Risk of emergency hospital admission related to adverse events after antibiotic treatment in adults with a common infection: impact of COVID-19 and derivation and validation of risk prediction models.

BACKGROUND: With the global challenge of antimicrobial resistance intensified during the COVID-19 pandemic, evaluating adverse events (AEs) post-antibiotic treatment for common infections is crucial. This study aims to examines the changes in incidence rates of AEs during the COVID-19 pandemic and predict AE risk following antibiotic prescriptions for common infections, considering their previous antibiotic exposure and other long-term clinical conditions. METHODS: With the approval of NHS England, we used OpenSAFELY platform and analysed electronic health records from patients aged 18-110, prescribed antibiotics for urinary tract infection (UTI), lower respiratory tract infections (LRTI), upper respiratory tract infections (URTI), sinusitis, otitis externa, and otitis media between January 2019 and June 2023. We evaluated the temporal trends in the incidence rate of AEs for each infection, analysing monthly changes over time. The survival probability of emergency AE hospitalisation was estimated in each COVID-19 period (period 1: 1 January 2019 to 25 March 2020, period 2: 26 March 2020 to 8 March 2021, period 3: 9 March 2021 to 30 June 2023) using the Kaplan-Meier approach. Prognostic models, using Cox proportional hazards regression, were developed and validated to predict AE risk within 30 days post-prescription using the records in Period 1. RESULTS: Out of 9.4 million patients who received antibiotics, 0.6% of UTI, 0.3% of URTI, and 0.5% of LRTI patients experienced AEs. UTI and LRTI patients demonstrated a higher risk of AEs, with a noted increase in AE incidence during the COVID-19 pandemic. Higher comorbidity and recent antibiotic use emerged as significant AE predictors. The developed models exhibited good calibration and discrimination, especially for UTIs and LRTIs, with a C-statistic above 0.70. CONCLUSIONS: The study reveals a variable incidence of AEs post-antibiotic treatment for common infections, with UTI and LRTI patients facing higher risks. AE risks varied between infections and COVID-19 periods. These findings underscore the necessity for cautious antibiotic prescribing and call for further exploration into the intricate dynamics between antibiotic use, AEs, and the pandemic.

Sepsis and case fatality rates and associations with deprivation, ethnicity, and clinical characteristics: population-based case-control study with linked primary care and hospital data in England.

PURPOSE: Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection. The purpose of the study was to measure the associations of specific exposures (deprivation, ethnicity, and clinical characteristics) with incident sepsis and case fatality. METHODS: Two research databases in England were used including anonymized patient-level records from primary care linked to hospital admission, death certificate, and small-area deprivation. Sepsis cases aged 65-100 years were matched to up to six controls. Predictors for sepsis (including 60 clinical conditions) were evaluated using logistic and random forest models; case fatality rates were analyzed using logistic models. RESULTS: 108,317 community-acquired sepsis cases were analyzed. Severe frailty was strongly associated with the risk of developing sepsis (crude odds ratio [OR] 14.93; 95% confidence interval [CI] 14.37-15.52). The quintile with most deprived patients showed an increased sepsis risk (crude OR 1.48; 95% CI 1.45-1.51) compared to least deprived quintile. Strong predictors for sepsis included antibiotic exposure in prior 2 months, being house bound, having cancer, learning disability, and diabetes mellitus. Severely frail patients had a case fatality rate of 42.0% compared to 24.0% in non-frail patients (adjusted OR 1.53; 95% CI 1.41-1.65). Sepsis cases with recent prior antibiotic exposure died less frequently compared to non-users (adjusted OR 0.7; 95% CI 0.72-0.76). Case fatality strongly decreased over calendar time. CONCLUSION: Given the variety of predictors and their level of associations for developing sepsis, there is a need for prediction models for risk of developing sepsis that can help to target preventative antibiotic therapy.

Adverse drug reactions and hospital admissions: Large case-control study of patients aged 65-100 years using linked English primary care and hospital data.

