Predicting mortality in acutely hospitalized older patients: a retrospective cohort study

Acutely hospitalized older patients have an increased risk of mortality, but at the moment of presentation this risk is difficult to assess. Early identification of patients at high risk might increase the awareness of the physician, and enable tailored decision-making. Existing screening instruments mainly use either geriatric factors or severity of disease for prognostication. Predictive performance of these instruments is moderate, which hampers successive interventions. We conducted a retrospective cohort study among all patients aged 70 years and over who were acutely hospitalized in the Acute Medical Unit of the Leiden University Medical Center, the Netherlands in 2012. We developed a prediction model for 90-day mortality that combines vital signs and laboratory test results reflecting severity of disease with geriatric factors, represented by comorbidities and number of medications. Among 517 patients, 94 patients (18.2 %) died within 90 days after admission. Six predictors of mortality were included in a model for mortality: oxygen saturation, Charlson comorbidity index, thrombocytes, urea, C-reactive protein and non-fasting glucose. The prediction model performs satisfactorily with an 0.738 (0.667–0.798). Using this model, 53 % of the patients in the highest risk decile (N = 51) were deceased within 90 days. In conclusion, we are able to predict 90-day mortality in acutely hospitalized older patients using a model with directly available clinical data describing disease severity and geriatric factors. After further validation, such a model might be used in clinical decision making in older patients

Optimal screening for increased risk for adverse outcomes in hospitalised older adults

Background: screening for frailty might help to prevent adverse outcomes in hospitalised older adults. Objective: to identify the most predictive and efficient screening tool for frailty. Design and setting: two consecutive observational prospective cohorts in four hospitals in the Netherlands. Subjects: patients aged ≥70 years, electively or acutely hospitalised for ≥2 days. Methods: screening instruments included in the Dutch Safety Management Programme [VeiligheidsManagementSysteem (VMS)] on four geriatric domains (ADL, falls, undernutrition and delirium) were used and the Identification of Seniors At Risk, the 6-item Cognitive Impairment Test and the Mini-Mental State Examination were assessed. Three months later, adverse outcomes including functional decline, high-healthcare demand or death were determined. Correlation and regression tree analyses were performed and predictive capacities were assessed. Results: follow-up data were available of 883 patients. All screening instruments were similarly predictive for adverse outcome ( predictive power 0.58–0.66), but the percentage of positively screened patients (13–72%), sensitivity (24–89%) and specificity (35–91%) highly differed. The strongest predictive model for frailty was scoring positive on ≥3 VMS domains if aged 70–80 years; or being aged ≥80 years and scoring positive on ≥1 VMS domains. This tool classified 34% of the patients as frail with a sensitivity of 68% and a specificity of 74%. Comparable results were found in the validation cohort. Conclusions: the VMS-tool plus age (VMS+ ) offers an efficient instrument to identify frail hospitalised older adults at risk for adverse outcome. In clinical practice, it is important to weigh costs and benefits of screening given the rather low-predictive power of screening instruments

Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: A comparative risk assessment

