The Early HOSPITAL Score to Predict 30-Day Readmission Soon After Hospitalization: a Prospective Multicenter Study.

BACKGROUND: The simplified HOSPITAL score is an easy-to-use prediction model to identify patients at high risk of 30-day readmission before hospital discharge. An earlier stratification of this risk would allow more preparation time for transitional care interventions. OBJECTIVE: To assess whether the simplified HOSPITAL score would perform similarly by using hemoglobin and sodium level at the time of admission instead of discharge. DESIGN: Prospective national multicentric cohort study. PARTICIPANTS: In total, 934 consecutively discharged medical inpatients from internal general services. MAIN MEASURES: We measured the composite of the first unplanned readmission or death within 30 days after discharge of index admission and compared the performance of the simplified score with lab at discharge (simplified HOSPITAL score) and lab at admission (early HOSPITAL score) according to their discriminatory power (Area Under the Receiver Operating characteristic Curve (AUROC)) and the Net Reclassification Improvement (NRI). KEY RESULTS: During the study period, a total of 3239 patients were screened and 934 included. In total, 122 (13.2%) of them had a 30-day unplanned readmission or death. The simplified and the early versions of the HOSPITAL score both showed very good accuracy (Brier score 0.11, 95%CI 0.10-0.13). Their AUROC were 0.66 (95%CI 0.60-0.71), and 0.66 (95%CI 0.61-0.71), respectively, without a statistical difference (p value 0.79). Compared with the model at discharge, the model with lab at admission showed improvement in classification based on the continuous NRI (0.28; 95%CI 0.08 to 0.48; p value 0.004). CONCLUSION: The early HOSPITAL score performs, at least similarly, in identifying patients at high risk for 30-day unplanned readmission and allows a readmission risk stratification early during the hospital stay. Therefore, this new version offers a timely preparation of transition care interventions to the patients who may benefit the most.

[Transitional care from hospital to home: how to target the right population?] / Soins de transition entre l'hôpital et le domicile: pour quels patient-es ?

When patients are discharged from the hospital and return home, they are at risk of adverse events if the continuity of care is broken. So far, the evidence for transitional care models to reduce readmission rates has focused mainly on patients with a single condition. Based on this observation, we identified the population that may benefit the most from the development of a new transitional care model, as part of the INSTEAD project, by consensus between patients and professionals in hospitals and the community. To ensure continuity of care, it is necessary to consider the patients' perception, their understanding of the care plan and changes impacting the home care plan. Interprofessional collaboration is essential to achieve this.

Lorsqu'un-e patient-e retourne à domicile suite à une hospitalisation il-elle est souvent confronté-e à des événements indésirables si la continuité de ses soins n'est pas assurée. Jusqu'à ce jour, les modèles de soins de transition qui ont montré une diminution du taux de réadmission concernaient des patient-es ne souffrant que d'une seule pathologie. Partant de ce constat, nous avons identifié la population qui pourrait le plus bénéficier de soins de transition, dans le cadre du projet INSTEAD, par un consensus incluant d'une part des patient-es et, d'autre part, des professionnel-les hospitaliers et communautaires. Pour assurer la continuité des soins, il s'avère nécessaire de prendre en compte la perception de la personne, sa compréhension ainsi que les changements influençant son plan de soins à domicile. Pour ce faire, une collaboration interprofessionnelle est indispensable.

Drug-related readmissions in older hospitalized adults: External validation and updating of OPERAM DRA prediction tool.

BACKGROUND: Drug-related readmissions (DRAs) are defined as rehospitalizations with an adverse drug event as their main or significant contributory cause. DRAs represent a major adverse health burden for older patients. A prediction model which identified older hospitalized patients at high risk of a DRA <1 year was previously developed using the OPERAM trial cohort, a European cluster randomized controlled trial including older hospitalized patients with multimorbidity and polypharmacy. This study has performed external validation and updated the prediction model consequently. METHODS: The MedBridge trial cohort (a multicenter cluster randomized crossover trial performed in Sweden) was used as a validation cohort. It consisted of 2516 hospitalized patients aged ≥65 years. Model performance was assessed by: (1) discriminative power, assessed by the C-statistic with a 95% confidence interval (CI); (2) calibration, assessed by visual examination of the calibration plot and use of the Hosmer-Lemeshow goodness-of-fit test; and (3) overall accuracy, assessed by the scaled Brier score. Several updating methods were carried out to improve model performance. RESULTS: In total, 2516 older patients were included in the validation cohort, of whom 582 (23.1%) experienced a DRA <1 year. In the validation cohort, the original model showed a good overall accuracy (scaled Brier score 0.03), but discrimination was moderate (C-statistic 0.62 [95% CI 0.59-0.64]), and calibration showed underestimation of risks. In the final updated model, the predictor "cirrhosis with portal hypertension" was removed and "polypharmacy" was added. This improved the model's discriminative capability to a C-statistic of 0.64 (95% CI 0.59-0.70) and enhanced calibration plots. Overall accuracy remained good. CONCLUSIONS: The updated OPERAM DRA prediction model may be a useful tool in clinical practice to estimate the risk of DRAs in older hospitalized patients subsequent to discharge. Our efforts lay the groundwork for the future development of models with even better performance.

