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Identify risk factors for poor pain outcomes six months after primary knee replacement surgery. Observational cohort study on patients receiving primary knee replacement from the UK Clinical Practice Research Datalink, Hospital Episode Statistics and Patient Reported Outcomes. A wide range of variables routinely collected in primary and secondary care were identified as potential predictors of worsening or only minor improvement in pain, based on the Oxford Knee Score pain subscale. Results are presented as relative risk ratios and adjusted risk differences (ARD) by fitting a generalized linear model with a binomial error structure and log link function. Information was available for 4,750 patients from 2009 to 2016, with a mean age of 69, of whom 56.1% were female. 10.4% of patients had poor pain outcomes. The strongest effects were seen for pre-operative factors: mild knee pain symptoms at the time of surgery (ARD 18.2% (95% Confidence Interval 13.6, 22.8), smoking 12.0% (95% CI:7.3, 16.6), living in the most deprived areas 5.6% (95% CI:2.3, 9.0) and obesity class II 6.3% (95% CI:3.0, 9.7). Important risk factors with more moderate effects included a history of previous knee arthroscopy surgery 4.6% (95% CI:2.5, 6.6), and use of opioids 3.4% (95% CI:1.4, 5.3) within three months after surgery. Those patients with worsening pain state change had more complications by 3 months (11.8% among those in a worse pain state vs. 2.7% with the same pain state). We quantified the relative importance of individual risk factors including mild pre-operative pain, smoking, deprivation, obesity and opioid use in terms of the absolute proportions of patients achieving poor pain outcomes. These findings will support development of interventions to reduce the numbers of patients who have poor pain outcomes.

ObjectivesUptake of influenza, pneumococcal and shingles vaccines in older adults vary across regions and socioeconomic backgrounds. In this study, we study the coverage and factors associated with vaccination uptake, as well as refusal in the unvaccinated population and their associations with ethnicity, deprivation, household size and health conditions.Design, setting and participantsThis is a cross-sectional study of adults aged 65 years or older in England, using a large primary care database. Associations of vaccine uptake and refusal in the unvaccinated with ethnicity, deprivation, household size and health conditions were modelled using multivariable logistic regression.Outcome measureInfluenza, pneumococcal and shingles vaccine uptake and refusal (in the unvaccinated).ResultsThis study included 2 054 463 patients from 1318 general practices. 1 711 465 (83.3%) received at least one influenza vaccine, 1 391 228 (67.7%) pneumococcal vaccine and 690 783 (53.4%) shingles vaccine. Compared with White ethnicity, influenza vaccine uptake was lower in Chinese (OR 0.49; 95% CI 0.45 to 0.53), ‘Other ethnic’ groups (0.63; 95% CI 0.60 to 0.65), black Caribbean (0.68; 95% CI 0.64 to 0.71) and black African (0.72; 95% CI 0.68 to 0.77). There was generally lower vaccination uptake among more deprived individuals, people living in larger household sizes (three or more persons) and those with fewer health conditions. Among those who were unvaccinated, higher odds of refusal were associated with the black Caribbean ethnic group and marginally with increased deprivation, but not associated with higher refusal in those living in large households or those with lesser health conditions.ConclusionCertain ethnic minority groups, deprived populations, large households and 'healthier' individuals were less likely to receive a vaccine, although higher refusal was only associated with ethnicity and deprivation but not larger households nor healthier individuals. Understanding these may inform tailored public health messaging to different communities for equitable implementation of vaccination programmes.