BACKGROUND: Adverse drug reactions (ADRs) are common and a leading cause of injury. However, information on ADR risks of individual medicines is often limited. The aim of this hypothesis-generating study was to assess the relative importance of ADR-related and emergency hospital admission for large group of medication classes. METHODS: This study was a propensity-matched case-control study in English primary care. Data sources were Clinical Practice Research Databank and Aurum with longitudinal, anonymized, patient level electronic health records (EHRs) from English general practices linked to hospital records. Cases aged 65-100 with ADR-related or emergency hospital admission were matched to up to six controls by age, sex, morbidity and propensity scores for hospital admission risk. Medication groups with systemic administration as listed in the British National Formulary (used by prescribers for medication advice). Prescribing in the 84 days before the index date was assessed. Only medication groups with 50+ cases exposed were analysed. The outcomes of interest were ADR-related and emergency hospital admissions. Conditional logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CI). RESULTS: The overall population included 121 546 cases with an ADR-related and 849 769 cases with emergency hospital admission. The percentage of hospitalizations with an ADR-related code for admission diagnosis was 1.83% and 6.58% with an ADR-related code at any time during hospitalization. A total of 137 medication groups was included in the main ADR analyses. Of these, 13 (9.5%) had statistically non-significant adjusted ORs, 58 (42.3%) statistically significant ORs between 1.0 and 1.5, 37 (27.0%) between 1.5-2.0, 18 (13.1%) between 2.0-3.0 and 11 (8.0%) 3.0 or higher. Several classes of antibiotics (including penicillins) were among medicines with largest ORs. Evaluating the 14 medications most often associated with ADRs, a strong association was found between the number of these medicines and the risk of ADR-related hospital admission (adjusted OR of 7.53 (95% CI 7.15-7.93) for those exposed to 6+ of these medicines). CONCLUSIONS AND RELEVANCE: There is a need for a regular systematic assessment of the harm-benefit ratio of medicines, harvesting the information in large healthcare databases and combining it with causality assessment of individual case histories.

Shorter and Longer Courses of Antibiotics for Common Infections and the Association With Reductions of Infection-Related Complications Including Hospital Admissions.

BACKGROUND: Antimicrobial resistance is a serious global health concern that emphasizes completing treatment course. Recently, the effectiveness of short versus longer antibiotic courses has been questioned. This study investigated the duration of prescribed antibiotics, their effectiveness, and associated risk of infection-related complications. METHODS: Clinical Practice Research Datalink identified 4 million acute infection episodes prescribed an antibiotic in primary care between January 2014-June 2014, England. Prescriptions were categorized by duration. Risk of infection-related hospitalizations within 30 days was modelled overall and by infection type. Risk was assessed immediately after or within 30 days follow-up to measure confounders given similar and varying exposure, respectively. An interaction term with follow-up time assessed whether hazard ratios (HRs) remained parallel with different antibiotic durations. RESULTS: The duration of antibiotic courses increased over the study period (5.2-19.1%); 6-7 days were most common (66.9%). Most infection-related hospitalizations occurred with prescriptions of 8-15 days (0.21%), accompanied by greater risk of infection-related complications compared to patients who received a short prescription (HR: 1.75 [95% CI: 1.54-2.00]). Comparing HRs in the first 5 days versus remaining follow-up showed longer antibiotic courses were no more effective than shorter courses (1.02 [95% CI: 0.90-1.16] and 0.92 [95% CI: 0.75-1.12]). No variation by infection-type was observed. CONCLUSIONS: Equal effectiveness was found between shorter and longer antibiotic courses and the reduction of infection-related hospitalizations. Stewardship programs should recommend shorter courses of antibiotics for acute infections. Further research is required for treating patients with a complex medical history.SummaryPrescribing of longer courses increased over the study period. The majority of hospitalizations occurred for patients receiving longer courses. Risk of developing a complication (immediate vs remaining follow-up) found longer courses were no more effective than shorter courses.

The Safety of Delayed Versus Immediate Antibiotic Prescribing for Upper Respiratory Tract Infections.