Factors associated with one-year mortality after hospital discharge: A multicenter prospective cohort study.

OBJECTIVES: 1) To identify predictors of one-year mortality in hospitalized medical patients using factors available during their hospital stay. 2) To evaluate whether healthcare system use within 30 days of hospital discharge is associated with one-year mortality. STUDY DESIGN AND SETTING: This prospective, observational study included adult patients from four mid-sized hospital general internal medicine units. During index hospitalization, we retrieved patient characteristics, including demographic and socioeconomic indicators, diagnoses, and early simplified HOSPITAL scores from electronic health records and patient interviews. Data on healthcare system use was collected using telephone interviews 30 days after discharge. Survival status at one year was collected by telephone and from health records. We used a univariable analysis including variables available from the hospitalization and 30-day post-discharge periods. We then performed multivariable analyses with one model using index hospitalization data and one using 30-day post-discharge data. RESULTS: Of 934 patients, 123 (13.2%; 95% CI 11.0-15.4%) were readmitted or died within 30 days. Of 814 patients whose primary outcome was available, 108 died (13.3%) within one year. Using factors obtained during hospitalization, the early simplified HOSPITAL score (OR 1.50; 95% CI 1.31-1.71; P < 0.001) and not living at home (OR 4.0; 95% CI 1.8-8.3; P < 0.001) were predictors of one-year mortality. Using 30-day post-discharge predictors, hospital readmission was significantly associated with one-year mortality (OR 4.81; 95% CI 2.77-8.33; P < 0.001). SIGNIFICANCE: Factors predicting one-year mortality were a high early simplified HOSPITAL score, not living at home, and a 30-day unplanned readmission.

Effects of a Multimodal Transitional Care Intervention in Patients at High Risk of Readmission: The TARGET-READ Randomized Clinical Trial.

Importance: Hospital readmissions are frequent, costly, and sometimes preventable. Although these issues have been well publicized and incentives to reduce them introduced, the best interventions for reducing readmissions remain unclear. Objectives: To evaluate the effects of a multimodal transitional care intervention targeting patients at high risk of hospital readmission on the composite outcome of 30-day unplanned readmission or death. Design, Setting, and Participants: A single-blinded, multicenter randomized clinical trial was conducted from April 2018 to January 2020, with a 30-day follow-up in 4 medium-to-large-sized teaching hospitals in Switzerland. Participants were consecutive patients discharged from general internal medicine wards and at higher risk of unplanned readmission based on their simplified HOSPITAL score (≥4 points). Data were analyzed between April and September 2022. Interventions: The intervention group underwent systematic medication reconciliation, a 15-minute patient education session with teach-back, a planned first follow-up visit with their primary care physician, and postdischarge follow-up telephone calls from the study team at 3 and 14 days. The control group received usual care from their hospitalist, plus a 1-page standard study information sheet. Main Outcomes and Measures: Thirty-day postdischarge unplanned readmission or death. Results: A total of 1386 patients were included with a mean (SD) age of 72 (14) years; 712 (51%) were male. The composite outcome of 30-day unplanned readmission or death was 21% (95% CI, 18% to 24%) in the intervention group and 19% (95% CI, 17% to 22%) in the control group. The intention-to-treat analysis risk difference was 1.7% (95% CI, -2.5% to 5.9%; P = .44). There was no evidence of any intervention effects on time to unplanned readmission or death, postdischarge health care use, patient satisfaction with the quality of their care transition, or readmission costs. Conclusions and Relevance: In this randomized clinical trial, use of a standardized multimodal care transition intervention targeting higher-risk patients did not significantly decrease the risks of 30-day postdischarge unplanned readmission or death; it demonstrated the difficulties in preventing hospital readmissions, even when multimodal interventions specifically target higher-risk patients. Trial Registration: ClinicalTrials.gov Identifier: NCT03496896.

Effectiveness of Transition Care Intervention Targeted to High-Risk Patients to Reduce Readmissions: Study Protocol for the TARGET-READ Multicenter Randomized-Controlled Trial.

