scholarly journals Development and validation of a life expectancy estimator for multimorbid older adults: a cohort study protocol

BMJ Open ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. e048168
Author(s):  
Viktoria Gastens ◽  
Cinzia Del Giovane ◽  
Daniela Anker ◽  
Martin Feller ◽  
Lamprini Syrogiannouli ◽  
...  
Keyword(s):  
Cohort Study ◽  
Life Expectancy ◽  
Preventive Care ◽  
Hospital Admissions ◽  
Survival Function ◽  
Prognostic Index ◽  
Research Strategy ◽  
Qualitative Assessment ◽  
Parametric Survival Model ◽  
Development And Validation

BackgroundOlder multimorbid adults have a high risk of mortality and a short life expectancy (LE). Providing high-value care and avoiding care overuse, including of preventive care, is a serious challenge among multimorbid patients. While guidelines recommend to tailor preventive care according to the estimated LE, there is no tool to estimate LE in this specific population. Our objective is therefore to develop an LE estimator for older multimorbid adults by transforming a mortality prognostic index, which will be developed and internally validated in a prospective cohort.Methods and analysisWe will analyse data of the Optimising Therapy to Prevent Avoidable Hospital Admissions in Multimorbid Older People cohort study in Bern, Switzerland. 822 participants were included at hospitalisation with age of 70 years or older, multimorbidity (three or more chronic medical conditions) and polypharmacy (use of five drugs or more for >30 days). All-cause mortality will be assessed during 3 years of follow-up. We will apply a flexible parametric survival model with backward stepwise selection to identify the mortality risk predictors. The model will be internally validated using bootstrapping techniques. We will derive a point-based risk score from the regression coefficients. We will transform the 3-year mortality prognostic index into an LE estimator using the Gompertz survival function. We will perform a qualitative assessment of the clinical usability of the LE estimator and its application. We will conduct the development and validation of the mortality prognostic index following the Prognosis Research Strategy (PROGRESS) framework and report it following the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statement.Ethics and disseminationWritten informed consent by patients themselves or, in the case of cognitive impairment, by a legal representative, was required before enrolment. The local ethics committee (Kantonale Ethikkommission Bern) has approved the study. We plan to publish the results in peer-reviewed journals and present them at national and international conferences.

Estimating life expectancy among older multimorbid adults to personalize preventive care

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
V Gastens ◽  
C Del Giovane ◽  
D Anker ◽  
L Syrogiannouli ◽  
N Schwab ◽  
...  
Keyword(s):  
Cohort Study ◽  
Cancer Screening ◽  
Life Expectancy ◽  
Preventive Care ◽  
Hospital Admissions ◽  
Prognostic Index ◽  
Preventive Treatment ◽  
Prognostic Indices ◽  
Multimorbid Patients

Abstract Background Providing high value care and avoiding care overuse is a challenge among older multimorbid adults. There is evidence on benefits and harms of cancer screening and cardiovascular diseases (CVD) preventive treatment up to the age of 75. However, this evidence is not directly applicable to older multimorbid patients. Because each cancer and CVD preventive care has a specific lagtime to benefit, many guidelines recommend tailoring preventive care according to the estimated life expectancy (LE). However, there is no tool to estimate LE among multimorbid patients. Our objectives are therefore to develop new mortality risk prognostic indices and to derive a new LE estimator, what will help clinicians tailoring preventive care in older multimorbid adults. Methods and Results We conduct a prospective cohort study by extending the follow-up of 822 patients in Bern, Switzerland, included in the OPtimising thERapy to prevent Avoidable hospital admissions in Mulitmorbid older people (OPERAM) study over 3 years. Detailed information about cancer screening and CVD preventive treatment will be collected. We will identify variables independently associated with mortality and weight the variables to create 1 year and 3 year mortality prognostic indices. We will transform the 3 year prognostic index into a LE estimator. Preliminary results will be presented at the congress. Conclusions We will develop the first life expectancy estimator specifically for older multimorbid adults. This tool will help clinicians to tailor cardiovascular and cancer preventive care in older multimorbid adults. Key messages Because of the lagtime to benefit, personalizing preventive care by estimated life expectancy is recommended. We will provide the first life expectancy estimator for older multimorbid adults.

