Independence in daily activities is defined as the ability to perform functions related to daily living, i.e. the capacity of living independently in the community with little or no help from others.
...We focused on non-attenders as a subgroup of patients whose health status is not well known to family practice teams. Our goal was to estimate the prevalence of dependence and its severity level in the daily activities of patients, and to determine the factors that are associated with the occurrence of dependence.
Cross-sectional observational study.
Data was obtained in family medicine settings. Participants in the study were adults living in the community (aged 18 or over) who had not visited their chosen family physician in the last 5 years (non-attenders) and who were able to participate in the study. Through the electronic system, we identified 2,025 non-attenders. Community nurses collected data in the participants' homes. The outcome measure was dependence in daily activities, assessed through eight items: personal hygiene; eating and drinking; mobility; dressing and undressing; urination and defecation; continence; avoiding hazards in the environment; and communication.
The final sample consisted of 1,999 patients (98.7% response rate). The mean age was 59.9 (range 20 to 99). Dependence in daily activities was determined in 466 or 23.3% (95% CI: 21.5, 25.2) of the patients. Older patients (over 60 years), with at least one chronic disease, increased risk of falling, moderate feelings of loneliness and a lower self-assessment of health were statistically significantly more likely to be dependent in their daily activities, according to our multivariate model.
A considerable proportion of family practice non-attenders were found to be dependent in daily activities, though at a low level. We identified several factors associated with this dependence. This could help to identify people at risk of being dependent in daily activities in the general adult population, and enable specific interventions that would improve their health status.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In the paper, we propose a semiparametric framework for modeling the COVID-19 pandemic. The stochastic part of the framework is based on Bayesian inference. The model is informed by the actual ...COVID-19 data and the current epidemiological findings about the disease.
The framework combines many available data sources (number of positive cases, number of patients in hospitals and in intensive care, etc.) to make outputs as accurate as possible and incorporates the times of non-pharmaceutical governmental interventions which were adopted worldwide to slow-down the pandemic. The model estimates the reproduction number of SARS-CoV-2, the number of infected individuals and the number of patients in different disease progression states in time. It can be used for estimating current infection fatality rate, proportion of individuals not detected and short term forecasting of important indicators for monitoring the state of the healthcare system. With the prediction of the number of patients in hospitals and intensive care units, policy makers could make data driven decisions to potentially avoid overloading the capacities of the healthcare system. The model is applied to Slovene COVID-19 data showing the effectiveness of the adopted interventions for controlling the epidemic by reducing the reproduction number of SARS-CoV-2. It is estimated that the proportion of infected people in Slovenia was among the lowest in Europe (0.350%, 90% CI 0.245–0.573%), that infection fatality rate in Slovenia until the end of first wave was 1.56% (90% CI 0.94–2.21%) and the proportion of unidentified cases was 88% (90% CI 83–93%).
The proposed framework can be extended to more countries/regions, thus allowing for comparison between them. One such modification is exhibited on data for Slovene hospitals.
•Semiparametric framework combines epidemiological background with Bayesian inference.•Reproduction number, number of hospitalized/ICU patients according to interventions are estimated.•Given reliability and availability of the data, the model can be easily adapted.•Flexibility and reliability is showcased using Slovene COVID-19 data.•Software is publicly available, requiring basic R programming skills.
Random cancers as supported by registry data Stare, Janez; Henderson, Robin; Gorenjec, Nina Ružić
Statistics in medicine,
20 September 2020, Letnik:
39, Številka:
21
Journal Article
Recenzirano
Summary
There has been considerable interest in recent years in quantifying the rate of unavoidable or so‐called random cancers, as opposed to cancers linked to environmental, genetic or other ...factors. We propose a data‐based approach to estimate an upper limit to this probability, based on an analysis of multiple registry data. The argument is that the cumulative hazards for random cancers cannot exceed the minimum reliable cumulative hazard observed across the registries. We propose a Monte Carlo method to identify this upper limit and apply the method to data on nine different cancers recorded by 423 registries. We compare our values with estimates obtained from a random mutations argument.
