Predictors and Outcomes of 30-Day Readmissions in Patients Hospitalized for Acute Ischemic Stroke Undergoing Mechanical Thrombectomy
Adeena Jamil1, Eliza Aisha Javed1, Khadija Alam2, Fatima Awais3, Rana Faheem Ullah Khan4, Hadiya Javed5, Syeda Takreem Fatima6, Yusra Rizwan7, Sabeeh Khawar Farooqui7, Ezza Bashir8, Khadija Tanvir9, Muhammad Haider Sultan10, Hafiz Muhammad Usama Javed11, Hafiz Muhammad Sameer12
1Department of Medicine, Dow University of Health Sciences, Karachi, 2Department of Medicine, Liaquat National Hospital and Medical College, Karachi, 3Department of Neurology, Khyber Medical College, Peshawar, 4Department of Neurology, Shaikh Khalifa bin Zayed Al-Nahyan Medical and Dental College, Lahore, 5Department of Neurology, Dow University of Health Sciences, Karachi, 6Department of Medicine, Services Institute of Medical Sciences, Lahore, 7Department of Neurology, Ziauddin Medical College, Karachi, 8Department of Medicine, Akhter Saeed Medical and Dental College, Lahore, 9Department of Neurology, King Edward Medical University, Lahore., 10Department of Neurology, Amna Inayat Medical College, Lahore, 11Department of Neurology, Sharif Medical and Dental college, Lahore, 12Department of Neurology, King Edward Medical University, Lahore Email: sameer2376@hotmail.com
Objective:
We evaluated the 30-day all-cause readmission rate and identified independent demographic and clinical predictors of readmissions among AIS patients undergoing Mechanical thrombectomy (MT).
Background:
Acute ischemic stroke (AIS) is a medical emergency with a mortality rate of 19.06 per 100,000 person-years. MT following AIS improves clinical outcomes but lacks data for its short-term readmission outcomes.
Design/Methods:
Using the Nationwide Readmissions Database (2016–2017), we identified adult patients hospitalized for AIS who underwent MT. Outcomes included 30-day all-cause readmission, in-hospital mortality, length of stay (LOS) and inflation-adjusted hospitalization charges. Weighted baseline characteristics of index hospitalizations were stratified by readmission status. Independent predictors of readmission were identified using multivariable Cox proportional hazards regression and reported as hazard ratios (HRs) with 95% confidence intervals (CI).
Results:
Among 29,783 AIS index hospitalizations, 8.9% (n= 2,676) experienced a 30-day non-elective readmission, most commonly due to cerebral infarction (14.15%) and sepsis (13.72%). Readmitted patients were predominantly aged 65-79 (40%) and female (52.0%). Compared with non-readmitted patients, they more frequently had Medicare insurance (70.0% vs. 63.0%; p<0.004), were discharged to non-home settings (63.0% vs. 58.0%; p<0.001), and exhibited a greater comorbidity burden (p<0.001), particularly arrhythmia, congestive heart failure, diabetes, coronary artery disease (CAD), fluid/electrolyte imbalance, chronic pulmonary disease, renal disease and valvular disease. The mean LOS was longer during index admission than readmission (11.6 vs 6.9 days), with higher corresponding hospitalization charges ($203,889 vs $65,778) and in-patient mortality rate (14.2% vs 6.4%). Independent predictors of readmission included comorbid renal disease, CAD, and fluid/electrolyte imbalance (p<0.05).
Conclusions:
Nearly 1 in 10 AIS patients undergoing MT was readmitted within 30 days, most commonly due to cerebral infarction and sepsis. Renal disease, CAD, and fluid/electrolyte imbalance predicted early readmission. Improved post-discharge management addressing comorbidities may reduce preventable readmissions and mitigate the clinical and economic burden of AIS.
Disclaimer: Abstracts were not reviewed by Neurology® and do not reflect the views of Neurology® editors or staff.