scholarly journals Work-unit organisational changes and subsequent prescriptions for psychotropic medication: a longitudinal study among public healthcare employees

2019 ◽  
Vol 76 (3) ◽  
pp. 143-150 ◽  
Author(s):  
Johan Høy Jensen ◽  
Jens Peter Bonde ◽  
Esben Meulengracht Flachs ◽  
Janne Skakon ◽  
Naja Hulvej Rod ◽  
...  
Keyword(s):  
Psychotropic Medication ◽  
Organisational Change ◽  
Survival Models ◽  
Public Healthcare ◽  
Budget Cuts ◽  
Work Unit ◽  
Increased Risk ◽  
Parametric Survival ◽  
Healthcare Employees

ObjectivesWe examined exposure to different types of organisational changes at work as risk factors for subsequent prescription for psychotropic medication among employees.MethodsThe study population included 15 038 public healthcare employees nested within 1284 work units in the Capital Region of Denmark. Multilevel mixed-effects parametric survival models were developed to examine time to prescription for psychotropic medications (anxiolytics/hypnotics/sedatives/antidepressants) during the 12-month interval following exposure to organisational changes relative to no change from January to December 2013. Data on work-unit level organisational changes (including mergers, split-ups, relocation, change in management, employee lay-offs and budget cuts) were collected from work-unit managers (59% response).ResultsAny organisational change versus no change was associated with a higher risk of psychotropic prescription (HR: 1.14, 95% CI: 1.02 to 1.26), especially change in management (HR: 1.23, 95% CI: 1.07 to 1.41). Splitting the 12-month follow-up period into two halves yielded particularly high rates of psychotropic prescription in the latter half of the follow-up, for example, any change (HR: 1.25, 95% CI: 1.11 to 1.41), change in management (HR: 1.42, 95% CI: 1.22 to 1.65), mergers (HR: 1.26, 95% CI: 1.06 to 1.50), employee lay-off (HR: 1.23, 95% CI: 1.03 to 1.46) and budget cuts (HR: 1.13, 95% CI: 1.00 to 1.41). The associations did not vary by sex.ConclusionsOrganisational changes in the workplace, especially change in management, may be associated with increased risk of psychotropic prescription among employees regardless of sex.

scholarly journals Dual impact of organisational change on subsequent exit from work unit and sickness absence: a longitudinal study among public healthcare employees

2018 ◽  
Vol 75 (7) ◽  
pp. 479-485 ◽  
Author(s):  
Johan Høy Jensen ◽  
Esben Meulengracht Flachs ◽  
Janne Skakon ◽  
Naja Hulvej Rod ◽  
Jens Peter Bonde
Keyword(s):  
Sickness Absence ◽  
Cox Regression ◽  
Organisational Change ◽  
Public Healthcare ◽  
Work Unit ◽  
Subsequent Work ◽  
Individual Level ◽  
Level Data ◽  
Healthcare Employees

ObjectivesWe investigated work-unit exit, total and long-term sickness absence following organisational change among public healthcare employees.MethodsThe study population comprised employees from the Capital Region of Denmark (n=14 388). Data on reorganisation at the work-unit level (merger, demerger, relocation, change of management, employee layoff or budget cut) between July and December 2013 were obtained via surveys distributed to the managers of each work unit. Individual-level data on work-unit exit, total and long-term sickness absence (≥29 days) in 2014 were obtained from company registries. For exposure to any, each type or number of reorganisations (1, 2 or ≥3), the HRs and 95% CIs for subsequent work-unit exit were estimated by Cox regression, and the risk for total and long-term sickness absence were estimated by zero-inflated Poisson regression.ResultsReorganisation was associated with subsequent work-unit exit (HR 1.10, 95% CI 1.01 to 1.19) in the year after reorganisation. This association was specifically important for exposure to ≥3 types of changes (HR 1.52, 95% CI 1.30 to 1.79), merger (HR 1.29, 95% CI 1.12 to 1.49), demerger (HR 1.41, 95% CI 1.16 to 1.71) or change of management (HR 1.24, 95% CI 1.11 to 1.38). Among the employees remaining in the work unit, reorganisation was also associated with more events of long-term sickness absence (OR 1.15, 95% CI 1.00 to 1.33), which was particularly important for merger (OR 1.31, 95% CI 1.00 to 1.72) and employee layoff (OR 1.31, 95% CI 1.08 to 1.59).ConclusionsSpecific types of reorganisation seem to have a dual impact on subsequent work-unit exit and sickness absence in the year after change.