Hospital readmissions within 30 days represent a burden for the patients and the entire health care system. Improving the care around hospital discharge period could decrease the risk of avoidable readmissions. We describe the methods of a trial that aims to evaluate the effect of a structured multimodal transitional care intervention targeted to higher-risk medical patients on 30-day unplanned readmissions and death. The TARGET-READ study is an investigator-initiated, pragmatic single-blinded randomized multicenter controlled trial with two parallel groups. We include all adult patients at risk of hospital readmission based on a simplified HOSPITAL score of ≥4 who are discharged home or nursing home after a hospital stay of one day or more in the department of medicine of the four participating hospitals. The patients randomized to the intervention group will receive a pre-discharge intervention by a study nurse with patient education, medication reconciliation, and follow-up appointment with their referring physician. They will receive short follow-up phone calls at 3 and 14 days after discharge to ensure medication adherence and follow-up by the ambulatory care physician. A blind study nurse will collect outcomes at 1 month by phone call interview. The control group will receive usual care. The TARGET-READ study aims to increase the knowledge about the efficacy of a bundled intervention aimed at reducing 30-day hospital readmission or death in higher-risk medical patients.

Association of CT-based diagnosis of sarcopenia with prognosis and treatment response in patients at risk of malnutrition - A secondary analysis of the Effect of early nutritional support on Frailty, Functional Outcomes, and Recovery of malnourished medical inpatients Trial (EFFORT) trial.

BACKGROUND & AIM: CT-derived measures of muscle mass may help to identify patients with sarcopenia. We investigated the prognostic significance of CT-derived sarcopenia and muscle attenuation with nutritional markers, clinical outcomes and response to nutritional support in medical in-patients at nutritional risk. METHOD: Within this secondary analysis of the randomized-controlled Effect of early nutritional support on Frailty, Functional Outcomes, and Recovery of malnourished medical inpatients Trial (EFFORT) comparing individualized nutritional support with usual care nutrition in medical inpatients, we investigated associations of CT-based sarcopenia and muscle attenuation at the level L3 with different nutritional and clinical outcomes, and the response to the nutritional intervention. The primary composite endpoint was adverse clinical outcome within 30 days of hospital admission. RESULTS: We included 573 of 2028 EFFORT patients with available CT scans, of which 68.4% met the CT-based definition of sarcopenia and 72.9% had low muscle attenuation. In multivariate analysis, low skeletal muscle index was associated with higher nutritional risk (coefficient per NRS class -0.94 (95%CI -1.87 to -0.01) p = 0.049) and higher risk for adverse clinical outcomes (adjusted odds ratio 1.59 (95% CI 1.06 to 2.38), p = 0.024). Low muscle attenuation was also associated with adverse clinical outcome (adjusted odds ratio 1.67 (95%CI 1.08 to 2.58), p = 0.02). Nutritional support tended to be more effective in reducing mortality in non-sarcopenic patients compared to patients with CT-based sarcopenia (p for interaction 0.058). CONCLUSIONS: Within a population of medical patients at nutritional risk, CT-based sarcopenia and muscle attenuation were associated with several nutritional parameters and predicted adverse clinical outcomes. Information from CT scans, thus may help to better characterize these patients, and may be helpful in guiding therapeutic interventions.

Barriers and facilitators to mobility of patients hospitalised on an acute medical ward: a systematic review.

BACKGROUND: low patient mobility is common during hospitalisation and is associated with adverse outcomes. To change practice, interventions should address barriers and facilitators to mobility. Our aim was to systematically review the literature to provide a synthesised overview of patient-, health care professional (HCP)- and environment-/system-related barriers and facilitators to mobility of patients hospitalised on an acute care medical ward. METHODS: we searched Medline, Embase, PsycInfo, Web of Science Core Collection, Cochrane CENTRAL, CINHAHL and Google Scholar (inception to 18 October 2021) to identify studies reporting barriers and/or facilitators to mobility of adults hospitalised on an acute medical ward. We applied a deductive and inductive thematic analysis to classify barriers and facilitators into themes and subthemes relevant for clinical practice. RESULTS: among 26 studies (16 qualitative, 7 quantitative and 3 mixed methods), barriers and facilitators were categorised into 10 themes: patient situation, knowledge, beliefs, experiences, intentions, emotions, social influences, role/identity, implementation/organisation and environment/resources. Barriers included patient characteristics (e.g. impaired cognitive/physical status) and symptoms, HCPs prioritising other tasks over mobility, HCPs labelling patients as 'too sick', fear of injury, lack of time, lack of clarity about responsibility, patient medical devices and non-encouraging environment. Facilitators included knowledge of mobility importance, HCP skills, interdisciplinarity, documentation and unit expectations, encouraging staff, goal individualisation, activity programme, family/visitor/volunteer support and availability of equipment. CONCLUSION: this synthesised overview of patient-, HCP- and environment-/system-related barriers and facilitators to mobility of adults hospitalised on an acute medical ward can help researchers and clinicians focus on what can realistically be influenced to improve mobility. SYSTEMATIC REVIEW REGISTRATION: PROSPERO, CRD42021285954.

