporary PC-RPLND outcomes at a high-volume centre with a complex case-mix, and compare with national registry data.

Design, setting, and participants

We retrospectively reviewed the medical records of PC-RPLNDs performed for germ cell tumours at our centre between July 2012 and September 2018.

Outcome measurements and statistical analysis

Primary outcomes were Clavien 3+ complications, histology, rates of positive margin, relapse, in-field recurrences, and mortality. Secondary outcomes were blood loss, operation time, blood transfusion, adjuvant procedures, length of stay, and lymph node count. Surgical and histological outcomes of all RPLNDs for testicular cancers were compared with national RPLND registry data. For statistical difference, χ² testing was used.

Results and limitations

A total of 178 procedures were performed, including 31 (17%) redo RPLNDs. Clavien 3+ complications occurred in 11 (7%). Histological findings in non-redo cases were the following: necrosis 24%, teratoma 62%, viable germ cell tumour 11%, and dedifferentiated cancers 3%. Rates of positive margin, relapse, and in-field recurrence were 11%, 17%, and 2%, respectively. Overall survival was 89% at a median of 36 mo. The median blood loss was 650 ml (350, 1250), with a transfusion rate of 8%. Nephrectomy, vascular reconstruction, and visceral resection was required in 12%, 6%, and 3% respectively. The median inpatient stay was 6 d (5, 8) and the median node count was 35 (20, 37). A comparison of all RPLNDs with national data showed no statistical difference in primary outcomes. Our blood transfusion rate was significantly lower (12% vs 21%, χ² [1, N = 322] = 4.296, p =  0.038).

Conclusions

Centralisation led to high quality of RPLND in UK. Within that, our series (the largest in the UK) demonstrates no significant difference in outcomes despite higher complexity cases. Our blood transfusion rates are in fact lower than national figures. Complex RPLNDs should be performed in high-volume centres where possible.

Patient summary

In the UK, retroperitoneal lymph node dissections (RPLND) are centralised to specialist centres and the quality of surgery is high, with low complications and good histological outcomes. When compared to national data, we found no significant difference in the majority of outcomes from our high-volume centre despite our complex case-mix.

An Early Warning Risk Prediction Tool (RECAP-V1) for Patients Diagnosed With COVID-19: Protocol for a Statistical Analysis Plan

BACKGROUND

Since the start of the COVID-19 pandemic, efforts have been made to develop early warning risk scores to help clinicians decide which patient is likely to deteriorate and require hospitalization. The RECAP (Remote COVID-19 Assessment in Primary Care) study investigates the predictive risk of hospitalization, deterioration, and death of patients with confirmed COVID-19, based on a set of parameters chosen through a Delphi process performed by clinicians. We aim to use rich data collected remotely through the use of electronic data templates integrated in the electronic health systems of several general practices across the United Kingdom to construct accurate predictive models. The models will be based on preexisting conditions and monitoring data of a patient's clinical parameters (eg, blood oxygen saturation) to make reliable predictions as to the patient's risk of hospital admission, deterioration, and death.

OBJECTIVE

This statistical analysis plan outlines the statistical methods to build the prediction model to be used in the prioritization of patients in the primary care setting. The statistical analysis plan for the RECAP study includes the development and validation of the RECAP-V1 prediction model as a primary outcome. This prediction model will be adapted as a three-category risk score split into red (high risk), amber (medium risk), and green (low risk) for any patient with suspected COVID-19. The model will predict the risk of deterioration and hospitalization.

METHODS

After the data have been collected, we will assess the degree of missingness and use a combination of traditional data imputation using multiple imputation by chained equations, as well as more novel machine-learning approaches to impute the missing data for the final analysis. For predictive model development, we will use multiple logistic regression analyses to construct the model. We aim to recruit a minimum of 1317 patients for model development and validation. We will then externally validate the model on an independent dataset of 1400 patients. The model will also be applied for multiple different datasets to assess both its performance in different patient groups and its applicability for different methods of data collection.

RESULTS

As of May 10, 2021, we have recruited 3732 patients. A further 2088 patients have been recruited through the National Health Service Clinical Assessment Service, and approximately 5000 patients have been recruited through the DoctalyHealth platform.

CONCLUSIONS

The methodology for the development of the RECAP-V1 prediction model as well as the risk score will provide clinicians with a statistically robust tool to help prioritize COVID-19 patients.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04435041; https://clinicaltrials.gov/ct2/show/NCT04435041.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/30083.

Using electronic health records to develop and validate a machine-learning tool to predict type 2 diabetes outcomes: a study protocol

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is a major cause of blindness, kidney failure, myocardial infarction, stroke and lower limb amputation. We are still unable, however, to accurately predict or identify which patients are at a higher risk of deterioration. Most risk stratification tools do not account for novel factors such as sociodemographic determinants, self-management ability or access to healthcare. Additionally, most tools are based in clinical trials, with limited external generalisability.

OBJECTIVE

The aim of this work is to design and validate a machine learning-based tool to identify patients with T2DM at high risk of clinical deterioration, based on a comprehensive set of patient-level characteristics retrieved from a population health linked dataset.

SAMPLE AND DESIGN

Retrospective cohort study of patients with diagnosis of T2DM on 1 January 2015, with a 5-year follow-up. Anonymised electronic healthcare records from the Whole System Integrated Care (WSIC) database will be used.

PRELIMINARY OUTCOMES

Outcome variables of clinical deterioration will include retinopathy, chronic renal disease, myocardial infarction, stroke, peripheral arterial disease or death. Predictor variables will include sociodemographic and geographic data, patients' ability to self-manage disease, clinical and metabolic parameters and healthcare service usage. Prognostic models will be defined using multidependence Bayesian networks. The derivation cohort, comprising 80% of the patients, will be used to define the prognostic models. Model parameters will be internally validated by comparing the area under the receiver operating characteristic curve in the derivation cohort with those calculated from a leave-one-out and a 10 times twofold cross-validation.

ETHICS AND DISSEMINATION

The study has received approvals from the Information Governance Committee at the WSIC. Results will be made available to people with T2DM, their caregivers, the funders, diabetes care societies and other researchers.

Getting the whole story: Integrating patient complaints and staff reports of unsafe care

Objective

It is increasingly recognized that patient safety requires heterogeneous insights from a range of stakeholders, yet incident reporting systems in health care still primarily rely on staff perspectives. This paper examines the potential of combining insights from patient complaints and staff incident reports for a more comprehensive understanding of the causes and severity of harm.

Methods

Using five years of patient complaints and staff incident reporting data at a large multi-site hospital in London (in the United Kingdom), this study conducted retrospective patient-level data linkage to identify overlapping reports. Using a combination of quantitative coding and in-depth qualitative analysis, we then compared level of harm reported, identified descriptions of adjacent events missed by the other party and examined combined narratives of mutually identified events.