scholarly journals Psychological trauma occurring during adolescence is associated with an increased risk of greater waist circumference in Early Psychosis patients treated with psychotropic medication

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0242569
Author(s):  
Luis Alameda ◽  
Axel Levier ◽  
Mehdi Gholam-Rezaee ◽  
Philippe Golay ◽  
Frederik Vandenberghe ◽  
...  
Keyword(s):  
Weight Gain ◽  
Waist Circumference ◽  
Psychotropic Medication ◽  
Psychological Trauma ◽  
Early Psychosis ◽  
Trauma Patients ◽  
Subsequent Increase ◽  
Increased Risk ◽  
Early Intervention In Psychosis

Background It has been suggested that exposure to Childhood Trauma [CT] may play a role in the risk of obesity in Early Psychosis [EP] patients; however, whether this is independently of age at exposure to CT and the medication profile has yet to be investigated. Methods 113 EP-patients aged 18–35 were recruited from the Treatment and Early Intervention in Psychosis Program [TIPP-Lausanne]. Body Mass Index [BMI], Weight Gain [WG] and Waist Circumference [WC] were measured prospectively at baseline and after 1, 2, 3, 6 and 12 months of weight gain inducing psychotropic treatment. Patients were classified as Early-Trauma and Late-Trauma if the exposure had occurred before age 12 or between ages 12 and 16 respectively. Generalized Linear Mixed-Models were adjusted for age, sex, socioeconomic status, baseline BMI, medication and for diagnosis of depression. Results Late-Trauma patients, when compared to Non-Trauma patients showed greater WCs during the follow-up [p = 0.013]. No differences were found in any of the other follow-up measures. Conclusions Exposition to CT during adolescence in EP-patients treated with psychotropic medication is associated with greater WC during the early phase of the disease. Further investigation exploring mechanisms underlying the interactions between peripubertal stress, corticoids responsiveness and a subsequent increase of abdominal adiposity is warranted.

scholarly journals Extrapolating Parametric Survival Models in Health Technology Assessment: A Simulation Study

2020 ◽  
Vol 41 (1) ◽  
pp. 37-50
Author(s):  
Daniel Gallacher ◽  
Peter Kimani ◽  
Nigel Stallard
Keyword(s):  
Health Technology Assessment ◽  
Technology Assessment ◽  
Goodness Of Fit ◽  
Information Criterion ◽  
Health Technology ◽  
Survival Models ◽  
Fit Statistics ◽  
Long Term Treatment ◽  
Parametric Survival

Extrapolations of parametric survival models fitted to censored data are routinely used in the assessment of health technologies to estimate mean survival, particularly in diseases that potentially reduce the life expectancy of patients. Akaike’s information criterion (AIC) and Bayesian information criterion (BIC) are commonly used in health technology assessment alongside an assessment of plausibility to determine which statistical model best fits the data and should be used for prediction of long-term treatment effects. We compare fit and estimates of restricted mean survival time (RMST) from 8 parametric models and contrast models preferred in terms of AIC, BIC, and log-likelihood, without considering model plausibility. We assess the methods’ suitability for selecting a parametric model through simulation of data replicating the follow-up of intervention arms for various time-to-event outcomes from 4 clinical trials. Follow-up was replicated through the consideration of recruitment duration and minimum and maximum follow-up times. Ten thousand simulations of each scenario were performed. We demonstrate that the different methods can result in disagreement over the best model and that it is inappropriate to base model selection solely on goodness-of-fit statistics without consideration of hazard behavior and plausibility of extrapolations. We show that typical trial follow-up can be unsuitable for extrapolation, resulting in unreliable estimation of multiple parameter models, and infer that selecting survival models based only on goodness-of-fit statistics is unsuitable due to the high level of uncertainty in a cost-effectiveness analysis. This article demonstrates the potential problems of overreliance on goodness-of-fit statistics when selecting a model for extrapolation. When follow-up is more mature, BIC appears superior to the other selection methods, selecting models with the most accurate and least biased estimates of RMST.

