Pre-pregnancy health of women with pre-existing diabetes or previous gestational diabetes: Analysis of pregnancy risk factors and behavioural data from a digital tool.

AIMS: To examine health behaviours and risk factors in women with pre-existing diabetes or previous gestational diabetes mellitus who are planning pregnancy. METHODS: Health behaviour, risk factor and demographic data obtained from a digital pregnancy planning advisory tool (Tommy's charity UK) were analysed. Descriptive statistical analysis was performed, stratified by diabetes type. RESULTS: Data from 84,359 women, including 668 with type 1 diabetes, 707 with type 2 diabetes and 1785 with previous gestational diabetes obtained over a 12-month period (September 2019-September 2020) were analysed. 65%, 95%CI (61,68%) of women with type 2 diabetes and 46%, 95%CI (43,48%) with previous gestational diabetes were obese (BMI ≥30 kg/m2 ), compared with 26%, 95%CI (26,26%) without diabetes. Use of folic acid supplements was low; 41%, 95%CI (40,41%) of women without diabetes and 42%, 95%CI (40,45%) with previous gestational diabetes reported taking folic acid (any dose) while 47%, 95%CI (43.50%) women with type 1 diabetes and 44%, 95%CI (40,47%) women with type 2 diabetes respectively reported taking the recommended dose (5 mg). More women with type 1 diabetes and type 2 diabetes reported smoking (20%, 95%CI [17,23%] and 23%, 95%CI [20,26%] respectively) and taking illicit/recreational drugs (7%, 95%CI [6,10%] and 9%, 95% CI [7,11%]) compared to women without diabetes (smoking 17%, 95% CI [16,17%], drug use 5%, 95%CI [5,5%]). Alcohol consumption, low levels of physical activity and of fruit and vegetable intake were also evident. CONCLUSIONS: This study highlights the potential of online pregnancy planning advisory tools to reach high-risk women and emphasises the need to improve pre-pregnancy care for women with pre-existing diabetes and previous gestational diabetes, many of whom are actively seeking advice. It is also the first to describe pre-pregnancy health behaviours in women with previous gestational diabetes.

The physical-mental health interface in the preconception period: analysis of 131 182 women planning pregnancy in the UK.

OBJECTIVE: The physical and mental health of women prior to conception can have a significant impact on pregnancy and child outcomes. Given the rising burden of non-communicable diseases, the aim was to explore the relation between mental health, physical health and health behaviour in women planning a pregnancy. METHODS: Cross-sectional analysis of responses from 131 182 women to a preconception health digital education tool, providing data on physical and mental health and health behaviour. Logistic regression was used to explore associations between mental health and physical health variables. RESULTS: Physical health conditions were reported by 13.1% and mental health conditions by 17.8%. There was evidence for an association between self-reported physical and mental health conditions (odds ratio [OR] 2.22, 95% CI 2.14-2.3). Those with a mental health condition were less likely to engage with healthy behaviour at preconception such as folate supplementation (OR 0.89, 95% CI 0.86-0.92) and consumption of the recommended amount of fruit and vegetables (OR 0.77, 95% CI 0.74-0.79). They were more likely to be physically inactive (OR 1.14, 95% CI 1.11-1.18), smoke tobacco (OR 1.72, 95% CI 1.66-1.78) and use illicit substances (OR 2.4, 95% CI 2.25-2.55). CONCLUSIONS: Greater recognition of mental and physical comorbidities is needed and closer integration of physical and mental healthcare in the preconception period, which could support people to optimise their health during this time and improve long-term outcomes.

Dynamic Prediction of Patient Outcomes in the Intensive Care Unit: A Scoping Review of the State-of-the-Art.

