Temporality of body mass index, blood tests, comorbidities and medication use as early markers for pancreatic ductal adenocarcinoma (PDAC): a nested case-control study.

OBJECTIVE: Prior 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 . DESIGN: We 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. RESULTS: Risk 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. CONCLUSION: Risk 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.

UK poSt Arthroplasty Follow-up rEcommendations (UK SAFE): what does analysis of linked, routinely collected national datasets tell us about mid-late term revision risk after knee replacement?

OBJECTIVE: To identify patients at risk of mid-late term revision of knee replacement (KR) to inform targeted follow-up. DESIGN: Analysis 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)). PARTICIPANTS: Primary elective KRs aged ≥18 years. EVENT OF INTEREST: Revision surgery ≥5 years (mid-late term) postprimary KR. STATISTICAL METHODS: Cox 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. RESULTS: NJR-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. CONCLUSION: The 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.

UK poSt Arthroplasty Follow-up rEcommendations (UK SAFE): what does analysis of linked, routinely collected national data sets tell us about mid-late term revision risk after hip replacement? Retrospective cohort study.

OBJECTIVE: To identify patients at risk of mid-late term revision of hip replacement to inform targeted follow-up. DESIGN: Analysis 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)). PARTICIPANTS: Primary elective total hip replacement (THR) aged≥18. EVENT OF INTEREST: Revision surgery≥5 years (mid-late term) after primary THR. STATISTICAL METHODS: Cox 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. RESULTS: NJR-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. CONCLUSION: The 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.

Costs of Joint Replacement in Osteoarthritis: A Study Using the National Joint Registry and Clinical Practice Research Datalink Data Sets.

OBJECTIVE: To estimate the costs of primary hip and knee replacement in individuals with osteoarthritis up to 2 years postsurgery, compare costs before and after the surgery, and identify predictors of hospital costs. METHODS: Patients age ≥18 years with primary planned hip or knee replacements and osteoarthritis in England between 2008 and 2016 were identified from the National Joint Registry and linked with Hospital Episode Statistics data containing inpatient episodes. Primary care data linked with hospital outpatient records were also used to identify patients age ≥18 years with primary hip or knee replacements between 2008 and 2016. All health care resource use was valued using 2016/2017 costs, and nonparametric censoring methods were used to estimate total 1-year and 2-year costs. RESULTS: We identified 854,866 individuals undergoing hip or knee replacement. The mean censor-adjusted 1-year hospitalization costs for hip and knee replacement were £7,827 (95% confidence interval [95% CI] 7,813, 7,842) and £7,805 (95% CI 7,790, 7,818), respectively. Complications and revisions were associated with up to a 3-fold increase in 1-year hospitalization costs. The censor-adjusted 2-year costs were £9,258 (95% CI 9,233, 9,280) and £9,452 (95% CI 9,430, 9,475) for hip and knee replacement, respectively. Adding primary and outpatient care, the mean total hip and knee replacement 2-year costs were £11,987 and £12,578, respectively. CONCLUSION: There are significant costs following joint replacement. Revisions and complications accounted for considerable costs and there is a significant incentive to identify best approaches to reduce these.

Risk factors associated with poor pain outcomes following primary knee replacement surgery: Analysis of data from the clinical practice research datalink, hospital episode statistics and patient reported outcomes as part of the STAR research programme.

OBJECTIVE: Identify risk factors for poor pain outcomes six months after primary knee replacement surgery. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.

Post-operative determinants of chronic pain after primary knee replacement surgery: Analysis of data on 258,386 patients from the National Joint Registry for England, Wales, Northern Ireland and the Isle of Man (NJR).

Objective: To identify post-operative risk factors for the development of chronic pain after knee replacement. Design: Primary knee replacements in persons aged ≥18 years between April 2008 and December 2016 from the National Joint Registry, linked with English Hospital Episode Statistics data, and Patient Reported Outcome Measures. The outcome was chronic pain 6-months after surgery (Oxford Knee pain score). Logistic regression modelling identified risk factors for chronic pain outcome. Results: 258,386 patients; 56.7% women; average age 70.1 years (SD â€‹± â€‹8.8 years). 43,702 (16.9%) were identified as having chronic pain 6-months post-surgery. Within 3 months of surgery complications were uncommon: intra-operative complications 1224 (0.5%); ≥1 medical complication 6073 (2.4%)); 32,930 (12.7%) hospital readmissions; 3848 (1.5%) re-operation; 835 (0.3%) revision. Post-surgical risk factors of chronic pain were: mechanical complication of prosthesis odds ratio (OR) 1.56 (95% Confidence Interval 1.35, 1.80); surgical site infection OR 1.13 (0.99, 1.29); readmission OR 1.47 (1.42, 1.52); re-operation OR 1.39 (1.27, 1.51); revision OR 1.92 (1.64, 2.25); length of stay e.g. 6+ vs. <2 days OR 1.48 (1.35, 1.63), blood transfusion OR 0.47 (0.26, 0.86) and myocardial infarction OR 0.69 (0.49, 0.97). Discriminatory ability of the model was only fair (c-statistic 0.71) indicating that post-surgical predictors explain a limited amount of variability in chronic pain. Conclusions: We identified a number of post-operative factors relating to the operation and early recovery that are associated with chronic pain following primary knee replacement. The model had weak discriminatory ability indicating that there remains considerable unexplained variability in chronic pain outcome.

