Predictive Validity of the Academy of Nutrition and Dietetics/American Society for Parental Nutrition Indicators to Diagnose Malnutrition and the Screening Tool for Risk on Nutritional Status and Growth among Hospitalized Children Relative to Medical Outcomes.

OBJECTIVE: To evaluate predictive validity of the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition Indicators to diagnose pediatric malnutrition (AAIMp) and the Screening Tool for Risk on Nutritional Status and Growth (STRONGkids) in regard to pediatric patient outcomes in US hospitals. STUDY DESIGN: A prospective cohort study (Clinical Trial Registry: NCT03928548) was completed from August 2019 through January 2023 with 27 pediatric hospitals or units from 18 US states and Washington DC. RESULTS: Three hundred and forty-five children were enrolled in the cohort (n = 188 in the AAIMp validation subgroup). There were no significant differences in the incidence of emergency department visits and hospital readmissions, hospital length of stay (LOS), or health care resource utilization for children diagnosed with mild, moderate, or severe malnutrition using the AAIMp tool compared with children with no malnutrition diagnosis. The STRONGkids tool significantly predicted more emergency department visits and hospital readmissions for children at moderate and high malnutrition risk (moderate risk - incidence rate ratio 1.65, 95% CI: 1.09, 2.49, P = .018; high risk - incidence rate ratio 1.64, 95% CI: 1.05, 2.56, P = .028) and longer LOS (43.8% longer LOS, 95% CI: 5.2%, 96.6%, P = .023) for children at high risk compared with children at low risk after adjusting for patient characteristics. CONCLUSIONS: Malnutrition risk based on the STRONGkids tool predicted poor medical outcomes in hospitalized US children; the same relationship was not observed for a malnutrition diagnosis based on the AAIMp tool.

Risk factors for readmission after a cholecystectomy: a case-control study.

OBJECTIVE: The aim of this study was to assess the risk factors associated with 30-day hospital readmissions after a cholecystectomy. METHODS: We conducted a case-control study, with data obtained from UC-Christus from Santiago, Chile. All patients who underwent a cholecystectomy between January 2015 and December 2019 were included in the study. We identified all patients readmitted after a cholecystectomy and compared them with a randomized control group. Univariate and multivariate analyses were conducted to identify risk factors. RESULTS: Of the 4866 cholecystectomies performed between 2015 and 2019, 79 patients presented 30-day hospital readmission after the surgical procedure (1.6%). We identified as risk factors for readmission in the univariate analysis the presence of a solid tumor at the moment of cholecystectomy (OR = 7.58), high pre-operative direct bilirubin (OR = 2.52), high pre-operative alkaline phosphatase (OR = 3.25), emergency admission (OR = 2.04), choledocholithiasis on admission (OR = 4.34), additional surgical procedure during the cholecystectomy (OR = 4.12), and post-operative complications. In the multivariate analysis, the performance of an additional surgical procedure during cholecystectomy was statistically significant (OR = 4.24). CONCLUSION: Performing an additional surgical procedure during cholecystectomy was identified as a risk factor associated with 30-day hospital readmission.

OBJETIVO: El objetivo de este estudio fue evaluar los factores de riesgo asociados al reingreso hospitalario en los primeros 30 días post colecistectomía. MÉTODOS: Estudio de casos-controles con datos obtenidos del Hospital Clínico de la UC-Christus, Santiago, Chile. Se ­incluyeron las colecistectomías realizadas entre los años 2015-2019. Se consideraron como casos aquellos pacientes que reingresaron en los 30 primeros días posterior a una colecistectomía. Se realizó un análisis univariado y multivariado de diferentes posibles factores de riesgo. RESULTADOS: De un total de 4866 colecistectomías, 79 pacientes presentaron reingreso hospitalario. Los resultados estadísticamente significativos en el análisis univariado fueron; tumor sólido al momento de la colecistectomía (OR = 7.58) bilirrubina directa preoperatoria alterada (OR = 2.52), fosfatasa alcalina preoperatoria alterada (OR = 3.25), ingreso de urgencia (OR = 2.04), coledocolitiasis al ingreso (OR = 4.34) realización de otros procedimientos (OR = 4.12) y complicaciones postoperatorias. En el análisis multivariado sólo la realización de otro procedimiento durante la colecistectomía fue estadísticamente significativa (OR = 4.24). CONCLUSIÓN: La realización de otros procedimientos durante la colecistectomía es un factor de riesgo de reingreso hospitalario en los 30 días posteriores a la colecistectomía.

Thirty-day readmissions in children with complex chronic conditions.

