Nationwide Estimates of 30-Day Readmission in Patients With Ischemic Stroke

Comparing the outcomes and costs of cardiac monitoring with implantable loop recorders and mobile cardiac outpatient telemetry following stroke using real-world evidence

Aim: Patients with ischemic stroke (IS) commonly undergo monitoring to identify atrial fibrillation with mobile cardiac outpatient telemetry (MCOT) or implantable loop recorders (ILRs). The authors compared readmission, healthcare cost and survival in patients monitored post-stroke with either MCOT or ILR. Materials & methods: The authors used claims data from Optum's de-identified Clinformatics® Data Mart Database to identify patients with IS hospitalized from January 2017 to December 2020 who were prescribed ambulatory cardiac monitoring via MCOT or ILR. They compared the costs associated with the initial inpatient visit as well as the rate and causes of readmission, survival and healthcare costs over the following 18 months. Datasets were balanced using patient baseline and hospitalization characteristics. Multivariable generalized linear gamma regression was used for cost comparisons. Cox proportional hazard regression was used for survival and readmission analysis. Sub-cohorts were analyzed based on the severity of the index IS. Results: In 2244 patients, readmissions were significantly lower in the MCOT monitored group (30.2%) compared with the ILR group (35.4%) (hazard ratio [HR] 1.23; 95% CI: 1.04-1.46). Average cost over 18 months starting with the index IS was $27,429 (USD) lower in the MCOT group (95% CI: $22,353-$32,633). Survival difference bordered on statistical significance and trended to lower mortality in MCOT (8.9%) versus ILR (11.3%) (HR 1.30; 95% CI: 1:00-1.69), led by significance in patients with complications or comorbidities with the index event (MCOT 7.5%, ILR 11.5%; HR 1.62; 95% CI: 1.11-2.36). Conclusion: The use of MCOT versus ILR as the primary monitor following IS was associated with significant decreases in readmission, lower costs for the initial IS and total care over the next 18 months, significantly lower mortality for patients with complications and comorbidities at the index stroke, and a trend toward improved survival across all patients.

Racial/Ethnic Differences in Association Between Medicaid Expansion and Causes and Costs of Readmission After Acute Ischemic Stroke

OBJECTIVE

The purpose of this study was to examine whether the relative frequency of leading causes and total associated costs of readmission after acute ischemic stroke changed with Medicaid expansion, and how these changes differed by racial/ethnic group.

METHODS

We used a difference-in-differences approach to compare changes in the relative frequency of leading causes of unplanned 30-day readmission and to examine changes in the costs associated with unplanned readmission between expansion states (AR, MD, NM, and WA) and non-expansion states (FL and GA). To estimate the differential effect of Medicaid expansion by race/ethnicity on the causes and cost of readmission, we added a time*treatment*race interaction. Multinomial logistic regression was performed to analyze the changes in readmission cause. Gamma log-link modeling was used to study changes in readmission costs for expansion compared to non-expansion states.

RESULTS

The final multinomial model showed an association between expanded Medicaid and the relative frequency of sepsis readmission for White patients. According to predictive margins, White patients in expansion states had an estimated increase of 3.3 percentage points in the share of readmissions for sepsis but not for White patients in non-expansion states. In contrast, non-White patients in expansion states had a decrease of 1.8 percentage points in the share of readmissions for sepsis. Overall, Medicaid expansion was associated with a net increase of 6.7 percentage points in the share of readmissions for sepsis among non-Hispanic Whites relative to all other groups. In the final gamma model, Medicaid expansion was associated with a decrease in readmission costs overall. According to predictive margins, the net cost reduction in expansion versus non-expansion states was an average of $2509.

CONCLUSIONS

Medicaid expansion is associated with an overall decrease in unplanned readmission costs and an increase among readmitted White patients in the likelihood of readmission for sepsis.

Causes and Predictors of 30-Day Readmission in Patients With Stroke Undergoing Mechanical Thrombectomy: A Large Single-Center Experience

BACKGROUND AND OBJECTIVES

The 30-day readmission rate has emerged as a metric of quality care and is associated with increased health care expenditure. We aim to identify the rate and causes of 30-day readmission after mechanical thrombectomy and provide the risk factors of readmission to highlight high-risk patients who may require closer care.

METHODS

This is a retrospective study from a prospectively maintained database of 703 patients presenting for mechanical thrombectomy between 2017 and 2023. All patients who presented with a stroke and underwent a mechanical thrombectomy were included in this study. Patients who were deceased on discharge were excluded from this study.

RESULTS

Our study comprised 703 patients, mostly female (n = 402, 57.2%) with a mean age of 70.2 years ±15.4. The most common causes of readmission were cerebrovascular events (stroke [n = 21, 36.2%], intracranial hemorrhage [n = 9, 15.5%], and transient ischemic attack [n = 1, 1.7%]).Other causes of readmission included cardiovascular events (cardiac arrest [n = 4, 6.9%] and bradycardia [n = 1, 1.7%]), infection (wound infection postcraniectomy [n = 3, 5.2%], and pneumonia [n = 1, 1.7%]). On multivariate analysis, independent predictors of 30-day readmission were history of smoking (odds ratio [OR]: 2.2, 95% CI: 1.1-4.2) P = .01), distal embolization (OR: 3.2, 95% CI: 1.1-8.7, P = .03), decompressive hemicraniectomy (OR: 9.3, 95% CI: 3.2-27.6, P < .01), and intracranial stent placement (OR: 4.6, 95% CI: 2.4-8.7) P < .01).

CONCLUSION

In our study, the rate of 30-day readmission was 8.3%, and the most common cause of readmission was recurrent strokes. We identified a history of smoking, distal embolization, decompressive hemicraniectomy, and intracranial stenting as independent predictors of 30-day readmission in patients with stroke undergoing mechanical thrombectomy.

Risk Perception Scale of Disease Aggravation for older patients with non-communicable diseases: Instrument development and cross-sectional validation study

AIM

The present study aimed to develop the Risk Perception Scale of Disease Aggravation for older patients with non-communicable diseases and evaluate its psychometric properties.

DESIGN

Instrument development and cross-sectional validation study were conducted.

METHODS

This study contained four phases. In phase I, a systematic literature review was conducted to identify the conception of disease aggravation and risk perception. In phase II, a draft scale was formulated from face-to-face semi-structured in-depth interviews by Colaizzi's seven-step qualitative analysis method and group discussions among the researchers. In phase III, domains and items of the scale were revised in accordance with the suggestions from Delphi consultation and patient feedback. In phase IV, psychometric properties were evaluated.

FINDINGS

Exploratory and confirmatory factor analyses determined four structural factors. Convergent and discriminant validities were acceptable because the average variance extracted coefficients ranged from .622 to .725, and the square roots of the average variance extracted coefficients for the four domains were larger than those of bivariate correlations between domains. The scale also exhibited excellent internal consistency and test-retest reliability (Cronbach's alpha coefficient = .973, intraclass correlation coefficient = .840).

CONCLUSIONS

Risk Perception Scale of Disease Aggravation is a new instrument that measures the risk perception of disease aggravation for older patients with non-communicable diseases, including possible reason, serious outcome, behaviour control and affection experience. The scale contains 40 items that are scored on a 5-point Likert scale, and it has acceptable validity and reliability.

IMPACT

The scale is applied to identify different levels of risk perception of disease aggravation for older patients with non-communicable diseases. Clinical nurses can provide targeted interventions to improve older patients' risk perception of disease aggravation based on levels of risk perception during hospitalization and the period before discharge.

PATIENT OR PUBLIC CONTRIBUTION

Experts provided suggestions for revising the scale dimensions and items. Older patients participated in the scale revision process to improve the wording of the scale.

Patient Readmission for Ischemic Stroke: Risk Factors and Impact on Mortality

Patient readmission for ischemic stroke significantly strains the healthcare and medical insurance systems. Current understanding of the risk factors associated with these readmissions, as well as their subsequent impact on mortality within China, remains insufficient. This is particularly evident in the context of comprehensive, contemporary population studies. This 4-year retrospective cohort study included 125 397 hospital admissions for ischemic stroke from 838 hospitals located in 22 regions (13 urban and 9 rural) of a major city in western China, between January 1, 2015 and December 31, 2018. The Chi-square tests were used in univariate analysis. Accounting for intra-subject correlations of patients' readmissions, accelerated failure time (AFT) shared frailty models were used to examine readmission events and pure AFT models for mortality. Risk factors for patient readmission after ischemic stroke include frequent admission history, male gender, employee's insurance, advanced age, residence in urban areas, index hospitalization in low-level hospitals, extended length of stay (LOS) during index hospitalization, specific comorbidities and subtypes of ischemic stroke. Furthermore, our findings indicated that an additional admission for ischemic stroke increased patient mortality by 16.4% (P < .001). Stroke readmission contributed to an increased risk of hospital mortality. Policymakers can establish more effective and targeted policies to reduce readmissions for stroke by controlling these risk factors.

Disparities in transitions of acute stroke care: The transitions of care stroke disparities study methodological report

OBJECTIVE

The Transitions of Stroke Care Disparities Study (TCSD-S) is an observational study designed to determine race-ethnic and sex disparities in post-hospital discharge transitions of stroke care and stroke outcomes and to develop hospital-level initiatives to reduce these disparities to improve stroke outcomes.

MATERIALS AND METHODS

Here, we present the study rationale, describe the methodology, report preliminary outcomes, and discuss a critical need for the development, implementation, and dissemination of interventions for successful post-hospital transition of stroke care. The preliminary outcomes describe the demographic, stroke risk factor, socioeconomic, and acute care characteristics of eligible participants by race-ethnicity and sex. We also report on all-cause and vascular-related death, readmissions, and hospital/emergency room representations at 30- and 90-days after hospital discharge.

