A long section of serpentinized depleted mantle peridotite.

The upper mantle is critical for our understanding of terrestrial magmatism, crust formation, and element cycling between Earth's solid interior, hydrosphere, atmosphere, and biosphere. Mantle composition and evolution have been primarily inferred by surface sampling and indirect methods. We recovered a long (1268-meter) section of serpentinized abyssal mantle peridotite interleaved with thin gabbroic intrusions. We find depleted compositions with notable variations in mantle mineralogy controlled by melt flow. Dunite zones have predominantly intermediate dips, in contrast to the originally steep mantle fabrics, indicative of oblique melt transport. Extensive hydrothermal fluid-rock interaction is recorded across the full depth of the core and is overprinted by oxidation in the upper 200 meters. Alteration patterns are consistent with vent fluid composition in the nearby Lost City hydrothermal field.

Pathways to MPN presentation and time-to-diagnosis: results from a cross-sectional study.

BACKGROUND: Early cancer recognition is key to improving patient outcomes. Diagnosis is often delayed in myeloproliferative neoplasm (MPN) patients, putting them at risk of thromboembolic events and other complications pre-diagnosis. A clear understanding of the barriers to presentation and diagnosis is required. AIMS: To explore barriers and factors influencing delayed presentation and diagnosis of MPNs. DESIGN & SETTING: A cross-sectional study of MPN patients within the United Kingdom and the Republic of Ireland. METHOD: An online cross-sectional survey of MPN patients. Symptoms and factors influencing patient and General Practitioner (GP) delay were examined. Adjusted odds ratios (aOR) were calculated to explore the relationship between these factors and patient/GP delay. RESULTS: Most (80.2%) of the 620 patients completing the survey reported symptomatic presentation. The most common symptoms associated with patient delay were pruritus (aOR 1.89, 95% CI 1.19-3.01), headaches (aOR 1.86, 95% CI 1.13-2.82) and concentration difficulties (aOR 1.75, 95% CI 1.12-2.76). Attributing symptoms to ageing (aOR 1.92, 95% CI 1.19-3.11) and not wanting to burden the GP (aOR 2.17, 95% CI 1.35-3.50) were significantly associated with patient delay. Those reporting >3 blood cancer warning signs were more likely to experience GP delay than those experiencing fewer (aOR 3.26, 95% CI 1.75-6.29), and lack of relational continuity of GP care was significantly associated with GP delay (aOR 3.41, 95% CI 1.65-7.28). CONCLUSION: Debunking misconceptions around ageing, encouraging timely communication with GPs and improving relational continuity of GP care could assist in reducing diagnostic delays, prevent potentially fatal disease complications and ultimately improve MPN patient outcomes.

Use of natural language processing techniques to predict patient selection for total hip and knee arthroplasty from radiology reports.

Aims: To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology reports. Methods: Data pre-processing and analyses were conducted according to the Artificial intelligence to Revolutionize the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project protocol. This included use of de-identified Scottish regional clinical data of patients referred for consideration of THA/TKA, held in a secure data environment designed for artificial intelligence (AI) inference. Only preoperative radiology reports were included. NLP algorithms were based on the freely available GatorTron model, a LLM trained on over 82 billion words of de-identified clinical text. Two inference tasks were performed: assessment after model-fine tuning (50 Epochs and three cycles of k-fold cross validation), and external validation. Results: For THA, there were 5,558 patient radiology reports included, of which 4,137 were used for model training and testing, and 1,421 for external validation. Following training, model performance demonstrated average (mean across three folds) accuracy, F1 score, and area under the receiver operating curve (AUROC) values of 0.850 (95% confidence interval (CI) 0.833 to 0.867), 0.813 (95% CI 0.785 to 0.841), and 0.847 (95% CI 0.822 to 0.872), respectively. For TKA, 7,457 patient radiology reports were included, with 3,478 used for model training and testing, and 3,152 for external validation. Performance metrics included accuracy, F1 score, and AUROC values of 0.757 (95% CI 0.702 to 0.811), 0.543 (95% CI 0.479 to 0.607), and 0.717 (95% CI 0.657 to 0.778) respectively. There was a notable deterioration in performance on external validation in both cohorts. Conclusion: The use of routinely available preoperative radiology reports provides promising potential to help screen suitable candidates for THA, but not for TKA. The external validation results demonstrate the importance of further model testing and training when confronted with new clinical cohorts.

A stakeholder analysis to prepare for real-world evaluation of integrating artificial intelligent algorithms into breast screening (PREP-AIR study): a qualitative study using the WHO guide.

