Predictors of Hospital Length of Stay in Heart Failure: Findings from Get With the Guidelines

Abdul Kader MA, Loch A, Mahendran K, Ramli AW, Ong TK, Mohd Amin NH, Lee CY, Che Hassan HH, Zainal Abidin SK, Liew HB, Ho WS, Mohd Ghazi A. Characteristics of patients admitted with heart failure: Insights from the first Malaysian Heart Failure Registry

AIMS

Heart failure (HF) is a growing health problem, yet there are limited data on patients with HF in Malaysia. The Malaysian Heart Failure (MY-HF) Registry aims to gain insights into the epidemiology, aetiology, management, and outcome of Malaysian patients with HF and identify areas for improvement within the national HF services.

METHODS AND RESULTS

The MY-HF Registry is a 3-year prospective, observational study comprising 2717 Malaysian patients admitted for acute HF. We report the description of baseline data at admission and outcomes of index hospitalization of these patients. The mean age was 60.2 ± 13.6 years, 66.8% were male, and 34.3% had de novo HF. Collectively, 55.7% of patients presented with New York Heart Association (NYHA) Class III or IV; ischaemic heart disease was the most frequent aetiology (63.2%). Most admissions (87.3%) occurred via the emergency department, with 13.7% of patients requiring intensive care, and of these, 21.8% needed intubation. The proportion of patients receiving guideline-directed medical therapy increased at discharge (84.2% vs. 93.6%). The median length of stay (LOS) was 5 days, and in-hospital mortality was 2.9%. Predictors of LOS and/or in-hospital mortality were age, NYHA class, estimated glomerular filtration rate, and comorbid anaemia. LOS and in-hospital mortality were similar regardless of ejection fraction.

CONCLUSIONS

The MY-HF Registry showed that the HF population in Malaysia is younger, predominantly male, and ischaemic-driven and has good prospects with hospitalization for optimization of treatment. These findings suggest a need to reassess current clinical practice and guide resource allocation to improve patient outcomes.

The role of illness perceptions in delayed care-seeking in heart failure: A mixed-methods study

BACKGROUND

Unclear illness perceptions are common in heart failure. The self-regulation model of illness behaviour highlights factors that may impact how people with chronic illness choose to cope with or manage their condition and has been used to study pre-hospital delay for stroke and acute myocardial infarction. The principles of self-regulation can be applied in heart failure to help illuminate the link between unclear illness perceptions and sub-optimal symptom self-management.

OBJECTIVE

Informed by the self-regulation model of illness behaviour, this study examines the role of illness perceptions in coping responses that lead to delayed care-seeking for heart failure symptoms.

DESIGN

Mixed-methods phenomenological study.

SETTING(S)

Quaternary referral hospital - centre of excellence for cardiovascular care and heart transplantation.

PARTICIPANTS

Seventy-two symptomatic patients with heart failure participated in a survey assessing illness perceptions. A subset of fifteen individuals was invited to participate in semi-structured interviews.

METHODS

Illness perceptions were assessed using the Brief Illness Perception Questionnaire. In-depth semi-structured interviews were conducted to elicit previous care-seeking experiences and decision-making that led to a passive, or active coping response to worsening symptoms. Descriptive statistics were used to report questionnaire findings, and open-ended responses were grouped into descriptive categories. Interpretative phenomenological analysis was undertaken on interview transcripts.

RESULTS

Participants perceived little personal control over their condition and mostly attributed heart failure to lifestyle factors such as diet and lack of activity. Cognitive dissonance between perceived self-identity and heart failure-identity led to a highly emotional response which drove coping towards avoidance strategies and denial.

CONCLUSIONS

This study demonstrates the use of the principles of self-regulation in heart failure and offers a framework to understand how patient representations and emotional responses can inform behaviour in illness. Findings highlight the value of empowering patients to take control of their health and the need to help align values (e.g. independence) with behaviours (e.g. actively addressing problems) to facilitate optimal symptom self-management.

Surgical scheduling via optimization and machine learning with long-tailed data : Health care management science, in press

Using data from cardiovascular surgery patients with long and highly variable post-surgical lengths of stay (LOS), we develop a modeling framework to reduce recovery unit congestion. We estimate the LOS and its probability distribution using machine learning models, schedule procedures on a rolling basis using a variety of optimization models, and estimate performance with simulation. The machine learning models achieved only modest LOS prediction accuracy, despite access to a very rich set of patient characteristics. Compared to the current paper-based system used in the hospital, most optimization models failed to reduce congestion without increasing wait times for surgery. A conservative stochastic optimization with sufficient sampling to capture the long tail of the LOS distribution outperformed the current manual process and other stochastic and robust optimization approaches. These results highlight the perils of using oversimplified distributional models of LOS for scheduling procedures and the importance of using optimization methods well-suited to dealing with long-tailed behavior.

Hospital Resource Utilization and Costs in Patients with Heart Failure in France

BACKGROUND AND OBJECTIVES

Heart failure (HF) is one of the leading causes of morbidity and mortality, and economic burden on the healthcare system. The aim of this study was to estimate the current hospital resource utilization and costs for HF patients in France.

METHODS

This retrospective cohort study included adult HF patients hospitalized in France between January 1, 2019 and December 31, 2019. Data related to sociodemographic characteristics, number and duration of hospital stays, use of medical procedures or expensive and innovative drugs/medical devices included in the "liste-en-sus", and comorbidities were retrieved from the French national hospital discharge database. Data were further stratified based on the presence or absence of cardiac decompensation, comorbidities, ejection fraction (EF) status, and incident/prevalent patients.

RESULTS

In 2019, a total of 430,544 patients were hospitalized in France with HF as a primary or associated diagnosis, with 51.9% male and 48.1% female and a mean age of 79.0 years. More than 75% of the study population was composed of prevalent HF patients. About 3.1% of patients were diagnosed with at least one event of cardiac decompensation during follow-up. Also, 20.2% and 9.9% of patients were identified with preserved and reduced EFs, respectively. The average number and length of hospital stays were 1.7 per patient and 10.4 days per patient, respectively. The annual cost of hospitalization for HF was €8341.3 per patient. Presence of cardiac decompensation at index date or during follow-up, reduced EF, and comorbidities were associated with numerically higher frequency and length of hospitalization, and hospitalization cost. For hospitalization and 'liste-en-sus' medical devices, higher cost was observed in incident than prevalent HF patients, while for 'liste-en-sus' drugs, higher cost was reported in prevalent than incident HF patients.

CONCLUSION

This study highlighted the high economic hospital burden of HF in France. More studies investigating different HF patient profiles must be conducted to help determine the main factors of hospital cost for HF.

Combination of low muscle strength and malnutrition is associated with longer length of hospital stay among older patients with heart failure

BACKGROUND

Muscle strength and nutritional status are associated with length of hospital stay (LOHS) in older patients with heart failure (HF).

OBJECTIVES

The purpose of the study was to examine the association of the combination of muscle strength and nutritional status on LOHS in older patients with HF.

METHODS

This retrospective cohort study included 414 older inpatients with HF (men, 57.2%; median age, 81 years; interquartile range, 75-86 years). Patients were categorized into four groups according to their muscle strength and nutritional status: group 1, high muscle strength and normal nutritional status; group 2, low muscle strength and normal nutritional status; group 3, high muscle strength and malnutrition; and group 4, low muscle strength and malnutrition. The outcome variable was the LOHS, and an LOHS of >16 days was defined as long LOHS.

RESULTS

Multivariate logistic regression analysis adjusted for baseline characteristics (reference, group 1) showed that group 4 was associated with a more significant risk of long LOHS (odds ratio [OR], 3.54 [95% confidence interval, 1.85-6.78]). In the subgroup analysis, this relationship was maintained for the first admission HF group (OR, 4.65 [2.07-10.45]) but not for the HF readmission group (OR, 2.80 [0.72-10.90]).