Comparison of 6 Mortality Risk Scores for Prediction of 1-Year Mortality Risk in Older Adults With Multimorbidity.

Importance: The most appropriate therapy for older adults with multimorbidity may depend on life expectancy (ie, mortality risk), and several scores have been developed to predict 1-year mortality risk. However, often, these mortality risk scores have not been externally validated in large sample sizes, and a head-to-head comparison in a prospective contemporary cohort is lacking. Objective: To prospectively compare the performance of 6 scores in predicting the 1-year mortality risk in hospitalized older adults with multimorbidity. Design, Setting, and Participants: This prognostic study analyzed data of participants in the OPERAM (Optimising Therapy to Prevent Avoidable Hospital Admissions in Multimorbid Older People) trial, which was conducted between December 1, 2016, and October 31, 2018, in surgical and nonsurgical departments of 4 university-based hospitals in Louvain, Belgium; Utrecht, the Netherlands; Cork, Republic of Ireland; and Bern, Switzerland. Eligible participants in the OPERAM trial had multimorbidity (≥3 coexisting chronic diseases), were aged 70 years or older, had polypharmacy (≥5 long-term medications), and were admitted to a participating ward. Data were analyzed from April 1 to September 30, 2020. Main Outcomes and Measures: The outcome of interest was any-cause death occurring in the first year of inclusion in the OPERAM trial. Overall performance, discrimination, and calibration of the following 6 scores were assessed: Burden of Illness Score for Elderly Persons, CARING (Cancer, Admissions ≥2, Residence in a nursing home, Intensive care unit admit with multiorgan failure, ≥2 Noncancer hospice guidelines) Criteria, Charlson Comorbidity Index, Gagné Index, Levine Index, and Walter Index. These scores were assessed using the following measures: Brier score (0 indicates perfect overall performance and 0.25 indicates a noninformative model); C-statistic and 95% CI; Hosmer-Lemeshow goodness-of-fit test and calibration plots; and sensitivity, specificity, and positive and negative predictive values. Results: The 1879 patients in the study had a median (IQR) age of 79 (74-84) years and 835 were women (44.4%). The median (IQR) number of chronic diseases was 11 (8-16). Within 1 year, 375 participants (20.0%) died. Brier scores ranged from 0.16 (Gagné Index) to 0.24 (Burden of Illness Score for Elderly Persons). C-statistic values ranged from 0.62 (95% CI, 0.59-0.65) for Charlson Comorbidity Index to 0.69 (95% CI, 0.66-0.72) for the Walter Index. Calibration was good for the Gagné Index and moderate for other mortality risk scores. Conclusions and Relevance: Results of this prognostic study suggest that all 6 of the 1-year mortality risk scores examined had moderate prognostic performance, discriminatory power, and calibration in a large cohort of hospitalized older adults with multimorbidity. Overall, none of these mortality risk scores outperformed the others, and thus none could be recommended for use in daily clinical practice.

Prospective validation of five malnutrition screening and assessment instruments among medical inpatients: Secondary analysis of a randomized clinical trial.

BACKGROUND & AIMS: Screening for malnutrition upon hospital admission is the first crucial step for proper nutritional assessment and treatment. While several nutritional screening and assessment instruments exist, there is a lack of head-to-head validation of these instruments. We studied the ability of five different nutrition screening and assessment instruments to predict 1-year mortality and response to nutritional treatment in participants of the EFFORT randomized trial. METHODS: In this secondary analysis of a Swiss-wide multicenter, randomized clinical trial comparing individualized nutritional support with usual care nutrition in medical inpatients, we prospectively classified patients as low, intermediate, and high nutritional risk based on five nutritional screening and assessment instruments (NRS 2002, SGA, SNAQ, MNA and MUST). RESULTS: Overall mortality at 1-year in the 1866 included patients was 30.4%. There were significant correlations and a significant concordance between all instruments with r-values ranging from 0.23 to 0.55 and kappa values ranging from 0.10 to 0.36. While high nutritional risk was associated with higher mortality in all instruments, SGA and MNA showed the strongest association with adjusted odds ratios of 3.17 (95%CI, 2.18 to 4.61, p < 0.001) and 3.45 (95%CI, 2.28 to 5.22, p < 0.001). When comparing mortality in intervention group patients to control group patients stratified by severity of malnutrition, there was overall no clear trend towards more benefit in patients with more severe malnutrition, with NRS 2002 and SGA showing the most pronounced relationship between the severity of malnutrition and reduction in mortality as a response to nutritional support. CONCLUSION: Among all five screening and assessment instruments, higher nutritional risk was associated with higher risk for mortality and adverse clinical outcome, but not with more or less treatment response from nutritional support with differences among scores. Adding more specific parameters to these instruments is important when using them to decide for or against nutritional support interventions in an individual patient. TRIAL REGISTRATION: ClinicalTrials.gov NCT02517476.