RESULTS

The preliminary sample included data from 1048 ischemic stroke and intracerebral hemorrhage discharged from 10 comprehensive stroke centers across the state of Florida. The overall sample was 45% female, 22% Non-Hispanic Black and 21% Hispanic participants, with an average age of 64 ± 14 years. All cause death, readmissions, or hospital/emergency room representations are 10% and 19% at 30 and 90 days, respectively. One in 5 outcomes was vascular-related.

CONCLUSIONS

This study highlights the transition from stroke hospitalization as an area in need for considerable improvement in systems of care for stroke patients discharged from hospital. Results from our preliminary analysis highlight the importance of investigating race-ethnic and sex differences in post-stroke outcomes.

Rates and reasons for hospital readmission after acute ischemic stroke in a US population-based cohort

Hospital readmissions following stroke are costly and lead to worsened patient outcomes. We examined readmissions rates, diagnoses at readmission, and risk factors associated with readmission following acute ischemic stroke (AIS) in a large United States (US) administrative database. Using the 2019 Nationwide Readmissions Database, we identified adults discharged with AIS (ICD-10-CM I63*) as the principal diagnosis. Survival analysis with Weibull accelerated failure time regression was used to examine variables associated with hospital readmission. In 2019, 273,811 of 285,451 AIS patients survived their initial hospitalization. Of these, 60,831 (22.2%) were readmitted within 2019. Based on Kaplan Meyer analysis, readmission rates were 9.7% within 30 days and 30.5% at 1 year following initial discharge. The most common causes of readmissions were stroke and post stroke sequalae (25.4% of 30-day readmissions, 15.0% of readmissions between 30-364 days), followed by sepsis (10.3% of 30-day readmissions, 9.4% of readmissions between 30-364 days), and acute renal failure (3.2% of 30-day readmissions, 3.0% of readmissions between 30-364 days). After adjusting for multiple patient and hospital-level characteristics, patients at increased risk of readmission were older (71.6 vs. 69.8 years, p<0.001) and had longer initial lengths of stay (7.6 vs. 6.2 day, p<0.001). They more often had modifiable comorbidities, including vascular risk factors (hypertension, diabetes, atrial fibrillation), depression, epilepsy, and drug abuse. Social determinants associated with increased readmission included living in an urban (vs. rural) setting, living in zip-codes with the lowest median income, and having Medicare insurance. All factors were significant at p<0.001. Unplanned hospital readmissions following AIS were high, with the most common reasons for readmission being recurrent stroke and post stroke sequalae, followed by sepsis and acute renal failure. These findings suggest that efforts to reduce readmissions should focus on optimizing secondary stroke and infection prevention, particularly among older socially disadvantaged patients.

Hospital Discharge and Readmissions Before and During the COVID-19 Pandemic for California Acute Stroke Inpatients

BACKGROUND

Acute stroke therapy and rehabilitation declined during the COVID-19 pandemic. We characterized changes in acute stroke disposition and readmissions during the pandemic.

METHODS

We used the California State Inpatient Database in this retrospective observational study of ischemic and hemorrhagic stroke. We compared discharge disposition across a pre-pandemic period (January 2019 to February 2020) to a pandemic period (March to December 2020) using cumulative incidence functions (CIF), and re-admission rates using chi-squared.

RESULTS

There were 63,120 and 40,003 stroke hospitalizations in the pre-pandemic and pandemic periods, respectively. Pre-pandemic, the most common disposition was home [46%], followed by skilled nursing facility (SNF) [23%], and acute rehabilitation [13%]. During the pandemic, there were more home discharges [51%, subdistribution hazard ratio 1.17, 95% CI 1.15-1.19], decreased SNF discharges [17%, subdistribution hazard ratio 0.70, 95% CI 0.68-0.72], and acute rehabilitation discharges were unchanged [CIF, p<0.001]. Home discharges increased with increasing age, with an increase of 8.2% for those ≥85 years. SNF discharges decreased in a similar distribution by age. Thirty-day readmission rates were 12.7 per 100 hospitalizations pre-pandemic compared to 11.6 per 100 hospitalizations during the pandemic [p<0.001]. Home discharge readmission rates were unchanged between periods. Readmission rates for discharges to SNF (18.4 vs. 16.7 per 100 hospitalizations, p=0.003) and acute rehabilitation decreased (11.3 vs. 10.1 per 100 hospitalizations, p=0.034).

CONCLUSIONS

During the pandemic a greater proportion of patients were discharged home, with no change in readmission rates. Research is needed to evaluate the impact on quality and financing of post-hospital stroke care.

Stroke nurse navigator utilization reduces unplanned 30-day readmission in stroke patients treated with thrombolysis

Background

Unplanned 30-day hospital readmissions following a stroke is a serious quality and safety issue in the United States. The transition period between the hospital discharge and ambulatory follow-up is viewed as a vulnerable period in which medication errors and loss of follow-up plans can potentially occur. We sought to determine whether unplanned 30-day readmission in stroke patients treated with thrombolysis can be reduced with the utilization of a stroke nurse navigator team during the transition period.

Methods

We included 447 consecutive stroke patients treated with thrombolysis from an institutional stroke registry between January 2018 and December 2021. The control group consisted of 287 patients before the stroke nurse navigator team implementation between January 2018 and August 2020. The intervention group consisted of 160 patients after the implementation between September 2020 and December 2021. The stroke nurse navigator interventions included medication reviews, hospitalization course review, stroke education, and review of outpatient follow-ups within 3 days following the hospital discharge.

Results

Overall, baseline patient characteristics (age, gender, index admission NIHSS, and pre-admission mRS), stroke risk factors, medication usage, and length of hospital stay were similar in control vs. intervention groups (P > 0.05). Differences included higher mechanical thrombectomy utilization (35.6 vs. 24.7%, P = 0.016), lower pre-admission oral anticoagulant use (1.3 vs. 5.6%, P = 0.025), and less frequent history of stroke/TIA (14.4 vs. 27.5%, P = 0.001) in the implementation group. Based on an unadjusted Kaplan-Meier analysis, 30-day unplanned readmission rates were lower during the implementation period (log-rank P = 0.029). After adjustment for pertinent confounders including age, gender, pre-admission mRS, oral anticoagulant use, and COVID-19 diagnosis, the nurse navigator implementation remained independently associated with lower hazards of unplanned 30-day readmission (adjusted HR 0.48, 95% CI 0.23-0.99, P = 0.046).

Conclusion

The utilization of a stroke nurse navigator team reduced unplanned 30-day readmissions in stroke patients treated with thrombolysis. Further studies are warranted to determine the extent of the results of stroke patients not treated with thrombolysis and to better understand the relationship between resource utilization during the transition period from discharge and quality outcomes in stroke.

An interpretable machine learning approach for predicting 30-day readmission after stroke

BACKGROUND

Stroke is the second leading cause of death worldwide and has a significantly high recurrence rate. We aimed to identify risk factors for stroke recurrence and develop an interpretable machine learning model to predict 30-day readmissions after stroke.

METHODS

Stroke patients deposited in electronic health records (EHRs) in Xuzhou Medical University Hospital between February 1, 2021, and November 30, 2021, were included in the study, and deceased patients were excluded. We extracted 74 features from EHRs, and the top 20 features (chi-2 value) were used to build machine learning models. 80% of the patients were used for pre-training. Subsequently, a 20% holdout dataset was used for verification. The Shapley Additive exPlanations (SHAP) method was used to explore the interpretability of the model.

RESULTS

The cohort included 6,558 patients, of whom the mean (SD) age was 65 (11) years, 3,926 were males (59.86 %), and 132 (2.01 %) were readmitted within 30 days. The area under the receiver operating characteristic curve (AUROC) for the optimized model was 0.80 (95 % CI 0.68-0.80). We used the SHAP method to identify the top 10 risk factors (i.e., severe carotid artery stenosis, weak, homocysteine, glycosylated hemoglobin, sex, lymphocyte percentage, neutrophilic granulocyte percentage, urine glucose, fresh cerebral infarction, and red blood cell count). The AUROC of a model with the 10 features was 0.80 (95 % CI 0.69-0.80) and was not significantly different from that of the model with 20 risk factors.

CONCLUSIONS

Our methods not only showed good performance in predicting 30-day readmissions after stroke but also revealed risk factors that provided valuable insights for treatments.

Investigating the effect of implementing a program based on transitional care model on the quality of life and the ability of doing activities of daily living among patients with stroke

BACKGROUND

Stroke is one of the major causes of disability among individuals. Transitional care of a stroke patient can contribute to sustaining and enhancing the quality of care. The aim of this study is to determine the effect of implementing a program based on the transitional care model on the quality of life and ability of doing daily activities among patients suffering from stroke.

MATERIALS AND METHODS

This research was an interventional study performed on 80 patients with stroke referring to the hospitals affiliated with Isfahan University of medical sciences. For data collection, demographic, quality of life measurement following stroke, and Bartell index of daily activity measurement questionnaires were used at the beginning of the study and 10 weeks following discharge. The transitional care model was undertaken for the intervention group from the second day of hospitalization until 10 weeks postdischarge. The data were analyzed using SPSS software and statistical methods.

RESULTS

The results indicated that the mean quality of life and ability of performing the activities changed significantly after the intervention between the two groups, with the mean changes of these scores becoming significant compared to the preintervention between the two groups (P < 0.05). In both groups, the mean value of these scores increased after the study compared to the baseline, though this increase was greater in the intervention group.