INTRODUCTION: The rate of hospital readmission within 30 days of discharge is a quality indicator in health care. Paediatric patients with complex chronic conditions have high readmission rates. Failure in the transition between hospital and home care could explain this phenomenon. OBJECTIVES: To estimate the incidence rate of 30-day hospital readmission in paediatric patients with complex chronic conditions, estimate how many are potentially preventable and explore factors associated with readmission. MATERIALS AND METHOD: Cohort study including hospitalised patients with complex chronic conditions aged 1 month to 18 years. Patients with cancer or with congenital heart disease requiring surgical correction were excluded. The outcomes assessed were 30-day readmission rate and potentially preventable readmissions. We analysed sociodemographic, geographic, clinical and transition to home care characteristics as factors potentially associated with readmission. RESULTS: The study included 171 hospitalizations, and 28 patients were readmitted within 30 days (16.4%; 95% CI, 11.6%-22.7%). Of the 28 readmissions, 23 were potentially preventable (82.1%; 95% CI, 64.4%-92.1%). Respiratory disease was associated with a higher probability of readmission. There was no association between 30-day readmission and the characteristics of the transition to home care. CONCLUSIONS: The 30-day readmission rate in patients with complex chronic disease was 16.4%, and 82.1% of readmissions were potentially preventable. Respiratory disease was the only identified risk factor for 30-day readmission.

Machine learning for hospital readmission prediction in pediatric population.

BACKGROUND AND OBJECTIVE: Pediatric readmissions are a burden on patients, families, and the healthcare system. In order to identify patients at higher readmission risk, more accurate techniques, as machine learning (ML), could be a good strategy to expand the knowledge in this area. The aim of this study was to develop predictive models capable of identifying children and adolescents at high risk of potentially avoidable 30-day readmission using ML. METHODS: Retrospective cohort study was carried out with 9,080 patients under 18 years old admitted to a tertiary university hospital. Demographic, clinical, and biochemical data were collected from electronic databases. We randomly divided the dataset into training (75 %) and testing (25 %), applied downsampling, repeated cross-validation with five folds and ten repetitions, and the hyperparameter was optimized of each technique using a grid search via racing with ANOVA models. We applied six ML classification algorithms to build the predictive models, including classification and regression tree (CART), random forest (RF), gradient boosting machine (GBM), extreme gradient boosting (XGBoost), decision tree and logistic regression (LR). The area under the receiver operating curve (AUC), sensitivity, specificity, Youden's J-index and accuracy were used to evaluate the performance of each model. RESULTS: The avoidable 30-day hospital readmissions rate was 9.5 %. Some algorithms presented similar AUC, both in the dataset training and in the dataset testing, such as XGBoost, RF, GBM and CART. Considering the Youden's J-index, the algorithm that presented the best index was XGBoost with bagging imputation, with AUC of 0.814 (J-index of 0.484). Cancer diagnosis, age, red blood cells, leukocytes, red cell distribution width and sodium levels, elective admission, and multimorbidity were the most important characteristics to classify between readmission and non-readmission groups. CONCLUSION: Machine learning approaches, especially XGBoost, can predict potentially avoidable 30-day pediatric hospital readmission into tertiary assistance. If implemented in the computer hospital system, our model can help in the early and more accurate identification of patients at readmission risk, targeting health strategic interventions.

The impact of universal induction therapy on early hospital readmission of kidney transplant recipients / O impacto da terapia de indução universal na readmissão hospitalar precoce de receptores de transplante renal

ABSTRACT Background: Early hospital readmission (EHR) is associated with worse outcomes. The use of anti-thymocyte globulin (rATG) induction therapy is associated with increased efficacy in preventing acute rejection, although safety concerns still exist. Methods: This retrospective single-center study compared the incidence, causes of EHR, and one-year clinical outcomes of patients receiving a kidney transplant between August 18, 2011 and December 31, 2012 (old era), in which only high-risk patients received 5 mg/kg rATG, with those transplanted between August 18, 2014 and December 31, 2015 (new era), in which all patients received a single 3 mg/kg dose of rATG. Results: There were 788 patients from the Old Era and 800 from the New Era. The EHR incidence in the old era patients was 26.4% and in the new era patients, 22.5% (p = 0.071). The main cause of EHR in both eras was infection (67% vs. 68%). The incidence of acute rejection episodes was lower (22.7% vs 3.5%, p < 0.001) and the one-year patient survival was higher (95.6% vs. 98.1%, vs. p = 0.004) in new era patients. Conclusion: The universal use of 3 mg/kg rATG single-dose induction therapy in the new era was associated with a trend towards reduced EHR and a reduction in the incidence of acute rejection and mortality.