Challenges in the transition from resident to attending physician in general internal medicine: a multicenter qualitative study.

BACKGROUND: The attending physician in general internal medicine (GIM) guarantees comprehensive care for persons with complex and/or multiple diseases. Attendings from other medical specialties often report that transitioning from resident to attending is burdensome and stressful. We set out to identify the specific challenges of newly appointed attendings in GIM and identify measures that help residents better prepare to meet these challenges. METHODS: We explored the perceptions of 35 residents, attendings, and department heads in GIM through focus group discussions and semi-structured interviews. We took a thematic approach to qualitatively analyze this data. RESULTS: Our analysis revealed four key challenges: 1) Embracing a holistic, patient centered perspective in a multidisciplinary environment; 2) Decision making under conditions of uncertainty; 3) Balancing the need for patient safety with the need to foster a learning environment for residents; and 4) Taking on a leader's role and orchestrating an interprofessional team of health care professionals. Newly appointed attendings required extensive practical experience to adapt to their new roles. Most attendings did not receive regular, structured, professional coaching during their transition, but those who did found it very helpful. CONCLUSIONS: Newly appointed attending physician in GIM face a number of critical challenges that are in part specific to the field of GIM. Further studies should investigate whether the availability of a mentor as well as conscious assignment of a series of increasingly complex tasks during residency by clinical supervisors will facilitate the transition from resident to attending.

Definition of patient complexity in adults: A narrative review.

Background: Better identification of complex patients could help to improve their care. However, the definition of patient complexity itself is far from obvious. We conducted a narrative review to identify, describe, and synthesize the definitions of patient complexity used in the last 25 years. Methods: We searched PubMed for articles published in English between January 1995 and September 2020, defining patient complexity. We extended the search to the references of the included articles. We assessed the domains presented in the definitions, and classified the definitions as based on (1) medical aspects (e.g., number of conditions) or (2) medical and/or non-medical aspects (e.g., socio-economic status). We assessed whether the definition was based on a tool (e.g., index) or conceptual model. Results: Among 83 articles, there was marked heterogeneity in the patient complexity definitions. Domains contributing to complexity included health, demographics, behavior, socio-economic factors, healthcare system, medical decision-making, and environment. Patient complexity was defined according to medical aspects in 30 (36.1%) articles, and to medical and/or non-medical aspects in 53 (63.9%) articles. A tool was used in 36 (43.4%) articles, and a conceptual model in seven (8.4%) articles. Conclusion: A consensus concerning the definition of patient complexity was lacking. Most definitions incorporated non-medical factors in the definition, underlining the importance of accounting not only for medical but also for non-medical aspects, as well as for their interrelationship.

HOSPITAL Score and LACE Index to Predict Mortality in Multimorbid Older Patients.

BACKGROUND: Estimating life expectancy of older adults informs whether to pursue future investigation and therapy. Several models to predict mortality have been developed but often require data not immediately available during routine clinical care. The HOSPITAL score and the LACE index were previously validated to predict 30-day readmissions but may also help to assess mortality risk. We assessed their performance to predict 1-year and 30-day mortality in hospitalized older multimorbid patients with polypharmacy. METHODS: We calculated the HOSPITAL score and LACE index in patients from the OPERAM (OPtimising thERapy to prevent Avoidable hospital admissions in the Multimorbid elderly) trial (patients aged ≥ 70 years with multimorbidity and polypharmacy, admitted to hospital across four European countries in 2016-2018). Our primary and secondary outcomes were 1-year and 30-day mortality. We assessed the overall accuracy (scaled Brier score, the lower the better), calibration (predicted/observed proportions), and discrimination (C-statistic) of the models. RESULTS: Within 1 year, 375/1879 (20.0%) patients had died, including 94 deaths within 30 days. The overall accuracy was good and similar for both models (scaled Brier score 0.01-0.08). The C-statistics were identical for both models (0.69 for 1-year mortality, p = 0.81; 0.66 for 30-day mortality, p = 0.94). Calibration showed well-matching predicted/observed proportions. CONCLUSION: The HOSPITAL score and LACE index showed similar performance to predict 1-year and 30-day mortality in older multimorbid patients with polypharmacy. Their overall accuracy was good, their discrimination low to moderate, and the calibration good. These simple tools may help predict older multimorbid patients' mortality after hospitalization, which may inform post-hospitalization intensity of care.