scholarly journals Pubarche and gonadarche onset and progression are differently associated to birth weight and infancy growth patterns

2021 ◽  
Author(s):  
Christine Wohlfahrt-Veje ◽  
Jeanette Tinggaard ◽  
Anders Juul ◽  
Jorma Toppari ◽  
Niels E Skakkebæk ◽  
...  
Keyword(s):  
Birth Weight ◽  
Growth Patterns ◽  
Survival Models ◽  
Childhood And Adolescence ◽  
Testis Size ◽  
Weight Changes ◽  
Pubertal Stages ◽  
Catch Up ◽  
Parametric Survival

Abstract Context Controversy exists regarding associations between early life growth patterns and timing of puberty. Objective To investigate associations between birth anthropometry, early growth patterns and onset/progression of pubertal milestones in boys and girls. Design and Participants Among children examined at birth (1997-2003) and at 36 months of age in a mother child cohort, pubertal Tanner stages (B1-5, PH1-5, G1-5) and testicular volume were examined by trained physicians at 1-5 follow-up examinations during childhood and adolescence (672 girls and 846 boys, 2006-2013). Main Outcome Measures With parametric survival models we analyzed associations between birth weight, changes in standard deviation scores (SDS) from birth to 36 months (Δ SDS 0-36 >0.67 SD defining catch up growth), and age at pubertal onset/attainment of late pubertal stages /menarche. Results A 1 kg higher birth weight was associated with earlier onset of B2+ (thelarche): -3.9 months (CI: -6.7; -1.1), G2+ (gonadarche): -2.7 months (-5.3;-0.1), Tvol3+ (testis size > 3ml):-2.8 months (-4.9; -0.7), but with later G4+ and PH4+ in boys, and a slower progression from B2 to menarche (5.3 months (1.2; 9.4)) in girls. Catch up growth was associated with earlier PH2+ (pubarche) in girls (-4.1 months (-7.6;-0.6)), earlier PH2+ in boys (-3.4 months (-6.6;-0.2)), faster progression from B2 to menarche in girls (-9.1 months (14.6; 3.5)) and earlier G4+ and PH4+ in boys. Conclusions Associations between birthweight and infancy catch up growth differed for gonadarche and pubarche, and for early and late pubertal markers, with similar patterns in both sexes.

scholarly journals Bacterial infections as novel risk factors of severe diabetic retinopathy in individuals with type 1 diabetes

2020 ◽  
pp. bjophthalmol-2020-316202
Author(s):  
Johan Rasmus Simonsen ◽  
Asko Järvinen ◽  
Kustaa Hietala ◽  
Valma Harjutsalo ◽  
Carol Forsblom ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 1 Diabetes ◽  
Diabetic Retinopathy ◽  
Diabetic Complications ◽  
Bacterial Infections ◽  
Survival Models ◽  
Increased Risk ◽  
Treatment Data