CONCLUSIONS

Our results suggest that the long LOHS for older patients with HF at first admission was associated with a combination of low muscle strength and malnutrition but not by either factor individually.

N-Terminal Pro B-Type Natriuretic Peptide as a Screening Tool for Inpatient Echocardiogram Requirement Among Patients With Suspected Heart Failure: Using NT-proBNP to Reduce Hospital Length of Stay

BACKGROUND

N-terminal pro-B-type natriuretic peptide (NT-proBNP) is a cardiac biomarker with diagnostic and prognostic utility in patients with heart failure (HF). Whether NT-proBNP can be used to triage inpatient transthoracic echocardiogram (TTE) requirements, and whether this impacts hospital length of stay (LOS), is not clear.

METHODS

Clinical and biochemical data were prospectively recorded on all inpatients at Wollongong Hospital, NSW, Australia, who had a TTE ordered for suspected HF over a 6-month period. NT-proBNP was used to triage TTE priority, where high-priority inpatient TTE, lower-priority inpatient TTE and outpatient (OP) TTE were performed for serum NT-proBNPs of ≥900, 300-899 and <300, respectively. Outcomes were compared with a baseline cohort of HF inpatients in whom TTE requirement was not guided by NT-proBNP.

RESULTS

A total of 236 patients were evaluated-31, 31, and 174 in the low, intermediate and high NT-proBNP cohorts, respectively, and 199 patients were in the baseline cohort. Average hospital LOS was significantly reduced in the study cohort compared to baseline (9.97 vs 13.87 days, p<0.001). Of the 31 patients with a very low NT-proBNP who were discharged for OP TTE, seven were readmitted within 30 days, though none were HF-related. There were no deaths at 30 days in the low or intermediate NT-proBNP groups.

CONCLUSIONS

Using NT-proBNP to triage requirements for inpatient TTE reduces hospital LOS. A very low NT-proBNP may help identify which patients with suspected HF can be safely discharged for OP TTE.

Hospital length of stay prediction tools for all hospital admissions and general medicine populations: systematic review and meta-analysis

Background

Unwarranted extended length of stay (LOS) increases the risk of hospital-acquired complications, morbidity, and all-cause mortality and needs to be recognized and addressed proactively.

Objective

This systematic review aimed to identify validated prediction variables and methods used in tools that predict the risk of prolonged LOS in all hospital admissions and specifically General Medicine (GenMed) admissions.

Method

LOS prediction tools published since 2010 were identified in five major research databases. The main outcomes were model performance metrics, prediction variables, and level of validation. Meta-analysis was completed for validated models. The risk of bias was assessed using the PROBAST checklist.

Results

Overall, 25 all admission studies and 14 GenMed studies were identified. Statistical and machine learning methods were used almost equally in both groups. Calibration metrics were reported infrequently, with only 2 of 39 studies performing external validation. Meta-analysis of all admissions validation studies revealed a 95% prediction interval for theta of 0.596 to 0.798 for the area under the curve. Important predictor categories were co-morbidity diagnoses and illness severity risk scores, demographics, and admission characteristics. Overall study quality was deemed low due to poor data processing and analysis reporting.

Conclusion

To the best of our knowledge, this is the first systematic review assessing the quality of risk prediction models for hospital LOS in GenMed and all admissions groups. Notably, both machine learning and statistical modeling demonstrated good predictive performance, but models were infrequently externally validated and had poor overall study quality. Moving forward, a focus on quality methods by the adoption of existing guidelines and external validation is needed before clinical application.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42021272198.

Prognostic Factors for Prolonged In-Hospital Stay in Patients with Heart Failure

Background and Objectives: Heart failure (HF) is a threatening health condition that is associated with an increasing prevalence and high expenses because of frequent patient hospitalizations. The purpose of this study was to evaluate the factors that influence the length of in-hospital stay in HF patients. Materials and Methods: A total of 220 patients (43.2% men), admitted to the Department of Cardiology, Kaunas Hospital of Lithuanian University of Health Sciences from the 1st of January 2021 to the 31st of May 2021, were included in this study. According to the length of in-hospital stay, patients were stratified into two groups: the first group's length of stay (LOS) was from 1 to 8 days, and the second group's LOS was 9 days or more. Results: The median LOS was 8 (6-10) days. Multivariate logistic regression analysis revealed five predictors as independent factors associated with prolonged hospitalization. These predictors included treatment interruption (OR 3.694; 95% CI 1.080-12.630, p = 0.037), higher value of NT-proBNP (OR 3.352; 95% CI 1.468-7.659, p = 0.004), estimated glomerular filtration rate (eGFR) ≤ 50 mL/min/1.73 m2 (OR 2.423; 95% CI 1.090-5.383, p = 0.030), systolic blood pressure (BP) ≤ 135 mmHg (OR 3.100; 95% CI 1.421-6.761, p = 0.004) and severe tricuspid valve regurgitation (OR 2.473; 95% CI 1.086-5.632, p = 0.031). Conclusions: Several variables were identified as significant clinical predictors for prolonged length of in-hospital stay in HF patients where treatment interruption, higher NT-proBNP value and lower systolic BP at admission were the most important.

The Length of Hospital Stay of Patients with Venous Thromboembolism: A Cross-Sectional Study from Jordan

Background and Objectives: Venous thromboembolism is one of the leading causes of mortality and disability worldwide. Treatment with anticoagulation therapy is essential and requires a delicate approach to select the most appropriate option to improve patient outcomes, including the length of hospital stay (LOS). The aim of this study was to determine the LOS among patients with acute onset of VTE in several public hospitals in Jordan. Materials and Methods: In this study, we recruited hospitalized patients with a confirmed diagnosis of VTE. We reviewed the electronic medical records and charts of VTE admitted patients in addition to a detailed survey to collect the patients' self-reported data. Hospital LOS was categorized into three levels: 1-3 days, 4-6 days, and ≥7 days. An ordered logistic regression model was used to study the significant predictors of LOS. Results: A total of 317 VTE patients were recruited, with 52.4% of them were male and 35.3% aged between 50 and 69 years. Most patients had a deep vein thrombosis (DVT) diagnosis (84.2%), and most of the VTE cases were admitted for the first-time (64.6%). The majority of the patients were smokers (57.2%), overweight/obese (66.3%), and hypertensive (59%). Most of the VTE patients received Warfarin overlapped with low molecular weight heparins as their treatment regimen (>70%). Almost half of the admitted VTE patients (45%) were hospitalized for at least 7 days. Longer LOS was significantly associated with hypertension. Conclusions: We recommend using therapies that have been proven to reduce hospital LOS, such as non-vitamin K antagonist oral anticoagulants or direct oral anticoagulants, to treat VTE patients in Jordan. Additionally, preventing and controlling comorbidities such as hypertension is essential.

Hospital length of stay prediction for general surgery and total knee arthroplasty admissions: Systematic review and meta-analysis of published prediction models

Objective

Systematic review of length of stay (LOS) prediction models to assess the study methods (including prediction variables), study quality, and performance of predictive models (using area under receiver operating curve (AUROC)) for general surgery populations and total knee arthroplasty (TKA).

Method

LOS prediction models published since 2010 were identified in five major research databases. The main outcomes were model performance metrics including AUROC, prediction variables, and level of validation. Risk of bias was assessed using the PROBAST checklist.

Results

Five general surgery studies (15 models) and 10 TKA studies (24 models) were identified. All general surgery and 20 TKA models used statistical approaches; 4 TKA models used machine learning approaches. Risk scores, diagnosis, and procedure types were predominant predictors used. Risk of bias was ranked as moderate in 3/15 and high in 12/15 studies. Discrimination measures were reported in 14/15 and calibration measures in 3/15 studies, with only 4/39 externally validated models (3 general surgery and 1 TKA). Meta-analysis of externally validated models (3 general surgery) suggested the AUROC 95% prediction interval is excellent and ranges between 0.803 and 0.970.