Results

Incidents where complaints and incident reports overlapped (n = 446, reported in 7.6%’ of all complaints and 0.6% of all incident reports) represented a small but critical area of investigation, with significantly higher rates of Serious Incidents and severe harm. Linked complaints described greater harm from safety incidents in 60% of cases, reported many surrounding safety events missed by staff (n = 582), and provided contesting stories of why problems occurred in 46% cases, and complementary accounts in 26% cases.

Conclusions

This study demonstrates the value of using patient complaints to supplement, test, and challenge staff reports, including to provide greater insight on the many potential factors that may give rise to unsafe care. Accordingly, we propose that a more holistic analysis of critical safety incidents can be achieved through combining heterogeneous data from different viewpoints, such as through the integration of patient complaints and staff incident reporting data.

Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool

Background

During the pandemic, remote consultations have become the norm for assessing patients with signs and symptoms of COVID-19 to decrease the risk of transmission. This has intensified the clinical uncertainty already experienced by primary care clinicians when assessing patients with suspected COVID-19 and has prompted the use of risk prediction scores, such as the National Early Warning Score (NEWS2), to assess severity and guide treatment. However, the risk prediction tools available have not been validated in a community setting and are not designed to capture the idiosyncrasies of COVID-19 infection.

Objective

The objective of this study is to produce a multivariate risk prediction tool, RECAP-V1 (Remote COVID-19 Assessment in Primary Care), to support primary care clinicians in the identification of those patients with COVID-19 that are at higher risk of deterioration and facilitate the early escalation of their treatment with the aim of improving patient outcomes.

Methods

The study follows a prospective cohort observational design, whereby patients presenting in primary care with signs and symptoms suggestive of COVID-19 will be followed and their data linked to hospital outcomes (hospital admission and death). Data collection will be carried out by primary care clinicians in four arms: North West London Clinical Commissioning Groups (NWL CCGs), Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), Covid Clinical Assessment Service (CCAS), and South East London CCGs (Doctaly platform). The study involves the use of an electronic template that incorporates a list of items (known as RECAP-V0) thought to be associated with disease outcome according to previous qualitative work. Data collected will be linked to patient outcomes in highly secure environments. We will then use multivariate logistic regression analyses for model development and validation.

Results

Recruitment of participants started in October 2020. Initially, only the NWL CCGs and RCGP RSC arms were active. As of March 24, 2021, we have recruited a combined sample of 3827 participants in these two arms. CCAS and Doctaly joined the study in February 2021, with CCAS starting the recruitment process on March 15, 2021. The first part of the analysis (RECAP-V1 model development) is planned to start in April 2021 using the first half of the NWL CCGs and RCGP RSC combined data set. Posteriorly, the model will be validated with the rest of the NWL CCGs and RCGP RSC data as well as the CCAS and Doctaly data sets. The study was approved by the Research Ethics Committee on May 27, 2020 (Integrated Research Application System number: 283024, Research Ethics Committee reference number: 20/NW/0266) and badged as National Institute of Health Research Urgent Public Health Study on October 14, 2020.

Conclusions

We believe the validated RECAP-V1 early warning score will be a valuable tool for the assessment of severity in patients with suspected COVID-19 in the community, either in face-to-face or remote consultations, and will facilitate the timely escalation of treatment with the potential to improve patient outcomes.

Trial Registration

ISRCTN registry ISRCTN13953727; https://www.isrctn.com/ISRCTN13953727

International Registered Report Identifier (IRRID)

DERR1-10.2196/29072

Applying natural language processing and machine learning techniques to patient experience feedback: a systematic review

OBJECTIVES

Unstructured free-text patient feedback contains rich information, and analysing these data manually would require a lot of personnel resources which are not available in most healthcare organisations.To undertake a systematic review of the literature on the use of natural language processing (NLP) and machine learning (ML) to process and analyse free-text patient experience data.

METHODS

Databases were systematically searched to identify articles published between January 2000 and December 2019 examining NLP to analyse free-text patient feedback. Due to the heterogeneous nature of the studies, a narrative synthesis was deemed most appropriate. Data related to the study purpose, corpus, methodology, performance metrics and indicators of quality were recorded.

RESULTS

Nineteen articles were included. The majority (80%) of studies applied language analysis techniques on patient feedback from social media sites (unsolicited) followed by structured surveys (solicited). Supervised learning was frequently used (n=9), followed by unsupervised (n=6) and semisupervised (n=3). Comments extracted from social media were analysed using an unsupervised approach, and free-text comments held within structured surveys were analysed using a supervised approach. Reported performance metrics included the precision, recall and F-measure, with support vector machine and Naïve Bayes being the best performing ML classifiers.

CONCLUSION

NLP and ML have emerged as an important tool for processing unstructured free text. Both supervised and unsupervised approaches have their role depending on the data source. With the advancement of data analysis tools, these techniques may be useful to healthcare organisations to generate insight from the volumes of unstructured free-text data.

Detection and staging of radio-recurrent prostate cancer using multiparametric MRI

OBJECTIVE

We determined the sensitivity and specificity of multiparametric magnetic resonance imaging (MP-MRI) in detection of locally recurrent prostate cancer and extra prostatic extension in the post-radical radiotherapy setting. Histopathological reference standard was whole-mount prostatectomy specimens. We also assessed for any added value of the dynamic contrast enhancement (DCE) sequence in detection and staging of local recurrence.

METHODS

This was a single centre retrospective study. Participants were selected from a database of males treated with salvage prostatectomy for locally recurrent prostate cancer following radiotherapy. All underwent pre-operative prostate-specific antigen assay, positron emission tomography CT, MP-MRI and transperineal template prostate mapping biopsy prior to salvage prostatectomy. MP-MRI performance was assessed using both Prostate Imaging-Reporting and Data System v. 2 and a modified scoring system for the post-treatment setting.

RESULTS

24 patients were enrolled. Using Prostate Imaging-Reporting and Data System v. 2, sensitivity, specificity, positive predictive value and negative predictive value was 64%, 94%, 98% and 36%. MP-MRI under staged recurrent cancer in 63%. A modified scoring system in which DCE was used as a co-dominant sequence resulted in improved diagnostic sensitivity (61%-76%) following subgroup analysis.

CONCLUSION

Our results show MP-MRI has moderate sensitivity (64%) and high specificity (94%) in detecting radio-recurrent intraprostatic disease, though disease tends to be under quantified and under staged. Greater emphasis on dynamic contrast images in overall scoring can improve diagnostic sensitivity.