Background Despite concerns about worsening pregnancy outcomes resulting from healthcare restrictions, economic difficulties and increased stress during the COVID-19 pandemic, preterm birth (PTB) rates declined in some countries in 2020, while stillbirth rates appeared stable. Like other shocks, the pandemic may have exacerbated existing socioeconomic disparities in pregnancy, but this remains to be established. Our objective was to investigate changes in PTB and stillbirth by socioeconomic status (SES) in European countries. Methods The Euro-Peristat network implemented this study within the Population Health Information Research Infrastructure (PHIRI) project. A common data model was developed to collect aggregated tables from routine birth data for 2015–2020. SES was based on mother’s educational level or area-level deprivation/maternal occupation if education was unavailable and harmonized into low, medium and high SES. Country-specific relative risks (RRs) of PTB and stillbirth for March to December 2020, adjusted for linear trends from 2015 to 2019, by SES group were pooled using random effects meta-analysis. Results Twenty-one countries provided data on perinatal outcomes by SES. PTB declined by an average 4% in 2020 {pooled RR: 0.96 [95% confidence intervals (CIs): 0.94–0.97]} with similar estimates across all SES groups. Stillbirths rose by 5% [RR: 1.05 (95% CI: 0.99–1.10)], with increases of between 3 and 6% across the three SES groups, with overlapping confidence limits. Conclusions PTB decreases were similar regardless of SES group, while stillbirth rates rose without marked differences between groups.

ObjectiveTo identify patients at risk of mid-late term revision of knee replacement (KR) to inform targeted follow-up.DesignAnalysis of linked national datasets from primary and secondary care (Clinical Practice Research Datalink (CPRD GOLD), National Joint Registry (NJR), English Hospital Episode Statistics (HES) and Patient Reported Outcome Measures (PROMs)).ParticipantsPrimary elective KRs aged ≥18 years.Event of interestRevision surgery ≥5 years (mid–late term) postprimary KR.Statistical methodsCox regression modelling to ascertain risk factors of mid–late term revision. HRs and 95% CIs assessed association of sociodemographic factors, comorbidities, medication, surgical variables and PROMs with mid–late term revision.ResultsNJR-HES-PROMs data were available from 2008 to 2011 on 188 509 KR. CPRD GOLD-HES data covered 1995–2011 on 17 378 KR. Patients had minimum 5 years postprimary surgery to end 2016. Age and gender distribution were similar across datasets; mean age 70 years, 57% female. In NJR, there were 8607 (4.6%) revisions, median time-to-revision postprimary surgery 1.8 years (range 0–8.8), with 1055 (0.6%) mid–late term revisions; in CPRD GOLD, 877 (5.1%) revisions, median time-to-revision 4.2 years (range 0.02–18.3), with 352 (2.0%) mid–late term revisions.Reduced risk of revision after 5 years was associated with older age (HR: 0.95; 95% CI 0.95 to 0.96), obesity (0.70; 0.56 to 0.88), living in deprived areas (0.71; 0.58 to 0.87), non-white ethnicity (0.58; 0.43 to 0.78), better preoperative pain and functional limitation (0.42; 0.33 to 0.53), better 6-month postoperative pain and function (0.33; 0.26 to 0.41) or moderate anxiety/depression (0.73; 0.63 to 0.83) at primary surgery.Increased risk was associated with male gender (1.32; 1.04 to 1.67); when anticonvulsants (gabapentin and pregabalin) (1.58; 1.01 to 2.47) or opioids (1.36; 1.08 to 1.71) were required prior to primary surgery.No implant factors were identified.ConclusionThe risk of mid–late term KR revision is very low. Increased risk of revision is associated with patient case-mix factors, and there is evidence of sociodemographic inequality.