Conclusion

This is the first systematic review assessing quality of risk prediction models for prolonged LOS in general surgery and TKA groups. We showed that these risk prediction models were infrequently externally validated with poor study quality, typically related to poor reporting. Both machine learning and statistical modelling methods, plus the meta-analysis, showed acceptable to good predictive performance, which are encouraging. Moving forward, a focus on quality methods and external validation is needed before clinical application.

Race, Social Determinants of Health, and Length of Stay Among Hospitalized Patients With Heart Failure: An Analysis From the Get With The Guidelines-Heart Failure Registry

BACKGROUND

Racial disparities in heart failure hospitalization and mortality are well established; however, the association between different social determinants of health (SDOH) and length of stay (LOS) and the extent to which this association may differ across racial groups is not well established.

METHODS

We utilized data from the Get With The Guidelines-Heart Failure registry to evaluate the association between SDOH, as determined by patients' residential ZIP Code and LOS among patients hospitalized with heart failure. We also assessed the race-specific contribution of the ZIP Code-level SDOH to LOS in patients of Black and non-Black races. Finally, we evaluated SDOH predictors of racial differences in LOS at the hospital level.

RESULTS

Among 301 500 patients (20.2% Black race), the median LOS was 4 days. In adjusted analysis accounting for patient-level and hospital-level factors, SDOH parameters of education, income, housing instability, and foreign-born were significantly associated with LOS after adjusting for clinical status and hospital-level factors. SDOH parameters accounted for 25.8% of the total attributable risk for prolonged LOS among Black patients compared with 10.1% in patients of non-Black race. Finally, hospitals with disproportionately longer LOS for Black versus non-Black patients were more likely to care for disadvantaged patients living in ZIP Codes with a higher percentage of foreign-born and non-English speaking areas.

CONCLUSIONS

ZIP Code-level SDOH markers can identify patients at risk for prolonged LOS, and the effects of SDOH parameters are significantly greater among Black adults with heart failure as compared with non-Black adults.

Improving Fairness in the Prediction of Heart Failure Length of Stay and Mortality by Integrating Social Determinants of Health

BACKGROUND

Machine learning (ML) approaches have been broadly applied to the prediction of length of stay and mortality in hospitalized patients. ML may also reduce societal health burdens, assist in health resources planning and improve health outcomes. However, the fairness of these ML models across ethnoracial or socioeconomic subgroups is rarely assessed or discussed. In this study, we aim (1) to quantify the algorithmic bias of ML models when predicting the probability of long-term hospitalization or in-hospital mortality for different heart failure (HF) subpopulations, and (2) to propose a novel method that can improve the fairness of our models without compromising predictive power.

METHODS

We built 5 ML classifiers to predict the composite outcome of hospitalization length-of-stay and in-hospital mortality for 210 368 HF patients extracted from the Get With The Guidelines-Heart Failure registry data set. We integrated 15 social determinants of health variables, including the Social Deprivation Index and the Area Deprivation Index, into the feature space of ML models based on patients' geographies to mitigate the algorithmic bias.

RESULTS

The best-performing random forest model demonstrated modest predictive power but selectively underdiagnosed underserved subpopulations, for example, female, Black, and socioeconomically disadvantaged patients. The integration of social determinants of health variables can significantly improve fairness without compromising model performance.

CONCLUSIONS

We quantified algorithmic bias against underserved subpopulations in the prediction of the composite outcome for HF patients. We provide a potential direction to reduce disparities of ML-based predictive models by integrating social determinants of health variables. We urge fellow researchers to strongly consider ML fairness when developing predictive models for HF patients.

Disparities in Hospital Length of Stay Across Race and Ethnicity Among Patients With Heart Failure

BACKGROUND

Reducing hospital length of stay (LOS) has been identified as an important lever for minimizing the burden of heart failure hospitalization, yet the impact of social and structural determinants of health on LOS has received little attention. We investigated disparities in LOS across race/ethnicity and their possible drivers.

METHODS

We analyzed patients hospitalized for heart failure from 2017 to 2020 using the Get With The Guidelines-Heart Failure registry. We characterized LOS differences across race/ethnicity by insurance and disposition, adjusting for demographics, comorbidities, and clinical severity. Effects of hospital-level clustering on LOS across race/ethnicity were assessed using hierarchical mixed-effects models. We evaluated the association between LOS and discharge rates of guideline-directed medical therapy.

RESULTS

Three thousand three seven hundred thirty patients hospitalized for heart failure were identified. After excluding inpatient deaths, the adjusted LOS for Black (5.72 days [95% CI, 5.62-5.82]), Hispanic (5.94 days [95% CI, 5.79-6.08]), and Indigenous American/Pacific Islander (6.06 days [95% CI, 5.85-6.27]) patients remained significantly longer compared with non-Hispanic White patients (5.32 days [95% CI, 5.25-5.39]). This pattern was driven by LOS differences among patients discharged to hospice or nursing facilities. After accounting for variability between hospitals, associations of race/ethnicity with LOS either were attenuated or reversed in direction. Guideline-directed medical therapy rates on discharge did not differ significantly across race/ethnicity despite longer LOS for Black, Hispanic, and Indigenous American/Pacific Islander patients.

CONCLUSIONS

Differences between hospitals drive LOS disparities across race/ethnicity. Longer LOS among Black, Hispanic, and Indigenous American/Pacific Islander patients was not associated with improved quality of care.

NT-Pro-BNP and echocardiography for the early assessment of cardiovascular dysfunction in neonates with sepsis

To investigate the predictive manner of N-terminal fragment of brain natriuretic peptide (NT-Pro-BNP) and echocardiography in the early assessment of cardiovascular dysfunction (CVD) in neonates with sepsis, we recruited 108 neonates with sepsis in intensive care units and divided them into a sepsis with CVD (sepsis + CVD) group (n = 48) and a sepsis only group (n = 60). Neonates with other infections (n = 65) constituted the control group. Clinical, laboratory, and bedside echocardiography findings were evaluated. Compared to both the sepsis only and control groups, the sepsis + CVD group showed an earlier onset of symptoms [52.94 (0-185.6) h], higher NT-Pro-BNP levels (P = .02), a higher Tei index (0.52 + 0.03; P = .03), and lower ejection fraction (62.61% ± 12.31%, P < .05). Compared to the control group, the sepsis + CVD group exhibited hematogenous etiology (P < .05), lower albumin (ALB) levels (P = .04), lower white blood cell counts (P = .03), a higher high-sensitivity C-reactive protein/ALB ratio, and a larger right-ventricle-inner diameter (10.74 + 2.42 mm; P = .01). CVD in the septic neonates could be predicted by either NT-Pro-BNP levels (cut-off: 12,291.5 pg/L; sensitivity, 80%; specificity, 79%; area under the curve-receiver operating characteristic, 0.81) or Tei index (cut-off: 0.45; sensitivity, 74%; specificity, 77%; area under the curve-receiver operating characteristic, 0.78). NT-Pro-BNP levels and echocardiography can be used to determine early onset of CVD in neonatal sepsis, which facilitates timely pharmacological interventions and treatment.

Length of hospital stay and associated factors among heart failure patients admitted to the University Hospital in Northwest Ethiopia

BACKGROUND

A prolonged length of hospital stay during heart failure-related hospitalization results in frequent readmission and high mortality. The study was aimed to determine the length of hospital stays and associated factors among heart failure patients.