Full compliance with Respiratory syncytial virus prophylaxis was associated with fewer respiratory‐related hospital admissions in preterm children: A cohort study

2020 ◽  
Author(s):  
Heloise Torchin ◽  
Marie‐Laure Charkaluk ◽  
Jessica Rousseau ◽  
Laetitia Marchand‐Martin ◽  
Ludovic Treluyer ◽  
...  
Keyword(s):  
Cohort Study ◽  
Respiratory Syncytial Virus ◽  
Hospital Admissions ◽  
Preterm Children ◽  
Full Compliance ◽  
Syncytial Virus

scholarly journals The development and validation of prognostic models for overall survival in the presence of missing data in the training dataset: a strategy with a detailed example

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Kara-Louise Royle ◽  
David A. Cairns
Keyword(s):  
Overall Survival ◽  
Missing Data ◽  
Prognostic Model ◽  
Prognostic Index ◽  
Risk Groups ◽  
Prognostic Models ◽  
Training Dataset ◽  
Validation Process ◽  
Test Dataset ◽  
Development And Validation

Abstract Background The United Kingdom Myeloma Research Alliance (UK-MRA) Myeloma Risk Profile is a prognostic model for overall survival. It was trained and tested on clinical trial data, aiming to improve the stratification of transplant ineligible (TNE) patients with newly diagnosed multiple myeloma. Missing data is a common problem which affects the development and validation of prognostic models, where decisions on how to address missingness have implications on the choice of methodology. Methods Model building The training and test datasets were the TNE pathways from two large randomised multicentre, phase III clinical trials. Potential prognostic factors were identified by expert opinion. Missing data in the training dataset was imputed using multiple imputation by chained equations. Univariate analysis fitted Cox proportional hazards models in each imputed dataset with the estimates combined by Rubin’s rules. Multivariable analysis applied penalised Cox regression models, with a fixed penalty term across the imputed datasets. The estimates from each imputed dataset and bootstrap standard errors were combined by Rubin’s rules to define the prognostic model. Model assessment Calibration was assessed by visualising the observed and predicted probabilities across the imputed datasets. Discrimination was assessed by combining the prognostic separation D-statistic from each imputed dataset by Rubin’s rules. Model validation The D-statistic was applied in a bootstrap internal validation process in the training dataset and an external validation process in the test dataset, where acceptable performance was pre-specified. Development of risk groups Risk groups were defined using the tertiles of the combined prognostic index, obtained by combining the prognostic index from each imputed dataset by Rubin’s rules. Results The training dataset included 1852 patients, 1268 (68.47%) with complete case data. Ten imputed datasets were generated. Five hundred twenty patients were included in the test dataset. The D-statistic for the prognostic model was 0.840 (95% CI 0.716–0.964) in the training dataset and 0.654 (95% CI 0.497–0.811) in the test dataset and the corrected D-Statistic was 0.801. Conclusion The decision to impute missing covariate data in the training dataset influenced the methods implemented to train and test the model. To extend current literature and aid future researchers, we have presented a detailed example of one approach. Whilst our example is not without limitations, a benefit is that all of the patient information available in the training dataset was utilised to develop the model. Trial registration Both trials were registered; Myeloma IX-ISRCTN68454111, registered 21 September 2000. Myeloma XI-ISRCTN49407852, registered 24 June 2009.

scholarly journals How does general practitioner discontinuity affect healthcare utilisation? An observational cohort study of 2.4 million Norwegians 2007–2017