Resumo Histórico: A Readmissão Hospitalar Precoce (RHP) está associada a piores desfechos. O uso de terapia de indução com globulina antitimócito (rATG, por sua sigla em inglês) está associado ao aumento da eficácia na prevenção de rejeição aguda, embora ainda existam preocupações quanto à segurança. Métodos: Este estudo retrospectivo de centro único comparou a incidência, as causas da RHP e os desfechos clínicos de um ano de pacientes que receberam transplante renal entre 18 de Agosto de 2011 e 31 de Dezembro de 2012 (Antiga Era), em que apenas pacientes de alto risco receberam 5 mg/kg de rATG, com aqueles transplantados entre 18 de Agosto de 2014 e 31 de Dezembro de 2015 (Nova Era), em que todos os pacientes receberam uma única dose de 3 mg/kg de rATG. Resultados: Houve 788 pacientes da Antiga Era e 800 da Nova Era. A incidência de RHP nos pacientes da antiga era foi de 26,4% e nos pacientes da nova era, 22,5% (p = 0,071). A principal causa de RHP em ambas as eras foi infecção (67% vs. 68%). A incidência de episódios de rejeição aguda foi menor (22,7% vs. 3,5%; p < 0,001) e a sobrevida do paciente em um ano foi maior (95,6% vs. 98,1%; vs. p = 0,004) em pacientes da nova era. Conclusão: O uso universal de terapia de indução de 3 mg/kg de rATG em dose única na nova era foi associado a uma tendência à redução da RHP e a uma redução na incidência de rejeição aguda e mortalidade.

Low calf circumference adjusted for body mass index is associated with prolonged hospital stay.

BACKGROUND: Calf circumference (CC) is of emerging importance because of its practicality, high correlation with skeletal muscle, and potential predictive value for adverse outcomes. However, the accuracy of CC is influenced by adiposity. CC adjusted for BMI (BMI-adjusted CC) has been proposed to counteract this problem. However, its accuracy to predict outcomes is unknown. OBJECTIVES: To evaluate the predictive validity of BMI-adjusted CC in hospital settings. METHODS: A secondary analysis of a prospective cohort study in hospitalized adult patients was conducted. The CC was adjusted for BMI by reducing 3, 7, or 12 cm for BMI (in kg/m2) of 25-29.9, 30-39.9, and ≥40, respectively. Low CC was defined as ≤34 cm for males and ≤33 cm for females. Primary outcomes included length of hospital stay (LOS) and in-hospital death, and secondary outcomes were hospital readmissions and mortality within 6 mo after discharge. RESULTS: We included 554 patients (55.2 ± 14.9 y, 52.9% men). Among them, 25.3% presented with low CC, whereas 60.6% had BMI-adjusted low CC. In-hospital death occurred in 13 patients (2.3%), and median LOS was 10.0 (5.0-18.0) d. Within 6 mo from discharge, 43 patients (8.2%) died, and 178 (34.0%) were readmitted to the hospital. BMI-adjusted low CC was an independent predictor of LOS ≥ 10 d (odds ratio = 1.70; 95% confidence interval: 1.18, 2.43], but it was not associated with the other outcomes. CONCLUSIONS: BMI-adjusted low CC was identified in more than 60% of hospitalized patients and was an independent predictor of longer LOS.

Validation of the HOSPITAL score as predictor of 30-day potentially avoidable readmissions in pediatric hospitalized population: retrospective cohort study.

Potentially avoidable pediatric readmissions are a burden to patients and their families. Identifying patients with higher risk of readmission could help minimize hospital costs and facilitate the targeting of care interventions. HOSPITAL score is a tool developed and widely used to predict adult patient's readmissions; however its predictive capacity for pediatric readmissions has not yet been evaluated. The aim of the study was to validate the HOSPITAL score application to predict 30-day potentially avoidable readmissions in a pediatric hospitalized population. This is a retrospective cohort study with patients under 18 years old admitted to a tertiary university hospital (n = 6,344). The HOSPITAL score was estimated for each admission. Subsequently, we classified the patients as low (0-4), intermediate (5-6), and high (7-12) risk groups. In order to estimate the discrimination power, the sensitivity, specificity, and accuracy were determined by the receiver operating characteristics (ROC) and the calibration by the Hosmer-Lemeshow goodness-of-fit. The 30-day hospital readmission was 11.70% (745). The accuracy was 0.80 (CI 95%, 0.77, 0.83), with a sensitivity of 70.96% and specificity of 78.29%, and a good calibration (p = 0.34).    Conclusion: HOSPITAL score showed a good discrimination and can be used to predict 30-day potentially avoidable readmission in a large pediatric population with different medical diagnoses. Our study validates and expands the usefulness of the HOSPITAL score as a tool to predict avoidable hospital readmissions for pediatric population. What is Known: •   Pediatric readmissions burden patients, the family network, and the health system. In addition, it influences negatively child development. •   The HOSPITAL score is one of the tools developed and widely used to identify patients at high risk of hospital readmission, but its predictive capacity for pediatric readmissions has not been yet assessed. What is New: • The HOSPITAL score showed good ability to identify a risk of 30-day potentially avoidable readmission in a pediatric population in different clinical contexts and diagnoses. • Our study expands the usefulness of the HOSPITAL score as a tool for predicting hospital readmissions for children and adolescents.