INTRODUCTION: Intensive care units (ICUs) are high-pressure, complex, technology-intensive medical environments where patient physiological data are generated continuously. Due to the complexity of interpreting multiple signals at speed, there are substantial opportunities and significant potential benefits in providing ICU staff with additional decision support and predictive modeling tools that can support and aid decision-making in real-time.This scoping review aims to synthesize the state-of-the-art dynamic prediction models of patient outcomes developed for use in the ICU. We define "dynamic" models as those where predictions are regularly computed and updated over time in response to updated physiological signals. METHODS: Studies describing the development of predictive models for use in the ICU were searched, using PubMed. The studies were screened as per Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, and the data regarding predicted outcomes, methods used to develop the predictive models, preprocessing the data and dealing with missing values, and performance measures were extracted and analyzed. RESULTS: A total of n = 36 studies were included for synthesis in our review. The included studies focused on the prediction of various outcomes, including mortality (n = 17), sepsis-related complications (n = 12), cardiovascular complications (n = 5), and other complications (respiratory, renal complications, and bleeding, n = 5). The most common classification methods include logistic regression, random forest, support vector machine, and neural networks. CONCLUSION: The included studies demonstrated that there is a strong interest in developing dynamic prediction models for various ICU patient outcomes. Most models reported focus on mortality. As such, the development of further models focusing on a range of other serious and well-defined complications-such as acute kidney injury-would be beneficial. Furthermore, studies should improve the reporting of key aspects of model development challenges.

Incidence of Clostridioides difficile infection (CDI) related to antibiotic prescribing by GP surgeries in Wales.

BACKGROUND: Clostridioides difficile infection (CDI) is a healthcare-acquired infection (HAI) causing significant morbidity and mortality. Welsh CDI rates are high in comparison with those in England and Scotland. OBJECTIVES: This retrospective ecological study used aggregated disease surveillance data to understand the impact of total and high-risk Welsh GP antibiotic prescribing on total and stratified inpatient/non-inpatient CDI incidence. METHODS: All cases of confirmed CDI, during the financial years 2014-15 to 2017-18, were linked to aggregated rates of antibiotic prescribing in their GP surgery and classified as 'inpatient', 'non-inpatient' or 'unknown' by Public Health Wales. Multivariable negative-binomial regression models, comparing CDI incidence with antibiotic prescribing rates, were adjusted for potential confounders: location; age; social deprivation; comorbidities (estimated from prevalence of key health indicators) and proton pump inhibitor (PPI) prescription rates. RESULTS: There were 4613 confirmed CDI cases, with an incidence (95% CI) of 1.44 (1.40-1.48) per 1000 registered patients. Unadjusted analysis showed that an increased risk of total CDI incidence was associated with higher total antibiotic prescribing [relative risk (RR) (95% CI) = 1.338 (1.170-1.529) per 1000 items per 1000 specific therapeutic group age-sex related GP prescribing units (STAR-PU)] and that high-risk antibiotic classes were positively associated with total CDI incidence. Location, age ≥65 years and diabetes were associated with increased risk of CDI. After adjusting for confounders, prescribing of clindamycin showed a positive association with total CDI incidence [RR (95% CI) = 1.079 (1.001-1.162) log items per 1000 registered patients]. CONCLUSIONS: An increased risk of CDI is demonstrated at a primary care practice population level, reflecting their antibiotic prescribing rates, particularly clindamycin, and population demographics.

Health behaviours in 131,182 UK women planning pregnancy.

BACKGROUND: A woman's health at the time of conception lays the foundation for a healthy pregnancy and the lifelong health of her child. We investigated the health behaviours of UK women planning pregnancy. METHODS: We analysed survey data from the 'Planning for Pregnancy' online tool (Tommy's, UK). We described all women planning pregnancy and compared the frequency of non-adherence to preconception recommendations in women who had already stopped contraception (active planners) and those who had not (non-active planners). RESULTS: One hundred thirty-one thousand one hundred eighty-two women from across the UK were included, of whom 64.8% were actively planning pregnancy. Of the whole cohort, twenty percent were smokers and less than one third took folic acid supplements (31.5%). Forty two percent engaged in less than the recommended 150 min of weekly physical activity and only 53.3% consumed five portions of fruit or vegetables 4 days a week. Smokers were 1.87 times more likely to be active planners than non-smokers (95% CI 1.79-1.94), and women who took folic acid were 7 times more likely to be active planners (95% CI 6.97-7.59) compared to women who did not. Smoking, drug use and lack of folic acid supplementation were common in younger women and those who were underweight. CONCLUSIONS: This unique survey of UK women has identified poor adherence to preconception recommendations in those planning pregnancies and supports the need for a greater public health focus on preconception health. This study provides a contemporary basis from which to inform preconception health advice and a benchmark to measure changes over time.