CONCLUSION

Implementing the transitional care model could contribute to improving the quality of life and performing the daily activities among stroke patients.

Association between the LACE+ index and unplanned 30-day hospital readmissions in hospitalized patients with stroke

Background

The LACE+ index is used to predict unplanned 30-day hospital readmissions, but its utility to predict 30-day readmission in hospitalized patients with stroke is unknown.

Methods

We retrospectively analyzed 1,657 consecutive patients presenting with ischemic or hemorrhagic strokes, included in an institutional stroke registry between January 2018 and August 2020. The primary outcome of interest was unplanned 30-day readmission for any reason after index hospitalization for stroke. The 30-day readmission risk was categorized by LACE+ index to high risk (≥78), medium-to-high risk (59–77), medium risk (29–58), and low risk (≤ 28). Kaplan-Meier analysis, Log rank test, and multivariable Cox regression analysis (with backward elimination) were used to determine whether the LACE+ score was an independent predictor for 30-day unplanned readmission.

Results

The overall 30-day unplanned readmission rate was 11.7% (194/1,657). The median LACE+ score was higher in the 30-day readmission group compared to subjects that had no unplanned 30-day readmission [74 (IQR 67–79) vs. 70 (IQR 62–75); p < 0.001]. On Kaplan-Meier analysis, the high-risk group had the shortest 30-day readmission free survival time as compared to medium and medium-to-high risk groups (p < 0.01, each; statistically significant). On fully adjusted multivariable Cox-regression, the highest LACE+ risk category was independently associated with the unplanned 30-day readmission risk (per point: HR 1.67 95%CI 1.23–2.26, p = 0.001).

Conclusion

Subjects in the high LACE+ index category had a significantly greater unplanned 30-day readmission risk after stroke as compared to lower LACE+ risk groups. This supports the validity of the LACE+ scoring system for predicting unplanned readmission in subjects with stroke. Future studies are warranted to determine whether LACE+ score-based risk stratification can be used to devise early interventions to mitigate the risk for unplanned readmission.

Implementation of an Advanced Practice Registered Nurse-Led Clinic to Improve Follow-up Care for Post-Ischemic Stroke Patients

ABSTRACT

BACKGROUND: Ischemic stroke continues to be a leading cause of serious disability within the United States, affecting 795 000 people annually. Approximately 12% to 21% of post-ischemic stroke patients will be readmitted to the hospital within 30 days of discharge. Studies suggest that implementation of a follow-up appointment within 7 to 14 days of discharge improves 30-day readmission rates; however, implementation of these guidelines is uncommon, and follow-up visits within the recommended window are not often achieved. The purpose of this project was to evaluate the impact of an advanced practice registered nurse (APRN)-led stroke clinic on follow-up care for post-ischemic stroke patients. The aims were to improve time to follow-up visit and reduce 30-day unplanned readmissions. METHODS: A pre/post intervention design was used to evaluate the impact of a process to access the APRN-led stroke clinic. The intervention included a scheduling process redesign, and subsequent APRN and scheduler education. RESULTS: The time to clinic follow-up preintervention averaged 116.9 days, which significantly reduced to 33.6 days post intervention, P = .0001. Unplanned readmissions within 30 days declined from 11.5% to 9.9%; however, it was not statistically significant, P = .149. Age was not statistically different between preintervention and postintervention groups, P = .092, and other demographics were similar between the groups. CONCLUSION: An APRN-led clinic can improve follow-up care and may reduce unplanned 30-day readmissions for post-ischemic stroke patients. Further work is needed to determine the impact of alternative approaches such as telehealth.

TASC (Telehealth After Stroke Care): a study protocol for a randomized controlled feasibility trial of telehealth-enabled multidisciplinary stroke care in an underserved urban setting

Background

Hypertension is the most important modifiable risk factor for recurrent stroke, and blood pressure (BP) reduction is associated with decreased risk of stroke recurrence. However, hypertension remains poorly controlled in many stroke survivors. Black and Hispanic patients have a higher prevalence of uncontrolled BP and higher rates of stroke. Limited access to care contributes to challenges in post-stroke care. Telehealth After Stroke Care (TASC) is a telehealth intervention that integrates remote BP monitoring (RBPM) including nursing telephone support, tailored BP infographics and telehealth video visits with a multidisciplinary team approach including pharmacy to improve post-stroke care and reduce stroke disparities.

Methods

In this pilot trial, 50 acute stroke patients with hypertension will be screened for inclusion prior to hospital discharge and randomized to usual care or TASC. Usual care patients will be seen by a primary care nurse practitioner at 1–2 weeks and a stroke neurologist at 1 and 3 months. In addition to these usual care visits, TASC intervention patients will see a pharmacist at 4 and 8 weeks and will be enrolled in RBPM consisting of home BP monitoring with interval calls by a centralized team of telehealth nurses. As part of RBPM, TASC patients will be provided with a home BP monitoring device and electronic tablet that wirelessly transmits home BP data to the electronic health record. They will also receive tailored BP infographics that help explain their BP readings. The primary outcome will be feasibility including recruitment, adherence to at least one video visit and retention rates. The clinical outcome for consideration in a subsequent trial will be within-patient change in BP from baseline to 3 months after discharge. Secondary outcomes will be medication adherence self-efficacy and satisfaction with post-stroke telehealth, both measured at 3 months. Additional patient reported outcomes will include depression, cognitive function, and socioeconomic determinants. Multidisciplinary team competency and fidelity measures will also be assessed.

Conclusions

Integrated team-based interventions may improve BP control and reduce racial/ethnic disparities in post-stroke care. TASC is a post-acute stroke care model that is novel in providing RBPM with tailored infographics, and a multidisciplinary team approach including pharmacy. Our pilot will determine if such an approach is feasible and effective in enhancing post-stroke BP control and promoting self-efficacy.

Trial registration

ClinicalTrials.gov NCT04640519

Supplementary Information

The online version contains supplementary material available at 10.1186/s40814-022-01025-z.

High Risk Features Contributing to 30-Day Readmission After Acute Ischemic Stroke: A Single Center Retrospective Case-Control Study

BACKGROUND AND PURPOSE

Risk of 30-day stroke readmission has been attributed to medical comorbidities, stroke severity, and hospitalization metrics. The leading etiologies appear to vary across institutions and remain a moving target. We hypothesized that patients with increased medical complexity have higher odds of 30-day readmission and the immediate time after discharge may be most vulnerable. We aimed to characterize patients with 30-day readmission after acute ischemic stroke (IS) and identify predictors of post-IS readmission.

METHODS

We performed a retrospective case-control study analyzing post-IS 30-day readmission between January 2016-December 2019 using data from Mount Sinai Hospital's Get With The Guidelines database. We performed chi square analyses and multivariate adjusted logistic regression model including age, sex, coronary artery disease (CAD), renal insufficiency (RI), history of prior stroke or TIA, length of stay (LOS) > 7, and NIHSS ≥ 5.

RESULTS

6.7% (n = 115) of 1,706 IS encounters had 30-day readmission. The 115 cases were compared to 1,591 controls without 30-day readmission. In our adjusted model, CAD (OR = 1.7, p = 0.01), history of prior stroke or TIA (OR = 1.6, p = 0.01), LOS >7 (OR = 1.7, p = 0.02), and NIHSS ≥ 5 (OR = 4.5, p < 0.001) predicted 30-day readmission. 65% (n = 75) of readmitted patients had readmission within 14 days post-discharge.

CONCLUSIONS

Patients with post-IS 30-day readmission were more likely to have complex medical comorbidities and history of stroke or TIA compared to controls. Patients with more severe stroke and longer LOS may benefit from individualized transition of care plans and closer follow up during the vulnerable 30-day post-stroke period.

Hospital Readmissions and Mortality Among Fee-for-Service Medicare Patients With Minor Stroke or Transient Ischemic Attack: Findings From the COMPASS Cluster-Randomized Pragmatic Trial

Background Mortality and hospital readmission rates may reflect the quality of acute and postacute stroke care. Our aim was to investigate if, compared with usual care (UC), the COMPASS-TC (Comprehensive Post-Acute Stroke Services Transitional Care) intervention (INV) resulted in lower all-cause and stroke-specific readmissions and mortality among patients with minor stroke and transient ischemic attack discharged from 40 diverse North Carolina hospitals from 2016 to 2018. Methods and Results Using Medicare fee-for-service claims linked with COMPASS cluster-randomized trial data, we performed intention-to-treat analyses for 30-day, 90-day, and 1-year unplanned all-cause and stroke-specific readmissions and all-cause mortality between INV and UC groups, with 90-day unplanned all-cause readmissions as the primary outcome. Effect estimates were determined via mixed logistic or Cox proportional hazards regression models adjusted for age, sex, race, stroke severity, stroke diagnosis, and documented history of stroke. The final analysis cohort included 1069 INV and 1193 UC patients (median age 74 years, 80% White, 52% women, 40% with transient ischemic attack) with median length of hospital stay of 2 days. The risk of unplanned all-cause readmission was similar between INV versus UC at 30 (9.9% versus 8.7%) and 90 days (19.9% versus 18.9%), respectively. No significant differences between randomization groups were seen in 1-year all-cause readmissions, stroke-specific readmissions, or mortality. Conclusions In this pragmatic trial of patients with complex minor stroke/transient ischemic attack, there was no difference in the risk of readmission or mortality with COMPASS-TC relative to UC. Our study could not conclusively determine the reason for the lack of effectiveness of the INV. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02588664.