For cohorts with long‐term follow‐up, the number of years lost due to a certain disease yields a measure with a simple and appealing interpretation. Recently, an overview of the methodology used for ...this goal has been published, and two measures have been proposed. In this work, we consider a third option that may be useful in settings in which the other two are inappropriate. In all three measures, the survival of the given dataset is compared to the expected survival in the general population which is calculated using external mortality tables. We thoroughly analyze the differences between the three measures, their assumptions, interpretation, and the corresponding estimators. The first measure is defined in a competing risk setting and assumes an excess hazard compared to the population, while the other two measures also allow estimation for groups that live better than the general population. In this case, the observed survival of the patients is compared to that in the population. The starting point of this comparison depends on whether the entry into the study is a hazard changing event (e.g., disease diagnosis or the age at which the inclusion criteria were met). Focusing on the newly defined life years difference measure, we study the estimation of the variance and consider the possible challenges (e.g., extrapolation) that occur in practice. We illustrate its use with a dataset of French Olympic athletes. Finally, an efficient R implementation has been developed for all three measures which make this work easily available to subsequent users.
Research on models of integrated health care for hypertension and diabetes is one of the priority issues in the world. There is a lack of knowledge about how integrated care is implemented in ...practice. Our study assessed its implementation in six areas: identification of patients, treatment, health education, self-management support, structured collaboration and organisation of care.
This was a mixed methods study based on a triangulation method using quantitative and qualitative data. It took place in different types of primary health care organisations, in one urban and two rural regions of Slovenia. The main instrument for data collection was the Integrated Care Package (ICP) Grid, assessed through four methods: 1) a document analysis (of a current health policy and available protocols; 2) observation of the infrastructure of health centres, organisation of work, patient flow, interaction of patients with health professionals; 3) interview with key informants and 4) review of medical documentation of selected patients.
The implementation of the integrated care in Slovenia was assessed with the overall ICP score of 3.7 points (out of 5 possible points). The element Identification was almost fully implemented, while the element Self-management support was weakly implemented.
The implementation of the integrated care of patients with diabetes and/or hypertension in Slovenian primary health care organisations achieved high levels of implementation. However, some week points were identified.
Integrated care of the chronic patients in Slovenia is already provided at high levels, but the area of self-management support could be improved.
The tumor microenvironment, composed of pro- and antitumor immune cells, affects cancer cell behavior. We aimed to evaluate whether tumor-infiltrating lymphocyte (TIL) density and TIL subtypes in ...core biopsies at the diagnosis of breast cancer patients could predict a pathologic complete response (pCR; ypT0/is ypN0) from neoadjuvant systemic therapy (NST). The TIL subtypes were determined based on the proportions of presumably antitumor (CD8+, CXCL13+) and protumor (PD-1+, FOXP3+) immune cells. A prospective, noninterventional study, including 171 participants undergoing NST, was performed. The median TIL density for the entire cohort was 10% (IQR: 3.5–23.8), and 59 (35%) patients achieved pCR. TIL density was positively associated with pCR (univariately and multivariably). In the multivariable logistic regression model, TIL density was an independent predictor of pCR (p = 0.012, OR 1.27; 95% CI 1.05–1.54) when controlled for age (p = 0.232), Ki-67 (p = 0.001), node-negative status (p = 0.024), and HER2+/triple negative vs. luminal B-like subtype (p < 0.001). In our sample, higher proportions of PD-1+ TILs and FOXP3+ TILs were associated with a higher probability of pCR but the association was not statistically significant and we could not make any conclusions on the direction of associations in the model with all four biomarkers. In the exploratory multivariable analysis, we showed that only higher CD8+ TILs were associated with pCR. In conclusion, TIL density and its subtypes are associated with pCR.
Patient empowerment is crucial for promoting and strengthening health. We aimed to assess patient empowerment and diabetes-specific health-related quality of life (HRQoL) in adults with type 2 ...diabetes (T2D). A multi-centre, cross-sectional survey was conducted among adults with T2D in urban and rural primary care settings in Slovenia between April and September 2023. The survey utilised convenience sampling and included sociodemographic and clinical data, the Diabetes Empowerment Scale (DES), and the Audit of Diabetes-Dependent QoL (ADDQoL). The study included 289 people with T2D and a mean age of 67.2 years (SD 9.2). The mean overall DES score was 3.9/5 (SD 0.4). In a multivariable linear regression model, higher empowerment was significantly associated with residing in a rural region (
= 0.034), higher education (
= 0.028), and a lack of comorbid AH (
= 0.016). The median overall ADDQoL score was -1.2 (IQR -2.5, -0.6). The greatest negative influence of diabetes on HRQoL was observed in the domain 'Freedom to eat', followed by 'Freedom to drink', 'Leisure activities', and 'Holidays'. Despite high empowerment among adults with T2D, the condition still imposes a personal burden. Integrated primary care models should prioritise the importance of implementing targeted interventions to enhance diabetes empowerment, address comorbidities, and improve specific aspects of QoL among individuals with T2D.