ObjectiveTo identify patients at risk of mid-late term revision of hip replacement to inform targeted follow-up.DesignAnalysis of linked national data sets from primary and secondary care (Clinical Practice Research Datalink (CPRD-GOLD); National Joint Registry (NJR); English Hospital Episode Statistics (HES); Patient-Reported Outcome Measures (PROMs)).ParticipantsPrimary elective total hip replacement (THR) aged≥18.Event of interestRevision surgery≥5 years (mid-late term) after primary THR.Statistical methodsCox regression modelling to ascertain risk factors of mid-late term revision. HR and 95% CI assessed association of sociodemographic factors, comorbidities, medication, surgical variables and PROMs with mid-late term revision.ResultsNJR-HES-PROMs data were available from 2008 to 2011 on 142 275 THR; mean age 70.0 years and 61.9% female. CPRD GOLD-HES data covered 1995–2011 on 17 047 THR; mean age 68.4 years, 61.8% female. Patients had minimum 5 years postprimary surgery to end 2016. In NJR-HES-PROMS data, there were 3582 (2.5%) revisions, median time-to-revision after primary surgery 1.9 years (range 0.01–8.7), with 598 (0.4%) mid-late term revisions; in CPRD GOLD, 982 (5.8%) revisions, median time-to-revision 5.3 years (range 0–20), with 520 (3.1%) mid-late term revisions.Reduced risk of mid-late term revision was associated with older age at primary surgery (HR: 0.96; 95% CI: 0.95 to 0.96); better 6-month postoperative pain/function scores (HR: 0.35; 95% CI: 0.27 to 0.46); use of ceramic-on-ceramic (HR: 0.73; 95% CI: 0.56 to 0.95) or ceramic-on-polyethylene (HR: 0.76; 95% CI: 0.58 to 1.00) bearing surfaces.Increased risk of mid-late term revision was associated with the use of antidepressants (HR: 1.32; 95% CI: 1.09 to 1.59), glucocorticoid injections (HR: 1.33; 95% CI: 1.06 to 1.67) and femoral head size≥44 mm (HR: 2.56; 95% CI: 1.09 to 6.02)No association of gender, obesity or Index of Multiple Deprivation was observed.ConclusionThe risk of mid-late term THR is associated with age at primary surgery, 6-month postoperative pain and function and implant factors. Further work is needed to explore the associations with prescription medications observed in our data.

Little is known about variation in outcomes of surgery or about the factors associated with such variation. To evaluate variation in patient outcomes and costs for primary hip and knee replacement across health areas in England and to identify whether patient, surgical, or hospital factors are associated with such variation. This cohort study used data from the National Joint Registry, linked to English Hospital Episode Statistics and Patient Reported Outcome Measures data sets, for 383 382 adult patients who underwent primary total hip replacement (THR) or primary total and unicompartmental knee replacement (TKR) surgical procedures from January 2014 to December 2016. Geographical Information Systems were used to display maps describing adjusted estimates of variation in outcomes across health areas. Data analysis took place from January 2018 to August 2019. Patient characteristics (eg, age, sex, body mass index [BMI], and socioeconomic deprivation), surgical factors (eg, surgeon volume and grade), and hospital organizational factors (eg, number of operating theaters, number of specialist consultants, and hospital volume). Length of stay (LOS), bed-day costs, change in Oxford hip or knee scores 6 months after surgery, and complications 6 months after surgery. A total of 173 107 patients (mean [SD] age, 69.3 [10.7] years; mean [SD] BMI, 28.9 [5.2]) underwent primary THR and 210 275 patients (mean [SD] age 69.7 [9.4] years; mean [SD] BMI, 31.1 [5.5]) underwent primary TKR, nested in 207 health areas. A number of factors were associated with longer LOS, higher bed-day costs, smaller changes in Oxford hip or knee scores, and a higher percentage of complications, including a workforce with a higher number of less experienced physicians (eg, LOS for less experienced surgeons, THR: regression coefficient, 0.02; 95% CI, 0.01 to 0.03; P < .001; TKR: regression coefficient, 0.01; 95% CI, 0.01 to 0.02; P < .001), public hospitals (eg, bed-day costs for private hospitals, THR: regression coefficient, -0.15; 95% CI, -0.15 to -0.14; P < .001; TKR: regression coefficient, -0.19; 95% CI, -0.19 to -0.19; P < .001), low volume of surgical procedures per surgeon (eg, change in Oxford hip or knee scores for lead surgeon with ≤10 vs >150 surgical procedures per year, THR: regression coefficient, -1.03; 95% CI, -1.47 to -0.58; P < .001; TKR: regression coefficient, -0.54; 95% CI, -1.01 to -0.06), and low volume of surgical procedures per hospital (eg, percentage of complications for hospitals with ≤200 vs ≥500 surgical procedures per year, THR: regression coefficient, 0.12; 95% CI, 0.04 to 0.21; P < .001; TKR: regression coefficient, 0.09; 95% CI, 0.01 to 0.18; P = .03). Although these factors did not attenuate the magnitude of variation across health areas, they had ecological correlations with the observed geographical variations in outcomes of surgery by health area. For example, the percentage of public and private hospitals was ecologically correlated at the health area level with longer and shorter stays, respectively (public hospital, THR: ρ, 0.41; public hospital, TKR: ρ, 0.44; private hospital, THR: ρ, -0.37; private hospital, THR: ρ, -0.38). Across health areas, estimated mean length of stay ranged from 3 to 7 days, and associated bed-day costs ranged from £4727 ($5827) to £8800 ($10 848) for both total hip and knee replacement. The absolute estimated mean change in Oxford hip score varied from 18.7 to 24.6 points and, for Oxford knee score, from 13.1 to 18.8. Estimated 6-month complications ranged from 2.9% to 5.8% for both THR and TKR. In this study, models indicated that higher surgical volume by surgeon and by hospital as well as private hospitals were associated with better patient outcomes, which could be explained by the changing case mix of public hospitals treating an increasing number of more complex patients. A higher proportion of less experienced physicians was associated with poorer outcomes. This variation was observed geographically.