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e042391
Author(s):  
Lena Janita Skarshaug ◽  
Silje Lill Kaspersen ◽  
Johan Håkon Bjørngaard ◽  
Kristine Pape
Keyword(s):  
Cohort Study ◽  
General Practitioner ◽  
Service Use ◽  
Hospital Admissions ◽  
Age Groups ◽  
Healthcare Utilisation ◽  
Acute Hospital ◽  
Secondary Outcome ◽  
Out Of Hours ◽  
Adult Age

ObjectivesPatients may benefit from continuity of care by a personal physician general practitioner (GP), but there are few studies on consequences of a break in continuity of GP. Investigate how a sudden discontinuity of GP care affects their list patients’ regular GP consultations, out-of-hours consultations and acute hospital admissions, including admissions for ambulatory care sensitive conditions (ACSC).DesignCohort study linking person-level national register data on use of health services and GP affiliation with data on GP activity and GP characteristics.SettingPrimary care.Participants2 409 409 Norwegians assigned to the patient lists of 2560 regular GPs who, after 12 months of stable practice, had a sudden discontinuity of practice lasting two or more months between 2007 and 2017.Primary and secondary outcome measuresMonthly GP consultations, out-of-hours consultations, acute hospital admissions and ACSC admissions in periods during and 12 months after the discontinuity, compared with the 12-month period before the discontinuity using logistic regression models.ResultsAll patient age groups had a 3%–5% decreased odds of monthly regular GP consultations during the discontinuity. Odds of monthly out-of-hours consultations increased 2%–6% during the discontinuity for all adult age groups. A 7%–9% increase in odds of ACSC admissions during the period 1–6 months after discontinuity was indicated in patients over the age of 65, but in general little or no change in acute hospital admissions was observed during or after the period of discontinuity.ConclusionsModest changes in health service use were observed during and after a sudden discontinuity in practice among patients with a previously stable regular GP. Older patients seem sensitive to increased acute hospital admissions in the absence of their personal GP.

Mortality and readmission risk can be predicted by the record-based Multidimensional Prognostic Index: a cohort study of medical inpatients older than 75 years

2021 ◽  
Vol 12 (2) ◽  
pp. 253-261 ◽  
Author(s):  
Troels Kjærskov Hansen ◽  
Seham Shahla ◽  
Else Marie Damsgaard ◽  
Sofie Ran Lindhardt Bossen ◽  
Jens Meldgaard Bruun ◽  
...  
Keyword(s):  
Cohort Study ◽  
Prognostic Index ◽  
Medical Inpatients ◽  
Readmission Risk

scholarly journals Hospital-based acute care in the last 30 days of life among patients with chronic disease that received early, late or no specialist palliative care: a retrospective cohort study of eight chronic disease groups

BMJ Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. e044196
Author(s):  
Madalene Earp ◽  
Pin Cai ◽  
Andrew Fong ◽  
Kelly Blacklaws ◽  
Truong-Minh Pham ◽  
...  
Keyword(s):  
Palliative Care ◽  
Cohort Study ◽  
Heart Disease ◽  
Chronic Disease ◽  
Acute Care ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Hospital Admissions ◽  
Specialist Palliative Care ◽  
Icu Admission