Background: High blood pressure, blood glucose, serum cholesterol, and BMI are risk factors for cardiovascular diseases and some of these factors also increase the risk of chronic kidney disease and diabetes. We estimated mortality from cardiovascular diseases, chronic kidney disease, and diabetes that was attributable to these four cardiometabolic risk factors for all countries and regions from 1980 to 2010. Methods: We used data for exposure to risk factors by country, age group, and sex from pooled analyses of population-based health surveys. We obtained relative risks for the effects of risk factors on cause-specific mortality from meta-analyses of large prospective studies. We calculated the population attributable fractions for each risk factor alone, and for the combination of all risk factors, accounting for multicausality and for mediation of the effects of BMI by the other three risks. We calculated attributable deaths by multiplying the cause-specific population attributable fractions by the number of disease-specific deaths. We obtained cause-specific mortality from the Global Burden of Diseases, Injuries, and Risk Factors 2010 Study. We propagated the uncertainties of all the inputs to the final estimates. Findings: In 2010, high blood pressure was the leading risk factor for deaths due to cardiovascular diseases, chronic kidney disease, and diabetes in every region, causing more than 40% of worldwide deaths from these diseases; high BMI and glucose were each responsible for about 15% of deaths, and high cholesterol for more than 10%. After accounting for multicausality, 63% (10·8 million deaths, 95% CI 10·1-11·5) of deaths from these diseases in 2010 were attributable to the combined effect of these four metabolic risk factors, compared with 67% (7·1 million deaths, 6·6-7·6) in 1980. The mortality burden of high BMI and glucose nearly doubled from 1980 to 2010. At the country level, age-standardised death rates from these diseases attributable to the combined effects of these four risk factors surpassed 925 deaths per 100 000 for men in Belarus, Kazakhstan, and Mongolia, but were less than 130 deaths per 100 000 for women and less than 200 for men in some high-income countries including Australia, Canada, France, Japan, the Netherlands, Singapore, South Korea, and Spain. Interpretation: The salient features of the cardiometabolic disease and risk factor epidemic at the beginning of the 21st century are high blood pressure and an increasing effect of obesity and diabetes. The mortality burden of cardiometabolic risk factors has shifted from high-income to low-income and middle-income countries. Lowering cardiometabolic risks through dietary, behavioural, and pharmacological interventions should be a part of the global response to non-communicable diseases. Funding: UK Medical Research Council, US National Institutes of Health. © 2014 Elsevier Ltd

Validity of a screening method for delirium risk in older patients admitted to a general hospital in the Netherlands

Objective: Delirium is an impactful, frequently occurring complication in older hospital patients. Consequently, risk stratification of delirium was included in a set of mandatory safety measures in general hospitals in the Netherlands. This risk stratification contains three consensus-based questions that have not been validated. Therefore, we evaluated their predictive performance and examined whether other routinely collected patient data can improve the prediction of delirium. Method: Using data from a continuous data registry from a general hospital, the prediction of the three questions was compared with the occurrence of delirium in 3786 older patients. Regression models were fitted that included other patient-related delirium risk factors. The performance was expressed by discrimination and calibration. Results: Delirium occurrence was 16.8%. The three questions, a regression model with the three questions, a full model and a reduced model – including the three questions, age, use of glasses, number of medications and Katz-ADL – showed sensitivities of 0.88, 0.88, 0.92 and 0.91 and specificities of 0.52, 0.52, 0.53 and 0.54, when treated as dichotomous models respectively. The three risk models had C-statistics of 0.81, 0.86 and 0.86, with excellent p-values of the U-statistics. Conclusion: The three risk-stratification questions show promising results but substantial overprediction (49% predicting positive). Further validation should be done outside the Netherlands, given the potential bias as a result of clinical activities following the risk stratification. The reduced model shows excellent calibration performance, indicating good prediction in each individual patient. In clinical practice, this advantage adds to clinical reasoning

HELP! Problems in executing a pragmatic, randomized, stepped wedge trial on the Hospital Elder Life Program to prevent delirium in older patients