Seasonal Influenza Vaccine Effectiveness in People With Asthma: A National Test-Negative Design Case-Control Study.

BACKGROUND: Influenza infection is a trigger of asthma attacks. Influenza vaccination can potentially reduce the incidence of influenza in people with asthma, but uptake remains persistently low, partially reflecting concerns about vaccine effectiveness (VE). METHODS: We conducted a test-negative designed case-control study to estimate the effectiveness of influenza vaccine in people with asthma in Scotland over 6 seasons (2010/2011 to 2015/2016). We used individual patient-level data from 223 practices, which yielded 1 830 772 patient-years of data that were linked with virological (n = 5910 swabs) data. RESULTS: Vaccination was associated with an overall 55.0% (95% confidence interval [CI], 45.8-62.7) risk reduction of laboratory-confirmed influenza infections in people with asthma over 6 seasons. There were substantial variations in VE between seasons, influenza strains, and age groups. The highest VE (76.1%; 95% CI, 55.6-87.1) was found in the 2010/2011 season, when the A(H1N1) strain dominated and there was a good antigenic vaccine match. High protection was observed against the A(H1N1) (eg, 2010/2011; 70.7%; 95% CI, 32.5-87.3) and B strains (eg, 2010/2011; 83.2%; 95% CI, 44.3-94.9), but there was lower protection for the A(H3N2) strain (eg, 2014/2015; 26.4%; 95% CI, -12.0 to 51.6). The highest VE against all viral strains was observed in adults aged 18-54 years (57.0%; 95% CI, 42.3-68.0). CONCLUSIONS: Influenza vaccination gave meaningful protection against laboratory-confirmed influenza in people with asthma across all seasons. Strategies to boost influenza vaccine uptake have the potential to substantially reduce influenza-triggered asthma attacks.

Use of record linkage to evaluate treatment outcomes and trial eligibility in a real-world metastatic prostate cancer population in Scotland.

PURPOSE: New treatments are introduced into standard care based on clinical trial results. However, it is not clear if these benefits are reflected in the broader population. This study analysed the clinical outcomes of patients with metastatic castration-resistant prostate cancer, treated with abiraterone and enzalutamide, within the Scottish National Health Service. METHODS: Retrospective cohort study using record linkage of routinely collected healthcare data (study period: February 2012 to February 2017). Overall survival (OS) was analysed using Kaplan-Meier methods and Cox Proportional Hazard models; a subgroup analysis comprised potentially trial-eligible patients. RESULTS: Overall, 271 patients were included and 73.8% died during the study period. Median OS was poorer than in the pivotal trials, regardless of medication and indication: 10.8 months (95% confidence interval [CI] 8.6-15.1) and 20.9 months (95% CI 14.9-29.0) for abiraterone, and 12.6 months (95% CI 10.5-18.2) and 16.0 months (95% CI 9.8-not reached) for enzalutamide, post and pre chemotherapy, respectively. Only 46% of patients were potentially "trial eligible" and in this subgroup OS improved. Factors influencing survival included baseline performance status, and baseline prostate-specific antigen, alkaline phosphatase, and albumin levels. CONCLUSIONS: Poorer prognostic features of non-trial eligible patients impact real-world outcomes of cancer medicines. Electronic record linkage of routinely collected healthcare data offers an opportunity to report outcomes on cancer medicines at scale and describe population demographics. The availability of such observational data to supplement clinical trial results enables patients and clinicians to make more informed treatment decisions, and policymakers to contextualise trial findings.