METHODS

A prospective hospital-based cross-sectional study was carried out to determine the length of hospital stay and associated factors among heart failure patients admitted to the medical ward of the University of Gondar Comprehensive Specialized Hospital from January 2019 to June 2020. Multiple linear regression was used to identify factors associated with length of hospital stay and reported with a 95% Confidence Interval (CI). P-value ≤ 0.05 was considered as statistically significant to declare the association.

RESULT

A total of 263 heart failure patients (mean age: 51.08 ± 19.24 years) were included. The mean length of hospital stay was 17.29 ± 7.27 days. Number of comorbidities (B = 1.494, p < 0.001), admission respiratory rate (B = -0.242, p = 0.009), serum potassium (B = -1.525, p = 0.005), third heart sound (B = -4.118, p = 0.005), paroxysmal nocturnal dyspnea (B = 2.494, p = 0.004), causes of acute heart failure; hypertensive heart disease (B = -6.349, p = 0.005), and precipitating factors of acute heart failure; infection (B = 2.867, p = 0.037) were significantly associated with length of hospital stay. Number of comorbidities, paroxysmal nocturnal dyspnea, and precipitating factors of AHF specifically infection were associated with a prolonged length of hospital stay.

CONCLUSION

Heart failure patients admitted to the medical ward had prolonged hospital stays. Thus, clinicians would be aware of the clinical features contributing to the longer hospital stay and implementation of interventions or strategies that could reduce the heart failure patient's hospital stay is necessary.

Utilization of Standard Therapy and Adjunctive Isosorbide Dinitrate Pump with Clinical Outcomes in Acute Heart Failure Patients

BACKGROUND: Acute heart failure is a life-threatening medical condition. Thus, effective therapy is very important for this case. Utilization of standard therapy and adjunctive isosorbide dinitrate (ISDN) pump play an important role in reducing mortality, length of hospitalization, and national early warning score – NEWS 2. However, the research on the utilization of the ISDN pump as adjunctive therapy is still limited. AIM: This study aimed to analyze the association between utilization of standard therapy and adjunctive ISDN pump with clinical outcomes (mortality, length of hospitalization, and NEWS 2) in patients with acute heart failure. METHODS: This was a cohort retrospective observational study. The purposive sampling technique was utilized to select the acute heart failure patients in UNS Sukoharjo Hospital. All the data were obtained from medical records. Logistic regression was used to analyze the data. RESULTS: A total of 94 patients were included as the samples. There was a significant association between the utilization of standard therapy (OR=7.9; CI 95%= 3.1–20.4; p < 0.001) or ISDN pump (OR=0.3; CI 95%= 0.1–0.7; p < 0.001) with the length of hospitalization. However, there was no significant association between the utilization of standard therapy (OR=1.1; CI 95%= 0.2–6.6; p = 0.9) and ISDN pump (OR=0.2; CI 95%= 0.02–1.6; p = 0.1) with NEWS 2 on patients with acute heart failure. CONCLUSION: There was a significant association between the utilization of standard therapy and ISDN pump with the length of hospitalization.

Network analytics and machine learning for predicting length of stay in elderly patients with chronic diseases at point of admission

Background

An aging population with a burden of chronic diseases puts increasing pressure on health care systems. Early prediction of the hospital length of stay (LOS) can be useful in optimizing the allocation of medical resources, and improving healthcare quality. However, the data available at the point of admission (PoA) are limited, making it difficult to forecast the LOS accurately.

Methods

In this study, we proposed a novel approach combining network analytics and machine learning to predict the LOS in elderly patients with chronic diseases at the PoA. Two networks, including multimorbidity network (MN) and patient similarity network (PSN), were constructed and novel network features were created. Five machine learning models (eXtreme Gradient Boosting, Gradient Boosting Decision Tree, Random Forest, Linear Support Vector Machine, and Deep Neural Network) with different input feature sets were developed to compare their performance.

Results

The experimental results indicated that the network features can bring significant improvements to the performances of the prediction models, suggesting that the MN and PSN are useful for LOS predictions.

Conclusion

Our predictive framework which integrates network science with data mining can forecast the LOS effectively at the PoA and provide decision support for hospital managers, which highlights the potential value of network-based machine learning in healthcare field.

Creatinine and NT-ProBNP levels could predict the length of hospital stay of patients with decompensated heart failure

BACKGROUND

Heart failure (HF) is a clinical syndrome that causes high morbidity and mortality with a high number of admissions and sometimes prolonged admissions. This study aimed at assessing whether parameters detected during the first 24 h of admission may predict a prolonged hospital stay in patients admitted to hospital for decompensated HF.

METHODS

From January 2016 to December 2019, 2359 admissions of decompensated HF were recorded. In-hospital transfers, de novo HF, deaths and scheduled admissions were discarded to homogenise the sample. Finally, 1196 patients were included. The sample was divided into two groups: (a) non-prolonged admission (n = 643, admission ≤7 days) or (b) prolonged admission (n = 553, admission >7 days). Clinical, analytical, electrocardiographic and echocardiographic variables obtained during the first 24 h of admission were analysed.

RESULTS

Univariate differences were found at admission in NT-ProBNP, creatinine, history of cardiac surgery, smoking and alcoholism, left and right ventricular ejection fraction, systolic blood pressure and heart rate. The ROC analysis showed significant areas under the curve for the NT-ProBNP (AUC: 0.63, 95% CI: 0.60-0.67; p < 0.001) and creatinine (AUC: 0.69, 95% CI: 0.66-0.72; p < 0.0001). The variables associated with prolonged hospital admission were NT-ProBNP (OR: 1, 95% CI: 1-1; p < 0.001), creatinine (OR: 2.2, 95% CI: 1.8-2.7; p < 0.0001) and previous smoking (OR: 1.5, 95% CI: 0.4-1; p < 0.02).

CONCLUSIONS

Variables such as creatinine and NT-ProBNP at hospital admission may define a subgroup of patients who will probably have a long hospital stay. Therefore, the planning of hospital care and transition to discharge may be enhanced.

Predicting length of stay and mortality among hospitalized patients with type 2 diabetes mellitus and hypertension

BACKGROUND

Type 2 diabetes mellitus (T2DM) and hypertension (HTN), both non-communicable diseases, are leading causes of death globally, with more imbalances in lower middle-income countries. Furthermore, poor treatment and management are known to lead to intensified healthcare utilization and increased medical care costs and impose a significant societal burden, in these countries, including Indonesia. Predicting future clinical outcomes can determine the line of treatment and value of healthcare costs, while ensuring effective patient care. In this paper, we present the prediction of length of stay (LoS) and mortality among hospitalized patients at a tertiary referral hospital in Tasikmalaya, Indonesia, between 2016 and 2019. We also aimed to determine how socio-demographic characteristics, and T2DM- or HTN-related comorbidities affect inpatient LoS and mortality.

METHODS

We analyzed insurance claims data of 4376 patients with T2DM or HTN hospitalized in the referral hospital. We used four prediction models based on machine-learning algorithms for LoS prediction, in relation to disease severity, physician-in-charge, room type, co-morbidities, and types of procedures performed. We used five classifiers based on multilayer perceptron (MLP) to predict inpatient mortality and compared them according to training time, testing time, and Area under Receiver Operative Curve (AUROC). Classifier accuracy measures, which included positive predictive value (PPV), negative predictive value (NPV), F-Measure, and recall, were used as performance evaluation methods.

RESULTS

A Random forest best predicted inpatient LoS (R2, 0.70; root mean square error [RMSE], 1.96; mean absolute error [MAE], 0.935), and the gradient boosting regression model also performed similarly (R2, 0.69; RMSE, 1.96; MAE, 0.935). For inpatient mortality, best results were observed using MLP with back propagation (AUROC 0.899; 69.33 and 98.61 for PPV and NPV, respectively). The other classifiers, stochastic gradient descent with regression loss function, Huber, and random forest models all showed an average performance.