Occupation and risk of knee osteoarthritis and knee replacement: A longitudinal, multiple-cohort study.

OBJECTIVES: To examine the effect of occupation on knee osteoarthritis (OA) and total knee replacement (TKR) in working-aged adults. METHODS: We used longitudinal data from the Chingford, Osteoarthritis Initiative (OAI) and Multicentre Osteoarthritis (MOST) studies. Participants with musculoskeletal disorders and/or a history of knee-related surgery were excluded. Participants were followed for up to 19-years (Chingford), 96-months (OAI) and 60-months (MOST) for incident outcomes including radiographic knee OA (RKOA), symptomatic RKOA and TKR. In those with baseline RKOA, progression was defined as the time from RKOA incidence to primary TKR. Occupational job categories and work-place physical activities were assigned to levels of workload. Logistic regression was used to examine the relationship between workload and incident outcomes with survival analyses used to assess progression (reference group: sedentary occupations). RESULTS: Heavy manual occupations were associated with a 2-fold increased risk (OR: 2.07, 95% CI 1.03 to 4.15) of incident RKOA in the OAI only. Men working in heavy manual occupations in MOST (2.7, 95% CI 1.17 to 6.26) and light manual occupations in OAI (2.00, 95% CI 1.09 to 3.68) had a 2-fold increased risk of incident RKOA. No association was observed among women. Increasing workload was associated with an increased risk of symptomatic RKOA in the OAI and MOST. Light work may be associated with a decreased risk of incident TKR and disease progression. CONCLUSION: Heavy manual work carries an increased risk of incident knee OA; particularly among men. Workload may influence the occurrence of TKR and disease progression.

Is Aspirin as Effective as the Newer Direct Oral Anticoagulants for Venous Thromboembolism Prophylaxis After Total Hip and Knee Arthroplasty? An Analysis From the National Joint Registry for England, Wales, Northern Ireland, and the Isle of Man.

BACKGROUND: Few studies have compared aspirin with direct oral anticoagulants (DOACs) (DOACs = direct thrombin inhibitors and factor Xa inhibitors) for venous thromboembolism (VTE) prophylaxis after total hip arthroplasty (THA) and total knee arthroplasty (TKA). We assessed the efficacy and safety of aspirin compared with DOACs for VTE prophylaxis after THA and TKA using the world's largest joint arthroplasty registry. METHODS: We studied the National Joint Registry linked to English hospital inpatient episodes for 218,650 THA and TKA patients. Patients receiving aspirin were matched separately to patients receiving direct thrombin inhibitors and factor Xa inhibitors using propensity scores. Outcomes assessed at 90 days included VTE, length of stay, and adverse events. RESULTS: After THA, there was a significantly lower risk of VTE associated with the use of direct thrombin inhibitors (0.44%; odds ratio [OR], 0.69; 95% confidence interval [95% CI], 0.55-0.87; P = .002) and factor Xa inhibitors (0.37%; OR, 0.63; 95% CI, 0.47-0.85; P = .003) compared with aspirin (0.63%). After THA, direct thrombin inhibitors (coefficient, -0.37 days; 95% CI, -0.43 to -0.31; P < .001) and factor Xa inhibitors (coefficient, -0.80 days; 95% CI, -0.87 to -0.74; P < .001) were associated with a reduced length of stay compared with aspirin. Similar findings for both outcomes were observed after TKA. Compared with aspirin, DOACs were not associated with an increase in the risk of short-term revision surgery, reoperation, major hemorrhage, wound disruption, surgical site infection, and mortality. CONCLUSION: After THA and TKA, DOACs were associated with a reduced risk of VTE compared with aspirin. DOACs were associated with a reduced length of stay, and DOACs were not associated with an increase in the risk of further surgery, wound problems, bleeding complications, or mortality compared with aspirin.