Head and neck cancer risk calculator (HaNC-RC)-V.2. Adjustments and addition of symptoms and social history factors.

OBJECTIVES: Head and neck cancer (HNC) diagnosis through the 2-week wait, urgent suspicion of cancer (USOC) pathway has failed to increase early cancer detection rates in the UK. A head and neck cancer risk calculator (HaNC-RC) has previously been designed to aid referral of high-risk patients to USOC clinics (predictive power: 77%). Our aim was to refine the HaNC-RC to increase its prediction potential. DESIGN: Following sample size calculation, prospective data collection and statistical analysis of referral criteria and outcomes. SETTING: Large tertiary care cancer centre in Scotland. PARTICIPANTS: 3531 new patients seen in routine, urgent and USOC head and neck (HaN) clinics. MAIN OUTCOME MEASURES: Data collected were as follows: demographics, social history, presenting symptoms and signs and HNC diagnosis. Univariate and multivariate regression analysis were performed to identify significant predictors of HNC. Internal validation was performed using 1000 sample bootstrapping to estimate model diagnostics included the area under the receiver operator curve (AUC), sensitivity and specificity. RESULTS: The updated version of the risk calculator (HaNC-RC v.2) includes age, gender, unintentional weight loss, smoking, alcohol, positive and negative symptoms and signs of HNC. It has achieved an AUC of 88.6% with two recommended triage referral cut-offs to USOC (cut-off: 7.1%; sensitivity: 85%, specificity: 78.3%) or urgent clinics (cut-off: 2.2%; sensitivity: 97.1%; specificity of 52.9%). This could redistribute cancer detection through USOC clinics from the current 60.9%-85.2%, without affecting total numbers seen in each clinical setting. CONCLUSIONS: The use of the HaNC-RC v.2 has a significant potential in both identifying patients at high risk of HNC early thought USOC clinics but also improving health service delivery practices by reducing the number of inappropriately urgent referrals.

Increased risk of HPV-associated genital cancers in men and women as a consequence of pre-invasive disease.

To assess the excess risk of HPV-associated cancer (HPVaC) in two at-risk groups-women with a previous diagnosis of high grade cervical intraepithelial neoplasia (CIN3) and both men and women treated for non-cervical pre-invasive anogenital disease. All CIN3 cases diagnosed in 1989-2015 in Scotland were extracted from the Scottish cancer registry (SMR06). All cases of pre-invasive penile, anal, vulval, and vaginal disease diagnosed in 1990-2015 were identified within the NHS pathology databases in the two largest NHS health boards in Scotland. Both were linked to SMR06 to extract subsequent incidence of HPVaC following the diagnosis of CIN3 or pre-invasive disease. Standardised incidence ratios were calculated for the risk of acquiring HPVaC for the two at-risk groups compared to the general Scottish population. Among 69,714 females in Scotland diagnosed with CIN3 (890,360.9 person-years), 179 developed non-cervical HPVaC. CIN3 cases were at 3.2-fold (95% CI: 2.7 to 3.7) increased risk of developing non-cervical HPVaC, compared to the general female population. Among 1,235 patients diagnosed with non-cervical pre-invasive disease (9,667.4 person-years), 47 developed HPVaC. Individuals with non-cervical pre-invasive disease had a substantially increased risk of developing HPVaC - 15.5-fold (95% CI: 11.1 to 21.1) increased risk for females and 28-fold (11.3 to 57.7) increased risk for males. We report a significant additional risk of HPV-associated cancer in those have been diagnosed with pre-invasive HPV-associated lesions including but not confined to the cervix. Uncovering the natural history of pre-invasive disease has potential for determining screening, prevention and treatment.

Risk factors for resistance and MDR in community urine isolates: population-level analysis using the NHS Scotland Infection Intelligence Platform.