ADVANCES IN KNOWLEDGE

MP-MRI tends to under quantify and under stage radio-recurrent prostate cancer. DCE has a potentially augmented role in detecting recurrent tumour compared with the de novo setting. This has relevance in the event of any future modified MP-MRI scoring system for the irradiated gland.

Functional outcomes and quality of life during long-term follow-up after acute pulmonary embolism: analysis of the prospective multicentre FOCUS study

Background

It is unclear to which extent persistence of symptoms and/or residual haemodynamic impairment clinical course of pulmonary embolism are associated with worse quality of life (QoL).

Aims

To study the correlation between symptoms and haemodynamic impairment with QoL during the first year after acute pulmonary embolism (PE).

Methods

The Follow-Up after acute pulmonary embolism (FOCUS) study prospectively enrolled and followed consecutive adult patients diagnosed with acute symptomatic objectively diagnosed PE. In the present analysis, we considered patients who completed the Pulmonary Embolism QoL (PEmb-QoL) Questionnaire at predefined visits 3 and 12 months after acute PE. The PEmb-QoL score ranges from 0% (best QoL) to 100% (worst QoL). We evaluated at these two time points the correlation between persisting symptoms (group: symptoms), elevation of natriuretic peptides or residual right ventricular dysfunction (group: RVD), or their combination (group: symptoms + RVD) and QoL.

Results

A total of 617 patients were included; their median age was 62 years, 44% were women; 8% had active cancer, and 21% previous venous thromboembolism. At 3 months, patients with neither symptoms nor RVD (n=302) had the highest quality of life (median score 18%, 25th–75th percentile: 8%–34%), followed by those without symptoms but with RVD (n=255; median score 19%, 25th–75th percentile: 7%–34%), and by those with symptoms only (n=131; median PEmb-QoL 31%, 25th–75th percentile: 18%–49%). Patients with both symptoms and RVD (n=170) had the worst quality of life (median score 38%, 25th–75th percentile: 19%–53%); Figure 1A. At 12 months, we found an overall improvement of PEmb-QoL score. The degree of this QoL improvement varied across groups, being largest for patients who recovered from having symptoms + RVD at 3 months to normalization of at least one at 12 months. The change in QoL from 3 to 12 months was smaller both in patients who had neither symptoms nor RVD and in patients who had no recovery in either symptoms or RVD; Figure 1B.

Conclusions

Persistent symptoms after PE, especially in patients with elevated biomarkers or residual echocardiographic dysfunction, were the main drivers of QoL at 3 months as well as of the course of QoL over time.

Figure 1

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): University Medical Center of the Johannes Gutenberg University, Mainz, Germany; German Federal Ministry of Education and Research

Shift in transcriptional landscape of human right ventricle in chronic thromboembolic pulmonary arterial hypertension

Background

Chronic thromboembolic pulmonary hypertension (CTEPH) is a sub group of pulmonary hypertension (PH). CTEPH is characterized by the existence of thromboemboli and vascular remodeling in pulmonary vessels. The effect of increase in pulmonary artery pressures causes right ventricle (RV) hypertrophy and dilatation and finally leads to right heart failure and death. Surgical intervention in operable patients makes the CTEPH as an only curable and unique form of ph. Pulmonary endarterectomy (PEA) is the surgical procedure to remove the thromboembolic clots from the pulmonary vasculature, which restores RV function back to normal with significant improvements in cardiovascular magnetic resonance.

Purpose

The aim of this study is to use transcriptomic profiling to identify signaling pathways, master regulators, and potentially new biomarkers that specifically indicate the effect of PEA on the RV of patients with chronic thromboembolic pulmonary hypertension.

Results

RNA -sequencing (RNA-seq) was performed on RV biopsies obtained from CTEPH patients at PEA baseline (before PEA surgery) and the results were compared with those from RV biopsies obtained during follow-up evaluation. Bioinformatic analysis of RNA-seq data identified 2799 genes (n=14, −0.585 ≤ Log2 fold change ≥0.585, FDR ≤0.05) differentially regulated between the PEA baseline and follow-up sample groups. The great number of genes (2799) differentially expressed after PEA surgery in CTEPH patients confirms a major shift in the transcriptional landscape of RV in these patients. To further identify potential biomarker candidates from the large pool of 2799 differentially expressed genes (DEGs), extensive bioinformatic analysis of different data sets shortlisted 250 DEGs that were functionally associated with cardiovascular development or disease. The findings of this study reveal prominent transcriptional changes that occur in response to PEA. Gene ontology enrichment and pathway analysis confirmed altered regulation of hypoxia-inducible factor 1 (HIF-1) signaling, advanced glycation end products and their receptors (AGE-RAGE), mitogen-activated protein kinase (MAPK) signaling, hippo signaling, the Janus kinase/ signal transducers and activators of transcription (Jak-STAT) signaling pathway, and proteoglycans after PEA compared with before PEA.

Conclusion

Comparison of the results of RNA-seq analysis of RV biopsies of CTEPH patients, pre and post PEA, revealed a major shift in the transcriptional landscape of these patients after reducing the pressure overload of the RV by PEA.

Funding Acknowledgement

Type of funding source: Foundation. Main funding source(s): German Research Foundation (DFG)

Novel potential diagnostic targets revealed by plasma proteomic analysis in chronic thromboembolic pulmonary hypertension

Background

Chronic thromboembolic pulmonary hypertension (CTEPH) is associated with poor outcome if untreated, although it is a curable form of pulmonary hypertension (PH). Successful treatment requires an optimized diagnostic work-up.

Purpose

The aim of this study was to identify non-invasive biomarkers that might serve as new diagnostic parameters in the multifaceted pathophysiology of CTEPH.

Methods

The biomarker profile of 64 CTEPH patients who underwent balloon pulmonary angioplasty (BPA) was analyzed prior to and after therapy and compared with that of a healthy control group (CG1, n=25) at baseline. Proteomes were analyzed by semiquantitative screening based on a proximity extension assay of three high-throughput, multiplex immunoassay panels. Serum levels of a subset of biomarkers identified in the screening were additionally measured by immunochemical methods.

Results

Fifty protein biomarkers were found to differ between CTEPH patients and CG1. Eight biomarkers changed significantly after therapy. The overlap of these two groups revealed six targets that were all upregulated in CTEPH at baseline and modifiable by treatment. In this group of biomarkers, the levels of DCN (decorin), HGF (hepatocyte growth factor), BNP (B-type natriuretic peptide), and PAPP-A (papalysin-1) decreased after therapy, whereas SPON-1 (spondin-1) and MEPE (matrix extracellular phosphoglycoprotein) further increased at follow-up. The differences in these biomarkers in CTEPH as well as the dynamics after therapy were confirmed and quantified in enzyme-linked immunosorbent assays.