Socio-demographic and -economic factors associated with 30-day readmission for conditions targeted by the hospital readmissions reduction program: a population-based study

Background

Early hospital readmissions remain common in patients with conditions targeted by the CMS Hospital Readmission Reduction Program (HRRP). There is still no consensus on whether readmission measures should be adjusted based on social factors, and there are few population studies within the U.S. examining how social characteristics influence readmissions for HRRP-targeted conditions. The objective of this study was to determine if specific socio-demographic and -economic factors are associated with 30-day readmissions in HRRP-targeted conditions: acute exacerbation of chronic obstructive pulmonary disease, pneumonia, acute myocardial infarction, and heart failure.

Methods

The Nationwide Readmissions Database was used to identify patients admitted with HRRP-targeted conditions between January 1, 2010 and September 30, 2015. Stroke was included as a control condition because it is not included in the HRRP. Multivariate models were used to assess the relationship between three social and economic characteristics (gender, urban/rural hospital designation, and estimated median household income within the patient’s zip code) and 30-day readmission rates using a hierarchical two-level logistic model. Age-adjusted models were used to assess relationship differences between Medicare vs. non-Medicare populations.

Results

There were 19,253,997 weighted index hospital admissions for all diagnoses and 3,613,488 30-day readmissions between 2010 and 2015. Patients in the lowest income quartile (≤$37,999) had an increased odds of 30-day readmission across all conditions (P < 0.0001). Female gender and rural hospital designation were associated with a decreased odds of 30-day readmission for most targeted conditions (P < 0.05). Similar findings were also seen in patients ≥65 years old.

Conclusions

Socio-demographic and -economic factors are associated with 30-day readmission rates and should be incorporated into tools or interventions to improve discharge planning and mitigate against readmission.

Correlations Between Physician and Hospital Stroke Thrombectomy Volumes and Outcomes: A Nationwide Analysis

[Figure: see text].

Idiopathic Intracranial Hypertension: Evaluation of Admissions and Emergency Readmissions through the Hospital Episode Statistic Dataset between 2002-2020

With increasing incidence and prevalence of Idiopathic intracranial hypertension in the UK, the aim of this study was to explore emerging themes in Idiopathic intracranial hypertension using the Hospital Episode Statistics dataset and to quantify recent change in hospital admissions and surgeries performed within England.

METHODS

Hospital Episode Statistics national data was extracted between 1 April 2002 and 31 March 2019, and followed up until 31 March 2020. All those within England with a diagnosis of Idiopathic Intracranial Hypertension were included. Those with secondary causes of raised intracranial pressure such as tumors, hydrocephalus and cerebral venous sinus thrombosis were excluded.

RESULTS

28,794 new IIH cases were diagnosed between 1 January 2002 and 31 December 2019. Incidence rose between 2002 to 2019 from 1.8 to 5.2 per 100,000 in the general population. Peak incidence occurred in females aged 25-29 years. Neurosurgical shunt was the commonest procedure performed (6.4%), followed by neovascular venous sinus stenting (1%), bariatric surgery (0.8%) and optic nerve sheath fenestration (0.5%). The portion of the total IIH population requiring a shunt fell from 10.8% in 2002/2003 to 2.46% in 2018/2019. The portion of the total IIH population requiring shunt revision also reduced over time from 4.84% in 2002/2003 to 0.44% in 2018/2019. The mean 30 days emergency readmissions for primary shunt, revision of shunt, bariatric surgery, neurovascular stent, and optic nerve sheath fenestration was 23.1%, 23.7%, 10.6%, 10.0% and 9.74%, respectively. There was a peak 30 days readmission rate following primary shunt in 2018/2019 of 41%. Recording of severe visual impairment fell to an all-time low of 1.38% in 2018/19.

CONCLUSIONS

Increased awareness of the condition, specialist surgery and expert guidance may be changing admissions and surgical trends in IIH. The high 30 readmission following primary shunt surgery for IIH requires further investigation.

Discharge Against Medical Advice in Acute Ischemic Stroke: the Risk of 30-Day Unplanned Readmission

BACKGROUND

Discharge against medical advice may be associated with more readmissions.

OBJECTIVE

To evaluate DAMA in patients with acute ischemic stroke (AIS) and identify the relationship between DAMA and 30-day unplanned readmissions.

DESIGN

A retrospective cohort study.

PARTICIPANTS

The National Readmission Database was used to identify inpatients with a primary diagnosis of AIS who were either discharged home or DAMA between 2010 and 2017 in the USA.

MEASURES

Demographic features, hospital type, comorbidities, stroke risk factors, severity indices, and treatments were compared between patients discharged routinely and DAMA. Multivariable logistic regression was used to evaluate predictors of DAMA, and a double robust inverse probability of treatment weighting method was used to assess the association between DAMA and 30-day unplanned readmissions.

KEY RESULTS

Overall, 1,335,484 patients with AIS were included, of whom 2.09% (n = 27,892) were DAMA. The prevalence of DAMA in AIS patients increased from 1.65 in 2010 to 2.57% in 2017. The rates of 30-day unplanned readmissions for DAMA and non-DAMA patients were 16.81% and 7.78%, respectively. Patients with drug abuse, alcohol abuse, smoking, prior stroke, psychoses, and intravenous thrombolysis had greater odds of DAMA. DAMA was associated with all-cause readmissions (OR, 2.04; 95% CI, 2.01-2.07) and remained a strong predictor for transient ischemic attack/stroke-specific and cardiac-specific causes of readmissions.

CONCLUSIONS

Although the DAMA rate is low in AIS patients, DAMA is a risk factor for all-cause and recurrent stroke-specific readmissions. Future studies are needed to address issues around compliance and engagement with health care to reduce DAMA.

Care of the Patient With Acute Ischemic Stroke (Posthyperacute and Prehospital Discharge): Update to 2009 Comprehensive Nursing Care Scientific Statement: A Scientific Statement From the American Heart Association

In 2009, the American Heart Association/American Stroke Association published a comprehensive scientific statement detailing the nursing care of the patient with an acute ischemic stroke through all phases of hospitalization. The purpose of this statement is to provide an update to the 2009 document by summarizing and incorporating current best practice evidence relevant to the provision of nursing and interprofessional care to patients with ischemic stroke and their families during the acute (posthyperacute phase) inpatient admission phase of recovery. Many of the nursing care elements are informed by nurse-led research to embed best practices in the provision and standard of care for patients with stroke. The writing group comprised members of the Stroke Nursing Committee of the Council on Cardiovascular and Stroke Nursing and the Stroke Council. A literature review was undertaken to examine the best practices in the care of the patient with acute ischemic stroke. The drafts were circulated and reviewed by all committee members. This statement provides a summary of best practices based on available evidence to guide nurses caring for adult patients with acute ischemic stroke in the hospital posthyperacute/intensive care unit. In many instances, however, knowledge gaps exist, demonstrating the need for continued nurse-led research on care of the patient with acute ischemic stroke.

Better nurse work environments associated with fewer readmissions and shorter length of stay among adults with ischemic stroke: A cross-sectional analysis of United States hospitals

Stroke is among the most common reasons for disability and death. Avoiding readmissions and long lengths of stay among ischemic stroke patients has benefits for patients and health care systems alike. Although reduced readmission rates among a variety of medical patients have been associated with better nurse work environments, it is unknown how the work environment might influence readmissions and length of stay for ischemic stroke patients. Using linked data sources, we conducted a cross-sectional analysis of 543 hospitals to evaluate the association between the nurse work environment and readmissions and length of stay for 175,467 hospitalized adult ischemic stroke patients. We utilized logistic regression models for readmission to estimate odds ratios (OR) and zero-truncated negative binomial models for length of stay to estimate the incident-rate ratio (IRR). Final models accounted for hospital and patient characteristics. Seven and 30-day readmission rates were 3.9% and 10.1% respectively and the average length of stay was 4.9 days. In hospitals with better nurse work environments ischemic stroke patients experienced lower odds of 7- and 30-day readmission (7-day OR, 0.96; 95% confidence interval [CI]: 0.93-0.99 and 30-day OR, 0.97; 95% CI: 0.94-0.99) and lower length of stay (IRR, 0.97; 95% CI: 0.95-0.99). The work environment is a modifiable feature of hospitals that should be considered when providing comprehensive stroke care and improving post-stroke outcomes.

Risk of 28-day readmissions among stroke patients in Malaysia (2008-2015): Trends, causes and its associated factors

BACKGROUND AND OBJECTIVES

Risk of readmissions is an important quality indicator for stroke care. Such information is limited among low- and middle-income countries. We assessed the trends for 28-day readmissions after a stroke in Malaysia from 2008 to 2015 and evaluated the causes and factors associated with readmissions in 2015.

METHODS

Using the national hospital admission records database, we included all stroke patients who were discharged alive between 2008 and 2015 for this secondary data analysis. The risk of readmissions was described in proportion and trends. Reasons were coded according to the International Classification of Diseases, 10th Edition. Multivariable logistic regression was performed to identify factors associated with readmissions.

RESULTS

Among 151729 patients, 11 to 13% were readmitted within 28 days post-discharge from their stroke events each year. The trend was constant for ischemic stroke but decreasing for hemorrhagic stroke. The leading causes for readmissions were recurrent stroke (32.1%), pneumonia (13.0%) and sepsis (4.8%). The risk of 28-day readmission was higher among those with stroke of hemorrhagic (adjusted odds ratio (AOR): 1.52) and subarachnoid hemorrhage (AOR: 2.56) subtypes, and length of index admission >3 days (AOR: 1.48), but lower among younger age groups of 35-64 (AORs: 0.61-0.75), p values <0.001.