BACKGROUND: Urinary tract infections (UTIs) are common. Antibiotic treatment is usually empirical, with the risk of under-treatment of resistant infections. OBJECTIVES: To characterize risk factors for antibiotic-resistant community urine isolates using routine record-linked health data. METHODS: Within the NHS Scotland Infection Intelligence Platform, national surveillance patient-level data on community urine isolates (January 2012-June 2015) were linked to hospital activity and community prescribing data. Associations between age, gender, comorbidity, care home residence, previous hospitalizations, antibiotic exposure and resistant (any antibiotic) or MDR (≥1 antibiotic from ≥3 categories) urinary isolates were quantified using multivariable logistic regression. RESULTS: Of 40984 isolates, 28% were susceptible, 45% were resistant and 27% were MDR. Exposure to ≥ 4 different antibiotics in the prior 6 months increased MDR risk (OR 6.81, 95% CI 5.73-8.11). MDR was associated with ≥29 DDD cumulative exposure, in the prior 6 months, for any antibiotic (OR 6.54, 95% CI 5.88-7.27), nitrofurantoin (OR 8.56, 95% CI 6.56-11.18) and trimethoprim (OR 14.61, 95% CI 10.53-20.27). Associations persisted for 10-12 months for nitrofurantoin (OR 2.31, 95% CI 1.93-2.76) and trimethoprim (OR 1.81, 95% CI 1.57-2.09). Increasing age, comorbidity, previous hospitalization and care home residence were independently associated with MDR. For resistant isolates the factors were the same, but with weaker associations. CONCLUSIONS: To our knowledge, we have demonstrated, using national capability at scale, the risk of MDR in community urine isolates for the first time and quantified the cumulative and sustained impact of antibiotic exposure. These data will inform the development of decision support tools for UTI treatment.

Building a national Infection Intelligence Platform to improve antimicrobial stewardship and drive better patient outcomes: the Scottish experience.

Background: The better use of new and emerging data streams to understand the epidemiology of infectious disease and to inform and evaluate antimicrobial stewardship improvement programmes is paramount in the global fight against antimicrobial resistance. Objectives: To create a national informatics platform that synergizes the wealth of disjointed, infection-related health data, building an intelligence capability that allows rapid enquiry, generation of new knowledge and feedback to clinicians and policy makers. Methods: A multi-stakeholder community, led by the Scottish Antimicrobial Prescribing Group, secured government funding to deliver a national programme of work centred on three key aspects: (i) technical platform development with record linkage capability across multiple datasets; (ii) a proportionate governance approach to enhance responsiveness; and (iii) generation of new evidence to guide clinical practice. Results: The National Health Service Scotland Infection Intelligence Platform (IIP) is now hosted within the national health data repository to assure resilience and sustainability. New technical solutions include simplified 'data views' of complex, linked datasets and embedded statistical programs to enhance capability. These developments have enabled responsiveness, flexibility and robustness in conducting population-based studies including a focus on intended and unintended effects of antimicrobial stewardship interventions and quantification of infection risk factors and clinical outcomes. Conclusions: We have completed the build and test phase of IIP, overcoming the technical and governance challenges, and produced new capability in infection informatics, generating new evidence for improved clinical practice. This provides a foundation for expansion and opportunity for global collaborations.

Cumulative and temporal associations between antimicrobial prescribing and community-associated Clostridium difficile infection: population-based case-control study using administrative data.