BACKGROUND: This study aimed to evaluate the clinical safety of delayed antibiotic prescribing for upper respiratory tract infections (URTIs), which is recommended in treatment guidelines for less severe cases. METHODS: Two population-based cohort studies used the English Clinical Practice Research Databank and Welsh Secure Anonymized Information Linkage, containing electronic health records from primary care linked to hospital admission records. Patients with URTI and prescriptions of amoxicillin, clarithromycin, doxycycline, erythromycin, or phenoxymethylpenicillin were identified. Patients were stratified according to delayed and immediate prescribing relative to URTI diagnosis. Outcome of interest was infection-related hospital admission after 30 days. RESULTS: The population included 1.82 million patients with an URTI and antibiotic prescription; 91.7% had an antibiotic at URTI diagnosis date (immediate) and 8.3% had URTI diagnosis in 1-30 days before (delayed). Delayed antibiotic prescribing was associated with a 52% increased risk of infection-related hospital admissions (adjusted hazard ratio, 1.52; 95% confidence interval, 1.43-1.62). The probability of delayed antibiotic prescribing was unrelated to predicted risks of hospital admission. Analyses of the number needed to harm showed considerable variability across different patient groups (median with delayed antibiotic prescribing, 1357; 2.5% percentile, 295; 97.5% percentile, 3366). CONCLUSIONS: This is the first large population-based study examining the safety of delayed antibiotic prescribing. Waiting to treat URTI was associated with increased risk of hospital admission, although delayed antibiotic prescribing was used similarly between high- and low-risk patients. There is a need to better target delayed antibiotic prescribing to URTI patients with lower risks of complications.

The effectiveness of frequent antibiotic use in reducing the risk of infection-related hospital admissions: results from two large population-based cohorts.

BACKGROUND: Previous research reported that individuals prescribed antibiotics frequently develop antimicrobial resistance. The objective of this study was to evaluate whether frequent antibiotic use is associated with reduced hospital admissions for infection-related complications. METHODS: Population-based cohort study analysing electronic health records from primary care linked to hospital admission records. The study population included patients prescribed a systemic antibiotic, recent record of selected infections and no history of chronic obstructive pulmonary disease. Propensity-matched cohorts were identified based on quintiles of prior antibiotic use in 3 years before. RESULTS: A total of 1.8 million patients were included. Repeated antibiotic use was frequent. The highest rates of hospital admissions for infection-related complications were observed shortly after antibiotic start in all prior exposure quintiles. For patients with limited prior antibiotic use, rates then dropped quickly and substantially. In contrast, reductions over time were substantially less in patients with frequent prior antibiotic use, with rates remaining elevated over the following 6 months. In patients without comorbidity comparing the highest to lowest prior exposure quintiles in the Clinical Practice Research Databank, the IRRs were 1.18 [95% CI 0.90-1.55] in the first 3 days after prescription, 1.44 [95% CI 1.14-1.81] in the days 4-30 after and 3.22 [95% CI 2.29-4.53] in the 3-6 months after. CONCLUSIONS: Repeated courses of antibiotics, although common practice, may have limited benefit and indicator of adverse outcomes. A potential mechanism is that antibiotics may cause dysbiosis (perturbations of intestinal microbiota), contributing to colonization with resistant bacteria. Antibiotics should be used judiciously and only periodically unless indicated. Antimicrobial stewardship should include activities focusing on the substantive number of patients who repeatedly but intermittently get antibiotics.

Correction to: The role of real-world data in the development of treatment guidelines: a case study on guideline developers' opinions about using observational data on antibiotic prescribing in primary care.

An amendment to this paper has been published and can be accessed via the original article.

The role of real-world data in the development of treatment guidelines: a case study on guideline developers' opinions about using observational data on antibiotic prescribing in primary care.

BACKGROUND: Antimicrobial resistance (AMR) is a prominent threat to public health. Although many guidelines have been developed over the years to tackle this issue, their impact on health care practice varies. Guidelines are often based on evidence from clinical trials, but these have limitations, particularly in the breadth and generalisability of the evidence and evaluation of the guidelines' uptake. The aim of this study was to investigate how national and local guidelines for managing common infections are developed and explore guideline committee members' opinions about using real-world observational evidence in the guideline development process. METHODS: Six semi-structured interviews were completed with participants who had contributed to the development or adjustment of national or local guidelines on antimicrobial prescribing over the past 5 years (from the English National Institute for Health and Care Excellence (NICE)). Interviews were audio recorded and transcribed verbatim. Data was analysed thematically. This also included review of policy documents including guidelines, reports and minutes of guideline development group meetings that were available to the public. RESULTS: Three key themes emerged through our analysis: perception versus actual guideline development process, using other types of evidence in the guideline development process, and guidelines are not enough to change antibiotic prescribing behaviour. In addition, our study was able to provide some insight between the documented and actual guideline development process within NICE, as well as how local guidelines are developed, including differences in types of evidence used. CONCLUSIONS: This case study indicates that there is the potential for a wider range of evidence to be included as part of the guideline development process at both the national and local levels. There was a general agreement that the inclusion of observational data would be appropriate in enhancing the guideline development process, as well providing a potential solution for monitoring guideline use in clinical practice, and improving the implementation of treatment guidelines in primary care.