CONCLUSIONS

Linear regression model best predicted LoS and mortality was best predicted using MLP. Patients with primary diseases such as T2DM or HTN may have comorbidities that can prolong inpatient LoS. Physicians play an important role in disseminating health related information. These predictions could assist in the development of health policies and strategies that reduce disease burden in resource-limited settings.

Determinants of Prolonged Length of Hospital Stay of Patients with Atrial Fibrillation

Background and Aim: The increasing prevalence and high hospitalization rates make atrial fibrillation (AF) a significant healthcare strain. However, there are limited data regarding the length of hospital stay (LOS) of AF patients. Our purpose was to determine the main drivers of extended LOS of AF patients. Methods: All AF patients, hospitalized consecutively in a tertiary cardiology center, from January 2018 to February 2020 were included in this retrospective cohort study. Readmissions were excluded. Prolonged LOS was defined as more than seven days (the upper limit of the third quartile). Results: Our study included 949 AF patients, 52.9% females. The mean age was 72.5 ± 10.3 years. The median LOS was 4 days. A total of 28.7% had an extended LOS. Further, 82.9% patients had heart failure (HF). In multivariable analysis, the independent predictors of extended LOS were: acute coronary syndromes (ACS) (HR 4.60, 95% CI 1.66–12.69), infections (HR 2.61, 95% CI 1.44–3.23), NT-proBNP > 1986 ng/mL (HR 1.96, 95% CI 1.37–2.82), acute decompensated HF (ADHF) (HR 1.76, 95% CI 1.23–2.51), HF with reduced ejection fraction (HFrEF) (HR 1.69, 95% CI 1.15–2.47) and the HAS-BLED score (HR 1.42, 95% CI 1.14–1.78). Conclusion: ACS, ADHF, HFrEF, increased NT-proBNP levels, infections and elevated HAS-BLED were independent predictors of extended LOS, while specific clinical or therapeutical AF characteristics were not.

Comparative role of hematological indices for the assessment of in-hospital outcome of heart failure patients

Background. The mutual relation between heart failure (HF) and inflammation is reflected in blood cell homeostasis. Neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR) and platelet-lymphocyte ratio (PLR) were linked to HF severity and prognosis. Aims. Our objective was to compare the three ratios for predicting in-hospital outcome of HF patients, in order to establish which is best suited for clinical practice. Methods. Consecutive HF patients admitted to a Cardiology Department from a tertiary hospital were retrospectively evaluated for inclusion. Readmissions and pathologies modifying the hematological indices were excluded. Extended length of hospital stay (LOS) was considered over 7 d. In-hospital all-cause mortality was evaluated. Results: The hematological indices in heart failure (HI-HF) cohort included 1299 patients with a mean age of 72.35 ± 10.45 years, 51.96% women. 2.85% died during hospitalization. 22.17% had extended LOS. In Cox regression for in-hospital mortality alongside parameters from the OPTIMIZE-HF proposed model, all three ratios were independent predictors of mortality. In Cox regression including NT-proBNP, dyspnea at rest, chronic obstructive pulmonary disease (COPD), age and systolic blood pressure, only MLR was an independent predictor of in-hospital mortality (HR 1.68, 95% CI 1.22 - 2.32, p = .002). In multivariable logistic regression, all three ratios independently predicted extended LOS. MLR > 0.48 associated the highest probability (OR 1.76, 95% CI 1.25 - 2.46, p = .001). Conclusions. Hematological indices could be cost-effective and easily available auxiliary biomarkers for in-hospital prognosis of HF patients. We propose MLR > 0.48 as the strongest predictor of in-hospital mortality and prolonged hospitalization.

Resource utilization and costs among patients with heart failure with reduced ejection fraction following a worsening heart failure event

Aims

The aim of this study is to characterize healthcare resource utilization and costs in patients with heart failure with reduced ejection fraction (HFrEF) following a worsening heart failure event.

Methods and results

This was a retrospective observational cohort analysis. Patients with HFrEF were identified from the PINNACLE Registry and linked to a nationwide pharmacy and medical claims database. Worsening heart failure was defined as stable heart failure with a subsequent hospitalization and/or intravenous diuretic therapy. Healthcare resource use and costs in 2015 US dollars were analysed for dispensed prescriptions, outpatient encounters, and hospital encounters. Among 11 064 patients with HFrEF, 3087 (27.9%) experienced a worsening heart failure event during an average follow‐up of 973 days. During the first 30 days after the worsening event, 19.8% of patients had hospital readmissions with heart failure as the primary or secondary diagnosis. During that same time period, mean per patient heart failure‐related healthcare resource use included 1.3 prescriptions, 0.5 practitioner visits, and 0.5 hospital encounters (admissions, observations, or emergency care), for an average total medical cost of $8779 per patient including $5359 in heart failure‐related costs. During the first year following worsening heart failure onset, mean per patient total and heart failure‐related costs were $62 615 and $35 329, respectively.

Conclusions

The economic burden following a worsening heart failure event calls for further review of methods to prevent progressive disease, improve adherence to guideline‐directed therapy, and develop novel treatments and care strategies to moderate further progression.

Length of hospital stay among oldest-old patients in acute geriatric ward

PURPOSE

To examine risk factors for prolonged hospital length of stay (LOS) in the oldest-old inpatients aged ≥ 90.

METHODS

This retrospective cross-sectional study was performed in acute Geriatrics Department at Kaplan Medical Center. The target population was the oldest-old inpatients aged ≥ 90 hospitalized with acute illness. In total 1536 admissions of 987 patients admitted between January 2007 and December 2010 from the emergency room were included in the study. We retrieved from the electronic hospital records the following data: demographics, admission diagnosis, comorbidities, laboratory tests, drugs, functional and cognitive status, Charlson Comorbidity Index (CCI) score and age-adjusted CCI score.

RESULTS

The risk factors for a prolonged LOS were tube-feeding, consumption of ≥ 5 drugs, non-independent functional status, diagnosis of urinary tract infection (UTI), pneumonia and malignancy on admission, and comorbidities of congestive heart failure (CHF) and hypoalbuminemia. Multiple linear regression analysis found that UTI, hypoalbuminemia, elevated troponin, pneumonia, number of drugs, malignancy, CHF and number of comorbidities explain a higher risk for a longer LOS.

CONCLUSION

Hospital LOS in the oldest-old patients in acute geriatric ward was associated with admission diagnosis and comorbidities. Awareness of the risk factors for a longer LOS might contribute to reducing hospitalization stay and its related negative consequences. Accurate prediction of prolonged LOS in this age group of patients may be more challenging and require variables that were not included in our study. Future research is warranted.

Clinical Predictors Influencing the Length of Stay in Emergency Department Patients Presenting with Acute Heart Failure

Background and objectives: Acute heart failure is a common problem encountered in the emergency department (ED). More than 80% of the patients with the condition subsequently require lengthy and repeated hospitalization. In a setting with limited in-patient capacity, the patient flow is often obstructed. Appropriate disposition decisions must be made by emergency physicians to deliver effective care and alleviate ED overcrowding. This study aimed to explore clinical predictors influencing the length of stay (LOS) in patients with acute heart failure who present to the ED. Materials and Methods: We conducted prognostic factor research with a retrospective cohort design. Medical records of patients with acute heart failure who presented to the ED of Ramathibodi Hospital from January to December 2015 were assessed for eligibility. Thirteen potential clinical predictors were selected as candidates for statistical modeling based on previous reports. Multivariable Poisson regression was used to estimate the difference in LOS between patients with and without potential predictors. Results: A total of 207 patients were included in the analysis. Most patients were male with a mean age of 74.2 ± 12.5 years. The median LOS was 54.6 h (Interquartile range 17.5, 149.3 h). From the multivariable analysis, four clinical characteristics were identified as independent predictors with an increase in LOS. These were patients with New York Heart Association (NYHA) functional class III/IV (+72.9 h, 95%Confidence interval (CI) 23.9, 121.8, p = 0.004), respiratory rate >24 per minute (+80.7 h, 95%CI 28.0, 133.3, p = 0.003), hemoglobin level <10 mg/dL (+60.4 h, 95%CI 8.6, 112.3, p = 0.022), and serum albumin <3.5 g/dL (+52.8 h, 95%CI 3.6, 102.0, p = 0.035). Conclusions: Poor NYHA functional class, tachypnea, anemia, and hypoalbuminemia are significant clinical predictors of patients with acute heart failure who required longer LOS.