Background: Community-associated Clostridium difficile infection (CA-CDI; defined as cases without prior hospitalization in the previous 12 weeks who were either tested outside of hospital or tested within 2 days of admission to hospital) is a major public health problem. This study estimates the magnitude of the association between temporal and cumulative prescribing of antimicrobials in primary care and CA-CDI. Methods: Three national patient-level datasets, covering CDI cases, community prescriptions and hospitalizations, were linked by the NHS Scotland unique patient identifier, the Community Health Index (CHI). All validated cases of CDI from August 2010 to July 2013 were extracted and up to six population-based controls were matched to each case from the CHI register for Scotland. Statistical analysis used conditional logistic regression. Results: The 1446 unique cases of CA-CDI were linked with 7964 age-, sex- and location-matched controls. Cumulative exposure to any antimicrobial in the previous 6 months has a monotonic dose-response association with CA-CDI. Individuals with more than 28 DDDs to any antimicrobial (19.9% of cases) had an OR of 4.4 (95% CI 3.4-5.6) compared with those unexposed. Individuals exposed to 29+ DDDs of high-risk antimicrobials (cephalosporins, clindamycin, co-amoxiclav or fluoroquinolones) had an OR of 17.9 (95% CI 7.6-42.2). Elevated CA-CDI risk following high-risk antimicrobial exposure was greatest in the first month (OR = 12.5, 95% CI 8.9-17.4), but was still present 4-6 months later (OR = 2.6, 95% CI 1.7-3.9). Cases exposed to 29+ DDDs had prescription patterns more consistent with repeated therapeutic courses, using different antimicrobials, than long-term prophylactic use. Conclusions: This analysis demonstrated temporal and dose-response associations between CA-CDI risk and antimicrobials, with an impact of exposure to high-risk antimicrobials remaining 4-6 months later.

Human Papillomavirus Prevalence and Herd Immunity after Introduction of Vaccination Program, Scotland, 2009-2013.

In 2008, a national human papillomavirus (HPV) immunization program using a bivalent vaccine against HPV types 16 and 18 was implemented in Scotland along with a national surveillance program designed to determine the longitudinal effects of vaccination on HPV infection at the population level. Each year during 2009-2013, the surveillance program conducted HPV testing on a proportion of liquid-based cytology samples from women undergoing their first cervical screening test for precancerous cervical disease. By linking vaccination, cervical screening, and HPV testing data, over the study period we found a decline in HPV types 16 and 18, significant decreases in HPV types 31, 33, and 45 (suggesting cross-protection), and a nonsignificant increase in HPV 51. In addition, among nonvaccinated women, HPV types 16 and 18 infections were significantly lower in 2013 than in 2009. Our results preliminarily indicate herd immunity and sustained effectiveness of the bivalent vaccine on virologic outcomes at the population level.

Population-Level Effects of Human Papillomavirus Vaccination Programs on Infections with Nonvaccine Genotypes.

We analyzed human papillomavirus (HPV) prevalences during prevaccination and postvaccination periods to consider possible changes in nonvaccine HPV genotypes after introduction of vaccines that confer protection against 2 high-risk types, HPV16 and HPV18. Our meta-analysis included 9 studies with data for 13,886 girls and women ≤19 years of age and 23,340 women 20-24 years of age. We found evidence of cross-protection for HPV31 among the younger age group after vaccine introduction but little evidence for reductions of HPV33 and HPV45. For the group this same age group, we also found slight increases in 2 nonvaccine high-risk HPV types (HPV39 and HPV52) and in 2 possible high-risk types (HPV53 and HPV73). However, results between age groups and vaccines used were inconsistent, and the increases had possible alternative explanations; consequently, these data provided no clear evidence for type replacement. Continued monitoring of these HPV genotypes is important.

Use of HPV testing for cervical screening in vaccinated women--Insights from the SHEVa (Scottish HPV Prevalence in Vaccinated Women) study.

The management of cervical disease is changing worldwide as a result of HPV vaccination and the increasing use of HPV testing for cervical screening. However, the impact of vaccination on the performance of HPV based screening strategies is unknown. The SHEVa (Scottish HPV Prevalence in Vaccinated women) projects are designed to gain insight into the impact of vaccination on the performance of clinically validated HPV assays. Samples collated from women attending for first cervical smear who had been vaccinated as part of a national "catch-up" programme were tested with three clinically validated HPV assays (2 DNA and 1 RNA). Overall HR-HPV and type specific positivity was assessed in total population and according to underlying cytology and compared to a demographically equivalent group of unvaccinated women. HPV prevalence was significantly lower in vaccinated women and was influenced by assay-type, reducing by 23-25% for the DNA based assays and 32% for the RNA assay (p = 0.0008). All assays showed over 75% reduction of HPV16 and/or 18 (p < 0.0001) whereas the prevalence of non 16/18 HR-HPV was not significantly different in vaccinated vs unvaccinated women. In women with low grade abnormalities, the proportion associated with non 16/18 HR-HPV was significantly higher in vaccinated women (p < 0.0001). Clinically validated HPV assays are affected differentially when applied to vaccinated women, dependent on assay chemistry. The increased proportion of non HPV16/18 infections may have implications for clinical performance, consequently, longitudinal studies linking HPV status to disease outcomes in vaccinated women are warranted.