Background/AimsDiabetic retinopathy (DR) is associated and shares many risk factors with other diabetic complications, including inflammation. Bacterial infections, potent inducers of inflammation have been associated with the development of diabetic complications apart from DR. Our aim was to investigate the association between bacterial infections and DR.MethodsAdult individuals with type 1 diabetes (n=1043) were recruited from the Finnish Diabetic Nephropathy Study (FinnDiane), a prospective follow-up study. DR was defined as incident severe diabetic retinopathy (SDR), identified as first laser treatment. Data on DR were obtained through fundus photographs and medical records, data on bacterial infections from comprehensive national registries (1 January 1995 to 31 December 2015). Risk factors for DR and serum bacterial lipopolysaccharide (LPS) activity were determined at baseline.ResultsIndividuals with incident SDR (n=413) had a higher mean number of antibiotic purchases/follow-up year compared with individuals without incident SDR (n=630) (0.92 [95% CI 0.82 to 1.02] vs 0.67 [0.62–0.73], p=0.02), as well as higher levels of LPS activity (0.61 [0.58–0.65] vs 0.56 [0.54–0.59] EU/mL, p=0.03). Individuals with on average ≥1 purchase per follow-up year (n=269) had 1.5 times higher cumulative incidence of SDR, compared with individuals with <1 purchase (n=774) per follow-up year (52% vs 35%, p<0.001). In multivariable Cox survival models, the mean number of antibiotic purchases per follow-up year as well as LPS activity were risk factors for SDR after adjusting for static confounders (HR 1.16 [1.05–1.27], p=0.002 and HR 2.77 [1.92–3.99], p<0.001, respectively).ConclusionBacterial infections are associated with an increased risk of incident SDR in type 1 diabetes.

scholarly journals Multimorbidity and adverse events of special interest associated with CoronaVac (Sinovac) and Comirnaty (Pfizer-BioNTech)

2021 ◽  
Author(s):  
Francisco Lai ◽  
Lei Huang ◽  
Celine Sze Ling Chui ◽  
Eric Wan ◽  
Xue Li ◽  
...  
Keyword(s):  
Adverse Events ◽  
Special Interest ◽  
Vaccine Safety ◽  
Population Based ◽  
World Health ◽  
Public Healthcare ◽  
Healthcare Database ◽  
Cox Models ◽  
Increased Risk

Abstract We examined the potential additional risk of adverse events of special interest (AESI) within 28 days post-Covid-19 vaccination with CoronaVac or Comirnaty (Pfizer-BioNTech) imposed by multimorbidity (2+ chronic conditions). Using a territory-wide public healthcare database with linkage to population-based vaccination records in Hong Kong, we conducted a retrospective cohort study of patients with chronic diseases. Thirty AESI according to World Health Organization’s Global Advisory Committee on Vaccine Safety were examined. In total, 883,416 patients were included. During follow-up, 2,807 (0.3%) patients had AESI. Weighted Cox models suggested that vaccinated patients had lower risks of any AESI than those unvaccinated, that multimorbidity was associated with an increased risk regardless of vaccination status, and there was no significant effect modification of the association of vaccination with AESI by multimorbidity status. To conclude, we found no evidence that multimorbidity imposes extra risks of AESI within 28 days following Covid-19 vaccination.

scholarly journals Particulate Matter Air Pollution and the Risk of Incident CKD and Progression to ESRD

2017 ◽  
Vol 29 (1) ◽  
pp. 218-230 ◽  
Author(s):  
Benjamin Bowe ◽  
Yan Xie ◽  
Tingting Li ◽  
Yan Yan ◽  
Hong Xian ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Environmental Protection Agency ◽  
Fine Particulate Matter ◽  
Survival Models ◽  
Time Varying ◽  
Department Of Veterans Affairs ◽  
Increased Risk ◽  
Observational Cohort ◽  
Egfr Decline