Conclusions

This study identified 6 biomarkers that might serve as new diagnostic parameters or constitute new therapeutic targets in CTEPH. Further prospective studies will be necessary to determine the specific pathophysiological role of each marker.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): SFB 1213 area CP01

Copeptin as a non-invasive biomarker in chronic thromboembolic pulmonary hypertension

Introduction

Copeptin is the C-terminal fragment of the precursor protein of vasopressin. In acute pulmonary embolism, copeptin has been suggested to be a strong predictor of outcome and to provide additional predictive value to the established cardiac biomarkers high-sensitivity cardiac troponin and N-terminal pro-brain natriuretic peptide (NT-proBNP). Chronic thromboembolic pulmonary hypertension (CTEPH) is diagnosed in about 5% of patients who survive acute pulmonary embolism. Individualized risk stratification remains a challenge in the work-up of CTEPH patients.

Purpose

The current study investigated whether copeptin has the potential to aid the stratification of patients who have experienced pulmonary embolism and CTEPH patients. We examined the baseline (BL) levels and dynamics of copeptin during therapy in CTEPH patients who underwent balloon pulmonary angioplasty (BPA) or pulmonary endarterectomy (PEA). Moreover, the study compared copeptin levels between patients with or without therapy response.

Methods

The study included a total of 125 CTEPH patients scheduled for treatment. A total of 78 underwent staged BPA and 64 underwent PEA. In accordance with recent studies from our group, therapy success was defined as a decrease in meanPAP ≥25% and PVR ≥35% or a normalization below the thresholds defining pulmonary hypertension. Blood samples were collected at BL, prior to each BPA session in the BPA cohort, and at follow-up (FU) 6 months after BPA or 12 months after PEA. Copeptin was measured in thawed serum aliquots by an immunochemical method.

Results

The 78 patients in the BPA cohort underwent a mean of 6 BPA procedures each; there were a total of 413 interventions. The hemodynamic clinical and functional status the CTEPH patients improved after BPA and PEA therapy: meanPAP (BL: 43±9 mmHg vs. FU: 27±9 mmHg; p&lt;0.001); PVR (BL: 7.6±3.4 WU vs. FU: 3.8±2.0 WU; p&lt;0.001); RAP (BL: 7.9±5.8 mmHg vs. FU: 5.4±2.7 mmHg; p&lt;0.001); WHO functional class [BL: I:0 / II:25 / III:80 / IV:20 vs. FU: I:56 / II:57 / III:10 / IV:2]; 6-minute-walk distance (BL: 405±99 m vs. FU: 456±112 m; p&lt;0.001).

The median serum levels of copeptin [BL 7.7 (4.6–14.2) pmol/L vs. FU 6.3 (3.9–12.5); p=0.009] and NT-proBNP [BL: 811 (157–1857) ng/L vs. FU: 142 (72–335) ng/L p&lt;0.001] decreased significantly after therapy. The copeptin levels did not correlate with hemodynamics at BL: PVR (rrs=0.02; p=0.79) and meanPAP (rrs=0.03; p=0.75). The copeptin levels at BL (AUC=0.61) and the relative change (AUC=0.53) did not predict the endpoint of therapy response.

Conclusions

Copeptin levels are elevated in CTEPH patients compared with normal values in the literature. Although copeptin is known to provide additional value in the context of risk stratification in acute pulmonary embolism, it failed to provide additional diagnostic benefit in CTEPH in the current study.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): SFB 1213 area CP01

Impact of providing patients access to electronic health records on quality and safety of care: a systematic review and meta-analysis

Objective

To evaluate the impact of sharing electronic health records (EHRs) with patients and map it across six domains of quality of care (ie, patient-centredness, effectiveness, efficiency, timeliness, equity and safety).

Design

Systematic review and meta-analysis.

Data sources

CINAHL, Cochrane, Embase, HMIC, Medline/PubMed and PsycINFO, from 1997 to 2017.

Eligibility criteria

Randomised trials focusing on adult subjects, testing an intervention consisting of sharing EHRs with patients, and with an outcome in one of the six domains of quality of care.

Data analysis

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Title and abstract screening were performed by two pairs of investigators and assessed using the Cochrane Risk of Bias Tool. For each domain, a narrative synthesis of the results was performed, and significant differences in results between low risk and high/unclear risk of bias studies were tested (t-test, p<0.05). Continuous outcomes evaluated in four studies or more (glycated haemoglobin (HbA1c), systolic blood pressure (SBP) and diastolic blood pressure (DBP)) were pooled as weighted mean difference (WMD) using random effects meta-analysis. Sensitivity analyses were performed for low risk of bias studies, and long-term interventions only (lasting more than 12 months).

Results

Twenty studies were included (17 387 participants). The domain most frequently assessed was effectiveness (n=14), and the least were timeliness and equity (n=0). Inconsistent results were found for patient-centredness outcomes (ie, satisfaction, activation, self-efficacy, empowerment or health literacy), with 54.5% of the studies (n=6) demonstrating a beneficial effect. Meta-analyses showed a beneficial effect in effectiveness by reducing absolute values of HbA1c (unit: %; WMD=−0.316; 95% CI −0.540 to −0.093, p=0.005, I²=0%), which remained significant in the sensitivity analyses for low risk of bias studies (WMD= −0.405; 95% CI −0.711 to −0.099), and long-term interventions only (WMD=−0.272; 95% CI −0.482 to −0.062). A significant reduction of absolute values of SBP (unit: mm Hg) was found but lost in sensitivity analysis for studies with low risk of bias (WMD= −1.375; 95% CI −2.791 to 0.041). No significant effect was found for DBP (unit: mm Hg; WMD=−0.918; 95% CI −2.078 to 0.242, p=0.121, I²=0%). Concerning efficiency, most studies (80%, n=4) found either a reduction of healthcare usage or no change. A beneficial effect was observed in a range of safety outcomes (ie, general adherence, medication safety), but not in medication adherence. The proportion of studies reporting a beneficial effect did not differ between low risk and high/unclear risk studies, for the domains evaluated.

Discussion

Our analysis supports that sharing EHRs with patients is effective in reducing HbA1c levels, a major predictor of mortality in type 2 diabetes (mean decrease of −0.405, unit: %) and could improve patient safety. More studies are necessary to enhance meta-analytical power and assess the impact in other domains of care.

Protocol registration

http://www.crd.york.ac.uk/PROSPERO (CRD42017070092).