Cohort Multiple Randomised Controlled Trials (cmRCT) design: efficient but biased? A simulation study to evaluate the feasibility of the Cluster cmRCT design.

BACKGROUND: The Cohort Multiple Randomised Controlled Trial (cmRCT) is a newly proposed pragmatic trial design; recently several cmRCT have been initiated. This study tests the unresolved question of whether differential refusal in the intervention arm leads to bias or loss of statistical power and how to deal with this. METHODS: We conduct simulations evaluating a hypothetical cluster cmRCT in patients at risk of cardiovascular disease (CVD). To deal with refusal, we compare the analysis methods intention to treat (ITT), per protocol (PP) and two instrumental variable (IV) methods: two stage predictor substitution (2SPS) and two stage residual inclusion (2SRI) with respect to their bias and power. We vary the correlation between treatment refusal probability and the probability of experiencing the outcome to create different scenarios. RESULTS: We found ITT to be biased in all scenarios, PP the most biased when correlation is strong and 2SRI the least biased on average. Trials suffer a drop in power unless the refusal rate is factored into the power calculation. CONCLUSIONS: The ITT effect in routine practice is likely to lie somewhere between the ITT and IV estimates from the trial which differ significantly depending on refusal rates. More research is needed on how refusal rates of experimental interventions correlate with refusal rates in routine practice to help answer the question of which analysis more relevant. We also recommend updating the required sample size during the trial as more information about the refusal rate is gained.

Safety and efficacy of new oral anticoagulants and low-molecular-weight heparins compared with aspirin in patients undergoing total knee and hip replacements.

BACKGROUND: There has been much debate recently on the best type of thromboprophylaxis following elective total joint replacement surgery. OBJECTIVE: This study aims to compare rates of venous thromboembolism (VTE), gastro-intestinal (GI) bleeding and mortality events, with use of new oral anticoagulants (NOAC) or low-molecular-weight heparins (LMWHs) compared with aspirin in patients undergoing total joint replacement. METHODS: A population-based retrospective cohort study was performed using the Clinical Practice Research Datalink. Patients ≥18 years of age who had undergone total knee (n = 3261) or hip replacement (THR (n = 4016)) between 2008 and 2012 were included. Within this population, three cohorts were selected, based on their first prescription within the 35-day period after surgery: use of NOACs only, LMWHs only and aspirin only. Incidence rates were calculated, and Cox proportional hazard models were fitted to estimate the risk of VTE, GI bleeding and all-cause mortality with the use of NOACs and LMWHs compared with aspirin use after total knee replacement and THR. We statistically adjusted our analyses for lifestyle factors, comorbidities and concomitant drug use. RESULTS: Total knee replacement and THR patients currently on LMWHs had higher risk of VTE (HR = 17.2 (6.9-43.0) and HR = 39.5 (18.0-87.0), respectively), GI bleeding (HR = 20.9 (1.9-232.3) and HR = 2.0 (0.2-17.2), respectively) and all-cause mortality (HR = 4.3 (1.7-12.4) and HR = 4.0 (2.4-6.7), respectively). NOAC use was associated with an increased risk of GI bleeding in patients undergoing THR surgery. CONCLUSIONS: In contrast to previous studies, we found an increased risk of VTE, GI bleeding and all-cause mortality with the use of LMWHs compared with aspirin. Risk of GI bleeding was increased with the use of NOACs compared with aspirin use after THR surgery. Copyright © 2016 John Wiley & Sons, Ltd.

Risk patterns in drug safety study using relative times by accelerated failure time models when proportional hazards assumption is questionable: an illustrative case study of cancer risk of patients on glucose-lowering therapies.