ObjectivesEffects of the UK Department of Health’s national Enhanced Recovery After Surgery (ERAS) Programme on outcomes after primary hip replacement.DesignNatural experimental study using interrupted time series to assess the changes in trends before, during and after ERAS implementation (April 2009 to March 2011).SettingSurgeries in the UK National Joint Registry were linked with Hospital Episode Statistics containing inpatient episodes from National Health Service trusts in England and patient reported outcome measures.ParticipantsPatients aged ≥18 years from 2008 to 2016.Main outcome measuresRegression coefficients of monthly means of length of hospital stay, bed day cost, change in Oxford Hip Scores (OHS) 6 months post-surgery, complications 6 months post-surgery and revision rates 5 years post-surgery.Results438 921 primary hip replacements were identified. Hospital stays shortened from 5.6 days in April 2008 to 3.6 in December 2016. There were also improvements in bed day costs (£7573 in April 2008 to £5239 in December 2016), positive change in self-reported OHS from baseline to 6 months post-surgery (17.7 points in April 2008 to 22.9 points in December 2016), complication rates (4.1% in April 2008 to 1.7% March 2016) and 5 year revision rates (5.9 per 1000 implant-years (95% CI 4.8 to 7.2) in April 2008 to 2.9 (95% CI 2.2 to 3.9) in December 2011). The positive trends in all outcomes started before ERAS was implemented and continued during and after the programme.ConclusionsPatient outcomes after hip replacement have improved over the last decade. A national ERAS programme maintained this improvement but did not alter the existing rate of change.

Antidepressants' effects are established in randomised controlled trials (RCTs), but not in the real world. To investigate real-world comparative effects of antidepressants for depression and compare them with RCTs. We performed a cohort study based on the QResearch database. We included people with a newly recorded diagnosis of depression, exposed to licensed antidepressants in the UK. We assessed all-cause dropouts (acceptability), dropouts for adverse events (tolerability), occurrence of at least one adverse event (safety), and response and remission on the Patient Health Questionnaire (PHQ)-9 (effectiveness) at 2 and 12 months. Logistic regressions were used to compute adjusted-odds ratio (aOR) with 99% CIs, assessing the associations between exposure to each antidepressant against fluoxetine (comparator) and outcomes of interest. We compared estimates from the real world with RCTs using ratio-of-odds ratio (ROR) with 95% CI. A total of 673 177 depressed people were studied: females 57.1%, mean age 42.8 (s.d. 17.7) years, mean baseline PHQ-9 17.1 (s.d. 5.0) (moderately severe depression). At 2 months, antidepressant acceptability was 61.4%, tolerability 94.4%, safety 54.5%, PHQ-9 decreased to 12.3 (s.d. 6.5). At 12 months, acceptability was 12.3%, tolerability 87.5%, safety 28.8%, PHQ-9 12.9 (s.d. 6.8). In the short and long term, tricyclics, mirtazapine and trazodone were worse than fluoxetine for most outcomes; citalopram had better acceptability than fluoxetine (aOR 0.95; 99% CI 0.92, 0.97), sertraline had lower tolerability (aOR 1.12; 99% CI 1.06, 1.18), and both citalopram and sertraline had lower safety (aOR 1.17 and 1.25, respectively). In the long term, citalopram had better acceptability (aOR 0.78; 99% CI 0.76, 0.81) and effectiveness (aOR 1.12 for both response and remission), but worse tolerability (aOR 1.09; 99% CI 1.06, 1.13) and safety (aOR 1.12; 99% CI 1.08, 1.16). Observational and randomised data were similar for citalopram and sertraline, while there was some difference for drugs less prescribed in the real world. Antidepressants showed low acceptability, moderate-to-high tolerability and safety, and small-to-moderate effectiveness in the real world. Real-world and RCT estimates showed similar findings only when the analyses were carried out using large datasets; otherwise, the results diverged.