Validation of modified GLIM criteria to predict adverse clinical outcome and response to nutritional treatment: A secondary analysis of a randomized clinical trial.

BACKGROUND & AIMS: The Global Leadership Initiative on Malnutrition (GLIM) recently suggested specific criteria to standardize the diagnosis of malnutrition. There is need for validation of these criteria regarding response to nutrition treatment. Our aim was to validate modified GLIM (mGLIM) criteria among medical inpatients at risk of disease related malnutrition for prediction of outcome and response to nutritional therapy. METHODS: This is a secondary analysis of the Effect of Early Nutritional Support on Frailty, Functional Outcomes, and Recovery of Malnourished Medical Inpatients Trial (EFFORT), a multicenter randomized controlled trial conducted between April 2014 and February 2018. Adult medical inpatients at nutritional risk (Nutrition Risk Score 2002 ≥ 3 points) were randomly assigned to receive nutritional therapy according to an algorithm based on individualized nutritional requirements (intervention group) or standard hospital food (control group). We included all participants with available information regarding mGLIM criteria. The primary outcome was adverse clinical outcome, which was a composite of 30-day all-cause mortality, ICU-admission, rehospitalization rate, major complications and decline in functional status. RESULTS: Of 1917 eligible participants at nutritional risk, 1181 (61.6%) met the diagnosis of malnutrition based on mGLIM criteria. The incidence of adverse clinical outcome was significantly higher in mGLIM-positive participants compared with mGLIM-negative participants [330/1181 (27.9%) versus 140/736 (19.0%); multivariable adjusted odds ratio [OR] 1.53; 95% CI 1.22-1.93; p < 0.001]. Regarding the effect of nutritional therapy, the reduction in adverse clinical outcomes was higher in mGLIM-positive participants [180/581 (31.0%) vs. 150/600 (25.0%), OR 0.69; 95% CI 0.53-0.9, p = 0.007], compared with mGLIM-negative participants [75/379 (19.8%) versus 65/357 (18.2%), OR 0.95; 95% CI 0.65-1.40, p = 0.797], a finding that was, however, not significant in interaction analysis (p for interaction = 0.217). CONCLUSION: Data from this secondary analysis of a multicenter randomized trial involving medical inpatients at nutritional risk validate the strong prognostic value of mGLIM criteria regarding adverse clinical outcomes and other long-term outcomes. However, further research is needed to improve the ability of GLIM criteria to predict therapeutic response to nutritional interventions. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02517476.

Admission serum albumin concentrations and response to nutritional therapy in hospitalised patients at malnutrition risk: Secondary analysis of a randomised clinical trial.

BACKGROUND: Historically, admission serum albumin concentrations have been considered useful biochemical markers for nutrition assessment. However, there is a lack of randomised trial data investigating whether low albumin concentrations are helpful for identifying patients benefitting from nutritional support. METHODS: This study was a secondary analysis of the EFFORT trial, a Swiss-wide multicentre, randomised controlled trial comparing individualised nutritional support with usual care nutrition in medical inpatients from April 1, 2014, to February 1, 2018. 1389 of 2028 patients at nutritional risk with available albumin concentrations on admission were included. The primary endpoint was all-cause mortality within 30 and 180 days. Patients were stratified into groups of low or normal albumin based on the albumin cut-off of 30 g/L. ClinicalTrials.gov number, NCT02517476. FINDINGS: 1389 patients (mean age, 73.1 (SD 3.5) years; 747 (53.8%) men) were included and 676 (48.7%) had low serum albumin concentrations at admission (<30 g/L). Mortality at 180 days was significantly increased in the low albumin group compared with patients with normal albumin concentrations (219/676 (32.4%) vs. 162/713 (22.7%), fully adjusted HR 1.4, 95%CI 1.11 to 1.77, p = 0.005]. Effects of nutritional support on 30-day mortality were similar for patients with low compared to patients with normal albumin concentrations (HR 0.68, 95%CI 0.44 to 1.05 vs. HR 0.70, 95%CI 0.41 to 1.20), with no evidence for a subgroup effect (p for interaction=0.97). INTERPRETATION: Based on this secondary analysis of a randomised trial, low admission serum albumin concentrations in hospitalised, non-critically ill, medical patients at nutritional risk had prognostic implications and indicated higher mortality risk but were not helpful in selecting patients for nutritional interventions. FUNDING: The Swiss National Science Foundation (SNSF) (PP00P3_150531) and the Research Council of the Kantonsspital Aarau (1410.000.058 and 1410.000.044) provided funding for the EFFORT trial.