Is the standardized phase angle a predictor of short- and long-term adverse cardiovascular events in patients with acute myocardial infarction? A cohort study.

OBJECTIVES: Acute myocardial infarction (AMI) is myocardial necrosis resulting from myocardial ischemia, and its risk factors are usually a combination of the consumption of tobacco, inadequate diet, obesity, and a sedentary lifestyle, in addition to preexisting comorbidities. These risk factors may compromise cellular integrity, affecting physiologic and nutritional components. The phase angle (PhA) has been measured by bioelectrical impedance analysis (BIA) to identify the quality of the cell membrane and the distribution of body fluids. The aim of this study was to verify if the standardized PhA (SPhA) is a predictor of short- and long-term adverse cardiovascular events in patients after AMI. METHODS: This was a prospective cohort study including hospitalized adult patients with a diagnosis of AMI. Demographic, clinical, and nutritional data were collected. The PhA was calculated through the measuring of the resistance (R) and reactance (Xc) from BIA, and it was adjusted based on reference values for sex and age, presenting, therefore, the SPhA. Low SPhA was defined as that <10th percentile of distribution. Hospital length of stay (LOS) and major adverse cardiac events (MACE), such as new hospital admission for unstable angina, new MI, and cardiovascular mortality, were observed. The sample comprised 153 patients, with a mean age of 61.2 ± 12.6 y, with 57.5% being older adults. RESULTS: Fifteen patients with low SPhA (values <-3.10) had a longer LOS compared with those with normal SPhA (median 14 versus 8 d, P = 0.007), and shorter time for the occurrence of death (320 versus 354 d, P = 0.024). In the multivariate analysis, an association was observed between SPhA and longer LOS (hazard ratio, 9.25; P = 0.005), but not with mortality and MACE (P > 0.05 for all). CONCLUSION: SPhA was a predictor of longer LOS, but not of long-term adverse cardiac events in patients following AMI.

Prognostic Value of Isolated Sarcopenia or Malnutrition-Sarcopenia Syndrome for Clinical Outcomes in Hospitalized Patients.

Malnutrition-sarcopenia syndrome (MSS) is frequent in the hospital setting. However, data on the predictive validity of sarcopenia and MSS are scarce. We evaluated the association between sarcopenia and MSS and clinical adverse outcomes (prolonged length of hospital stay-LOS, six-month readmission, and death) using a prospective cohort study involving adult hospitalized patients (n = 550, 55.3 ± 14.9 years, 53.1% males). Sarcopenia was diagnosed according to the EWGSOP2, and malnutrition according to the Subjective Global Assessment (SGA). Around 34% were malnourished, 7% probable sarcopenic, 15% sarcopenic, and 2.5% severe sarcopenic. In-hospital death occurred in 12 patients, and the median LOS was 10.0 days. Within six months from discharge, 7.9% of patients died, and 33.8% were readmitted to the hospital. Probable sarcopenia/sarcopenia had increased 3.95 times (95% CI 1.11-13.91) the risk of in-hospital death and in 3.25 times (95% CI 1.56-6.62) the chance of mortality in six months. MSS had increased the odds of prolonged LOS (OR = 2.73; 95% CI 1.42-5.25), readmission (OR = 7.64; 95% CI 3.06-19.06), and death (OR = 1.15; 95% CI 1.08-1.21) within six months after discharge. Sarcopenia and MSS were predictors of worse clinical outcomes in hospitalized patients.

Longer length of stay, days between discharge/first readmission, and pulmonary involvement ≥50% increase prevalence of admissions in ICU in unplanned readmissions after COVID-19 hospitalizations.