ObjectivePrior studies identified clinical factors associated with increased risk of pancreatic ductal adenocarcinoma (PDAC). However, little is known regarding their time-varying nature, which could inform earlier diagnosis. This study assessed temporality of body mass index (BMI), blood-based markers, comorbidities and medication use with PDAC risk .DesignWe performed a population-based nested case–control study of 28 137 PDAC cases and 261 219 matched-controls in England. We described the associations of biomarkers with risk of PDAC using fractional polynomials and 5-year time trends using joinpoint regression. Associations with comorbidities and medication use were evaluated using conditional logistic regression.ResultsRisk of PDAC increased with raised HbA1c, liver markers, white blood cell and platelets, while following a U-shaped relationship for BMI and haemoglobin. Five-year trends showed biphasic BMI decrease and HbA1c increase prior to PDAC; early-gradual changes 2–3 years prior, followed by late-rapid changes 1–2 years prior. Liver markers and blood counts (white blood cell, platelets) showed monophasic rapid-increase approximately 1 year prior. Recent diagnosis of pancreatic cyst, pancreatitis, type 2 diabetes and initiation of certain glucose-lowering and acid-regulating therapies were associated with highest risk of PDAC.ConclusionRisk of PDAC increased with raised HbA1c, liver markers, white blood cell and platelets, while followed a U-shaped relationship for BMI and haemoglobin. BMI and HbA1c derange biphasically approximately 3 years prior while liver markers and blood counts (white blood cell, platelets) derange monophasically approximately 1 year prior to PDAC. Profiling these in combination with their temporality could inform earlier PDAC diagnosis.

Antiretroviral therapy has led to a decrease in HIV-related mortality and to the emergence of non-AIDS defining diseases as competing causes of death. This study estimates the HIV mortality rate and their risk factors with regard to different causes in a large city from January 2001 to June 2013. We followed-up 3137 newly diagnosed HIV non-AIDS cases. Causes of death were classified as HIV-related, non-HIV-related and external. We examined the effect of risk factors on survival using mortality rates, Kaplan-Meier plots and Cox models. Finally, we estimated survival for each main cause of death groups through Fine and Gray models. 182 deaths were found [14.0/1000 person-years of follow-up (py); 95% confidence interval (CI):12.0-16.1/1000 py], 81.3% of them had a known cause of death. Mortality rate by HIV-related causes and non-HIV-related causes was the same (4.9/1000 py; CI:3.7-6.1/1000 py), external was lower [1.7/1000 py; (1.0-2.4/1000 py)]. Kaplan-Meier estimate showed worse survival in intravenous drug user (IDU) and heterosexuals than in men having sex with men (MSM). Factors associated with HIV-related causes of death include: IDU male (subHazard Ratio (sHR):3.2; CI:1.5-7.0) and <200 CD4 at diagnosis (sHR:2.7; CI:1.3-5.7) versus ≥500 CD4. Factors associated with non-HIV-related causes of death include: ageing (sHR:1.5; CI:1.4-1.7) and heterosexual female (sHR:2.8; CI:1.1-7.3) versus MSM. Factors associated with external causes of death were IDU male (sHR:28.7; CI:6.7-123.2) and heterosexual male (sHR:11.8; CI:2.5-56.4) versus MSM. There are important differences in survival among transmission groups. Improved treatment is especially necessary in IDUs and heterosexual males.