The burden of HPV-associated anogenital cancers.

The epidemiology of anogenital cancers is under going substantial change. Cervical cancer remains a major public health concern, particular in resource-limited settings. Cancers of the anus, penis, vagina and vulva are relatively uncommon cancers, but may be increasing in incidence. The change in occurrence of anogenital cancers may be due to increasing HPV transmission secondary to changes in sexual behaviour. Screening programmes and the HPV vaccine offer optimism that anogenital cancers can be prevented. This article reviews the epidemiology of anogenital cancers with a focus on Scottish data.

Invasive cervical cancer incidence following bivalent human papillomavirus vaccination: a population-based observational study of age at immunization, dose, and deprivation.

BACKGROUND: High-risk human papillomavirus causes cervical cancer. Vaccines have been developed that significantly reduce the incidence of preinvasive and invasive disease. This population-based observational study used linked screening, immunization, and cancer registry data from Scotland to assess the influence of age, number of doses, and deprivation on the incidence of invasive disease following administration of the bivalent vaccine. METHODS: Data for women born between January 1, 1988, and June 5, 1996, were extracted from the Scottish cervical cancer screening system in July 2020 and linked to cancer registry, immunization, and deprivation data. Incidence of invasive cervical cancer per 100 000 person-years and vaccine effectiveness were correlated with vaccination status, age at vaccination, and deprivation; Kaplan Meier curves were calculated. RESULTS: No cases of invasive cancer were recorded in women immunized at 12 or 13 years of age irrespective of the number of doses. Women vaccinated at 14 to 22 years of age and given 3 doses of the bivalent vaccine showed a significant reduction in incidence compared with all unvaccinated women (3.2/100 000 [95% confidence interval (CI) = 2.1 to 4.6] vs 8.4 [95% CI = 7.2 to 9.6]). Unadjusted incidence was significantly higher in women from most deprived (Scottish Index of Multiple Deprivation 1) than least deprived (Scottish Index of Multiple Deprivation 5) areas (10.1/100 000 [95% CI = 7.8 to 12.8] vs 3.9 [95% CI = 2.6 to 5.7]). Women from the most deprived areas showed a significant reduction in incidence following 3 doses of vaccine (13.1/100 000 [95% CI = 9.95 to 16.9] vs 2.29 [95% CI = 0.62 to 5.86]). CONCLUSION: Our findings confirm that the bivalent vaccine prevents the development of invasive cervical cancer and that even 1 or 2 doses 1 month apart confer benefit if given at 12-13 years of age. At older ages, 3 doses are required for statistically significant vaccine effectiveness. Women from more deprived areas benefit more from vaccination than those from less deprived areas.

Machine learning-enabled maternal risk assessment for women with pre-eclampsia (the PIERS-ML model): a modelling study.