Abstract ES8-2: Future Directions in Endocrine Therapy for Advanced HR+/HER2- Breast Cancer

The majority of metastatic breast cancer is hormone receptor positive (HR+), HER2 negative. Substantial advances over the prior decades have demonstrated the efficacy of endocrine monotherapies, including aromatase inhibitors, tamoxifen, and fulvestrant, in controlling disease and prolonging survival. More recently, the introduction of targeted therapies used in concert with endocrine therapy have further improved outcomes. The CDK4/6 inhibitors (CDK4/6i): palbociclib, abemaciclib, and ribociclib, have uniformly demonstrated efficacy in the first-line and pretreated settings in prolonging progression free survival, with hazard ratios across at least 8 randomized trials (PALOMA, MONARCH, MONALEESA series) ranging from 0.50-0.55. Recent reports from these trials also support prolongation in overall survival with the use of CDK4/6i in combination with an endocrine backbone. Since initial approval in 2015, CDK4/6i in combination with an endocrine partner have become a mainstay of treatment for metastatic HR+ HER-2 negative breast cancer. Additionally, in the setting of endocrine resistance, a deeper understanding of resistance signaling, such as the mTOR/PI3kinase/AKT pathway, has led to the development and approval of active therapies, including everolimus and alpelisib, with further agents in development.

Despite substantial progress, a major challenge within the current landscape is to better identify mechanisms of resistance to these therapies, with a goal of utilizing a personalized approach to tailor subsequent treatment options. Significant ongoing work focuses on the post-CDK4/6i space, to identify molecular mechanisms of resistance, and whether resistance extends exclusively to CDK4/6i, or to endocrine therapy as well. Examination of tumor and blood samples post-CDK4/6i exposure has suggested a heterogenous mutational landscape. Loss of Rb is a rare observation, however other important events include alterations in AKT1, aurora kinase A (AURKA), FGFR1, cyclin E2 (CCNE2), ESR1, and RAS. Agents of interest post-CDK4/6i thus include SERDs (selective estrogen receptor down regulators), AKT inhibtors, FGFR1 antagonists, as well as aurora kinase inhibitors.

In conclusion, the area of empiric endocrine monotherapy has become a notion of the past. The advent of CDK4/6i has changed paradigms of therapy and introduced improved survival outcomes. Substantial ongoing work attempts to characterize the heterogenous genomic alternations which underlie resistance to endocrine and targeted therapies, and novel agents matched to these specific mutations are in development. Moving beyond CDK4/6i, we are now entering a new era of personalized and targeted therapy for metastatic HR+ HER-2 negative breast cancer, with the potential to provide significant benefit to the many patients with this disease.

Citation Format: E Mayer. Future Directions in Endocrine Therapy for Advanced HR+/HER2- Breast Cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr ES8-2.

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

Visual behaviour in robotic surgery-Demonstrating the validity of the simulated environment

BACKGROUND

Eye metrics provide insight into surgical behaviour allowing differentiation of performance, however have not been used in robotic surgery. This study explores eye metrics of robotic surgeons in training in simulated and real tissue environments.

METHODS

Following the Fundamentals of Robotic Surgery (FRS), training curriculum novice robotic surgeons were trained to expert-derived benchmark proficiency using real tissue on the da Vinci Si and the da Vinci skills simulator (dVSS) simulator. Surgeons eye metrics were recorded using eye-tracking glasses when both "novice" and "proficient" in both environments. Performance was assessed using Global Evaluative Assessment of Robotic skills (GEARS) and numeric psychomotor test score (NPMTS) scores.

RESULTS

Significant (P ≤ .05) correlations were seen between pupil size, rate of change and entropy, and associated GEARS/NPMTS in "novice" and "proficient" surgeons. Only number of blinks per minute was significantly different between pupilometrics in the simulated and real tissue environments.

CONCLUSIONS

This study illustrates the value of eye tracking as an objective physiological tool in the robotic setting. Pupilometrics significantly correlate with established assessment methods and could be incorporated into robotic surgery assessments.

Traumatic renal injury in a UK major trauma centre - current management strategies and the role of early re-imaging

OBJECTIVES

To analyse the contemporary management of renal injuries in a UK major trauma centre and to evaluate the utility and value of re-imaging.

PATIENTS AND METHODS

The prospectively maintained 'Trauma Audit and Research Network' database was interrogated to identify patients with urinary tract injuries between January 2014 and December 2017. Patients' records and imaging were reviewed to identify injury grades, interventions, outcomes, and follow-up.

RESULTS

Renal injury was identified in 90 patients (79 males and 11 females). The mean (sd; range) age was 35.5 (17.4; 1.5-94) years. Most of the renal traumas were caused by blunt mechanisms (74%). The overall severity of injuries was: 18 (20%) Grade I, 19 (21%) Grade II, 27 (30%) Grade III, 22 (24%) Grade IV, and four (4%) Grade V. Most patients (84%) were managed conservatively. Early intervention (<24 h) was performed in 14 patients (16%) for renal injuries. Most of these patients were managed by interventional radiology techniques (nine of 14). Only two patients required an emergency nephrectomy, both of whom died from extensive polytrauma. In all, 19 patients underwent laparotomy for other injuries and did not require renal exploration. The overall 30-day mortality was 13%. Re-imaging was performed in 66% of patients at an average time of 3.4 days from initial scan. The majority of re-imaging was planned (49 patients) and 12% of these scans demonstrated a relevant finding (urinoma, pseudoaneurysm) that altered management in three of the 49 patients (6.1%).

CONCLUSION

Non-operative management is the mainstay for all grades of injury. Haemodynamic instability and persistent urine leak are primary indications for intervention. Open surgical management is uncommon. Repeat imaging after injury is advocated for stable patients with high-grade renal injuries (Grade III-V), although more research is needed to determine the optimal timing.

4283Exercise right heart catheterization before and after balloon pulmonary angioplasty in inoperable patients with chronic thromboembolic pulmonary hypertension

Background

Balloon pulmonary angioplasty (BPA) is an evolving treatment option for inoperable patients with chronic thromboembolic pulmonary hypertension (CTEPH). The main indicator for success is improvement in pulmonary hemodynamics, but outcome data are heterogeneous.

Purpose

The aim of the present study was to evaluate pulmonary hemodynamics not only at rest, but also during exercise before and 6 months after BPA.

Methods

We report a prospective series of 64 consecutive patients with inoperable CTEPH who were treated interventionally with BPA. All patients underwent standardized assessment prior to the first BPA and 6 months after the last intervention. Assessment included WHO FC, Cambridge Pulmonary Hypertension Outcome Review (CAMPHOR), 6-minute walking distance (6MWD), serum levels of the N-terminal fragment of pro-brain natriuretic peptide (NT-proBNP), and exercise RHC.