Hospital readmissions due to COVID-19 are one of the main concerns for the health system due to risks to the patient's life and increased use of health resources. Studies focusing on this issue are important to understand the risk factors and create strategies to avoid readmissions. We evaluated the readmission of patients with confirmed COVID-19 in a private hospital in southern Brazil, between March 2020 and 2021. Also, the characteristics and clinical outcomes of patients admitted to the intensive care unit (ICU) and nonadmitted were compared. Poisson regression models with prevalence ratio (PR) with 95% confidence intervals (95% CIs) were applied to confirm the association between variables and ICU admission. Of the 2084 hospitalized patients with COVID-19, 1806 were discharged alive. Among them, 106 were readmitted for unplanned reasons during one year. Early hospital readmission (≤30 days) occurred in 52.8% of the cases. The main reasons were respiratory, gastroenterological, kidney, and cardiac disease. The median age was 73.0 years old and women correspond to 52.8%. The presence of at least one comorbidity was detected in 87.7% of patients. Hypertension, diabetes, cardiac, and lung disease were more frequent. The ICU admitted patients (n = 43; 40.5%) mostly had 4-5 comorbidities, pulmonary involvement ≥50%, length of stay (LOS), and days between discharge and first readmission. Longer LOS (PR: 3.46; 95% CI: 1.24-5.67), days between discharge/first readmission (PR: 2.21; 95% CI: 1.15-5.88), and pulmonary involvement (≥50%; PR: 1.59; 95% CI: 1.11-3.54) were independently associated with ICU admission. Longer LOS, longer days between discharge/first readmission, and pulmonary involvement (≥50%) were associated with ICU admission in readmitted patients. Readmissions evaluation is pivotal and may help in ensuring safe care transition and postdischarge follow-up.

Prevalence of hospital readmissions and related factors in patients with autoimmune diseases.

OBJECTIVE: Autoimmune diseases generate an impact on the morbidity and mortality of patients and are a burden for the health system through hospital admissions and readmissions. The prevalence of readmission of patients with these diseases has not yet been described as a group, but rather as sub-phenotype. The objective of this study is to determine the prevalence of hospital readmissions in a Colombian population with autoimmunity and the factors related to readmission. METHODS: All patients with autoimmune diseases who were evaluated by the rheumatology service and hospitalized between August 2018 and December 2019 at the Fundación Hospital Infantil Universitario De San José de Bogotá were described. A bivariate analysis was done, and three multivariate logistic regression models were built with the dependent variable being readmission. RESULTS: Of the total 199 admissions, 131 patients were evaluated and 32% were readmitted. The most frequent sub-phenotype in both groups (readmission and no readmission) was SLE (51% and 59%). The most frequent cause of hospitalization and readmission was disease activity (68.7% and 64.3%). History of hypertension was associated with readmission (adjusted OR: 2.98-95% CI: 1.15-7.72). In a second model adjusted for confounding variables, no factor was associated. In a third model analyzing the history of kidney disease and previous use of immunosuppressants (adjusted for confounding variables), the previous use of immunosuppressants was related to readmission (OR: 2.78-95% CI 1.12-6.89). CONCLUSION: Up to a third of patients with autoimmunity were readmitted and arterial hypertension was an associated factor. This suggested a greater systemic compromise and accumulated damage in patients who have these two conditions that may favor readmission. A history of immunosuppressant use may play a role in readmission, possibly by increasing the risk of developing infections.

Risk factors for potentially preventable hospital readmissions among persons living with human immunodeficiency virus infection.

People living with HIV (PLWH) have a significant risk for experiencing a 30-day readmission; many of which may be potentially preventable readmissions (PPR). The objective of this study was to evaluate 30-day readmission rates for PLWH and identify risk factors for PPR. This was a single center retrospective study. Patients were included if they were ≥18 years of age, had a diagnosis of HIV, and were admitted to University of New Mexico Hospitals between 1 January 2010 and 31 December 2014 and readmitted within 30-days of the index admission. Preventability of readmission was defined using previously published criteria. Of the 908 identified admissions for PLWH during 2010-2014, 162 (17.8%) were 30-day readmissions. A total of 60 patient readmissions met study inclusion criteria, of which 55% were determined to be PPR. Multivariate logistic regression analysis revealed that being discharged on ≥10 medications (OR 3.92, 95% CI 1.181-13.043) and having an appointment scheduled upon discharge (OR 3.59, 95% CI 1.057-12.212) were significantly associated a PPR. These results further highlight the vulnerability of this patient population and help to identify risk factors for PPR. Targeted transitions of care interventions that address polypharmacy may help to reduce PPR among PLWH.

Decline of nutritional status in the first week of hospitalisation predicts longer length of stay and hospital readmission during 6-month follow-up.

