1,720,971 research outputs found
PTH-058 smart colonoscopy: using big-data to identify predictors of normal colonoscopic examinations
No full textIntroduction: endoscopy workload is increasing at a faster pace than available resources. The NHS has a wealth of data, which if used properly can improve resource allocation in future. The aim of this study was to review mass colonoscopy data to identify those factors most associated with a normal examination, in order to help rationalise future resource utilisation.Methods: we constructed a standardised, anonymised database, containing all colonoscopies performed locally between 01/01/2010 and 10/12/2016. The records were then histology matched. The data was then analysed using the AnacondasTM 3 distribution of Python, using numpy, pandas, matplotlib and seaborn to clean and prepare, plot and perform statistical analysis on the data.Results: 23 837 colonoscopies were performed on 18 489 individual adults during the study period. 544 procedures had to be excluded as they lacked an NHS number and couldn’t be histology matched. 23 293 procedures remained.50.4% of the procedures were performed on females. The median age was 64. Across all the procedures, 25.46% were reported as entirely normal by the endoscopist. 3.04% of procedures contained a histologically confirmed cancer.[PTH-058 Figure 1 Age vs% normal examinations not included].Age: we found that the chances of obtaining a normal examination declined from ~49%±5% ≤43 years to ≤20%±2% in those ≥61 years. In patients aged ≤43 OR of a normal exam=3.29. For those aged ≥61, (OR=0.32 for a normal exam). Note, all OR’s in this study had p<0.0001 significance.Sex: examinations performed on females were more likely to be reported as normal compared to men (OR=1.73). For women≤43, OR for normality=3.88.Priority: routine priority was strongly associated with normal colonoscopy, (OR=1.99). Routine procedures on females≤43 were very likely to be normal (OR=4.90). These patients were very unlikely to have cancer (OR=0.093).Indications: abdominal pain, anaemia (iron deficient) and bowel habit changes (of all types) and family history of colonic cancer were all found to be associated with a≥40% rate of normal examinations, (OR=3.57). The highest incidence of normal examinations was found amongst women≤43 undergoing routine colonoscopy for abdominal pain (OR=7.85), followed by bowel habit changes (OR=6.49), and anaemia (OR=5.91). Conversely, the highest rates of pathology were found in men≥61 undergoing bowel cancer screening, (OR for pathology=4.98; OR for malignancy=2).Conclusions: we have developed a method for performing mass data analysis to identify trends in endoscopy data. Our data can help improve future utilisation of other colonic investigational modalities like colon capsule for low risk individuals. This can release colonoscopy capacity for the patients most at need.<br/
P75 comparison between 4% formalin instillation and purastat application for radiation proctopathy
No full textIntroduction: Formalin therapy is an established method for the treatment of radiation proctopathy (RP). Emerging data suggests a potential role for Purastat application in the treatment of RP; however, no comparison to conventional treatment has been made to date. The aim of this study was to assess the safety and efficacy of Purastat for the treatment of RP compared to conventional treatment. Methods: consecutive patients with RP referred between January 2018 and December 2019 were treated with either conventional formalin or Purastat, based on endoscopist preference. Patients symptoms were scored with the subjective, objective management analysis (SOMA) scale, and the endoscopic severity of RP was graded by Zincola score. These measures were taken pre-treatment and prior to any subsequently planned treatments if clinically warranted, typically at 6-week intervals up to a maximum of 4 sessions. Results: of 17 patients (all male) referred for treatment, 11 patients underwent conventional Formalin instillation and 6 patients Purastat. Table 1 shows demographic and treatment outcomes. There was no statistical difference between the 2 groups in patient demographics, baseline symptom severity and Zincola score. Post-treatment protocol SOMA score reduction was significantly greater in the formalin group v Purastat group (8 to 1 v 8.2 to 4, p=0.01 respectively), and Zincola score reduction ( 4–2 v 4–3, p= 0.04 respectively). There was 1 case of mild anaphylaxis with facial flushing with Formalin, which settled with observation. [P75 Table 1 Demographic and treatment outcomes not included]. Conclusions: formalin instillation is still a cheap and effective treatment of RP. Although Purastat has a beneficial adverse event profile, its limited effect in this small cohort does not yet warrant widespread usage