Results

The mean number of sessions per patient was 5.6 (± 1.3) and the mean number of pulmonary segments targeted in all interventions was 11 (± 3). BPA treatment led to improvements in pulmonary hemodynamics and exercise capacity (6MWD: 416±94 m vs. 463±96 m; p<0.0001) except for CO and CI during RHC at rest; these parameters showed improvements only during exercise RHC. MPAP at rest showed a reduction from 41±9 to 31±9 mmHg (p<0.0001) and PVR at rest decreased from 6.8±2.3 WU to 4.3±1.9 WU (p<0.0001). Further decreases were observed for systolic pulmonary arterial pressure, TPG, PVR, and TPR. Cardiac output (7.0±2.0 L/min vs. 8.3±2.0 L/min; p<0.0001) and cardiac index during exercise RHC (3.8±1.1 L/min/m2 vs. 4.4±1.1 L/min/m2; p<0.0001) improved significantly. Median NT-proBNP concentrations decreased from 741 ng/L (IQR 192–1425 ng/L) to 139 ng/L (IQR 60–266 ng/L) during BPA treatment (p<0.0001). Results from the CAMPHOR questionnaire showed significant improvements in symptoms (11±5.8 vs. 5.5±4.9, p<0.0001), activity limitations (9.2±5.6 vs. 5.2±4.5, p<0.0001), and quality of life (6.4±5.7 vs. 3.5±3.7, p<0.0001).

Conclusion

Significant improvements in pulmonary hemodynamics at rest and during exercise were observed 6 months after BPA. Exercise right heart catheterization offers a more discriminating evaluation of the changes in pulmonary hemodynamics after BPA.

P2774Galectin-3, GDF-15, and ST2 in noninvasive assessment of myocardial remodelling in chronic thromboembolic pulmonary hypertension

Background

In chronic thromboembolic pulmonary hypertension (CTEPH), pulmonary artery obstruction leads to impaired pulmonary hemodynamics and secondary right heart failure, which is highly predictive of outcome. Thus, the extent of myocardial -especially right heart- remodelling is an indicator of disease severity.

Purpose

The aim of the present study was to assess growth differentiation factor-15 (GDF-15), galectin-3, and suppression of tumorigenicity 2 (ST2) as non-invasive biomarkers of myocardial remodelling in patients suffering from CTEPH.

Methods

We analysed the serum levels of GDF-15, galectin-3 and ST2 in a cohort of 64 CTEPH patients and in a control group of 25 patients without cardiovascular disease. The biomarker levels were further correlated with clinical, laboratory, and hemodynamic data, including 6-minute walking distance (6-MWD), N-terminal pro-brain natriuretic peptide (NT-proBNP), mean pulmonary artery pressure (meanPAP), pulmonary vascular resistance (PVR), and right atrial pressure (RAP).

Results

The biomarker levels in the control group were: galectin-3: 3.5 ng/l (IQR 2.7–4.0), GDF-15: 92.6 pg/ml (IQR 78.5–129.1), and ST2: 48.65 ng/l (IQR 35.5–57.0). CTEPH patients had higher levels of GDF-15 (196.7 pg/ml; IQR 128.4–302.8; p<0.001) and ST2 (52.6 ng/l; IQR 44.5–71.9; p=0.05) but not galectin-3 (3.4 ng/l; IQR 2.7–4.3; p=0.84). In the CTEPH cohort, patients with a meanPAP >35 mmHg (GDF-15: p=0.01; ST2: p=0.04) and patients with a PVR >500 dyn sec cm–5 (GDF-15: p=0.004; ST2: p=0.002) had significantly increased biomarker levels. For the detection of a meanPAP >35mmHg, ROC analysis revealed an AUC of 0.71 for GDF-15 and 0.67 for ST2. The level of GDF-15 correlated with the level of NT-proBNP (rrs=0.69; p≤0.001) and the RAP (rrs=0.54; p≤0.001) and inversely with the 6-MWD (rrs=−0.47; p≤0.001). The level of ST2 correlated with the level of NT-proBNP (rrs=0.67; p≤0.001) and the RAP (rrs=0.54; p≤0.001) and inversely with the 6-MWD (rrs=-0.31; p=0.02).

Conclusion

Our results demonstrate that GDF-15 and ST2, non-invasive biomarkers of myocardial remodelling, are significantly elevated in patients suffering from CTEPH. The correlation of biomarker levels with established outcome predictors suggests a use as indicators of disease severity.

P2540Sex-specific differences in the clinical presentation, surgical complications, and course of chronic thromboembolic pulmonary hypertension

Background

Women are more susceptible to develop several forms of pulmonary hypertension, but they may have better survival rates than men. Sparse data are available concerning sex-specific differences in chronic thromboembolic pulmonary hypertension (CTEPH).

Purpose and methods

We investigated sex-specific differences in the clinical presentation of CTEPH, functional parameters, exposure to pulmonary endarterectomy (PEA), and survival.

Results

Women constituted half of the study population (N=679 treatment-naïve patients from the European CTEPH registry) and were characterized by a lower prevalence of some cardiovascular risk factors (e.g. prior acute coronary syndrome, smoking habit, chronic obstructive pulmonary disease), but more prevalent obesity, cancer, and thyroid diseases. Median age was 62 (IQR 50–73) years in women and 63 (IQR 53–70) in men. Women underwent PEA less often than men (54% vs 65%; Figure 1, Panel A) and were exposed to fewer additional cardiac procedures, notably coronary artery bypass graft surgery (0.5% vs. 9.5%). The prevalence of specific reasons for not being operated, including the patient's refusal and the proportion of proximal vs. distal lesions, did not differ between sexes. A total of 57 (17.0%) deaths in women and 70 (20.7%) in men were recorded over long-term follow-up. Female sex was positively associated with long-term survival (adjusted Hazard Ratio 0.66; 95% Confidence Interval 0.46–0.94). Short-term mortality was identical in the two groups (Figure 1, Panel B).

Conclusions

Women with CTEPH had a lower prevalence of cardiovascular risk factors and underwent PEA less frequently than men, who, in turn, were more often exposed to additional major cardiac surgery procedures. Women had more favorable long-term survival.

Acknowledgement/Funding

The CTEPH registry is supported by a research grant from Actelion Pharmaceuticals Ltd.

Impact of Ga-68-PSMA PET/CT on management in prostate cancer patients with very early biochemical recurrence after radical prostatectomy

PURPOSE

With the availability of ultra-sensitive PSA assays, early biochemical relapse (eBCR) of prostate cancer is increasingly being detected at values much lower than the conventional threshold of 0.2 ng/ml. Accurate localisation of disease in this setting may allow treatment modification and improved outcomes, especially in patients with pelvis-confined or extra-pelvic oligometastasis (defined as up to three pelvic nodal or distant sites). We aimed to measure the detection rate of [68]Ga-PSMA-HBNED-CC (PSMA)-PET/CT and its influence on patient management in eBCR of prostate cancer following radical prostatectomy (RP).