BACKGROUND: Affecting 2-4% of pregnancies, pre-eclampsia is a leading cause of maternal death and morbidity worldwide. Using routinely available data, we aimed to develop and validate a novel machine learning-based and clinical setting-responsive time-of-disease model to rule out and rule in adverse maternal outcomes in women presenting with pre-eclampsia. METHODS: We used health system, demographic, and clinical data from the day of first assessment with pre-eclampsia to predict a Delphi-derived composite outcome of maternal mortality or severe morbidity within 2 days. Machine learning methods, multiple imputation, and ten-fold cross-validation were used to fit models on a development dataset (75% of combined published data of 8843 patients from 11 low-income, middle-income, and high-income countries). Validation was undertaken on the unseen 25%, and an additional external validation was performed in 2901 inpatient women admitted with pre-eclampsia to two hospitals in south-east England. Predictive risk accuracy was determined by area-under-the-receiver-operator characteristic (AUROC), and risk categories were data-driven and defined by negative (-LR) and positive (+LR) likelihood ratios. FINDINGS: Of 8843 participants, 590 (6·7%) developed the composite adverse maternal outcome within 2 days, 813 (9·2%) within 7 days, and 1083 (12·2%) at any time. An 18-variable random forest-based prediction model, PIERS-ML, was accurate (AUROC 0·80 [95% CI 0·76-0·84] vs the currently used logistic regression model, fullPIERS: AUROC 0·68 [0·63-0·74]) and categorised women into very low risk (-LR <0·1; eight [0·7%] of 1103 women), low risk (-LR 0·1 to 0·2; 321 [29·1%] women), moderate risk (-LR >0·2 and +LR <5·0; 676 [61·3%] women), high risk (+LR 5·0 to 10·0, 87 [7·9%] women), and very high risk (+LR >10·0; 11 [1·0%] women). Adverse maternal event rates were 0% for very low risk, 2% for low risk, 5% for moderate risk, 26% for high risk, and 91% for very high risk within 48 h. The 2901 women in the external validation dataset were accurately classified as being at very low risk (0% with outcomes), low risk (1%), moderate risk (4%), high risk (33%), or very high risk (67%). INTERPRETATION: The PIERS-ML model improves identification of women with pre-eclampsia who are at lowest and greatest risk of severe adverse maternal outcomes within 2 days of assessment, and can support provision of accurate guidance to women, their families, and their maternity care providers. FUNDING: University of Strathclyde Diversity in Data Linkage Centre for Doctoral Training, the Fetal Medicine Foundation, The Canadian Institutes of Health Research, and the Bill & Melinda Gates Foundation.

Estimation of HPV prevalence in young women in Scotland; monitoring of future vaccine impact.

BACKGROUND: Estimation of pre-immunisation prevalence of HPV and distribution of HPV types is fundamental to understanding the subsequent impact of HPV vaccination. We describe the type specific prevalence of HPV in females aged 20-21 in Scotland who attended or defaulted from cervical screening using three specimen types; from attenders liquid based cytology and from defaulters urine or self-taken swabs. METHODS: Residual liquid based cytology samples (n = 2148), collected from women aged 20-21 attending for their first smear were genotyped for HPV. A sample (n = 709) from women who had defaulted from screening was also made available for HPV testing through the use of postal testing kits (either urine samples (n = 378) or self-taken swabs (n = 331)). Estimates of prevalence weighted by deprivation, and for the postal testing kit, also by reminder status and specimen type were calculated for each HPV type. The distribution of HPV types were compared between specimen types and the occurrence of multiple high-risk infections examined. The influence of demographic factors on high-risk HPV positivity and multiple infections was examined via logistic regression. RESULTS: The prevalence of any HPV in young women aged 20-21 was 32.2% for urine, 39.5% for self-taken swab, and 49.4% for LBC specimens. Infection with vaccine specific types (HPV 16, 18) or those associated with cross-protection (HPV 31, 33, 45, 51) was common. Individuals were more likely to test positive for high-risk HPV if they resided in an area of high deprivation or in a rural area. The overall distribution of HPV types did not vary between defaulters and attenders. Multiple infections occurred in 48.1% of high-risk HPV positive individuals. Excluding vaccine types the most common pairing was HPV 56 and 66. CONCLUSIONS: Understanding of the pre-immunisation prevalence of HPV in young women puts Scotland in a prime position to assess the early effect of vaccination as the first highly vaccinated cohorts of individuals enter the screening programme. Differences in results with different specimen types must be taken into account when monitoring the impact of vaccination programmes.