Weight change in heart failure inpatients not associated with 30-day readmission

Background: The association of weight change and short-term readmission in patients hospitalized for heart failure (HF) has not been well studied. Methods: We collected clinical and weight data from patients admitted with decompensated HF to a single center (2012-2013). We performed logistic regression to determine the association between weight change and two outcomes: a total of 30-day HF-specific readmission and 30-day all-cause readmission. Results: Admission and discharge weights were documented in 479/658 patients (73%). Weight loss >2 kg was not associated with 30-day all-cause or HF-specific readmission when compared with more modest inpatient weight change (-2 kg to +2 kg; all-cause readmission odds ratio: 0.86; CI: 0.56-1.37; HF-specific readmission odds ratio: 1.15; CI: 0.61-2.16). Conclusion: Among HF inpatients, in-hospital weight loss was not associated with 30-day all-cause or HF-specific readmission.

Comparing inpatient costs of heart failure admissions for patients with reduced and preserved ejection fraction with or without type 2 diabetes

Both heart failure (HF) and diabetes mellitus (DM) account for major healthcare expenditures. We evaluated inpatient expenditures and cost drivers in patients admitted with HF with and without DM.

Methods

We created a retrospective cohort of acutely decompensated HF patients, using linked data from cost accounting systems and electronic medical records. We stratified patients by LVEF into reduced ejection fraction (HFrEF, LVEF ≤40%) and preserved ejection fraction (HFpEF, LVEF >40%) groups and by DM status at admission.

Results

Our population had 544 people: 285 HFrEF patients (43.5% with DM) and 259 HFpEF patients (43.6% with DM). Patients with HFrEF and DM had the longest hospital stay (5.10 ± 5.21 days). Patients with HFrEF and DM had the highest hospitalization cost ($11 576 ± 15 818). HFrEF and HFpEF patients with DM had the highest cost, and cost per day alive was highest for HFpEF patients with DM [$3153 (95% CI 2332, 4262)].

Conclusion

Overall cost was higher for patients with DM, whether or not they were admitted with acute HF due to HFrEF or HFpEF. Cost per day alive for patients with DM continued to exceed corresponding costs for patients without DM, with HFpEF patients with DM having the highest cost.

30-Day Potentially Preventable Hospital Readmissions In Older Patients: Clinical Phenotype And Health Care Related Risk Factors

Purpose

Early readmission rate has been regarded as an indicator of in-hospital and post-discharge quality of care. Evaluating the contributing factors is crucial to optimize the healthcare and target the intervention. In this study we evaluated the potential for preventing 30-day hospital readmission in a cohort of older patients and identified possible risk factors for readmission.

Patients and methods

Diagnosis-Related Group (DRG) codes of patients consecutively hospitalized for acute disease in the Geriatrics Unit of the University Hospital of Pisa within a 1-year window were recorded. All the patients had received a comprehensive geriatric assessment. Crossing and elaboration of the DRG codes was performed by the Potentially Preventable Readmission Grouping software (3M^™ Corporation). DRG codes were classified as stand-alone admissions (SA), index admissions (IA) and potentially preventable readmissions (PPR) within a time window of 30 days after discharge.

Results

In total, 1263 SA and 171 IA were identified, with an overall PPR rate of 11.9%. Hospitalizations were significantly longer in IA and PPR than SA (p<0.05). The more frequent readmission causes were acute heart failure, pulmonary edema, sepsis, pneumonia and stroke. In acute heart failure a nonlinear U-shaped readmission trend (with nadir at 5 days of hospitalization) was observed while, in all the other DRG codes, the PPR rate increased with increasing length of hospitalization. Comprehensive geriatric assessment showed a significantly lower degree of disability and comorbidity in SA than IA patients. At stepwise regression analysis, a high degree of disability and comorbidity as well as the diagnosis of sepsis emerged as independent risk factors for PPR.

Conclusion

Addressing PPR is crucial, especially in older patients. The adequacy of treatment during hospitalization (especially in cases of sepsis) as well as the setting of a comprehensive discharge plan, accounting for comorbidity and disability of the patients, are essential to reduce PPR.

Trends in Noncardiovascular Comorbidities Among Patients Hospitalized for Heart Failure: Insights From the Get With The Guidelines-Heart Failure Registry

BACKGROUND

The increase in medical complexity among patients hospitalized with heart failure (HF) may be reflected by an increase in concomitant noncardiovascular comorbidities. Among patients hospitalized with HF, the temporal trends in the prevalence of noncardiovascular comorbidities have not been well described.

METHODS AND RESULTS

We used data from 207 984 patients in the Get With The Guidelines-Heart Failure registry (from 2005 to 2014) to evaluate the prevalence and trends of noncardiovascular comorbidities (chronic obstructive pulmonary disorder/asthma, anemia, diabetes mellitus, obesity [body mass index ≥30 kg/m²], and renal impairment) among patients hospitalized with HF. Medicare beneficiaries aged ≥65 years were used to assess 30-day mortality. The prevalence of 0, 1, 2, and ≥3 noncardiovascular comorbidities was 18%, 30%, 27%, 25%, respectively. From 2005 to 2014, there was a decline in patients with 0 noncardiovascular comorbidities (22%-16%; P<0.0001) and an increase in patients with ≥3 noncardiovascular comorbidities (18%-29%; P<0.0001). Among Medicare beneficiaries, there was an increased 30-day adjusted mortality risk among patients with 1 noncardiovascular comorbidity (hazard ratio, 1.16; 95% confidence interval, 1.09-1.24; P<0.0001), 2 noncardiovascular comorbidities (hazard ratio, 1.34; 95% confidence interval, 1.25-1.44; P<0.0001), and ≥3 noncardiovascular comorbidities (hazard ratio, 1.63; 95% confidence interval, 1.51-1.75; P<0.0001). Similar trends were seen for in-hospital mortality.

CONCLUSIONS

Patients admitted in hospital for HF have an increasing number of noncardiovascular comorbidities over time, which are associated with worse outcomes. Strategies addressing the growing burden of noncardiovascular comorbidities may represent an avenue to improve outcomes and should be included in the delivery of in-hospital HF care.

In-hospital mortality is associated with high NT-proBNP level

Objective

To compare in-hospital mortality in unselected adult patients according to N-terminal pro-brain natriuretic peptide (NT-proBNP) levels.

Method

Retrospective study including 3833 adult patients (median age 72 years, 45% women) hospitalized between January 2013 and April 2015 in a Swiss university hospital, with at least one NT-proBNP level measurement during hospitalization. Patients were categorized in quintiles regarding their highest NT-proBNP level. In-hospital mortality and length of stay (LOS) were compared between the highest and the other quintiles.

Results

In-hospital mortality rate and LOS (average±standard deviation) were higher in the fifth quintile than in the others (6.5% vs 20.3%, and 20.8±24.0 vs. 14.9±26.5 days respectively, both p<0.001). After multivariate adjustment on age, gender, principal diagnoses, stage 5 renal failure and type of management, patients in the fifth quintile had a hazard ratio [95% confidence interval] of 1.97 [1.57–2.46] for in-hospital mortality and an adjusted LOS (average±standard error) of 20.4±1.0 vs. 14.9±0.5 days for the other quintiles (p<0.001). Further stratification on the main diagnosis at discharge led to similar findings.