METHODS

We retrospectively identified 28 patients who underwent PSMA-PET/CT for post-RP eBCR (PSA < 0.5 ng/ml) at our tertiary care cancer centre. Two nuclear medicine physicians independently recorded the sites of PSMA-PET/CT positivity. Multidisciplinary meeting records were accessed to determine changes in management decisions following PSMA-PET/CT scans.

RESULTS

The mean age of patients was 65.6 years (range: 50-76.2 years); median PSA was 0.22 ng/ml (interquartile range: 0.15 ng/ml to 0.34 ng/ml). Thirteen patients (46.4%) had received radiotherapy in the past. PSMA-PET/CT was positive in 17 patients (60.7%). Only one patient had polymetastasis (> 3 sites); the remainder either had prostatectomy bed recurrence (n = 2), pelvic oligometastasis (n = 10), or extra-pelvic oligometastasis (n = 4). PSMA-PET/CT resulted in management change in 12 patients (42.8%), involving stereotactic body radiotherapy (n = 6), salvage radiotherapy (n = 4), and systemic treatment (n = 2).

CONCLUSIONS

Our findings show that PSMA-PET/CT has a high detection rate in the eBCR setting following RP, with a large proportion of patients found to have fewer than three lesions. PSMA-PET/CT may be of value in patients with early PSA failure, and impact on the choice of potentially curative salvage treatments.

The features and management of late relapse of non-seminomatous germ cell tumors: The Royal Marsden Experience

529

Background: Late relapses (LR) of non-seminomatous germ cell tumours (NSGCT), defined as those occurring after a disease free interval of 2 years, are increasingly recognised. We reviewed the features of LR in NSGCT within a tertiary referral testicular cancer service. Methods: 3,064 patients (pts) were referred to the testis multi-disciplinary team (January 2005 to Dec 2017). Pts who experienced a LR where initial pathology demonstrated NSGCT were identified. Data of their original and late presentation and management was reviewed from patient electronic records. Results: Of the 3,064 pts, 101 (3.3%) had a LR, with 43 pts (43%) relapsing after 10 years. 36 were symptomatic and 39 had raised markers (AFP 29, HCG 9, both 1). Table 1 shows stage at initial presentation and time to relapse. As regards treatment before late relapse, 13 CS1 patients had received prior chemotherapy (Cht) (8 as adjuvant and 5 Cht for early relapse). 59/60 CS2/3 patients received Cht as primary treatment and 41 had a post chemotherapy retroperitoneal lymph node dissection(PC-RPLND (bilateral template in 12). 20 of these 41 men who had a PC-RPLND experienced a LR in the retroperitoneum (6 after bilateral template) Patient management at relapse is summarised in table.Time to recurrence was longer in CS2/3 patients (p<0.001). 84 surgical procedures were [performed in 82 patients; histology was TD in 43, Yolk sac 14, De-differentiated in 7 and viable GCT in 12, benign 8. To date 22 patients have died, 13 of these patients relapsed at multiple sites. Conclusions: LR of NSGCT frequently occurs after an extended interval and typically occurs earlier in CS1 disease compared to higher stages. Aggressive surgery +/- chemotherapy can cure most patients. [Table: see text]

Clinical outcomes of minimally invasive retroperitoneal lymph node dissection and single dose carboplatin for clinical stage IIa seminoma

530

Background: Standard management of Stage 2 seminoma (SEM) is 3 cycles of cisplatin based multi-agent chemotherapy or paraaortic/pelvic radiotherapy. Both treatments have potential short and long term toxicity. We report the use of minimally invasive (robotic or laparoscopic) retroperitoneal lymph node dissection (MI-RPLND) and adjuvant carboplatin. Methods: From 01/2013-04/2017, patients (pt) with SEM and Stage 2a disease on computed tomography (CT) staging scan were considered for MI-RPLND included the radiologically enlarged lymph nodes for Stage 2a SEM. Adjuvant carboplatin (AUC 7) x 1 cycle was administered after confirmation of nodal involvement. Post-operative outcomes including length of stay, Clavien-Dindo 1 complications and pathological staging were recorded. CT was performed at 3 months to verify nodal clearance and then pts monitored with a standard surveillance protocol. Results: Twenty modified unilateral templates were performed. Median and mean post-operative stay was 1 and 1.5 days. One pt required conversion to open surgery and two experienced Clavien-Dindo 1 complications. All pts had preserved ejaculation. Mean number of nodes removed per pt 14.3 (range 5-31) with average 1.75 nodes involved (range 0-5). In 2 pts the enlarged nodes were pN0; they were surveyed and are relapse free at 44+ months. In one case the enlarged lymph node contained embryonal carcinoma (EC) despite primary histology of pure SEM. The remaining 17 pts had confirmed pathological stage 2 SEM. The pt with EC and one pt who had adjuvant carboplatin for stage 1 disease received (B) EP x 2 cycles. 16 patients received a single cycle of adjuvant carboplatin (AUC 7). After median follow-up of 41 months (range 22-70), one patient has relapsed. This occurred at 18 months outside the template of dissection. This patient initially had multifocal disease with 3 pathologically involved nodes. He received BEP X 3 with complete radiological resolution of disease and remains disease free. Conclusions: MI-RPLND in conjunction with a single dose of carboplatin may potentially be an option for the management of Stage 2a SEM. In this series, a subset of pts were overstaged using standard CT imaging.

Subject-specific modelling of pneumoperitoneum: model implementation, validation and human feasibility assessment

PURPOSE

The aim of this study is to propose a model that simulates patient-specific anatomical changes resulting from pneumoperitoneum, using preoperative data as input. The framework can assist the surgeon through a real-time visualisation and interaction with the model. Such could further facilitate surgical planning preoperatively, by defining a surgical strategy, and intraoperatively to estimate port positions.

METHODS

The biomechanical model that simulates pneumoperitoneum was implemented within the GPU-accelerated NVIDIA FleX position-based dynamics framework. Datasets of multiple porcine subjects before and after abdominal insufflation were used to generate, calibrate and validate the model. The feasibility of modelling pneumoperitoneum in human subjects was assessed by comparing distances between specific landmarks from a patient abdominal wall, to the same landmark measurements on the simulated model.

RESULTS

The calibration of simulation parameters resulted in a successful estimation of an optimal set parameters. A correspondence between the simulation pressure parameter and the experimental insufflation pressure was determined. The simulation of pneumoperitoneum in a porcine subject resulted in a mean Hausdorff distance error of 5-6 mm. Feasibility of modelling pneumoperitoneum in humans was successfully demonstrated.