CONCLUSION

The risk of 28-day readmission remained constant from 2008 to 2015, where one in eight stroke patients required readmission, mainly attributable to preventable causes. Age, ethnicity, stroke subtypes and duration of the index admission influenced the risk of readmission. Efforts should focus on minimizing potentially preventable admissions, especially among those at higher risk.

Medicaid Expansion and Racial/Ethnic Differences in Readmission After Acute Ischemic Stroke

To examine whether rates of 30-day readmission after acute ischemic stroke changed differentially between Medicaid expansion and non-expansion states, and whether race/ethnicity moderated this change, we conducted a difference-in-differences analysis using 6 state inpatient databases (AR, FL, GA, MD, NM, and WA) from the Healthcare Cost and Utilization Project. Analysis included all patients aged 19-64 hospitalized in 2012–2015 with a principal diagnosis of ischemic stroke and a primary payer of Medicaid, self-pay, or no charge, who resided in the state where admitted and were discharged alive (N=28 330). No association was detected between Medicaid expansion and readmission overall, but there was evidence of moderation by race/ethnicity. The predicted probability of all-cause readmission among non-Hispanic White patients rose an estimated 2.6 percentage points (or 39%) in expansion states but not in non-expansion states, whereas it increased by 1.5 percentage points (or 23%) for non-White and Hispanic patients in non-expansion states. Therefore, Medicaid expansion was associated with a rise in readmission probability that was 4.0 percentage points higher for non-Hispanic Whites compared to other racial/ethnic groups, after adjustment for covariates. Similar trends were observed when unplanned and potentially preventable readmissions were isolated. Among low-income stroke survivors, we found evidence that 2 years of Medicaid expansion promoted rehospitalization, but only for White patients. Future studies should verify these findings over a longer follow-up period.

A Machine Learning Approach to Predicting Readmission or Mortality in Patients Hospitalized for Stroke or Transient Ischemic Attack

Readmissions after stroke are not only associated with greater levels of disability and a higher risk of mortality but also increase overall medical costs. Predicting readmission risk and understanding its causes are thus essential for healthcare resource allocation and quality improvement planning. By using machine learning techniques on initial admission data, this study aimed to develop prediction models for readmission or mortality after stroke. During model development, resampling methods were implemented to balance the class distribution. Two-layer nested cross-validation was used to build and evaluate the prediction models. A total of 3422 patients were included for analysis. The 90-day rate of readmission or mortality was 17.6%. This study identified several important predictive factors, including age, prior emergency department visits, pre-stroke functional status, stroke severity, body mass index, consciousness level, and use of a nasogastric tube. The Naïve Bayes model with class weighting to compensate for class imbalance achieved the highest discriminatory capacity in terms of the area under the receiver operating characteristic curve (0.661). Despite having room for improvement, the prediction models could be used for early risk assessment of patients with stroke. Identification of patients at high risk for readmission or mortality immediately after admission has the potential of enabling early discharge planning and transitional care interventions.

Characteristics of Acute Stroke Patients Readmitted to Inpatient Rehabilitation Facilities: A Cohort Study

BACKGROUND

Reducing acute care readmissions from inpatient rehabilitation facilities (IRFs) is a healthcare reform goal. Stroke patients have higher acute readmission rates and persistent impairments, warranting second IRF hospitalization consideration.

OBJECTIVE

To provide evidence-based information to justify IRF readmission for patients with post-stroke impairments.

MAIN OUTCOME MEASURE

Variables that increase the likelihood of a second IRF hospitalization.

DESIGN

Retrospective cohort study.

SETTING

Seven-center rehabilitation network.

PARTICIPANTS

Stroke patients, readmitted to acute care, who returned or did not return to an in-network IRF between 1 October 2014-31 December 2017(n = 380).

INTERVENTIONS

Univariable analyses (Returned/Did Not Return to IRF) described demographics, stroke type and risk factors. Between group differences in readmission causes, motor impairments and functional independence measure (FIM) scores were examined. Return to IRF logistic regression model included variables with P < .1. Odds ratio and 95% CI were calculated; Relative risk was calculated for categorical variables. P < .05 equaled statistical significance.

RESULTS

One hundred ninety-two stroke patients returned to IRF, 188 did not. Returned to IRF patients were younger (60.6 vs. 66 years; P < .001), sustained hemorrhagic strokes (22.4 vs. 14.2%; P = .01), had lower cardiac disease prevalence (41.7 vs. 55.3%; P = .008) or non-Medicare insurance (59.9 vs. 39.4%; P < .001). Did Not Return to IRF patients had higher admission and discharge motor and total FIM scores. Per point decrease in discharge FIM, second IRF hospitalization odds increased 4% (OR 1.04; 95% CI 1.01-1.07; P = .02). Hemorrhagic stroke patients had 33% increased odds or a 15% higher relative risk of second IRF hospitalization than patients with ischemic stroke [OR 1.33; 95% CI 1.21-1.47; RR 1.15; 95% CI 1.1-1.2; P < .001]. Non-Medicare insurance was associated with 39% increased odds or a 20% higher relative risk of second IRF hospitalization than Medicare [OR 1.39; 95% CI 1.01-1.92; RR 1.2, 95% CI 1.006-1.404; P = .04).

CONCLUSIONS

Hemorrhagic stroke, non-Medicare insurance or lower discharge FIM score during the first IRF hospitalization predict a second IRF stay. Further work is needed to establish the validity of within IRF stay readmission measures.

Predictors, causes and outcome of 30-day readmission among acute ischemic stroke

BACKGROUND AND PURPOSE

Readmission within 30 days of index acute ischemic stroke (AIS) after hospitalization increases the burden on patients and healthcare expense. The purpose of our study was to investigate predictors and causes of 30-day readmission after AIS and investigate hospitalization expenses, length of stay (LOS) and in-hospital mortality of 30-day readmission.

METHODS

This is a multicenter retrospective study. AIS were captured by International Classification of Diseases, Tenth Revision (ICD-10) diagnosis codes, patients with readmitted within 30 days after discharge were identified as readmission group. Multivariable logistic regression was used to identify independent predictors of 30-day readmissions. Hospitalization expenses, LOS and in-hospital mortality were compared for index admission and readmission.

RESULTS

We identified 2371 patients with AIS, 176 patients died before discharge, 504(23.0%) patients were admitted within 30 days. Older age, prior stroke, non-neurology floor during index admission, indwelling urinary catheter and diabetes were independently associated with increased risk of 30-day readmission (P<0.05). The most common causes for 30-day readmission were infection (28.8%) and recurrent stroke and TIA (22.8%). Patients with 30-day readmission have longer LOS and higher hospitalization expenses on readmission compared with the mean of these metrics on index admission (P<0.001). The in-hospital mortality after a within 30-day readmission was higher than index admission (13.1% vs 8.0%; OR 1.88, 95% CI 2.5-5.3; P<0.001).

CONCLUSIONS

Older age, stroke severity, prior stroke, diabetes, indwelling urinary catheter and admission to non-neurology floor during index admission were associated with 30-day readmission. 30-readmission after AIS increased hospitalization expenses, LOS and in-hospital mortality.

Readmissions and Mortality During the First Year After Stroke-Data From a Population-Based Incidence Study

Background: After a first-ever-in-a-lifetime stroke (FELS), hospital readmissions are common and associated with increased mortality and morbidity of stroke survivors, thus, raising the overall health burden of stroke. Population-based stroke studies on hospital readmissions are scarce despite it being an important healthcare service quality indicator. We evaluated unplanned readmissions or death during the first year after a FELS and their potential factors, based on a Portuguese community register.

Methods: Data were retrieved from a population-based prospective register undertaken in Northern Portugal (ACIN2) in 2009–2011. Retrospective information about unplanned hospital readmissions and case fatality within 1 year after FELS index hospitalization (FELS-IH) was evaluated. Readmission/death-free survival 1 year after discharge was estimated using the Kaplan–Meyer method. Independent risk factors for readmission/death were identified using Cox proportional hazard models.

Results: Unplanned readmission/death within 1 year occurred in 120 (31.6%) of the 389 hospitalized FELS survivors. In 31.2% and 33.5% of the cases, it occurred after ischemic stroke or intracerebral hemorrhage, respectively. Infections and cerebrovascular and cardiovascular diseases were the main causes of readmission. Of the readmissions, 65.3% and 52.5% were potentially avoidable or stroke related, respectively. The main cause of potentially avoidable readmissions was the continuation/recurrence of the event responsible for the initial admission or a closely related condition (71.2%). Male sex, age, previous and post-stroke functional status, and FELS-IH length of stay were independent factors of readmission/death within 1 year.

Conclusions: Almost one-third of FELS survivors were readmitted/dead 1 year after their FELS-IH. This outcome persisted after the first months after stroke hospitalization in all stroke subtypes. More than half of readmissions were considered potentially avoidable or stroke related.