Elevated levels of fine particulate matter <2.5 µm in aerodynamic diameter (PM2.5) are associated with increased risk of cardiovascular outcomes and death, but their association with risk of CKD and ESRD is unknown. We linked the Environmental Protection Agency and the Department of Veterans Affairs databases to build an observational cohort of 2,482,737 United States veterans, and used survival models to evaluate the association of PM2.5 concentrations and risk of incident eGFR <60 ml/min per 1.73 m2, incident CKD, eGFR decline ≥30%, and ESRD over a median follow-up of 8.52 years. County-level exposure was defined at baseline as the annual average PM2.5 concentrations in 2004, and separately as time-varying where it was updated annually and as cohort participants moved. In analyses of baseline exposure (median, 11.8 [interquartile range, 10.1–13.7] µg/m3), a 10-µg/m3 increase in PM2.5 concentration was associated with increased risk of eGFR<60 ml/min per 1.73 m2 (hazard ratio [HR], 1.21; 95% confidence interval [95% CI], 1.14 to 1.29), CKD (HR, 1.27; 95% CI, 1.17 to 1.38), eGFR decline ≥30% (HR, 1.28; 95% CI, 1.18 to 1.39), and ESRD (HR, 1.26; 95% CI, 1.17 to 1.35). In time-varying analyses, a 10-µg/m3 increase in PM2.5 concentration was associated with similarly increased risk of eGFR<60 ml/min per 1.73 m2, CKD, eGFR decline ≥30%, and ESRD. Spline analyses showed a linear relationship between PM2.5 concentrations and risk of kidney outcomes. Exposure estimates derived from National Aeronautics and Space Administration satellite data yielded consistent results. Our findings demonstrate a significant association between exposure to PM2.5 and risk of incident CKD, eGFR decline, and ESRD.

Estimating long-term survival of previously untreated patients with EGFR mutation-positive (EGFRm) advanced non-small cell lung cancer (NSCLC) who received osimertinib in the FLAURA study.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e20560-e20560
Author(s):  
Matthew Dyer ◽  
Matthew Green ◽  
simon jones ◽  
Rachel Hodge
Keyword(s):  
Advanced Nsclc ◽  
Survival Rates ◽  
Survival Model ◽  
Survival Models ◽  
Term Survival ◽  
Parametric Survival Model ◽  
Best Fitting ◽  
Parametric Survival

e20560 Background: In the Phase III FLAURA trial (NCT02296125), osimertinib, a third-generation EGFR-TKI, provided clinically and statistically significantly longer progression-free survival versus gefitinib/erlotinib as first-line treatment for patients with EGFRm advanced NSCLC. At the time of analysis, data on overall survival (OS) were immature (25% maturity). To better understand the long-term survival potential of osimertinib beyond the observed trial follow-up period, mathematical parametric survival models were used to estimate clinically plausible survival rates up to 5 years from FLAURA. Methods: Following published best-practice guidelines, candidate parametric survival models were evaluated based on both statistical and visual goodness-of-fit to the observed FLAURA OS data. Two modeling approaches were considered: single models with treatment included as a covariate; and separate models fitted to the osimertinib and gefitinib/erlotinib arms. Point estimates of 5-year survival rates with 95% confidence intervals (CIs) are reported for the best fitting model. Results: The best fitting parametric survival model to the FLAURA OS data was the Weibull model with treatment included as a covariate. Based on this model, estimated median OS was longer with osimertinib than with gefitinib/erlotinib (41.4 months vs 30.6 months). The estimated 3- and 5-year survival rates with osimertinib were 57.3% (95% CI 46.6%, 69.2%) and 31.1% (95% CI 23.7%, 41.8%), respectively. In comparison, the estimated 3- and 5-year survival rates with gefitinib/erlotinib were 41.1% (95% CI 31.9%, 52.9%) and 15.5% (95% CI 11.6%, 22.1%), respectively. Conclusions: Based on the best fitting parametric survival model to FLAURA OS data, the estimated 5-year survival rate with osimertinib was double that with gefitinib/erlotinib (31.1% vs 15.5%) in patients with EGFRm advanced NSCLC. Long-term follow-up data from FLAURA (60% OS maturity) will further validate this finding. Clinical trial information: NCT02296125.

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