Observational drug safety studies may be susceptible to confounding or protopathic bias. This bias may cause a spurious relationship between drug exposure and adverse side effect when none exists and may lead to unwarranted safety alerts. The spurious relationship may manifest itself through substantially different risk levels between exposure groups at the start of follow-up when exposure is deemed too short to have any plausible biological effect of the drug. The restrictive proportional hazards assumption with its arbitrary choice of baseline hazard function renders the commonly used Cox proportional hazards model of limited use for revealing such potential bias. We demonstrate a fully parametric approach using accelerated failure time models with an illustrative safety study of glucose-lowering therapies and show that its results are comparable against other methods that allow time-varying exposure effects. Our approach includes a wide variety of models that are based on the flexible generalized gamma distribution and allows direct comparisons of estimated hazard functions following different exposure-specific distributions of survival times. This approach lends itself to two alternative metrics, namely relative times and difference in times to event, allowing physicians more ways to communicate patient's prognosis without invoking the concept of risks, which some may find hard to grasp. In our illustrative case study, substantial differences in cancer risks at drug initiation followed by a gradual reduction towards null were found. This evidence is compatible with the presence of protopathic bias, in which undiagnosed symptoms of cancer lead to switches in diabetes medication.

Variability of antibiotic prescribing in patients with chronic obstructive pulmonary disease exacerbations: a cohort study.

BACKGROUND: The role of antibiotics in treating mild or moderate exacerbations in patients with acute chronic obstructive pulmonary disease (COPD) is unclear. The aims were to: (i) describe patient characteristics associated with acute exacerbations amongst a representative COPD population, (ii) explore the relationship between COPD severity and outcomes amongst patients with exacerbations, and (iii) quantify variability by general practice in prescribing of antibiotics for COPD exacerbations. METHOD: A cohort of 62,747 patients with COPD was identified from primary care general practices (GP) in England, and linked to hospital admission and death certificate data. Exacerbation cases were matched to three controls and characteristics compared using conditional logistic regression. Outcomes were compared using incidence rates and Cox regression, stratified by disease severity. Variability of prescribing at the GP level was evaluated graphically and by using multilevel models. RESULTS: COPD severity was found to be associated with exacerbation and subsequent mortality (very severe vs. mild, odds ratio for exacerbation 2.12 [95%CI 19.5-2.32]), hazard ratio for mortality 2.14 [95%CI 1.59-2.88]). Whilst 61% of exacerbation cases were prescribed antibiotics, this proportion varied considerably between GP practices (interquartile range, 48-73%). This variation is greater than can be explained by patient characteristics alone. CONCLUSIONS: There is significant variability between GP practices in the prescribing of antibiotics to COPD patients experiencing exacerbations. Combined with a lack of evidence on the effects of treatment, this supports the need and opportunity for a large scale pragmatic randomised trial of the prescribing of antibiotics for COPD patients with exacerbations, in order to clarify their effectiveness and long term outcomes whilst ensuring the representativeness of subjects.

Clinical Relevance of Drug-Drug Interactions With Antibiotics as Listed in a National Medication Formulary: Results From Two Large Population-Based Case-Control Studies in Patients Aged 65-100 Years Using Linked English Primary Care and Hospital Data.

This study evaluated drug-drug interactions (DDIs) between antibiotic and nonantibiotic drugs listed with warnings of severe outcomes in the British National Formulary based on adverse drug reaction (ADR) detectable with routine International Classification of Diseases, Tenth Revision coding. Data sources were Clinical Practice Research Databank GOLD and Aurum anonymized electronic health records from English general practices linked to hospital admission records. In propensity-matched case-control study, outcomes were ADR or emergency admissions. Analyzed were 121,546 ADR-related admission cases matched to 638,238 controls. For most antibiotics, adjusted odds ratios (aORs) for ADR-related hospital admission were large (aOR for trimethoprim 4.13; 95% confidence interval (CI), 3.97-4.30). Of the 51 DDIs evaluated for ADR-related admissions, 38 DDIs (74.5%) had statistically increased aORs of concomitant exposure compared with nonexposure (mean aOR 3.96; range 1.59-11.42); for the 89 DDIs for emergency hospital admission, the results were 75 (84.3%) and mean aOR 2.40; range 1.43-4.17. Changing reference group to single antibiotic exposure reduced aORs for concomitant exposure by 76.5% and 83.0%, respectively. Medicines listed to cause nephrotoxicity substantially increased risks that were related to number of medicines (aOR was 2.55 (95% CI, 2.46-2.64) for current use of 1 and 10.44 (95% CI, 7.36-14.81) for 3 or more medicines). In conclusion, no evidence of substantial risk was found for multiple DDIs with antibiotics despite warnings of severe outcomes in a national formulary and flagging in electronic health record software. It is proposed that the evidence base for inclusion of DDIs in national formularies be strengthened and made publicly accessible and indiscriminate flagging, which compounds alert fatigue, be reduced.