Robust comparative evaluation of 15 natural language processing algorithms to positively identify patients with inflammatory bowel disease from secondary care records
No full textObjective: natural language processing (NLP) can identify cohorts of patients with inflammatory bowel disease (IBD) from free text. However, limited sharing of code, models, and data sets continues to hinder progress. The aim of this study was to evaluate multiple open-source NLP models for identifying IBD cohorts, reporting on document-to-patient-level classification, while exploring explainability, generalisability, fairness and cost.Methods: 15 algorithms were assessed, covering all types of NLP spanning over 50 years of NLP development. Rule-based (regular expressions, spaCy with negation), and vector-based (bag-of-words (BoW), term frequency inverse document frequency (TF IDF), word-2-vector), to transformers: (two sentence-based sBERT models, three bidirectional encoder representations from transformers (BERT) models (distilBERT, BioclinicalBERT, RoBERTa), and five large language models (LLMs): (Mistral-Instruct-v0.3-7B, M42-Health/Llama-v3-8B, Deepseek-R1-Distill-Qwen-v2.5-32B, Qwen-v3-32B, and Deepseek-R1-Distill-Llama-v3-70B). Models were comparatively evaluated based on full confusion matrices, time/environmental costs, fairness, and explainability.Results: a total of 9311 labelled documents were evaluated. The fine-tuned DistilBERT_IBD model achieved the best performance overall (micro F1: 93.54%), followed by sBERT-Base (micro F1: 93.05%); however, specificity was an issue for both: (67.80-64.41%) respectively. LLMs performed well, given that they had never seen the training data (micro F1: 86.47-92.20%), but were comparatively slow (18-300 hours) and expensive. Bias was a significant issue for all effective model types.Conclusion: NLP has undergone significant advancements over the last 50 years. LLMs appear likely to solve the problem of re-identifying patients with IBD from clinical free text sources in the future. Once cost, performance and bias issues are addressed, they and their successors are likely to become the primary method of data retrieval for clinical data warehousing.</p
O69 outcome of direct access IBD physician delivered endoscopy for general practice referrals with suspected IBD
No full textIntroduction: patients with suspected IBD referred by primary care (GP) are traditionally seen in gastroenterology outpatient clinics followed by endoscopic investigations. This 2 phase model leads to delay in diagnosis and treatment, increasing pressure on gastroenterology outpatient services while still requiring endoscopic intervention. Our novel pilot project compared outcomes between direct-access IBD physician-delivered endoscopy versus the traditional clinic model for patients with suspected IBD.Method: a prospective cohort of consecutive patients referred by GP with suspected IBD were triaged either direct to IBD endoscopy (n=50) or to outpatient IBD clinic followed by IBD endoscopy (n=50) at the discretion of 10 gastroenterology consultants grading GP referrals. Data on demographics, faecal calprotectin, C-reactive protein, endoscopy outcomes, treatment, and follow up was collected. (Group A = direct to IBD endoscopy and Group B = IBD endoscopy via IBD clinic).Results: both groups were age and gender-matched. Group A had a higher mean calprotectin (1363 ug/g vs 302 ug/g) and a higher C-reactive protein (10.6 mg/l vs 4.5 mg/l). In Group A only 38% had a full colonoscopy versus 86% in Group B. Definitive diagnosis and treatment at time of IBD endoscopy took 27 days in Group A versus 212 days in Group B. Treatment with immunomodulators and biologics was similar in both groups but mesalazine and steroid use was higher in Group A due to more severe disease and higher rate of ulcerative colitis, table 1 shows the diagnostic breakdowns from both groups following endoscopy. The IBD pick up was significantly higher in Group A with 70% vs 42%. Endoscopy DNA rate was twice as high in Group B (n=6). The direct to IBD endoscopy pathway resulted in 50 less initial IBD consultant clinics (100% reduction) with a follow-up shift from IBD consultant to IBD nurse clinics. [O69 Table 1 Diagnostic breakdown not included].Conclusion: triaging patients referred with suspected IBD directly to IBD physician delivered endoscopy resulted in more than a 26-week reduction in time to diagnosis and treatment while saving 100% of initial IBD consultant clinics. IBD pick up was high at 70% in direct to IBD endoscopy group, identifying a higher-need IBD population. Triaging GP referrals with suspected IBD direct to IBD endoscopy delivers rapid assessment and treatmen