Comparison of Rates and Outcomes of Readmission to Index vs Non-index Hospitals After Intravenous Thrombolysis in Acute Stroke Patients

National and regional systems of stroke care are designed to provide patients with widespread access to hospitals with thrombolytic capabilities. However, such triaging systems may contribute to fragmentation of care. This study aims to compare rates of readmission and outcomes between index and non-index hospitals for stroke patients following intravenous thrombolytic therapy (IVT). This study utilized a nationally representative sample of stroke patients with IVT from the Nationwide Readmissions Database from 2010 to 2014. Descriptive and regression analyses were performed for patient and hospital level factors that influenced 90-day readmissions and regression models were used to identify differences in mortality, complications, and repeat readmissions between patients readmitted to index (facility where IVT was administered) and non-index hospitals. In the study, 49415 stroke patients were treated with IVT, of whom 21.7% were readmitted within 90 days. Among readmissions, 79.4% of patients were readmitted to index hospitals and 20.6% to non-index hospitals. On multivariate logistic regression analysis, index hospital readmission was independently associated with lower frequency of second readmissions (non-index OR 1.09, 95%CI 1.07-1.11, p<0.0001) but not with increased mortality or major complications (p=ns). Approximately one-fifth of stroke patients treated with thrombolysis were readmitted within 90 days, one-fifth of whom were readmitted to non-index hospitals. Although readmission to index hospital was associated with lower frequency of subsequent readmissions, readmission to non-index hospital was not associated with increased mortality or major complications. This difference may be due to standardized algorithms, mature systems of care, and demanding metrics required of stroke centers.

Predictors of 30-day hospital readmission after mechanical thrombectomy for acute ischemic stroke

OBJECTIVE

The 30-day readmission rate is of increasing interest to hospital administrators and physicians, as it is used to evaluate hospital performance and is associated with increased healthcare expenditures. The estimated yearly cost to Medicare of readmissions is $17.4 billion. The Centers for Medicare and Medicaid Services therefore track unplanned 30-day readmissions and institute penalties against hospitals whose readmission rates exceed disease-specific national standards. One of the most important conditions with potential for improvement in cost-effective care is ischemic stroke, which affects 795,000 people in the United States and is a leading cause of death and disability. Recent widespread adoption of mechanical thrombectomy has revolutionized stroke care, requiring reassessment of readmission causes and costs in this population.

METHODS

The authors retrospectively analyzed a prospectively maintained database of stroke patients and identified 561 patients who underwent mechanical thrombectomy between 2010 and 2019 at the authors' institution. Univariate and multivariate analyses were conducted to identify clinical variables and comorbidities related to 30-day readmissions in this patient population.

RESULTS

Of the 561 patients, 85.6% (n = 480) survived their admission and were discharged from the hospital to home or rehabilitation, and 8.8% (n = 42/480) were readmitted within 30 days. The median time to readmission was 10.5 days (IQR 6.0-14.3). The most common reasons for readmission were infection (33.3%) and acute cardiac or cerebrovascular events (19% and 20%, respectively). Multivariate analysis showed that hypertension (p = 0.030; OR 2.72) and length of initial hospital stay (p = 0.040; OR 1.032) were significantly correlated with readmission within 30 days, while hemorrhagic conversion (grades 3 and 4) approached significance (p = 0.053; OR 2.23). Other factors, such as unfavorable outcome at discharge, history of coronary artery disease, and discharge destination, did not predict readmission.

CONCLUSIONS

The study data demonstrate that hypertension, length of hospital stay, and hemorrhagic conversion were predictors of 30-day hospital readmission in stroke patients after mechanical thrombectomy. Infection was the most common cause of 30-day readmission, followed by cardiac and cerebrovascular diagnoses. These results therefore may serve to identify patients within the stroke population who require increased surveillance following discharge to reduce complications and unplanned readmissions.

Comparison of effectiveness and safety of direct oral anticoagulants versus vitamin-k antagonists in elderly patients with atrial fibrillation: a systematic review and cost-effectiveness analysis protocol

Background

Current evidence regarding the effectiveness and safety of direct oral anticoagulants (DOACs) in the elderly with atrial fibrillation (AF) remains scarce. Based on the emerging evidence from real-world studies (RWSs) associated with DOACs, we will perform a systematic review and meta-analysis of data from RWSs and randomized controlled trials (RCTs) to compare the effectiveness, safety and cost of DOACs versus Vitamin K antagonists (VKAs) in elderly patients with AF.

Methods

The MEDLINE, EMBASE and Cochrane Library databases will be systematically searched until June 30, 2019 for eligible RWSs and RCTs that reported the clinical outcomes between DOACs and VKAs in elderly patients with AF. The effectiveness outcome is stroke or systemic embolism (SE), and the safety outcomes are major bleeding, intracranial haemorrhage (ICH), gastrointestinal bleeding (GIB), myocardial infarction (MI) and all-cause mortality. A random-effects model will be used to calculate adjusted hazard ratios (HRs) for RWSs and relative risks (RRs) for RCTs, separately. The interaction analysis and the ratio of HRs (RHRs) will be applied to compare the treatment effect difference between RWSs and RCTs. A Markov model will be constructed to evaluate the cost-effectiveness of DOACs versus VKAs in elderly AF patients in real-world setting.

Discussion

This study will summarize all available evidences from RWSs and RCTs for a comprehensive and rigorous systematic review on the effectiveness and safety associated with DOACs, as well as perform a cost-effectiveness analysis to evaluate the price performance of DOACs among elderly AF patients in real clinical setting.

Trial registration

PROSPERO register platform (CRD42019142881, www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID =142881).

Relationship between early follow-up and readmission within 30 and 90 days after ischemic stroke

OBJECTIVE

To examine whether early follow-up with primary care or neurology is associated with lower all-cause readmissions within 30 and 90 days after acute ischemic stroke admission.

METHODS

We performed a retrospective cohort study of patients who were discharged home after acute ischemic stroke, identified by ICD-9 and ICD-10 codes, using PharMetrics, a nationally representative claims database of insured Americans from 2009 to 2015. The primary predictor was outpatient primary care or neurology follow-up within 30 and 90 days of discharge, and the primary outcome was all-cause 30- and 90-day readmissions. Multivariable Cox models were used with primary care and neurology visits specified as time-dependent covariates, with adjustment for patient demographics, comorbid conditions, and stroke severity measures.

RESULTS

The cohort included 14,630 patients. Readmissions within 30 days occurred in 7.3% of patients, and readmissions within 90 days occurred in 13.7% of patients. By 30 days, 59.3% had a primary care visit, and 24.4% had a neurology visit. Primary care follow-up was associated with reduced 30-day readmissions (hazard ratio [HR] 0.84, 95% confidence interval [CI] 0.72-0.98). Primary care follow-up before 90 days did not reach significance (HR 0.92, 95% CI 0.83-1.03). Neurology follow-up was not associated with reduced readmissions within 30 or 90 days (HR 1.05, 95% CI; HR 1.00, 95% CI, respectively).

CONCLUSION

Early outpatient follow-up with primary care is associated with a reduction in 30-day hospital readmissions. Early outpatient follow-up may represent an important opportunity for intervention after acute stroke admissions.

Annual incidences and predictors of 30-day readmissions following spontaneous intracerebral hemorrhage from 2010 to 2014 in the United States: A retrospective Nationwide analysis

Objective

30-day readmission rate is a quality metric often employed to represent hospital and provider performance. Currently, little is known regarding 30-day readmissions (30dRA) following spontaneous intracerebral hemorrhage (sICH). The purpose of this study was to use a national database to identify risk factors and trends in 30dRAs following sICH.

Patients and methods

64,909 cases with a primary diagnosis of sICH were identified within the Nationwide Readmission Database (NRD) from 2010 through 2014. Charlson Comorbidity Index (CCI) was used to adjust for the severity of each patient's comorbidities. A binary logistic regression model was constructed to identify predictors of 30-day readmission. Cochran-Mantel-Haenszel test was used to generate a pooled odd ratio (OR) describing the likelihood of experiencing a 30dRA according to year.

Results

The 30dRA rate following sICH decreased from 13.9% in 2010 to 12.5% in 2014 (pooled OR = 0.90, 95% CI 0.87–0.94). Cerebrovascular and cardiovascular etiologies accounted for the greatest number of admissions (36.1%). Sodium abnormality, healthcare-associated infection, gastrostomy, venous thromboembolism, and ischemic stroke during the index admission were associated with 30-day readmission. Furthermore, patients who underwent ventriculostomy (OR = 1.20, 95% CI 1.03–1.38) and craniotomy (OR = 1.20, 95% CI 1.09–1.31) were more likely to be readmitted within 30 days. Hospital volume, hospital teaching status, mechanical ventilation, and tracheostomy did not affect 30dRAs. Median readmission costs increased from $9,875 in 2012 to $11,028 in 2014 (p = 0.040).

Conclusion

The overall U.S. 30dRA rate after sICH from 2010 to 2014 was 12.9% and decreased slightly during this time period, but associated costs increased. Prospective studies are required to confirm the risk factors described in this study and to identify methods for preventing readmissions.

In vivo brain imaging with multimodal optical coherence microscopy in a mouse model of thromboembolic photochemical stroke

We used a new multimodal imaging system that combines optical coherence microscopy and brightfield microscopy. Using this in vivo brain monitoring approach and cranial window implantation, we three-dimensionally visualized the vascular network during thrombosis, with high temporal (18 s) and spatial (axial, 2.5    μ m ; lateral, 2.2    μ m ) resolution. We used a modified mouse model of photochemical thromboembolic stroke in order to more accurately parallel human stroke. Specifically, we applied green laser illumination to focally occlude a branch of the middle cerebral artery. Despite the recanalization of the superficial arteries at 24 h after stroke, no blood flow was detected in the small vessels within deeper regions. Moreover, after 24 h of stroke progression, scattering signal enhancement was observed within the stroke region. We also evaluated the infarct extent and shape histologically. In summary, we present a novel approach for real-time mouse brain monitoring and ischemic variability analysis. This multimodal imaging method permits the analysis of thrombosis progression and reperfusion. Additionally and importantly, the system could be used to study the effect of poststroke drug treatments on blood flow in small arteries and capillaries of the brain.