Nutritional status (NS) monitoring is an essential step of the nutrition care process. To assess changes in NS throughout hospitalisation and its ability to predict clinical outcomes, a prospective cohort study with patients over 18 years of age was conducted. The Subjective Global Assessment (SGA) was performed within 48 h of admission and 7 d later. For each patient, decline in NS was assessed by two different methods: changes in SGA category and severe weight loss alone (≥2 % during the first week of hospitalisation). Patients were followed up until discharge to assess length of hospital stay (LOS) and in-hospital mortality and contacted 6 months post-discharge to assess hospital readmission and death. Out of the 601 patients assessed at admission, 299 remained hospitalised for at least 7 d; of those, 16·1 % had a decline in SGA category and 22·8 % had severe weight loss alone. In multivariable analysis, decline in SGA category was associated with 2-fold (95 % CI 1·06, 4·21) increased odds of prolonged LOS and 3·6 (95 % CI 1·05, 12·26) increased odds of hospital readmission at 6 months. Severe weight loss alone was associated with 2·5-increased odds (95 % CI 1·40, 4·64) of prolonged LOS. In conclusion, deterioration of NS was more often identified by severe weight loss than by decline in SGA category. While both methods were associated with prolonged LOS, only changes in the SGA predicted hospital readmission. These findings reinforce the importance of nutritional monitoring and provide guidance for further research to prevent short-term NS deterioration from being left undetected.

Emergency department visits and hospital readmissions in an Argentine health system.

BACKGROUND AND GOAL OF STUDY: The scope of health in the Sustainable Development Goals is much broader than the Millennium Development Goals, spanning functions such as health-system access and quality of care. Hospital readmission rate and ED-visits within 30 days from discharge are considered low-cost quality indicators. This work assesses an indicator of quality of care in a tertiary referral hospital in Argentina, using data available from clinical records. PURPOSE: To estimate the rate of ED-visits and the hospital readmission rate (HRR) after a first hospitalization (First-H), and to identify associated factors. METHODS: This retrospective cohort included patients who had a First-H in Hospital Italiano de Buenos Aires between 2014-2015. Follow-up occurred from discharge until ED-visit, readmission, death, disaffiliation from health insurance, or 13 months. We present HRR at 30 days and ED-visits rate at 72 h, using the Cox proportional-hazards regression model to explore associated factors, and reporting adjusted hazard ratios (HR) with their respective 95 %CI. RESULTS: The study comprised 10,598 hospitalizations (median age was 68 years). Of these, 5966 had at least one consultation to the ED during follow up, resulting in a 24 h rate of consultations to ED of 1.51 % (95 %CI 1.29-1.72); at 48 h 3.18 % (95 %CI 2.86-3.54); at 72 h 4.71 % (95 %CI 4.32-5.13). In multivariable models, factors associated for 72 h ED-visits were: age (aHR 1.06), male (aHR 1.14), Charlson Comorbidity Index (aHR 1.16), unscheduled hospitalization (aHR 1.39), prior consultation with the ED (aHR 1.08) and long hospital stay (aHR 1.39). Meanwhile, 2345 patients had at least one hospital readmission (98 % unscheduled), resulting a 24 h rate of 0.5 % (95 %CI 0.42-0.71), at 48 h 0.98 % (95 %CI 0.80-1.18), at 72 h 1.4 % (95 %CI 1.2-1.6); at 30 days 7.7 % (95 %CI 7.2-8.2); at 90 days 13 % (95 %CI 12.4-13.8); and one-year 22.5 % (95 %CI 21.7-23.4). Associated factors for HRR at 30 days were: age (HR 1.16), male (HR 1.09), Charlson comorbidities score (HR 1.27), social service requirement during First-H (HR 1.37), unscheduled First-H (HR 1.16), previous ED-visits (HR 1.03) and length of stay (HR 1.08). CONCLUSION: Priorities efforts to improve must include greater attention to patients' readiness prior discharge, to explore causes of preventable readmissions, and better support for patient self-management.

Hierarchical analysis of factors associated with hospital readmissions for coronary heart disease: A case-control study.

AIMS AND OBJECTIVES: To analyse, hierarchically, factors associated with hospital readmissions for acute coronary syndrome. BACKGROUND: Hospital readmissions have risen, especially in patients with multiple comorbidities, which are most often chronic. The leading causes of hospital readmission include acute coronary syndrome, which is costly and often preventable. Determining clinical and nonclinical variables that increase the chances of readmission is important to assess and evaluate patients hospitalised for coronary heart diseases. DESIGN: A case-control study whose dependent variable was hospital readmission for acute coronary syndrome. METHODS: The study included 277 inpatients, of whom 132 were in their first hospitalisation and 145 had already been hospitalised for acute coronary syndrome. The independent variables for this hierarchical model were sociodemographic conditions, life habits, access to health services and physical health measures. Data were obtained by interviews, anthropometric measurements and patient records. Logistic regression analysis was performed using the stepwise technique, with Microsoft Excel and R version 3.2.3. The research was reported via strengthening the reporting of observational studies in epidemiology (STROBE). RESULTS: In the final hierarchical logistic model, the following risk factors were associated with readmission for acute coronary syndrome: inadequate drug therapy adherence, stress, history of smoking for 30 years or more, and the lack of use of primary healthcare services. CONCLUSIONS: Clinical and nonclinical variables are related to hospital readmission for acute coronary syndrome and can increase the chance of readmission by up to six times. RELEVANCE TO CLINICAL PRACTICE: The predictive model can be used to avoid readmission for acute coronary syndrome, and it represents an advance in the prediction of the occurrence of the outcome. This implies the need for a reorientation of the network for postdischarge care in the first hospitalisation for acute coronary syndrome.