Routine molecular point-of-care testing for SARS-CoV-2 reduces hospital-acquired COVID-19
No full textObjectives: Risk of hospital-acquired COVID-19 (HA-COVID-19) infection is increased by cohorting infected and non-infected patients together in assessment areas, whist awaiting laboratory PCR results. Molecular point-of-care tests (mPOCT) reduce time to results and improve patient flow but the impact on HA-COVID-19 is unknown. Methods: In this pre and post implementation study patients were evaluated across two time periods: March 1st to August 13th 2020, prior to the introduction of mPOCT in medical admissions areas, and 14th August 2020 to 1st April 2021, after mPOCT introduction. The primary outcome was proportion of HA-COVID-19 infection among all COVID-19 positive patients. Secondary outcome measures included time to SARS-CoV-2 results, length of time spent in the medical assessment area and comparison of local, regional and national proportions of HA-COVID-19. Results: 1988 patients were admitted through the acute medicine admission cohorting area and tested for SARS-CoV-2 prior to introducing mPOCT and 4640 afterwards. Median (IQR) time to SARS-CoV-2 result was 6.5 (2.1–17.9) hours prior to introducing mPOCT and 1.0 (0.8–1.3) hours afterwards (p < 0.0001). Median (IQR) duration in the assessment cohort area was 12.0 (4.8–20.6) hours prior to introduction of POCT and 3.2 (2.0–5.6) hours afterwards (p < 0.0001). The proportion of hospital-acquired COVID-19 cases was 108 (16.5%) of 654 prior to introducing mPOCT compared with 168 (9.4%) of 1782 afterwards, (HR 0.55, 95%CI 0.43–0.70; p < 0.0001). In the period following the introduction of mPOCT up to 1st April 2021 the median proportion of HA-COVID-19 was 13.6% (95%CI 8.2–18.9%) locally, compared with 43.8% (95%CI 37.8–49.9%) for all acute NHS trusts regionally and 30.9% (95%CI 28.4–33.5%) for all NHS trusts nationally. Conclusions: Routine mPOCT for SARS-CoV-2 was associated with reduced time to results, time spent in admission cohort areas, and hospital-acquired COVID-19, compared to laboratory PCR.</p
Acute kidney injury in COVID‐19: Identification of risk factors and potential biomarkers of disease in a large UK cohort
No full textBackground: COVID‐19 is associated with increased risk of acute kidney injury (AKI). Risk factors and biomarkers linked to AKI have now been recognized by national guidelines in the United Kingdom. This analysis aims to validate and expand the comorbidities and biomarkers associated with the presence and severity of AKI in these patients.Methods: Data were extracted via structured query language for patients with COVID‐19 at University Hospital Southampton between 1 March and 10 June 2020. Demographics, comorbidities, common biomarkers and AKI stage within 48 hours of admission, peak during admission and the last measurement prior to patient outcome (discharge or death) were collected and statistically analysed.Results: Six hundred and thirty‐two COVID‐19 positive patients were admitted during this period; 34.2% had an AKI during their entire admission, 20.3% had AKI stage 1, 8.5% stage 2 and 5.4% stage 3. This was higher when compared with data from the same period in 2019. AKI carried an increased risk of death, 50.0% vs 21.1% (P = <.001). AKI stage was significantly associated with age over 65, diabetes, heart failure, peripheral vascular disease, haematological malignancy, hypertension, respiratory rate, albumin, C‐reactive protein (CRP), d‐dimer, ferritin, high‐sensitivity troponin‐I, neutrophil count, total white cell counts, National Early Warning Score‐2 (NEWS‐2), Charlson comorbidity index and alanine‐aminotransferase. COVID‐19 specific treatment, including dexamethasone, reduced discharge creatinine.Conclusion: COVID‐19 increases the risk of AKI and this kidney injury may be responsive to treatment. This analysis identified that AKI is associated with both previously described and new comorbidities and biomarkers
O44 new GI bleed nursing model & unit changes outcomes