Does Regional Anesthesia Reduce Complications Following Total Hip and Knee Replacement Compared With General Anesthesia? An Analysis From the National Joint Registry for England, Wales, Northern Ireland and the Isle of Man.

BACKGROUND: Regional anesthesia is increasingly used in enhanced recovery programs following total hip replacement (THR) and total knee replacement (TKR). However, debate remains about its potential benefit over general anesthesia given that complications following surgery are rare. We assessed the risk of complications in THR and TKR patients receiving regional anesthesia compared with general anesthesia using the world's largest joint replacement registry. METHODS: We studied the National Joint Registry for England, Wales, Northern Ireland and the Isle of Man linked to English hospital inpatient episodes for 779,491 patients undergoing THR and TKR. Patients received either regional anesthesia (n = 544,620, 70%) or general anesthesia (n = 234,871, 30%). Outcomes assessed at 90 days included length of stay, readmissions, and complications. Regression models were adjusted for patient and surgical factors to determine the effect of anesthesia on outcomes. RESULTS: Length of stay was reduced with regional anesthesia compared with general anesthesia (THR = -0.49 days, 95% confidence interval [CI] = -0.51 to -0.47 days, P < .001; TKR = -0.47 days, CI = -0.49 to -0.45 days, P < .001). Regional anesthesia also had a reduced risk of readmission (THR odds ratio [OR] = 0.93, CI = 0.90-0.96; TKA OR = 0.91, CI = 0.89-0.93), any complication (THR OR = 0.88, CI = 0.85-0.91; TKA OR = 0.90, CI = 0.87-0.93), urinary tract infection (THR OR = 0.85, CI = 0.77-0.94; TKR OR = 0.87, CI = 0.79-0.96), and surgical site infection (THR OR = 0.87, CI = 0.80-0.95; TKR OR = 0.84, CI = 0.78-0.89). Anesthesia type did not affect the risk of revision surgery or mortality. CONCLUSION: Regional anesthesia was associated with reduced length of stay, readmissions, and complications following THR and TKR when compared with general anesthesia. We recommend regional anesthesia should be considered the reference standard for patients undergoing THR and TKR.

Assessment on patient outcomes of primary hip replacement: an interrupted time series analysis from 'The National Joint Registry of England and Wales'.

OBJECTIVES: Effects of the UK Department of Health's national Enhanced Recovery After Surgery (ERAS) Programme on outcomes after primary hip replacement. DESIGN: Natural experimental study using interrupted time series to assess the changes in trends before, during and after ERAS implementation (April 2009 to March 2011). SETTING: Surgeries 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. PARTICIPANTS: Patients aged ≥18 years from 2008 to 2016. MAIN OUTCOME MEASURES: Regression 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. RESULTS: 438 921 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. CONCLUSIONS: Patient 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.

Geographical Variation in Outcomes of Primary Hip and Knee Replacement.

Importance: Little is known about variation in outcomes of surgery or about the factors associated with such variation. Objectives: 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. Design, Setting, and Participants: 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. Exposures: 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). Main Outcomes and Measures: Length of stay (LOS), bed-day costs, change in Oxford hip or knee scores 6 months after surgery, and complications 6 months after surgery. Results: 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. Conclusions and Relevance: 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.

Development of a model predicting non-satisfaction 1 year after primary total knee replacement in the UK and transportation to Switzerland.

We aimed to develop a predictive model for non-satisfaction following primary total knee replacement (TKR) and to assess its transportability to another health care system. Data for model development were obtained from two UK tertiary hospitals. Model transportation data were collected from Geneva University Hospitals in Switzerland. Participants were individuals undergoing primary TKR with non-satisfaction with surgery after one year the outcome of interest. Multiple imputation and logistic regression modelling with bootstrap backward selection were used to identify predictors of outcome. Model performance was assessed by discrimination and calibration. 64 (14.2%) patients in the UK and 157 (19.9%) in Geneva were non-satisfied with their TKR. Predictors in the UK cohort were worse pre-operative pain and function, current smoking, treatment for anxiety and not having been treated with injected corticosteroids (corrected AUC = 0.65). Transportation to the Geneva cohort showed an AUC of 0.55. Importantly, two UK predictors (treated for anxiety, injected corticosteroids) were not predictive in Geneva. A better model fit was obtained when coefficients were re-estimated in the Geneva sample (AUC = 0.64). The model did not perform well when transported to a different country, but improved when it was re-estimated. This emphasises the need to re-validate the model for each setting/country.