Are Clinical Outcomes Associated With Medication Regimen Complexity? A Systematic Review and Meta-analysis.

Background: Current evidence of the influence of the medication regimen complexity (MRC) on the patients' clinical outcomes are not conclusive. Objective: To systematically and analytically assess the association between MRC measured by the Medication Regimen Complexity Index (MRCI) and clinical outcomes. Methods: A search was carried out in the databases Cochrane Library, LILACS, PubMed, Scopus, EMBASE, Open Thesis, and Web of Science to identify studies evaluating the association between MRC and clinical outcomes that were published from January 1, 2004, to April 2, 2018. The search terms included outcome assessment, drug therapy, and medication regimen complexity index and their synonyms in different combinations for case-control and cohort studies that used the MRCI to measure MRC and related the MRCI with clinical outcomes. Odds ratios (ORs), hazard ratios (HRs), and mean differences (WMDs) were calculated, and heterogeneity was assessed using the I2 test. Results: A total of 12 studies met the eligibility criteria. The meta-analysis showed that MRC is associated with the following clinical outcomes: hospitalization (HR = 1.20; 95% CI = 1.14 to 1.27;I2 = 0%) in cohort studies, hospital readmissions (WMD = 7.72; 95% CI = 1.19 to 14.25; I2 = 84%) in case-control studies, and medication nonadherence (adjusted OR = 1.05; 95% CI = 1.02 to 1.07; I2 = 0%) in cohort studies. Conclusion and Relevance: This systematic review and meta-analysis gathered relevant scientific evidence and quantified the combined estimates to show the association of MRC with clinical outcomes: hospitalization, hospital readmission, and medication adherence.

72-hour hospital readmission of older people after hospital discharge with home care services.

In this retrospective cohort study in Argentina, risk factors for hospital readmission of older adults, within 72 hours after hospital discharge with home care services, were analyzed. Fifty-three percent of unplanned emergency room visits within 72 hours after hospital discharge resulted in hospital readmissions, 65% of which were potentially avoidable. By multivariate logistic regression, low functionality, pressure ulcers, and age over 83 years predicted hospital readmission among emergency room attendees. It is important to identify and analyze barriers in current home care services and the high-risk population of hospital readmission to improve the strategies to avoid adverse outcomes.

Community health services and risk of readmission in public psychiatric hospitals of Belo Horizonte, Brazil, 2005-2011 / Cobertura de serviços extra-hospitalares e risco de reinternação nos hospitais psiquiátricos públicos de Belo Horizonte, 2005 a 2011

Abstract Introduction The readmission phenomenon in psychiatry not only reflects the severity and chronicity of the underlying disorders, but also indicates the quality of mental healthcare. In the context of the Brazilian mental healthcare reform, no study has included the availability of outpatient care among the potential determinants for psychiatric readmission. Objective To correlate the availability of community healthcare resources at the place of residence with the risk of psychiatric readmission. Methods All admission records from 2005 to 2011 in the two public psychiatric hospitals of Belo Horizonte were included (n=19,723). Variables related to patients and characteristics of hospitalization were collected, and indicators of community healthcare coverage were calculated for each place of residence yearly. The outcome of interest was early (<7 days), medium-term (8-30 days) and late (31-365 days) readmissions. The analysis was based on Cox regressions. Results The coverage of basic health units and of psychiatrists was associated with lower readmission risks. Coverage of specialized centers for psychosocial attention (Centros de Atenção Psicossocial [CAPS]) and psychologists did not show any protective effects. Young, male patients and those residing outside the capital had greater risk of early readmission. Compared to other psychotic disorders, mood disorders and neurotic disorders were seen as protective factors for readmission. Conclusion Regionalized attention offered by the CAPS did not result in reduced readmission risks.