Conclusion

Patients with high levels of NT-proBNP are at higher risk of in-hospital mortality and longer LOS, regardless of their clinical characteristics. NT-proBNP level can be a helpful tool for predicting in-hospital patient outcome in unselected adult patients.

Cost comparison across heart failure patients with reduced and preserved ejection fractions: Analyses of inpatient decompensated heart failure admissions

BACKGROUND

Heart failure (HF) is the leading cause of inpatient admissions in the US for adults aged over 65 years and accounts for more than $17 billion in Medicare expenditures annually. There are limited published data on factors influencing expenditure and the relationship between cost and hospital length of stay. We sought to describe institutional costs of HF hospitalization, as well as demographic and clinical predictors of higher hospitalization costs in an academic hospital setting.

METHODS AND RESULTS

Demographic and clinical information was collected retrospectively for 564 unique consecutive patients with a decompensated HF admission during 2010-2013. Forty-six percent had a baseline LVEF >40%, categorized as HF with preserved ejection fraction (HFpEF). Forty-three percent were female and the mean age was 71 years. Patients with reduced ejection fraction (HFrEF) were predominantly male, younger and had a lower burden of baseline comorbidities than HFpEF patients. Length of stay was longer for HFrEF (median 4 days) than HFpEF (median 3 days, p = 0.01). Mean total hospitalization cost was $9521. Mean costs trended higher for HFrEF patients than for HFpEF patients ($10,286 versus $8858, p = 0.07). Room and board contributed more than half of all costs.

CONCLUSIONS

In this single-center study, we observed a trend towards higher HF hospitalization costs for patients with HFrEF, compared to HFpEF, even though patients with HFpEF are older and had more comorbid conditions. Costs were largely driven by length of stay, with higher heart rate at admission, lower systolic blood pressure, and higher creatinine associated with higher inpatient costs.

Length of Hospital Stay Prediction at the Admission Stage for Cardiology Patients Using Artificial Neural Network

For hospitals' admission management, the ability to predict length of stay (LOS) as early as in the preadmission stage might be helpful to monitor the quality of inpatient care. This study is to develop artificial neural network (ANN) models to predict LOS for inpatients with one of the three primary diagnoses: coronary atherosclerosis (CAS), heart failure (HF), and acute myocardial infarction (AMI) in a cardiovascular unit in a Christian hospital in Taipei, Taiwan. A total of 2,377 cardiology patients discharged between October 1, 2010, and December 31, 2011, were analyzed. Using ANN or linear regression model was able to predict correctly for 88.07% to 89.95% CAS patients at the predischarge stage and for 88.31% to 91.53% at the preadmission stage. For AMI or HF patients, the accuracy ranged from 64.12% to 66.78% at the predischarge stage and 63.69% to 67.47% at the preadmission stage when a tolerance of 2 days was allowed.

Higher diuretic dosing within the first 72 h is predictive of longer length of stay in patients with acute heart failure

Objective:

High-dose diuretic strategies during the first 72 h of hospitalization have been shown to improve symptom resolution in patients with acute heart failure with decreased ejection fraction; however, they have not been shown to decrease length of stay (LOS). This study aimed to examine a possible relationship between higher diuretic dosing in the first 72 h of hospitalization and longer LOS in such patients.

Methods:

In this retrospective study, we included 333 consecutive patients hospitalized for acute heart failure with decreased or preserved ejection fraction between July 2014 and June 2015 in an urban academic medical center. Multiple regression models with stepwise selection were used for data analysis. We also performed mediation analysis to assess the relationships between diuretic dose, worsening renal function (WRF) during the hospitalization, and LOS.

Results:

In the multiple regression analysis, higher diuretic dosing in the first 72 h independently predicted longer LOS [β=0.42, 95% CI (0.27, 0.56), p<0.001] after adjustments for baseline characteristics, disease severity, and comorbidities. In the mediation analysis, higher diuretic dosing remained a significant predictor for longer LOS even after controlling for the mediator WRF [β=0.39, 95% CI (0.26, 0.53), p<0.001]. WRF had a weak mediation effect on the relationship between higher diuretic dosing and longer LOS [indirect effect of higher diuretic dosing on longer LOS: 0.07, 95% CI (0.02, 0.14)].

Conclusion:

Higher diuretic dosing in the first 72 h of hospitalization was an independent predictor for longer LOS.

Revision: review of non-elective hospitalisations of adults with CHD

Introduction The adult CHD population is increasing and ageing and remains at high risk for morbidity and mortality. In a retrospective single-centre study, we conducted a comprehensive review of non-elective hospitalisations of adults with CHD and explored factors associated with length of stay.

METHODS

We identified adults (⩾18 years) with CHD admitted during a 12-month period and managed by the adult CHD service. Data regarding demographics, cardiac history, hospital admission, resource utilisation, and length of stay were extracted.

RESULTS

There were 103 admissions of 91 patients (age 37±10 years; 52% female). Of 91 patients, 96% had moderate or complex defects. Of 103 admissions, 45% were through the emergency department. The most common reasons for admission were arrhythmia (37%) and heart failure (28%); 29% of admissions included a stay in the ICU. The mean number of consultations by other services was 2.0. Electrophysiology and anaesthesiology departments were most frequently consulted. After removing outliers, the mean length of stay was 7.9±7.4 days (median=5 days). The length of stay was longer for patients admitted for heart failure (12.2±10.3 days; p=0.001) and admitted directly to the ward (9.6±8.9 days; p=0.009).

CONCLUSIONS

Among non-electively hospitalised adults with CHD in a tertiary-care centre, management often entails an interdisciplinary approach, and the length of stay is longest for patients admitted with heart failure. The healthcare system must ensure optimal resources to maintain high-quality care for this expanding patient population.

Red Blood Cell Distribution Width: A Novel Predictive Indicator for Cardiovascular and Cerebrovascular Diseases

The red blood cell distribution width (RDW) obtained from a standard complete blood count (CBC) is a convenient and inexpensive biochemical parameter representing the variability in size of circulating erythrocytes. Over the past few decades, RDW with mean corpuscular volume (MCV) has been used to identify quite a few hematological system diseases including iron-deficiency anemia and bone marrow dysfunction. In recent years, many clinical studies have proved that the alterations of RDW levels may be associated with the incidence and prognosis in many cardiovascular and cerebrovascular diseases (CVDs). Therefore, early detection and intervention in time of these vascular diseases is critical for delaying their progression. RDW as a new predictive marker and an independent risk factor plays a significant role in assessing the severity and progression of CVDs. However, the mechanisms of the association between RDW and the prognosis of CVDs remain unclear. In this review, we will provide an overview of the representative literatures concerning hypothetical and potential epidemiological associations between RDW and CVDs and discuss the underlying mechanisms.

Current Management of Hyponatremia in Acute Heart Failure: A Report From the Hyponatremia Registry for Patients With Euvolemic and Hypervolemic Hyponatremia (HN Registry)

Background

Hyponatremia (HN) occurs commonly in patients with acute heart failure and confers a worse prognosis. Current HN treatment varies widely, with no consensus. This study recorded treatment practices currently used for patients hospitalized with acute heart failure and HN.