Combinations of medicines in patients with polypharmacy aged 65-100 in primary care: Large variability in risks of adverse drug related and emergency hospital admissions.

BACKGROUND: Polypharmacy can be a consequence of overprescribing that is prevalent in older adults with multimorbidity. Polypharmacy can cause adverse reactions and result in hospital admission. This study predicted risks of adverse drug reaction (ADR)-related and emergency hospital admissions by medicine classes. METHODS: We used electronic health record data from general practices of Clinical Practice Research Datalink (CPRD GOLD) and Aurum. Older patients who received at least five medicines were included. Medicines were classified using the British National Formulary sections. Hospital admission cases were propensity-matched to controls by age, sex, and propensity for specific diseases. The matched data were used to develop and validate random forest (RF) models to predict the risk of ADR-related and emergency hospital admissions. Shapley Additive eXplanation (SHAP) values were calculated to explain the predictions. RESULTS: In total, 89,235 cases with polypharmacy and hospitalised with an ADR-related admission were matched to 443,497 controls. There were over 112,000 different combinations of the 50 medicine classes most implicated in ADR-related hospital admission in the RF models, with the most important medicine classes being loop diuretics, domperidone and/or metoclopramide, medicines for iron-deficiency anaemias and for hypoplastic/haemolytic/renal anaemias, and sulfonamides and/or trimethoprim. The RF models strongly predicted risks of ADR-related and emergency hospital admission. The observed Odds Ratio in the highest RF decile was 7.16 (95% CI 6.65-7.72) in the validation dataset. The C-statistics for ADR-related hospital admissions were 0.58 for age and sex and 0.66 for RF probabilities. CONCLUSIONS: Polypharmacy involves a very large number of different combinations of medicines, with substantial differences in risks of ADR-related and emergency hospital admissions. Although the medicines may not be causally related to increased risks, RF model predictions may be useful in prioritising medication reviews. Simple tools based on few medicine classes may not be effective in identifying high risk patients.

Clinical and health inequality risk factors for non-COVID-related sepsis during the global COVID-19 pandemic: a national case-control and cohort study.

Background: Sepsis, characterised by significant morbidity and mortality, is intricately linked to socioeconomic disparities and pre-admission clinical histories. This study aspires to elucidate the association between non-COVID-19 related sepsis and health inequality risk factors amidst the pandemic in England, with a secondary focus on their association with 30-day sepsis mortality. Methods: With the approval of NHS England, we harnessed the OpenSAFELY platform to execute a cohort study and a 1:6 matched case-control study. A sepsis diagnosis was identified from the incident hospital admissions record using ICD-10 codes. This encompassed 248,767 cases with non-COVID-19 sepsis from a cohort of 22.0 million individuals spanning January 1, 2019, to June 31, 2022. Socioeconomic deprivation was gauged using the Index of Multiple Deprivation score, reflecting indicators like income, employment, and education. Hospitalisation-related sepsis diagnoses were categorised as community-acquired or hospital-acquired. Cases were matched to controls who had no recorded diagnosis of sepsis, based on age (stepwise), sex, and calendar month. The eligibility criteria for controls were established primarily on the absence of a recorded sepsis diagnosis. Associations between potential predictors and odds of developing non-COVID-19 sepsis underwent assessment through conditional logistic regression models, with multivariable regression determining odds ratios (ORs) for 30-day mortality. Findings: The study included 224,361 (10.2%) cases with non-COVID-19 sepsis and 1,346,166 matched controls. The most socioeconomic deprived quintile was associated with higher odds of developing non-COVID-19 sepsis than the least deprived quintile (crude OR 1.80 [95% CI 1.77-1.83]). Other risk factors (after adjusting comorbidities) such as learning disability (adjusted OR 3.53 [3.35-3.73]), chronic liver disease (adjusted OR 3.08 [2.97-3.19]), chronic kidney disease (stage 4: adjusted OR 2.62 [2.55-2.70], stage 5: adjusted OR 6.23 [5.81-6.69]), cancer, neurological disease, immunosuppressive conditions were also associated with developing non-COVID-19 sepsis. The incidence rate of non-COVID-19 sepsis decreased during the COVID-19 pandemic and rebounded to pre-pandemic levels (April 2021) after national lockdowns had been lifted. The 30-day mortality risk in cases with non-COVID-19 sepsis was higher for the most deprived quintile across all periods. Interpretation: Socioeconomic deprivation, comorbidity and learning disabilities were associated with an increased odds of developing non-COVID-19 related sepsis and 30-day mortality in England. This study highlights the need to improve the prevention of sepsis, including more precise targeting of antimicrobials to higher-risk patients. Funding: The UK Health Security Agency, Health Data Research UK, and National Institute for Health Research.