Predictors of 1-year drug-related admissions in older multimorbid hospitalized adults.

BACKGROUND: Identifying patients at high risk of drug-related hospital admission (DRA) may help to efficiently target preventive interventions. We developed a score to predict DRAs in older patients with multimorbidity and polypharmacy. METHODS: We used participants from the multicenter European OPERAM trial ("Optimising PharmacothERapy in the Mutlimorbid Elderly"). We assessed the association between easily identifiable predictors and 1-year DRAs by univariable logistic regression. Variables with p-value< 0.20 were taken forward to backward regression. We retained all variables with p < 0.05 in the model. We assessed the C-statistic, calibration (observed/predicted proportions), and overall accuracy (scaled Brier score, <0.25 indicating a useful model) of the score, and internally validated it by tenfold cross-validation. RESULTS: Within 1 year, 435/1879 (23.2%) patients (mean age 79.4 years) had a DRA. The score included seven variables: previous hospitalizations, non-elective admission, hypertension, cirrhosis with portal hypertension, chronic kidney disease, diuretic, oral corticosteroid. The C-statistic was 0.64 (95% CI 0.61-0.67). Patients with <1 point had a 12.4% predicted and observed risk of DRA, while those with >3 points had a 40.4% predicted and 38.9% observed risk of DRA. The scaled Brier score was 0.05. Calibration showed an adequate match between predicted and observed proportions. CONCLUSION: Comorbidities related to drug metabolism, specific medications, non-elective admission, and a history of hospitalization, were associated with a higher risk of DRA. Awareness of these associations and the score we developed may help identify patients most likely to benefit from preventive interventions.

Associations between post-discharge medical consultations and 30-day unplanned hospital readmission: A prospective observational cohort study.

BACKGROUND: The period following hospital discharge is one of significant vulnerability. Little is known about the relationship between post-discharge healthcare use and the risk of readmission. OBJECTIVES: To explore associations between medical consultations and other healthcare use parameters and the risk of 30-day unplanned hospital readmission. METHODS: Between July 2017 and March 2018, we monitored all adult internal medicine patients for 30 days after their discharge from four mid-sized hospitals. Using follow-up telephone calls, we assessed their post-discharge healthcare use: consultations with general practitioners (GPs) and specialist physicians, emergency room (ER) visits, and home visits by nurses. The binary outcome was defined as any unplanned hospital readmission within 30 days of discharge, and this was analyzed using logistic regression. RESULTS: Of 934 patients discharged, 111 (12%) experienced at least one unplanned hospital readmission within 30 days. Attending at least one GP consultation decreased the odds of readmission by half (adjusted OR: 0.5; 95%CI: 0.3-0.7), whereas attending at least one specialist consultation doubled those odds (aOR: 2.0; 95%CI: 1.2-3.3). GP consultations also reduced the odds of the combined risk of an ER visit or unplanned hospital readmission (aOR: 0.5; 95%CI: 0.3-0.7). ER visits were also associated with a higher readmission risk after adjusting for confounding factors (aOR: 10.0; 95%CI: 6.0-16.8). CONCLUSION: GP consultations were associated with fewer ER visits and unplanned hospital readmissions.

Age and Sex Specific Prevalence of Clinical and Screen-Detected Atrial Fibrillation in Hospitalized Patients.

BACKGROUND: The prevalence of atrial fibrillation (AF) is high in older patients. The present study aimed to estimate the age and sex specific prevalence of clinical and screen-detected atrial fibrillation (AF) in hospitalized patients. METHODS: The STAR-FIB cohort study was a prospective cohort study recruiting participants from a large source population of hospitalized patients aged 65-84 years. The estimated size of the source population was 26,035 (95% CI 25,918-26,152), and 795 consenting patients without clinical AF were included in the cohort study after stratification by sex and age (49.2% females; mean age 74.7 years). Patients in the cohort study underwent three seven-day Holter ECGs in intervals of two months to screen for AF. RESULTS: In the source population, the estimated prevalence of clinical AF was 22.2% (95% CI 18.4-26.1), 23.8% for males (95% CI 20.9-26.6) and 19.8% for females (95% CI 17.3-22.4; p for difference between sexes, 0.004). There was a linear trend for an increase in the prevalence of clinical AF with increasing age, overall and in both sexes. In the cohort study, AF was newly diagnosed in 38 patients, for an estimated prevalence of screen-detected AF of 4.9% overall (95% CI 3.3-6.6), 5.5% in males (95% CI 3.2-7.8) and 4.0% in females (95% CI 2.0-6.0; p for difference between sexes, 0.041). The estimated prevalence of screen-detected AF in the source population was 3.8% overall, 4.2% in males and 3.2% in females. CONCLUSION: In a large hospital-based patient population aged 65-84 years, the prevalence of clinical AF and of screen-detected AF was 22.2% and 3.8%, respectively, and significantly higher in males than females.