Methods and Results

Data were collected prospectively from 146 US sites on patients hospitalized with acute heart failure and HN (serum sodium concentration [Na⁺] ≤130 mEq/L) present at admission or developing in the hospital. Baseline variables, HN treatment, and laboratory values were recorded. Of 762 patients, median [Na⁺] was 126 mEq/L (interquartile range, 7) at baseline and increased to 130 mEq/L at discharge. Fluid restriction was the most commonly prescribed therapy (44%), followed by no specific HN treatment beyond therapy for congestion (23%), isotonic saline (5%), tolvaptan (4%), and hypertonic saline (2%). Median rate of change in [Na⁺] varied by treatment (0.5 [interquartile range, 1.0] to 2.3 [8.0] mEq/L/d) and median treatment duration ranged from 1 (interquartile range, 1) to 6 (5) days. Fluid restriction and no specific HN treatment resulted in similar changes in [Na⁺], and were least effective in correcting HN. Few patients (19%) had [Na⁺] ≥135 mEq/L at discharge.

Conclusions

The most commonly used treatment approaches for HN (fluid restriction and no specific treatment) in acute heart failure increased [Na⁺] minimally, and most patients remained hyponatremic at discharge.

Cancer Antigen 125 is Associated with Length of Stay in Patients with Acute Heart Failure

Length of stay is the primary driver of heart-failure hospitalization costs. Because cancer antigen 125 has been associated with poor morbidity and mortality rates in heart failure, we investigated the relationship between admission cancer antigen 125 levels and lengths of stay in heart-failure patients. A total of 267 consecutive patients (184 men, 83 women) with acute decompensated heart failure were evaluated prospectively. The median length of stay was 4 days, and the patients were classified into 2 groups: those with lengths of stay ≤4 days and those with lengths of stay >4 days. Patients with longer lengths of stay had a significantly higher cancer antigen 125 level of 114 U/mL (range, 9-298 U/mL) than did those with a shorter length of stay (19 U/mL; range; 3-68) (P <0.001). The optimal cutoff level of cancer antigen 125 in the prediction of length of stay was >48 U/mL, with a specificity of 95.8% and a sensitivity of 96% (area under the curve, 0.979; 95% confidence interval [CI], 0.953-0.992). In the multivariate logistic regression model, cancer antigen 125 >48 U/mL on admission (odds ratio=4.562; 95% CI, 1.826-11.398; P=0.001), sodium level (P<0.001), creatinine level (P=0.009), and atrial fibrillation (P=0.015) were also associated with a longer length of stay after adjustment for variables found to be statistically significant in univariate analysis and correlated with cancer antigen 125 level. In addition, it appears that in a cohort of patients with acute decompensated heart failure, cancer antigen 125 is independently associated with prolonged length of stay.

Right ventricular dysfunction as predictor of longer hospital stay in patients with acute decompensated heart failure: a prospective study in Indonesian population

BACKGROUND

Hospital length of stay (LOS) is a key determinant of heart failure hospitalization costs. Longer LOS is associated with lower quality of care measures and higher rates of readmission and mortality. Right ventricular (RV) dysfunction predicted poor outcomes in patients with stable chronic heart failure (CHF), however, its prognostic value in the acute decompensated heart failure (ADHF) patients has not been sufficiently clarified. This study investigated the prognostic value of RV dysfunction in predicting longer LOS in ADHF patients.

METHODS

A prospective cohort study was conducted in National Cardiovascular Center Harapan Kita to all patients admitted with ADHF. Clinical data and baseline RV function assessed by tricuspid annular plane systolic excursion (TAPSE) were collected. Clinical comorbidities including malnutrition, pneumonia and worsening renal function (WRF) were monitored during hospitalization. The primary outcome was hospital LOS. Cox regression analysis was used to identify independent predictors for longer LOS.

RESULTS

Two hundred and fifty-nine ADHF patients were included in this cohort study. On time-to-event analysis, diastolic blood pressure (HR = 1.011; 95 % CI = 1.004-1.018; p = 0.002), hemoglobin levels (HR = 1.102; 95 % CI = 1.045-1.162; p < 0.001), RV function (HR = 0.659; 95 % CI = 0.506-0.857; p = 0.002), WRF (HR = 2.015; 95 % CI = 1.520-2.670; p < 0.001) and malnutrition (HR = 5.965; 95 % CI = 4.402-8.082; p < 0.001) were associated with longer LOS. In a multivariate Cox regression model, RV function (HR = 0.466; 95 % CI = 0.238-0.915; p = 0.026), WRF (HR = 2.985; 95 % CI = 2.032-4.386; p < 0.001) and malnutrition (HR = 7.479; 95 % CI = 5.071-11.030; p < 0.001) were the independent predictors of longer hospital LOS. Based on the median TAPSE values, patients with TAPSE ≤ 16 mm had significantly longer LOS (HR = 2.227; 95 % CI = 1.103-4.494; p = 0.026) compared to those with TAPSE > 16 mm.

CONCLUSIONS

Right ventricular dysfunction, WRF and malnutrition are important predictors of longer LOS. This is the first study to describe that in ADHF patients, lower the TAPSE resulted in longer the LOS.

Comparison of Length of Stay, 30-Day Mortality, and 30-Day Readmission Rates in Medicare Patients With Heart Failure and With Reduced Versus Preserved Ejection Fraction

Length of stay (LOS), 30-day mortality, and 30-day readmission rates have not been compared between Medicare beneficiaries with heart failure (HF) with reduced ejection fraction (HFrEF) and beneficiaries with heart failure with preserved ejection fraction (HFpEF), although HFpEF is common in patients with HF. To determine whether type of HF (HFrEF or HFpEF) was associated with LOS, 30-day mortality, and 30-day readmission, we used a cohort of 19,477 Medicare beneficiaries admitted to the hospital and discharged alive with a primary discharge diagnosis of HF between 2007 and 2011. Gamma regression, Poisson regression, and Cox proportional hazards with a competing risk for death were used to model LOS, 30-day mortality, and 30-day readmission rate, respectively. All models were adjusted for HF severity, co-morbidities, demographics, nursing home residence, and calendar year of admission. Beneficiaries with HFpEF had an LOS 0.02 days shorter than beneficiaries with HFrEF and a nearly identical 30-day readmission rate. Thirty-day mortality was 10% lower in beneficiaries with HFpEF versus HFrEF. In conclusion, readmission rates were as high in those with HFpEF as they are in those with HFrEF, with comparable LOS in the hospital.

Constipation prophylaxis reduces length of stay in elderly hospitalized heart failure patients with home laxative use

BACKGROUND AND AIM

Elderly, hospitalized patients suffer disproportionately from constipation; however, little data suggest that constipation prophylaxis reduces length of stay (LOS). We performed a retrospective analysis of elderly patients admitted to our hospital with congestive heart failure (CHF) to determine the effects of constipation prophylaxis on LOS.

METHODS

Patients ≥ 65 years old admitted with the diagnosis of CHF in 2012 were evaluated for home and hospital laxative use on admission. Our primary outcome was LOS. We used linear regression modeling to independently evaluate the impact of constipation prophylaxis on LOS.

RESULTS

Among 618 patients who were eligible for our study, 201 (32.5%) were using laxatives at home, whereas 254 (41.1%) were started on a prophylactic laxative on admission. There was no significant difference in LOS between patients receiving prophylaxis versus those who did not (P = 0.32). Patients with home laxative use had a 1 day longer LOS compared to those without laxative use (6 vs 5, P = 0.03). Among patients with home laxative use, there were 2 days longer LOS in those who were not given constipation prophylaxis on admission (8 vs 6, P = 0.002). After multivariate adjustment, failure to use constipation prophylaxis in patients with home laxative use was the only independent predictor of increased LOS (P = 0.03).

CONCLUSIONS

Among elderly patients admitted for CHF exacerbations, failure to use constipation prophylaxis in patients with home laxative use is associated with a significantly longer LOS. Our data suggest that routine use of bowel prophylaxis for elderly CHF patients with preexisting constipation may reduce LOS.