ObjectiveFor eight chronic diseases, evaluate the association of specialist palliative care (PC) exposure and timing with hospital-based acute care in the last 30 days of life.DesignRetrospective cohort study using administrative data.SettingAlberta, Canada between 2007 and 2016.Participants47 169 adults deceased from: (1) cancer, (2) heart disease, (3) dementia, (4) stroke, (5) chronic lower respiratory disease (chronic obstructive pulmonary disease (COPD)), (6) liver disease, (7) neurodegenerative disease and (8) renovascular disease.Main outcome measuresThe proportion of decedents who experienced high hospital-based acute care in the last 30 days of life, indicated by ≥two emergency department (ED) visit, ≥two hospital admissions,≥14 days of hospitalisation, any intensive care unit (ICU) admission, or death in hospital. Relative risk (RR) and risk difference (RD) of hospital-based acute care given early specialist PC exposure (≥90 days before death), adjusted for patient characteristics.ResultsIn an analysis of all decedents, early specialist PC exposure was associated with a 32% reduction in risk of any hospital-based acute care as compared with those with no PC exposure (RR 0.69, 95% CI 0.66 to 0.71; RD 0.16, 95% CI 0.15 to 0.17). The association was strongest in cancer-specific analyses (RR 0.53, 95% CI 0.50 to 0.55; RD 0.31, 95% CI 0.29 to 0.33) and renal disease-specific analyses (RR 0.60, 95% CI 0.43 to 0.84; RD 0.22, 95% CI 0.11 to 0.34), but a~25% risk reduction was observed for each of heart disease, COPD, neurodegenerative diseases and stroke. Early specialist PC exposure was associated with reducing risk of four out of five individual indicators of high hospital-based acute care in the last 30 days of life, including ≥two ED visit,≥two hospital admission, any ICU admission and death in hospital.ConclusionsEarly specialist PC exposure reduced the risk of hospital-based acute care in the last 30 days of life for all chronic disease groups except dementia.

scholarly journals Development and validation of a prognostic index (BODEXS90) for mortality in stable chronic obstructive pulmonary disease

Pulmonology ◽  
2020 ◽  
Author(s):  
Rafael Golpe ◽  
Cristóbal Esteban ◽  
Juan Marco Figueira-GonÇalves ◽  
Carlos Antonio Amado-Diago ◽  
Nagore Blanco-Cid ◽  
...  
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Pulmonary Disease ◽  
Prognostic Index ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Development And Validation

scholarly journals Association between home insulation and hospital admission rates: retrospective cohort study using linked data from a national intervention programme

BMJ ◽  
2020 ◽  
pp. m4571 ◽  
Author(s):  
Caroline Fyfe ◽  
Lucy Telfar ◽  
Barnard ◽  
Philippa Howden-Chapman ◽  
Jeroen Douwes
Keyword(s):  
Cohort Study ◽  
Heart Disease ◽  
Confidence Interval ◽  
Hospital Admission ◽  
Retrospective Cohort ◽  
Rate Ratio ◽  
Hospital Admissions ◽  
Relative Rate ◽  
Intervention Programme ◽  
Admission Rates

Abstract Objectives To investigate whether retrofitting insulation into homes can reduce cold associated hospital admission rates among residents and to identify whether the effect varies between different groups within the population and by type of insulation. Design A quasi-experimental retrospective cohort study using linked datasets to evaluate a national intervention programme. Participants 994 317 residents of 204 405 houses who received an insulation subsidy through the Energy Efficiency and Conservation Authority Warm-up New Zealand: Heat Smart retrofit programme between July 2009 and June 2014. Main outcome measure A difference-in-difference approach was used to compare the change in hospital admissions of the study population post-insulation with the change in hospital admissions of the control population that did not receive the intervention over the same two timeframes. Relative rate ratios were used to compare the two groups. Results 234 873 hospital admissions occurred during the study period. Hospital admission rates after the intervention increased in the intervention and control groups for all population categories and conditions with the exception of acute hospital admissions among Pacific Peoples (rate ratio 0.94, 95% confidence interval 0.90 to 0.98), asthma (0.92, 0.86 to 0.99), cardiovascular disease (0.90, 0.88 to 0.93), and ischaemic heart disease for adults older than 65 years (0.79, 0.74 to 0.84). Post-intervention increases were, however, significantly lower (11%) in the intervention group compared with the control group (relative rate ratio 0.89, 95% confidence interval 0.88 to 0.90), representing 9.26 (95% confidence interval 9.05 to 9.47) fewer hospital admissions per 1000 in the intervention population. Effects were more pronounced for respiratory disease (0.85, 0.81 to 0.90), asthma in all age groups (0.80, 0.70 to 0.90), and ischaemic heart disease in those older than 65 years (0.75, 0.66 to 0.83). Conclusion This study showed that a national home insulation intervention was associated with reduced hospital admissions, supporting previous research, which found an improvement in self-reported health.

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