Influence of a Comorbid Diagnosis of Seizure on 30-Day Readmission Rates Following Hospitalization for an Index Stroke

OBJECTIVE

To examine the association of a comorbid seizure diagnosis with early hospital readmission rates following an index hospitalization for stroke in the United States.

METHODS

Retrospective analysis of the 2014 National Readmission Database. The study population included adult patients (age >18 years old) with stroke, identified using the International Classification of Disease Ninth Revision, Clinical Modification (ICD-9-CM) codes 433.X1, 434.X1, and 436 for ischemic stroke as well as 430, 431, 432.0, 432.1, and 432.9 for hemorrhagic stroke. A subgroup of patients with a secondary discharge diagnosis of seizures was identified using the ICD-9-CM codes 780.39 and 345.X. We computed all-cause 30-day readmission rates for all strokes and by stroke type (ischemic versus hemorrhagic). Finally, we used a multivariable logistic regression model to examine the independent association between seizure and readmission by stroke type.

RESULTS

Of 271,148 stroke patients, 6.3% (16,970) had a secondary discharge diagnosis of seizures including 5.0% (11,562) of patients with ischemic stroke and 13.4% (5,409) with hemorrhagic stroke. Overall readmission rate for stroke patients was 11.9% (hemorrhagic stroke: 14.2% versus ischemic strokes: 11.6%). Thirty-day readmission rate was higher in patients with seizures for all strokes (15.6% versus 11.7%, P value <.001), ischemic strokes (15.0% versus11.4%, P value <.001), and hemorrhagic strokes (16.7% versus 13.8%, P value <.001). After adjusting for several patient-specific and healthcare system-specific confounders, hospitalized stroke patients with comorbid seizure diagnosis were more likely than those without seizures to be readmitted within 30 days (OR: 1.20, 95% CI: 1.14-1.25).

CONCLUSION

The presence of a comorbid diagnosis of seizure disorder in a hospitalized stroke patient significantly raises the occurrence of early hospital readmission in the United States.

30-Day Readmissions After Endovascular Thrombectomy for Acute Ischemic Stroke

OBJECTIVES

The authors sought to investigate the incidence, predictors, and causes of 30-day nonelective readmissions after endovascular thrombectomy (EVT).

BACKGROUND

Randomized trials have demonstrated that EVT improves outcomes in patients with acute ischemic stroke.

METHODS

The Nationwide Readmissions Database, years 2013 and 2014, was used to identify hospitalizations for a primary diagnosis of acute ischemic stroke during which patients underwent EVT, with or without intravenous thrombolysis. The incidence and reasons of 30-day readmissions were investigated. A hierarchical Cox regression model was used to identify independent predictors of 30-day nonelective readmissions. A propensity score-matched analysis was performed to compare the risk of 30-day nonelective readmissions in those who underwent EVT versus thrombolysis alone.

RESULTS

Among 2,055,365 weighted hospitalizations with acute ischemic stroke and survival to discharge, 10,795 (0.5%) underwent EVT. The 30-day readmission rate was 12.4% within a median of 9 days (interquartile range: 4 to 18 days). Diabetes mellitus, coagulopathy, Medicare or Medicaid insurance, and gastrostomy during the index hospitalization were independent predictors of 30-day readmission, but coadministration of thrombolytics with EVT was not an independent predictor. The most common reasons for readmission were infections (17.2%), cardiac causes (17.0%), and recurrent stroke or transient ischemic attack (14.8%). Compared with thrombolysis alone, the hazard of 30-day readmissions was similar (hazard ratio: 0.98; 95% confidence interval: 0.91 to 1.05; p = 0.55).

CONCLUSIONS

In patients hospitalized with acute ischemic stroke who underwent EVT, 30-day nonelective readmissions were common, occurring in approximately 1 in 8 patients, but were similar to those of patients treated with thrombolysis alone. Risk of readmission was associated with certain patient demographics, comorbidities, and complications, but not thrombolysis coadministration. Infections, cardiac causes, and recurrent stroke or transient ischemic attack are the most common reasons for readmission after EVT, emphasizing the need for comprehensive multidisciplinary treatment in the transition to outpatient care.

Extreme Gradient Boosting Model Has a Better Performance in Predicting the Risk of 90-Day Readmissions in Patients with Ischaemic Stroke

OBJECT

Ischemic stroke readmission within 90 days of hospital discharge is an important quality of care metric. The readmission rates of ischemic stroke patients are usually higher than those of patients with other chronic diseases. Our aim was to identify the ischemic stroke readmission risk factors and establish a 90-day readmission prediction model for first-time ischemic stroke patients.

METHODS

The readmission prediction model was developed using the extreme gradient boosting (XGboost) model, which can generate an ensemble of classification trees and assign a predictive risk score to each feature. The patient data were split into a training set (5159) and a validation set (911). The prediction results were evaluated with the receiver operating characteristic (ROC) curve and time-dependent ROC curve, which were compared with the outputs from the logistic regression (LR) model.

RESULTS

A total of 6070 adult patients (39.6% female, median age 67 years) without any ischemic attack (IS) history were included, and 520 (8.6%) were readmitted within 90 days. The XGboost-based prediction model achieved a standard area under the curve (AUC) value of .782 (.729-.834), and the best time-dependent AUC value was .808 in 54 days for the validation set. In contrast, the LR model yielded a standard AUC value of .771 (.714-.828) and best time-dependent AUC value of .797.

CONCLUSIONS

The XGboost model obtained a better risk prediction for 90-day readmission for first-time ischemic stroke patients than the LR model. This model can also reveal the high risk factors for stroke readmission in first-time ischemic stroke patients.

Readmission to a different hospital following acute stroke is associated with worse outcomes

OBJECTIVE

There is a high risk of readmission within 30 days of index acute ischemic stroke (AIS), but effect of readmission to a different hospital is not known. We performed a retrospective cohort study to assess our hypothesis that 30-day readmission outcomes after AIS are worse for those readmitted to another hospital vs the discharging hospital.

METHODS

We utilized the 2013 Nationwide Readmissions Database to identify patients with index stroke admissions with ICD-9-CM codes. We identified all-cause readmissions with Clinical Classification Software. Outcomes included length of stay (LOS), total charges of hospitalization, and in-hospital mortality during 30-day readmission. Using linear and logistic regression, outcomes were compared in those readmitted to another hospital vs the discharging hospital.

RESULTS

There were 194,549 patients included, with an average age of 80.0 ± 14.0 years; 51.2% were female; 24,545 were readmitted within 30 days, and 7,274 (29.6%) to a different hospital. Readmission to a different hospital was associated with an increased LOS of 1.0 days (95% confidence interval [CI] 0.7-1.2, p < 0.0001) and $7,677.28 (95% CI $5,496-$9,858, p < 0.0001) greater total charges. The odds ratio for in-hospital mortality during readmission was 1.2 for readmission to another hospital (95% CI 1.0-1.3, p = 0.0079).

CONCLUSIONS

Readmission to another hospital within 30 days of AIS index admission was independently associated with longer LOS, increased total charges, and greater in-hospital mortality compared to readmission to the same hospital.

Preventable Readmissions and Predictors of Readmission After Subarachnoid Hemorrhage

OBJECTIVE

To estimate rates of all-cause and potentially preventable readmissions up to 90 days after discharge for aneurysmal subarachnoid hemorrhage (SAH) and medical comorbidities associated with readmissions BACKGROUND: Readmission rate is a common metric linked to compensation and used as a proxy to quality of care. Prior studies in SAH have reported 30-day readmission rates of 7-17% with a higher readmission risk among those with the higher SAH severity, ≥ 3 comorbidities, and non-home discharge. Intermediate-term rates, up to 90-days, and the proportion of these readmissions that are potentially preventable are unknown. Furthermore, the specific medical comorbidities associated with readmissions are unknown.

METHODS

Index SAH admissions were identified from the 2013 Nationwide Readmissions Database. All-cause readmissions were defined as any readmission during the 30-, 60-, and 90-day post-discharge period. Potentially preventable readmissions were identified using Prevention Quality Indicators developed by the US Agency for Healthcare Research and Quality. Unadjusted and adjusted Poisson models were used to identify factors associated with increased readmission rates.

RESULTS

Out of 9987 index admissions for SAH, 7949 (79%) survived to discharge. The percentage of 30-, 60-, and 90-day all-cause readmissions were 7.8, 16.6, and 26%, respectively. Up to 14% of readmissions in the first 30 days were considered potentially preventable and acute conditions (dehydration, bacterial pneumonia, and urinary tract infections) accounted for over half, whereas acute cerebrovascular disease was the most common cause for neurological return. In multivariable analysis, significant predictors of a higher readmission rate included diabetes (rate ratio [RR] 1.09, 95% confidence interval [CI] 1.03-1.15), congestive heart failure (RR 1.09, 1.003-1.18), and renal impairment (RR 1.35, 1.13-1.61). Only discharge home was associated with a lower readmission rate (RR 0.89, 0.85-0.93).

CONCLUSIONS

SAH has a 30-day readmission rate of 7.8% which continues to rise into the intermediate-term. A low but constant proportion of readmissions are potentially preventable. Several chronic medical comorbidities were associated with readmissions. Prospective studies are warranted to clarify causal relationships.