CONCLUSION

Simulation of pneumoperitoneum provides an accurate subject-specific 3D model of the inflated abdomen, which is a more realistic representation of the intraoperative scenario when compared to preoperative imaging alone. The simulation results in a stable and interactive framework that performs in real time, and supports patient-specific data, which can assist in surgical planning.

Abstract P1-15-01: Withdrawn

This abstract was withdrawn by the authors.

Citation Format: Metzger Filho O, Janiszewska M, Guo H, Yardley D, Mayer I, Spring L, Arteaga C, Wrabel E, DeMeo M, Freedman R, Tolaney S, Waks A, Bardia A, Parsons H, Partridge A, Mayer E, King T, Polyak K, Viale G, Winer E, Krop I. Withdrawn [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-15-01.

Evaluating Digital Maturity and Patient Acceptability of Real-Time Patient Experience Feedback Systems: Systematic Review

Background

One of the essential elements of a strategic approach to improving patients’ experience is to measure and report on patients’ experiences in real time. Real-time feedback (RTF) is increasingly being collected using digital technology; however, there are several factors that may influence the success of the digital system.

Objective

The aim of this review was to evaluate the digital maturity and patient acceptability of real-time patient experience feedback systems.

Methods

We systematically searched the following databases to identify papers that used digital systems to collect RTF: The Cochrane Library, Global Health, Health Management Information Consortium, Medical Literature Analysis and Retrieval System Online, EMBASE, PsycINFO, Web of Science, and CINAHL. In addition, Google Scholar and gray literature were utilized. Studies were assessed on their digital maturity using a Digital Maturity Framework on the basis of the following 4 domains: capacity/resource, usage, interoperability, and impact. A total score of 4 indicated the highest level of digital maturity.

Results

RTF was collected primarily using touchscreens, tablets, and Web-based platforms. Implementation of digital systems showed acceptable response rates and generally positive views from patients and staff. Patient demographics according to RTF responses varied. An overrepresentation existed in females with a white predominance and in patients aged ≥65 years. Of 13 eligible studies, none had digital systems that were deemed to be of the highest level of maturity. Three studies received a score of 3, 2, and 1, respectively. Four studies scored 0 points. While 7 studies demonstrated capacity/resource, 8 demonstrated impact. None of the studies demonstrated interoperability in their digital systems.

Conclusions

Patients and staff alike are willing to engage in RTF delivered using digital technology, thereby disrupting previous paper-based feedback. However, a lack of emphasis on digital maturity may lead to ineffective RTF, thwarting improvement efforts. Therefore, given the potential benefits of RTF, health care services should ensure that their digital systems deliver across the digital maturity continuum.

Prospective Risk Factor Analysis for the Development of Post-operative Urinary Retention Following Ambulatory General Surgery

Aims

Post-operative urinary retention (POUR) is a common cause of unplanned admission following day-case surgery and has negative effects on both patient and surgical institution. We aimed to prospectively evaluate potential risk factors for the development of POUR following day-case general surgical procedures.

Methods

Over a 24-week period, consecutive adult patients undergoing elective day-case general surgery at a single institution were prospectively recruited. Data regarding urinary symptoms, comorbidities, drug history, surgery and perioperative anaesthetic drug use were collected. The primary outcome was the incidence of POUR, defined as an impairment of bladder voiding requiring either urethral catheterisation, unplanned overnight admission or both. Potential risk factors for the development of POUR were analysed by logistic regression.

Results

A total of 458 patients met the inclusion criteria during the study period, and data were collected on 382 (83%) patients (74.3% male). Sixteen patients (4.2%) experienced POUR. Unadjusted analysis demonstrated three significant risk factors for the development of POUR: age ≥ 56 years (OR 7.77 [2.18–27.78], p = 0.002), laparoscopic surgery (OR 3.37 [1.03–12.10], p = 0.044) and glycopyrrolate administration (OR 5.56 [2.00–15.46], p = 0.001). Male sex and lower urinary tract symptoms were not significant factors. Multivariate analysis combining type of surgery, age and glycopyrrolate use revealed that only age ≥ 56 years (OR 8.14 [2.18–30.32], p = 0.0018) and glycopyrrolate administration (OR 3.48 [1.08–11.24], p = 0.0370) were independently associated with POUR.

Conclusions

Patients aged at least 56 years and/or requiring glycopyrrolate—often administered during laparoscopic procedures—are at increased risk of POUR following ambulatory general surgery.

Electronic supplementary material

The online version of this article (10.1007/s00268-018-4697-4) contains supplementary material, which is available to authorized users.

From free text to clusters of content in health records: an unsupervised graph partitioning approach

Electronic healthcare records contain large volumes of unstructured data in different forms. Free text constitutes a large portion of such data, yet this source of richly detailed information often remains under-used in practice because of a lack of suitable methodologies to extract interpretable content in a timely manner. Here we apply network-theoretical tools to the analysis of free text in Hospital Patient Incident reports in the English National Health Service, to find clusters of reports in an unsupervised manner and at different levels of resolution based directly on the free text descriptions contained within them. To do so, we combine recently developed deep neural network text-embedding methodologies based on paragraph vectors with multi-scale Markov Stability community detection applied to a similarity graph of documents obtained from sparsified text vector similarities. We showcase the approach with the analysis of incident reports submitted in Imperial College Healthcare NHS Trust, London. The multiscale community structure reveals levels of meaning with different resolution in the topics of the dataset, as shown by relevant descriptive terms extracted from the groups of records, as well as by comparing a posteriori against hand-coded categories assigned by healthcare personnel. Our content communities exhibit good correspondence with well-defined hand-coded categories, yet our results also provide further medical detail in certain areas as well as revealing complementary descriptors of incidents beyond the external classification. We also discuss how the method can be used to monitor reports over time and across different healthcare providers, and to detect emerging trends that fall outside of pre-existing categories.

Intraoperative ultrasound for improved 3D tumour reconstruction in robot-assisted surgery: An evaluation of feedback modalities

BACKGROUND

Intraoperative ultrasound scanning induces deformation on the tissue in the absence of a feedback modality, which results in a 3D tumour reconstruction that is not directly representative of real anatomy.

METHODS

A biomechanical model with different feedback modalities (haptic, visual, or auditory) was implemented in a simulation environment. A user study with 20 clinicians was performed to assess which modality resulted in the 3D tumour volume reconstruction that most resembled the reference configuration from the respective computed tomography (CT) scans.

RESULTS

Integrating a feedback modality significantly improved the scanning performance across all participants and data sets. The optimal feedback modality to adopt varied depending on the evaluation. Nonetheless, using guidance with feedback is always preferred compared with none.

CONCLUSIONS

The results demonstrated the urgency to integrate a feedback modality framework into clinical practice, to ensure an improved scanning performance. Furthermore, this framework enabled an evaluation that cannot be performed in vivo.