Risk of fracture with thiazolidinediones: disease or drugs?

The use of thiazolidinediones (TZDs) has been associated with an increased fracture risk. In addition, type 2 diabetes mellitus (T2DM) has been linked with fracture. We evaluated to what extent the association between TZD use and fracture risk is related to the drug or to the underlying disease. We conducted a population-based cohort study using the Danish National Health Registers (1996-2007), which link pharmacy data to the national hospital registry. Oral antidiabetic users (n = 180,049) were matched 1:3 by year of birth and sex to nonusers. Cox proportional hazards models were used to estimate hazard ratios (HRs) of fracture. Time-dependent adjustments were made for age, comorbidity, and drug use. We created a proxy indicator for the severity of disease. The first stage was defined as current use of either a biguanide or a sulfonyluerum, the second stage as current use of a biguanide and a sulfonyluerum at the same time, the third stage as patients using TZDs, and the fourth stage as patients using insulin. The risk of osteoporotic fracture was increased 1.3-fold for stages 3 and 4 compared with controls. Risk with current TZD use (stage 3 HR = 1.27, 95 % CI 1.06-1.52) and risk with current use of insulin (stage 4 HR = 1.25, 95 % CI 1.20-1.31) were similar. In the first (HR = 1.15, 95 % CI 1.13-1.18) and second (HR = 1.00, 95 % CI 0.96-1.04) stages risks were lower. Risk of osteoporotic fracture was similar for TZD users and insulin users. When studying fracture risk with TZDs, the underlying T2DM should be taken into account.

Incidence of fractures in patients with multiple sclerosis: the Danish National Health Registers.

BACKGROUND: Patients with multiple sclerosis (MS) are potentially at high risk of fracture due to falls and osteoporosis. OBJECTIVE: To estimate incidence rates of fractures in MS patients, stratified by fracture type, sex and age, and to compare these rates with controls. METHODS: The case population consisted of all patients with an accepted diagnosis of MS in the Danish MS Registry (1949-2007). Data were linked to the National Hospital Discharge Register (1977-2007). Patients with MS (n = 11,157) were 1:6 matched by year of birth, gender, calendar time and region to persons without MS (controls). Incidence rates of fracture were estimated as the number of fractures per 1000 person-years. Incidence rate ratios (IRRs) were calculated by dividing fracture rates in MS patients by fracture rates in controls. RESULTS: Among patients with MS, the incidence rate of any fracture yielded 22.8 per 1000 person-years. The IRR of any fracture between MS patients and controls was 1.40 (95% CI 1.33-1.46). In particular, IRRs of tibia fracture (3.36 [2.75-4.11]), femur fracture (6.66 [5.06-8.76]) and hip fracture (3.20 [2.83-3.62]) were elevated in MS patients versus controls. CONCLUSION: Fractures occurred more often in patients with MS, especially fractures of the tibia, hip and femur.

The risk of fracture in incident multiple sclerosis patients: the Danish National Health Registers.