Resumo Introdução O fenômeno da reinternação psiquiátrica reflete não apenas a gravidade e cronicidade da doença de base, mas também a qualidade dos serviços de saúde. Ainda não há estudos incluindo a disponibilidade de recursos assistenciais extra-hospitalares como preditor da readmissão psiquiátrica, no contexto da reforma da assistência à saúde mental brasileira. Objetivo Correlacionar a disponibilidade de recursos de assistência extra-hospitalar das localidades de residência com o risco de readmissão psiquiátrica. Métodos Foram analisados todos os registros de internações ocorridas de 2005 a 2011 nos dois hospitais psiquiátricos públicos de Belo Horizonte (n=19.723). Foram coletadas variáveis relativas aos pacientes e às características da internação, e calculados indicadores de cobertura em saúde extra-hospitalar para cada localidade de residência e ano. O desfecho de interesse foi a reinternação precoce (<7 dias), de médio prazo (8-30 dias) e tardia (31-365 dias). A análise se deu por regressões de Cox. Resultados A cobertura de unidades básicas de saúde e de psiquiatras se associou a menores riscos de reinternação. A cobertura de Centros de Atenção Psicossocial (CAPS) e de psicólogos não apresentou efeitos protetores. Pacientes jovens e do sexo masculino, assim como os residentes fora da capital, tiveram risco maior de reinternação precoce. Em comparação com outros transtornos psicóticos, os transtornos de humor e os transtornos neuróticos se apresentaram como fatores protetores para a reinternação. Conclusão A atenção regionalizada oferecida pelos CAPS não resultou em riscos reduzidos de reinternação.

Calf Circumference: A Marker of Muscle Mass as a Predictor of Hospital Readmission.

Hospital readmissions (HRs) are common, potentially preventable, and a marker of poor quality in health services. This study aimed to identify risk factors for HR in clinical patients, with an emphasis on nutrition aspects, especially calf circumference (CC), as a marker of muscle mass. A prospective cohort study of patients admitted to the internal medicine ward was conducted. The short form of the Patient-Generated Subjective Global Assessment was performed in the first 24 hours of hospitalization. In addition, single-frequency bioelectrical impedance analysis was used to estimate the phase angle, CC as a surrogate of muscle mass, and handgrip strength as a marker of strength. The Charlson Comorbidity Index (CCI) was used to assess the severity of the comorbidities. Reassessments were performed every 7 days during hospitalization. HR was evaluated 30 days after discharge by phone contact. A sample of 161 patients was assessed; 54.6% were male, with a mean age of 59.2 ± 17.8 years. The median CCI was 2.76 (interquartile range: 1-4), and nutrition risk and low CC were present in 77.6% and 46% of the patients, respectively. The readmission rate was 16.8% after 30 days. After controlling for sex and age, a CCI > 2 (odds ratio [OR]: 3.29; 95% confidence interval [CI]: 1.21-8.97), the presence of cancer (OR: 4.52; 95% CI: 1.11-18.42), nutrition risk (OR: 9.53; 95% CI: 1.16-77.9), and a low CC (OR: 3.89; 95% CI: 1.34-11.31) were significantly associated with 30 day HR. In conclusion, muscle mass loss, identified by CC, can be a good predictor of 30-day HR, even after controlling for other well-known risk factors.

Pattern and Predictors of Hospital Readmission During the First Year After Lung Transplantation.

Hospital readmission after lung transplantation negatively affects quality of life and resource utilization. A secondary analysis of data collected prospectively was conducted to identify the pattern of (incidence, count, cumulative duration), reasons for and predictors of readmission for 201 lung transplant recipients (LTRs) assessed at 2, 6, and 12 mo after discharge. The majority of LTRs (83.6%) were readmitted, and 64.2% had multiple readmissions. The median cumulative readmission duration was 19 days. The main reasons for readmission were other than infection or rejection (55.5%), infection only (25.4%), rejection only (9.9%), and infection and rejection (0.7%). LTRs who required reintubation (odds ratio [OR] 1.92; p = 0.008) or were discharged to care facilities (OR 2.78; p = 0.008) were at higher risk for readmission, with a 95.7% cumulative incidence of readmission at 12 mo. Thirty-day readmission (40.8%) was not significantly predicted by baseline characteristics. Predictors of higher readmission count were lower capacity to engage in self-care (incidence rate ratio [IRR] 0.99; p = 0.03) and discharge to care facilities (IRR 1.45; p = 0.01). Predictors of longer cumulative readmission duration were older age (arithmetic mean ratio [AMR] 1.02; p = 0.009), return to the intensive care unit (AMR 2.00; p = 0.01) and lower capacity to engage in self-care (AMR 0.99; p = 0.03). Identifying LTRs at risk may assist in optimizing predischarge care, discharge planning and long-term follow-up.