The impact of nutritional support on malnourished inpatients with aging-related vulnerability.

OBJECTIVES: Malnutrition is highly prevalent in patients with aging-related vulnerability defined by very old age (≥80 y), physical frailty or cognitive impairment, and increases the risks for morbidity and mortality. The effects of individualized nutritional support for patients with aging-related vulnerability in the acute hospital setting on mortality and other clinical outcomes remains understudied. METHODS: For this secondary analysis of the randomized-controlled Effect of Early Nutritional Support on Frailty, Functional Outcomes, and Recovery of Malnourished Medical Inpatients Trial (EFFORT), we analyzed data of patients at a nutritional risk (Nutritional Risk Screening 2002 score ≥3 points) with aging-related vulnerability, randomized to receive protocol-guided individualized nutritional support to reach specific protein and energy goals (intervention group) or routine hospital food (control group). The primary endpoint was all-cause 30-d mortality. RESULTS: Of the 881 patients with aging-related vulnerability, 23.4% presented with a frailty syndrome, 81.8% were age ≥80 y and 15.3% showed cognitive impairment. Patients with aging-related vulnerability receiving individualized nutritional support compared with routine hospital food showed a >50% reduction in the risk of 30-day mortality (60 of 442 [13.6%] versus 31 of 439 [7.1%]; odds ratio: 0.48; 95% confidence interval, 0.31-0.76; P = 0.002). Significant improvements were also found for long-term mortality at 180 days, as well as functional outcomes and quality of life measures. CONCLUSIONS: Malnourished patients with aging-related vulnerability show a significant and clinically relevant reduction in the risk of mortality and other adverse clinical outcomes after individualized in-hospital nutritional support compared to routine hospital nutrition. These data support the early screening of patients with aging-related vulnerability for nutritional risk, followed by a nutritional assessment and implementation of individualized nutritional interventions.

Individualized Nutritional Support for Hospitalized Patients With Chronic Heart Failure.

BACKGROUND: Deterioration of nutritional status during hospitalization in patients with chronic heart failure increases mortality. Whether nutritional support during hospitalization reduces these risks, or on the contrary, may be harmful due to an increase in salt and fluid intake, remains unclear. OBJECTIVES: The purpose of this trial was to study the effect of nutritional support on mortality in patients hospitalized with chronic heart failure who are at nutritional risk. METHODS: A total of 645 patients with chronic heart failure (36% [n = 234] with acute decompensation) participated in the investigator-initiated, open-label EFFORT (Effect of early nutritional support on Frailty, Functional Outcomes and Recovery of malnourished medical inpatients) trial. Patients were randomized to protocol-guided individualized nutritional support to reach energy, protein, and micronutrient goals (intervention group) or standard hospital food (control group). The primary endpoint was all-cause mortality at 30 days. RESULTS: Mortality over 180 days increased with higher severity of malnutrition (odds ratio per 1-point increase in Nutritional Risk Screening 2002 score: 1.65; 95% confidence interval [CI]: 1.21 to 2.24; p = 0.001). By 30 days, 27 of 321 intervention group patients (8.4%) died, compared with 48 of 324 (14.8%) control group patients (odds ratio: 0.44; 95% CI: 0.26 to 0.75; p = 0.002). Patients at high nutritional risk showed the most benefit from nutritional support. Mortality effects remained significant at 180-day follow-up. Intervention group patients also had a lower risk for major cardiovascular events at 30 days (17.4% vs. 26.9%; odds ratio: 0.50; 95% CI: 0.34 to 0.75; p = 0.001). CONCLUSIONS: Among hospitalized patients with chronic heart failure at high nutritional risk, individualized nutritional support reduced the risk for mortality and major cardiovascular events compared with standard hospital food. These data support malnutrition screening upon hospital admission followed by an individualized nutritional support strategy in this vulnerable patient population. (Effect of Early Nutritional Therapy on Frailty, Functional Outcomes and Recovery of Undernourished Medical Inpatients Trial [EFFORT]; NCT02517476).