The present retrospective study was undertaken to investigate the association of relative dose intensity (RDI) with the outcome of patients with advanced stage Hodgkin lymphoma (HL) receiving ABVD ...(doxorubicin, bleomycin, vinblastine, dacarbazine) and escalated BEACOPP regimens (bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, prednisone). A total of 114 patients with HL treated between 2004 and 2013 were enrolled for evaluation. The association of variables with overall survival (OS) and progression-free survival (PFS) was analysed using univariate and multivariate Cox proportional hazards models. The median age of patients was 39 years, and the majority were male and had stage IV disease. A total of 54 patients received ABVD and 60 received BEACOPP chemotherapy with 24 and four deaths, respectively. Patients in the BEACOPP group were significantly younger with lower Charlson comorbidity index (CCI) and better performance status in comparison with the ABVD group, making the comparison of groups not possible. In the ABVD group, RDI was not significantly associated with OS (P=0.590) or PFS (P=0.354) in a multivariate model where age was controlled. The low number of events prevented this analysis in the BEACOPP group. The age of patients was strongly associated with both OS and PFS; all statistically significant predictors for OS and PFS from univariate analyses (chemotherapy regimen, CCI, RDI, performance status) lost their effect in multivariate analyses where age was controlled. Based on these observations, it was concluded that RDI was not associated with OS or PFS after age is controlled, neither in all patients combined nor in the ABVD group.
During the first wave of the COVID-19 pandemic in spring 2020, Slovenia was among the least affected countries, but the situation became drastically worse during the second wave in autumn 2020 with ...high numbers of deaths per number of inhabitants, ranking Slovenia among the most affected countries. This was true even though strict non-pharmaceutical interventions (NPIs) to control the progression of the epidemic were being enforced. Using a semi-parametric Bayesian model developed for the purpose of this study, we explore if and how the changes in mobility, their timing and the activation of contact tracing can explain the differences in the epidemic progression of the two waves. To fit the model, we use data on daily numbers of deaths, patients in hospitals, intensive care units, etc., and allow transmission intensity to be affected by contact tracing and mobility (data obtained from Google Mobility Reports). Our results imply that though there is some heterogeneity not explained by mobility levels and contact tracing, implementing interventions at a similar stage as in the first wave would keep the death toll and the health system burden low in the second wave as well. On the other hand, sticking to the same timeline of interventions as observed in the second wave and focusing on enforcing a higher decrease in mobility would not be as beneficial. According to our model, the ‘dance’ strategy, i.e., first allowing the numbers to rise and then implementing strict interventions to make them drop again, has been played at too-late stages of the epidemic. In contrast, a 15–20% reduction of mobility compared to pre-COVID level, if started at the beginning and maintained for the entire duration of the second wave and coupled with contact tracing, could suffice to control the epidemic. A very important factor in this result is the presence of contact tracing; without it, the reduction in mobility needs to be substantially larger. The flexibility of our proposed model allows similar analyses to be conducted for other regions even with slightly different data sources for the progression of the epidemic; the extension to more than two waves is straightforward. The model could help policymakers worldwide to make better decisions in terms of the timing and severity of the adopted NPIs.
•This was the first study to focus on the risk for malnutrition in a general population (family practice non-attenders, living at home).•One in 10 community-living family practice non-attenders had ...an increased risk for malnutrition.•A screening program at the primary health level can aid in performing early identification of patients at risk for malnutrition.
The aim of this study was to determine the prevalence of malnutrition and the factors associated with malnutrition in a population of family practice non-attenders. This would enable us to recognize the extent of the problem and anticipate the measures needed to improve the current situation.
This was a cross-sectional observational study in a family medicine setting. Participants were adults living in the community (≥18 y of age) who had not visited their chosen family physician in the previous 5 y (non-attenders) and who were able to participate in the study. Through the electronic system, we identified 2025 non-attenders. Data were collected by community nurses in the participants’ homes. The main outcome measure was the Malnutrition Universal Screening Tool.
The sample consisted of 1641 participants (81% response rate). Increased risk for malnutrition was determined in 216 participants (13.2%; 95% confidence interval, 11.6–14.9). The multivariate model showed a significant association of increased risk for malnutrition with age and body mass index interaction (P = 0.022); number of chronic diseases (P = 0.001); poor assessment of current health (P = 0.001); a feelings of loneliness (P <0.001); and increased pain intensity (P = 0.003).
A screening program at the primary health care level could help identify patients at risk for malnutrition early. This could be followed by appropriate nutrition support, which may help to reverse or halt the malnutrition trajectory and the negative outcomes associated with poor nutritional status.
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