No full textIntroduction: a dedicated GI bleed and liver unit (GIBLU) was created within the GI inpatient footprint. Each bay is staffed by 1 specially trained nurse to 4 patients with continuous monitoring available, a readily accessible medical team and 24-hour access to senior gastroenterology support. Aim: to assess the effectiveness of this change across the hospital.Methods: the pre-implementation cohort contained all patients undergoing inpatient therapeutic endoscopy between April 2019 &amp Feb 2020. The post-implementation cohort contained all cases between April 2021 – Feb 2022. GI bleeds outside the GIBLU were also analysed. Measured covariates included age, sex, Charlson comorbidity index (CCI) and hospital frailty risk score (HFRS). Outcomes of interest included 30-day mortality (30DM), length of stay (LOS), readmission and rescoped rebleed rates. Chi2, Mann-Whitney U and Logistic Regression (LR) were calculated using p<0.05.Results: there were 225 scoped bleeds in the 2019 cohort and 359 in the 2021 cohort. There were no significant differences in age (p=0.8450) or sex (p=0.2057) between the 2019 and 2021 cohorts. Overall 30DM in 2019 was 10.6%(95%CI:6.6–14.7) vs 11.1%(95%CI:7.8–14.4) in 2021, difference 0.5%(95%CI: -0.3–1.3), (p=0.8565). A comparison of the GIBLU and non-GIBLU cohorts in 2021 is given in table 1: [O44 Table 1 Key Outcomes (means) not included].To help control for confounding 30DM LR prediction models were constructed: Coefficients = GIBLU: -0.67 (p=0.1378), Age: 0.02 (p=0.2801), Male Sex: 0.89 (p=0.0857), CCI: 0.21 (p=0.1004), HFRS: -0.07 (p=0.7571). Although none of the covariates reached significance GIBLU is the only protective factor with any strength.Conclusions: despite increased demands on the service, length of stay and 30DM were both significantly lower in the GIBLU cohort which cannot be explained purely by demographic differences between the cohorts. Expanding the scope of GIBLU locally in 2022 seems highly likely given these results
P318 electronic referral grading system that puts patients and clinicians first
No full textIntroduction: the NHS Long Term Plan estimates demand for gastroenterology outpatient appointments (OPA) will continue to increase with the Royal College of Physicians deeming up to 20% of new referrals unnecessary. Bespoke electronic referral grading provides direct access to all community and hospital electronic patient records allowing fully informed immediate decision making. This can avoid unnecessary OPAs by redirecting/rejecting and sending appropriate patients direct-to-test while getting the right patient to the right clinician through sub-speciality tagging.Methods Outcomes: proportion/number of first OPA appointments saved, time to first appointment and subspecialty focus. Pre-grading period: Sep 2018–Mar 2020. Post-grading period: Aug 2020–Feb 2022. The separate 2WW IDA pathway was excluded. Cardiology/rheumatology were used as controls. Wait in days at the 50th percentile was calculated. One-tailed Mann Whitney U test calculated statistical significance at the p<0.05 level. Number of appointments saved per year and resultant financial implications were estimated.Results: GI received 3,768 consultant-graded referrals (Sep 2018–Mar 2020) and 3,908 (Aug 2020–Feb 2022).Referral sub-specialty groupings:1) Inflammatory Bowel Disease–765(19.6%)1. Irritable Bowel Syndrome–755(19.3%)2. Upper GI Diseases–753(19.3%)3. Non–IBD Colorectal–426(10.9%)4. Non–2WW Iron Deficiency Anaemia–345(8.8%)5. Unexplained Weight Loss–165(4.2%)6. Surgical/Hepatology–159(4.1%)7. Coeliac–139(3.6%)8. Endoscopy–126(3.2%)9. Complex Functional–106(2.7%)10. Not Tagged–88(2.3%)11. Intestinal Failure–81(2.1%)Documented referral rejection rates increased from 1% to 19% (n=745/3908) in the second period. 456 (11.6%) of patients were diverted directly to endoscopy, cumulatively saving 30.7% (n=1201) first OPA appointments equivalent to 150 new patient clinics. Total savings = £101,731/year in first GI OPA alone given the current block contract structure. Time to first appointment reduced by 58% but no improvement was seen in comparator specialties: [P318 Table 1Clinic wait times compared @ the 50th percentile not included]. Conclusions: use of a consultant-led electronic grading system had dramatic effects on the quality of data collected and significantly reduced first OPA waits at the trust. The reasons for this were triage direct-to-test and proactive rejection/redirection of referrals using sub-speciality tagging to get the right patient to the right clinician
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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