BACKGROUND: Patients with multiple sclerosis (MS) may be at increased risk of fractures owing to osteoporosis and falling. OBJECTIVE: To evaluate the risk of fracture in incident MS patients drawn from a dedicated MS registry compared with population-based controls. METHODS: We conducted a population-based cohort study (1996-2007) utilising the Danish National Health Registers that were linked to the Danish MS Registry and the Danish MS Treatment Registry. Incident MS patients (2963 cases) were 1:6 matched by year of birth, gender, calendar time and region to persons without MS (controls). Cox proportional hazards models and logistic regression were used to estimate the risk of fracture in MS. Time-dependent adjustments were made for age, history of diseases and drug use. RESULTS: Compared with controls, patients with MS had no overall increased risk of fracture (adjusted hazard ratio (adj. HR): 1.0, 95% CI: 0.9-1.2). However, the risk of femur/hip fracture (adj. HR: 1.9, 95% CI: 1.1-3.4) was significantly increased compared to controls. As compared with unexposed patients, MS patients who had been exposed to a short course of methylprednisolone in the prior year had no significantly increased risk of osteoporotic fracture (adj. HR: 1.2, 95% CI: 0.5-2.9). Disabled MS patients with Expanded Disability Status Scale [EDSS] scores between 6 and 10, had a 2.6-fold increased risk of osteoporotic fracture (adjusted odds ratio (adj. OR): 2.6, 95% CI: 1.0-6.6) compared to patients with an EDSS score between 0 and 3. CONCLUSION: Patients with MS had a higher risk of femur/hip fracture than controls. Disability status is probably more important than glucocorticoid use in the aetiology of MS and osteoporotic fracture.

Use of thiazolidinediones and risk of osteoporotic fracture: disease or drugs?

PURPOSE: Clinical and observational studies suggest that use of thiazolidinediones (TZDs) is associated with an increased fracture risk. In addition, type 2 diabetes mellitus (T2DM) is a risk factor for osteoporotic fracture. Our aim was to estimate fracture risks in TZD users and users of other antidiabetic drugs, classified according to proxies of disease severity. METHODS: We conducted a population-based cohort study utilizing the Dutch PHARMO database (1998-2008). PHARMO links pharmacy-dispensing data to the National Hospital Registry. Oral antidiabetic users (n = 123,452) were matched 1:4 by year of birth and sex to non-users. Cox proportional hazards models were used to estimate hazard ratios (HRs) of fracture in TZD users. We created a proxy indicator for disease severity. The first stage was defined as current use of either a biguanide or a sulfonylureum, the second stage as current use of a biguanide and a sulfonylureum at the same time, the third stage was assigned to patients using TZDs and the fourth stage to patients using insulin. RESULTS: The risk of osteoporotic fracture was increased 1.5-fold (HR 1.49, 95%CI 1.28-1.73) in patients who currently used TZDs (stage 3), and for patients using insulin (stage 4), the risk was increased 1.2-fold (HR 1.24, 1.14-1.36), as compared with controls. In the first and second stages, risks were lower: HR 1.11 (1.06-1.17) for stage 1 and HR 1.03 (0.96-1.11) for stage 2. CONCLUSIONS: When observational studies assess risk of fracture in patients with TZDs, the severity of T2DM should be taken into account.

Safety of saxagliptin: rationale for and design of a series of postmarketing observational studies.

PURPOSE: To describe the design and rationale of a series of postmarketing studies to examine the safety of saxagliptin, an oral dipeptidyl peptidase-4 inhibitor for the treatment of type 2 diabetes mellitus, in real-world settings. METHODS: We are conducting a series of retrospective cohort studies using two UK (General Practice Research Database, and The Health Improvement Network) and two US (Medicare, HealthCore Integrated Research Database(SM) ) data sources. The primary outcomes of interest will include (i) hospitalization with acute liver failure, (ii) hospitalization for acute kidney injury, (iii) hospitalization for severe hypersensitivity reactions, (iv) hospitalization for severe infections, (v) hospitalization with infections associated with T-lymphocyte dysfunction (i.e., herpes zoster, tuberculosis, or nontuberculous mycobacteria), and (vi) major cardiovascular events. Diagnosis codes for the outcomes of interest will be validated by medical record review within each data source. Projected use and estimated incidence rates of outcomes of interest suggest there will be at least 80% statistical power to detect a minimum hazard ratio of 1.5 for major cardiovascular events, 2.0 for acute kidney injury and severe infections, 2.4 for acute liver failure, and 4.0 for severe hypersensitivity reactions. RESULTS: Forthcoming. CONCLUSIONS: This postmarketing safety assessment will provide important information regarding the safety of saxagliptin and could potentially identify important dipeptidyl peptidase-4 inhibitor class effects. The methods described may be useful to others planning similar evaluations.