BACKGROUND: The national breast screening programme in the United Kingdom is under pressure due to workforce shortages and having been paused during the COVID-19 pandemic. Artificial intelligence has the potential to transform how healthcare is delivered by improving care processes and patient outcomes. Research on the clinical and organisational benefits of artificial intelligence is still at an early stage, and numerous concerns have been raised around its implications, including patient safety, acceptance, and accountability for decisions. Reforming the breast screening programme to include artificial intelligence is a complex endeavour because numerous stakeholders influence it. Therefore, a stakeholder analysis was conducted to identify relevant stakeholders, explore their views on the proposed reform (i.e., integrating artificial intelligence algorithms into the Scottish National Breast Screening Service for breast cancer detection) and develop strategies for managing 'important' stakeholders. METHODS: A qualitative study (i.e., focus groups and interviews, March-November 2021) was conducted using the stakeholder analysis guide provided by the World Health Organisation and involving three Scottish health boards: NHS Greater Glasgow & Clyde, NHS Grampian and NHS Lothian. The objectives included: (A) Identify possible stakeholders (B) Explore stakeholders' perspectives and describe their characteristics (C) Prioritise stakeholders in terms of importance and (D) Develop strategies to manage 'important' stakeholders. Seven stakeholder characteristics were assessed: their knowledge of the targeted reform, position, interest, alliances, resources, power and leadership. RESULTS: Thirty-two participants took part from 14 (out of 17 identified) sub-groups of stakeholders. While they were generally supportive of using artificial intelligence in breast screening programmes, some concerns were raised. Stakeholder knowledge, influence and interests in the reform varied. Key advantages mentioned include service efficiency, quicker results and reduced work pressure. Disadvantages included overdiagnosis or misdiagnosis of cancer, inequalities in detection and the self-learning capacity of the algorithms. Five strategies (with considerations suggested by stakeholders) were developed to maintain and improve the support of 'important' stakeholders. CONCLUSIONS: Health services worldwide face similar challenges of workforce issues to provide patient care. The findings of this study will help others to learn from Scottish experiences and provide guidance to conduct similar studies targeting healthcare reform. STUDY REGISTRATION: researchregistry6579, date of registration: 16/02/2021.

Autoimmune conditions and gastric cancer risk in a population-based study in the United Kingdom.

BACKGROUND: Although overall incidence of gastric cancer is decreasing, incidence has been increasing among young people in some Western countries. This trend may stem from the increase in autoimmune conditions. METHODS: A nested case-control study of gastric cancer in UK Clinical Practice Research Datalink. Up to ten cancer-free controls were matched to cases by age and sex. Conditional logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI) for associations between analyzable autoimmune conditions (n = 34) and gastric cancer with Bonferroni correction. We evaluated associations between pernicious anaemia and other conditions. A meta-analysis of published prospective studies and ours was conducted. RESULTS: Among 6586 cases (1156 cardia, 1104 non-cardia, and 4334 overlapping/unspecified tumours) and 65,687 controls, any autoimmune condition was associated with gastric cancer (OR = 1.10; 95% CI: 1.01-1.20). Individuals with pernicious anaemia had higher gastric cancer risk than those without (OR = 2.75; 2.19-3.44). Among controls, pernicious anaemia was associated with seven other conditions (OR range: 2.21-29.80). The pooled estimate for any autoimmune condition and gastric cancer was 1.17 (1.14-1.21; n = 47,126 cases). CONCLUSION: Autoimmunity increases gastric cancer risk. Some autoimmune conditions may be indirectly associated with gastric cancer via pernicious anaemia. Pernicious anaemia could be considered for gastric cancer risk stratification and screening.

Service and clinical impacts of reader bias in breast cancer screening: a retrospective study.

OBJECTIVES: To determine factors influencing reader agreement in breast screening and investigate the relationship between agreement level and patient outcomes. METHODS: Reader pair agreement for 83 265 sets of mammograms from the Scottish Breast Screening service (2015-2020) was evaluated using Cohen's kappa statistic. Each mammography examination was read by two readers, per routine screening practice, with the second initially blinded but able to choose to view the first reader's opinion. If the two readers disagreed, a third reader arbitrated. Variation in reader agreement was examined by: whether the reader acted as the first or second reader, reader experience, and recall, cancer detection and arbitration recall rate. RESULTS: Readers' opinions varied by whether they acted as the first or second reader. Furthermore, reader 2 was more likely to agree with reader 1 if reader 1 was more experienced than they were, and less likely to agree if they themselves were more experienced than reader 1 (P < .001). Agreement was not significantly associated with cancer detection rate, overall recall rate or arbitration recall rates (P > .05). Lower agreement between readers led to a higher arbiter workload (P < .001). CONCLUSIONS: In mammography screening, the second reader's opinion is influenced by the first reader's opinion, with the degree of influence dependent on the readers' relative experience levels. ADVANCES IN KNOWLEDGE: While less-experienced readers relied on their more experienced reading partner, no adverse impact on service outcomes was observed. Allowing access to the first reader's opinion may benefit newly qualified readers, but reduces independent evaluation, which may lower cancer detection rates.