Infections Increase the Risk of 30-Day Readmissions Among Stroke Survivors

Background and Purpose- Hospitals are increasingly using 30-day readmission (30dRA) to define the quality of care and reimbursement. We hypothesized that common infections occurring during the stroke stay are associated with 30dRA. Methods- We conducted a weighted analysis of the federally managed 2013 National Readmission Database to assess the relationship between infection during a stroke hospitalization and 30dRA among ischemic stroke survivors. Ischemic stroke, common infections (defined as sepsis, pneumonia, and urinary tract infection), and comorbidities were identified using International Classification of Diseases Ninth Revision ( ICD-9) diagnosis codes, and intravenous tPA (tissue-type plasminogen activator) or intra-arterial therapy was identified using ICD-9 procedure codes. Survey design logistic regression models were fit to estimate crude and adjusted odds ratios and 95% CI for the association between infections and 30dRA. Results- Among 319 317 ischemic stroke patients, 12.1% were readmitted within 30 days, and 29% had an infection during their index hospitalization. Patients with infection during their stroke admission had a 21% higher odds of being readmitted than patients without any type of infection (adjusted odds ratio, 1.21; 95% CI, 1.16-1.26). The association between infection and unplanned readmission was similar with an increased odds of unplanned readmission (adjusted odds ratio, 1.23; 95% CI, 1.18-1.29). When assessing specific types of infections, only urinary tract infections were associated with 30dRA in adjusted models (odds ratio, 1.10; 95% CI, 1.04-1.16). Conclusions- In a nationally representative cohort, patients who had a common infection during their stroke hospitalization were at increased odds of being readmitted. Patients with infection may benefit from earlier poststroke follow-up or closer monitoring.

Prediction Model of Early Return to Hospital after Discharge Following Acute Ischemic Stroke

BACKGROUND

Reducing hospital readmissions for stroke remains a significant challenge to improve outcomes and decrease healthcare costs.

METHODS

We analyzed 10,034 adult patients with ischemic stroke, presented within 24 hours of onset from a hospital-based stroke registry. The risk factors for early return to hospital after discharge were analyzed using multivariate logistic regression and classification and regression tree (CART) analyses.

RESULTS

Among the study population, 277 (2.8%) had 3-day Emergency Department (ED) reattendance, 534 (5.3%) had 14-day readmission, and 932 (9.3%) had 30-day readmission. Multivariate logistic regression revealed that age, nasogastric tube feeding, indwelling urinary catheter, healthcare utilization behaviour, and stroke severity were major and common risk factors for an early return to the hospital after discharge. CART analysis identified nasogastric tube feeding and length of stay for 72-hour ED reattendance, Barthel Index (BI) score, total length of stay in the Year Preceding the index admission (YLOS), indwelling urinary catheter, and age for 14-day readmission, and nasogastric tube feeding, BI score, YLOS, and number of inpatient visits in the year preceding the index admission for 30-day readmission as important factors to classify the patients into subgroups.

CONCLUSION

Although CART analysis did not improve the prediction of an early return to the hospital after stroke compared with logistic regression models, decision rules generated by CART can easily be interpreted and applied in clinical practice.

Association Between Early Outpatient Visits and Readmissions After Ischemic Stroke

BACKGROUND

Reducing hospital readmission is an important goal to optimize poststroke care and reduce costs. Early outpatient follow-up may represent one important strategy to reduce readmissions. We examined the association between time to first outpatient contact and readmission to inform postdischarge transitions.

METHODS AND RESULTS

We performed a retrospective cohort study of all Medicare fee-for-service patients discharged home after an acute ischemic stroke in 2012 identified by the InternationalClassification of Diseases, Ninth Revision, Clinical Modification codes. Our primary predictor variable was whether patients had a primary care or neurology visit within 30 days of discharge. Our primary outcome variable was all-cause 30-day hospital readmission. We used separate multivariable Cox models with primary care and neurology visits specified as time-dependent covariates, adjusted for numerous patient- and systems-level factors. The cohort included 78 345 patients. Sixty-one percent and 16% of patients, respectively, had a primary care and neurology visit within 30 days of discharge. Visits occurred a median (interquartile range) 7 (4-13) and 15 (5-22) days after discharge for primary care and neurology, respectively. Thirty-day readmission occurred in 9.4% of patients. Readmissions occurred a median 14 (interquartile range, 7-21) days after discharge. Patients who had a primary care visit within 30 days of discharge had a slightly lower adjusted hazard of readmission than those who did not (hazard ratio, 0.98; 95% confidence interval, 0.97-0.98). The association was nearly identical for 30-day neurology visits (hazard ratio, 0.98; 95% confidence interval, 0.97-0.98).

CONCLUSIONS

Thirty-day outpatient follow-up was associated with a small reduction in hospital readmission among elderly patients with stroke discharged home. Further work should assess how outpatient care may be improved to further reduce readmissions.

Frequency, predictors, and outcomes of readmission to index versus non-index hospitals after mechanical thrombectomy in patients with ischemic stroke

Background

Stroke systems of care employ a hub-and-spoke model, with fewer centers performing mechanical thrombectomy (MT) compared with stroke-receiving centers, where a higher number offer high-level, centralized treatment to a large number of patients.

Objective

To characterize rates and outcomes of readmission to index and non-index hospitals for patients with ischemic stroke who underwent MT.

Methods

This study leveraged a population-based, nationally representative sample of patients with stroke undergoing MT from the Nationwide Readmissions Database between 2010 and 2014. Descriptive, logistic regression analyses, and univariate and multivariate logistic regression models were carried out to determine patient- and hospital-level factors, mortality, complications, and subsequent readmissions associated with index and non-index hospitals' 90-day readmissions.

Results

In the study, 2111 patients with a stroke were treated with MT, of whom 534 were readmitted within 90 days. The most common reasons for readmission were: septicemia (5.9%), atrial fibrillation (4.8%), and cerebral artery occlusion with infarct (4.8%). Among readmitted patients, 387 (74%) were readmitted to index and 136 (26%) to non-index hospitals. On multivariable logistic regression analysis, non-index hospital readmission was not independently associated with major complications (p=0.09), mortality (p=0.34), neurological complications (p=0.47), or second readmission (p=0.92).

Conclusion

One-quarter of patients with a stroke treated with MT were readmitted within 90 days, and one quarter of these patients were readmitted to non-index hospitals. Readmission to a non-index hospital was not associated with mortality or increased complication rates. In a hub-and-spoke model it is important that follow-up care for a specialized procedure can be performed effectively at a vast number of non-index hospitals covering a large geographic area.

"Weekend Effect" on 30-Day Readmissions among Stroke Survivors: An Analysis of the National Readmission Database

Background and Purpose

Previous studies suggested that quality of care may be lower on weekends than during the week. We hypothesized that, among patients hospitalized for an index ischemic stroke, those admitted on weekends would have a higher risk of 30-day readmission than those admitted on weekdays.

Methods

We utilized the 2013 Nationwide Readmission Database, which includes data on US inpatient admissions from the Agency for Healthcare Research and Quality Healthcare Utilization Project. The database includes a nationally representative weighted probability sample of inpatient hospitalizations regardless of insurance status. Patients with primary acute ischemic stroke were identified using previously validated ICD-9-CM diagnosis codes. We conducted a weighted analysis using survey design logistic regression models to estimate crude and adjusted odds ratios (OR) and 95% confidence intervals (95% CI) for the association between weekend admission and 30-day readmission in ischemic stroke patients.

Results

Among 319,317 patients admitted for ischemic stroke, 12.1% were readmitted within 30 days. Those with 30-day readmissions had an average of 8 chronic conditions, and all cardiovascular-related comorbidities increased the risk of 30-day readmissions. Ischemic stroke patients admitted on weekends had odds of 30-day readmission similar to patients admitted on weekdays (OR 1.02; 95% CI 0.98–1.06). Weekend admission also did not affect readmission at 7 or 60 days.

Conclusions

We found no association between weekend admission and 30-day readmissions, providing indirect evidence of homogeneity in the quality of care delivered during week day and weekend admissions.

Use of Hospital-Based Rehabilitation Services and Hospital Readmission Following Ischemic Stroke in the United States

OBJECTIVE

To examine the association between hospital-based rehabilitation service use and all-cause 30-day hospital readmission among patients with ischemic stroke.

DESIGN

Secondary analysis of inpatient Medicare claims data using Standard Analytical Files.

SETTING

Acute hospitals across the United States.

PARTICIPANTS

From nationwide data, Medicare fee-for-service beneficiaries (N=88,826) aged 66 years or older hospitalized for ischemic stroke between January to November 2010.

INTERVENTIONS

Hospital-based rehabilitation services were quantified using Medicare inpatient claims revenue center codes for evaluation (occupational therapy [OT] and physical therapy [PT]), as well as the number of therapy units delivered. Therapy minutes for both OT and PT services were categorized into none, low, medium, and high.

MAIN OUTCOME MEASURES

All-cause 30-day hospital readmission. A generalized linear mixed model was used to examine the effect of hospital-based rehabilitation services on 30-day hospital readmission, after adjusting for patient and hospital characteristics.

RESULTS

In fully adjusted models, compared to patients who received no PT, we observed a monotonic inverse relationship between the amount of PT and hospital readmission. For low PT (30 minutes), the odds ratio (OR) was 0.90 (95% confidence interval [CI], 0.83-0.96). For medium PT (>30 to ≤75 minutes), the OR was 0.89 (95% CI, 0.82-0.95). For high PT (>75 minutes), the OR was 0.86 (95% CI, 0.80-0.93).

CONCLUSION

Hospital-based PT services were associated with lower risk of 30-day hospital readmission in patients with ischemic stroke.