Background: A pragmatic, stepped wedge trial design can be an appealing design to evaluate complex interventions in real-life settings. However, there are certain pitfalls that need to be considered. This paper reports on the experiences and lessons learned from the conduct of a cluster randomized, stepped wedge trial evaluating the effect of the Hospital Elder Life Program (HELP) in a Dutch hospital setting to prevent older patients from developing delirium. Methods: We evaluated our trial which was conducted in eight departments in two hospitals in hospitalized patients aged 70 years or older who were at risk for delirium by reflecting on the assumptions that we had and on what we intended to accomplish when we started, as compared to what we actually realized in the different phases of our study. Lessons learned on the design, the timeline, the enrollment of eligible patients and the use of routinely collected data are provided accompanied by recommendations to address challenges. Results: The start of the trial was delayed which caused subsequent time schedule problems. The requirement for individual informed consent for a quality improvement project made the inclusion more prone to selection bias. Most units experienced major difficulties in including patients, leading to excluding two of the eight units from participation. This resulted in failing to include a similar number of patients in the control condition versus the intervention condition. Data on outcomes routinely collected in the electronic patient records were not accessible during the study, and appeared to be often missing during analyses. Conclusions: The stepped wedge, cluster randomized trial poses specific risks in the design and execution of research in real-life settings of which researchers should be aware to prevent negative consequences impacting the validity of their results. Valid conclusions on the effectiveness of the HELP in the Dutch hospital setting are hampered by the limited quantity and quality of routine clinical data in our pragmatic trial. Executing a stepped wedge design in a daily practice setting using routinely collected data requires specific attention to ethical review, flexibility, a spacious time schedule, the availability of substantial capacity in the research team and early checks on the data availability and quality. Trial registration Netherlands Trial Register, identifier: NTR3842. Registered on 24 January 2013

Predicting mortality in acutely hospitalized older patients: a retrospective cohort study

textabstractAcutely hospitalized older patients have an increased risk of mortality, but at the moment of presentation this risk is difficult to assess. Early identification of patients at high risk might increase the awareness of the physician, and enable tailored decision-making. Existing screening instruments mainly use either geriatric factors or severity of disease for prognostication. Predictive performance of these instruments is moderate, which hampers successive interventions. We conducted a retrospective cohort study among all patients aged 70 years and over who were acutely hospitalized in the Acute Medical Unit of the Leiden University Medical Center, the Netherlands in 2012. We developed a prediction model for 90-day mortality that combines vital signs and laboratory test results reflecting severity of disease with geriatric factors, represented by comorbidities and number of medications. Among 517 patients, 94 patients (18.2 %) died within 90 days after admission. Six predictors of mortality were included in a model for mortality: oxygen saturation, Charlson comorbidity index, thrombocytes, urea, C-reactive protein and non-fasting glucose. The prediction model performs satisfactorily with an 0.738 (0.667–0.798). Using this model, 53 % of the patients in the highest risk decile (N = 51) were deceased within 90 days. In conclusion, we are able to predict 90-day mortality in acutely hospitalized older patients using a model with directly available clinical data describing disease severity and geriatric factors. After further validation, such a model might be used in clinical decision making in older patients

Increasing value and reducing waste by optimizing the development of complex interventions : Enriching the development phase of the Medical Research Council (MRC) Framework

BACKGROUND: In recent years there has been much emphasis on 'research waste' caused by poor question selection, insufficient attention to previous research results, and avoidable weakness in research design, conduct and analysis. Little attention has been paid to the effect of inadequate development of interventions before proceeding to a full clinical trial. OBJECTIVE: We therefore propose to enrich the development phase of the MRC Framework by adding crucial elements to improve the likelihood of success and enhance the fit with clinical practice METHODS: Based on existing intervention development guidance and synthesis, a comprehensive iterative intervention development approach is proposed. Examples from published reports are presented to illustrate the methodology that can be applied within each element to enhance the intervention design. RESULTS: A comprehensive iterative approach is presented by combining the elements of the MRC Framework development phase with essential elements from existing guidance including: problem identification, the systematic identification of evidence, identification or development of theory, determination of needs, the examination of current practice and context, modelling the process and expected outcomes leading to final element: the intervention design. All elements are drawn from existing models to provide intervention developers with a greater chance of producing an intervention that is well adopted, effective and fitted to the context. CONCLUSION: This comprehensive approach of developing interventions will strengthen the internal and external validity, minimize research waste and add value to health care research. In complex interventions in health care research, flaws in the development process immediately impact the chances of success. Knowledge regarding the causal mechanisms and interactions within the intended clinical context is needed to develop interventions that fit daily practice and are beneficial for the end-user