Risk factors for 30-day readmission in patients with ischemic stroke: a systematic review and meta-analysis

Introduction

According to a report on the global burden of stroke between 1990 and 2016 (1), stroke is the second leading cause of death worldwide, second only to ischemic heart disease, accounting for nearly 50 million deaths annually. Stroke is a major public health problem throughout the world due to its high prevalence, mortality, disability rate, and incidence of complications. Stroke has a long disease course, and the recovery period ranges from 2 weeks to 6 months after the onset of the disease, with the sequelae period even continuing beyond 6 months. These facts make out-of-hospital management of stroke particularly important. However, the 30-day readmission rates in stroke survivors remain high due to a variety of factors, including disease recurrence, infection, limb dysfunction, and falls. In 2018, a Chinese study involving 50,912 stroke survivors from 375 hospitals in 29 provinces in China showed that 28.8% of patients were readmitted within 30 days of discharge (2). In a 6-year population-based cohort study of approximately 2 million adult stroke survivors in the United States, 13.7% of patients with hemorrhagic stroke, 12.4% of patients with acute ischemic stroke, and 11.5% of patients with subarachnoid hemorrhage were readmitted within 30 days (3). The high readmission rate reduces the quality of life of patients, causes considerable harm to patients and their families, and increases the medical and economic burden. It is also important to investigate the 15- or 60-day readmission rates of patients with ischemic stroke, but the study of Bjerkreim et al. (4) showed that 30-day readmission significantly increased the risk of 1-year mortality in patients surviving 30 days after discharge. Furthermore, the frequency of 30-day readmissions after stroke has become an indicator for the quality of care, quality of immediate post-discharge care, and the presence of a chronically ill and vulnerable population (5). Frequent readmissions can also affect hospital development and patient reimbursement (6). Vahidy et al. reported that 12.9% of 30-day readmissions were preventable (7). Therefore, it is important to assess the risk factors for 30-day readmissions in ischemic stroke survivors and intervene accordingly.

Although many multicenter, retrospective, observational studies with large sample sizes have investigated the risk factors for 30-day readmission in patients with ischemic stroke in recent years, few prospective cohort studies, longitudinal studies, and randomized controlled trials (RCTs) have been published in this field. With diverse foci, these studies provide no definite conclusions and have not been properly summarized. No previous relevant meta-analyses (8-10) have specifically explored the stroke types and the timing of readmissions due to the limited number of the included articles and databases. Only a small number of risk factors have been identified, and many other risk factors warrant further investigation. Furthermore, these previous meta-analyses did not include several high-quality articles published in the past 5 years, and their conclusions need to be updated. The aim of this meta-analysis was therefore to identify the risk factors for 30-day readmission in ischemic stroke survivors, with an attempt to inform the out-of-hospital management of stroke and lower the 30-day readmission rate, thus benefiting more patients.

Whilst some researchers reported similar studies (9) in 2016, the highlight of our study is that we searched 3 Chinese databases, namely Wanfang data, China National Knowledge Infrastructure (CNKI), and Chinese Science and Technology Journal Database (VIP), and included excellent research in Chinese, rather than just research published in English, which previous similar institutes have not. We believe that research by Chinese scholars is essential to advance clinical work and scientific research. We have added 12 of the latest studies since 2016, and many of the studies are multicenter studies with large sample sizes, making the results more reliable. In addition, only 4 studies were included in previous studies to compare the differences between the experimental group and the control group, while 17 studies were included in our study, which is conducive to improving the persuasiveness of the results. Our study considered nearly 30 risk factors for 30-day readmission after ischemic stroke, and finally identified 6 risk factors after 4 risk factors were ruled out, with 5 possible risk factors requiring further investigations. We present the following article in accordance with the PRISMA reporting checklist (available at https://dx.doi.org/10.21037/apm-21-2884).

Methods

Literature search

Four English-language databases, including Web of Science (WOS), the National Library of Medicine (MEDLINE), Excerpta Medica Database (EMBASE), and the Cochrane Library, along with the 3 top Chinese-language databases, including Wanfang data, China National Knowledge Infrastructure (CNKI), and Chinese Science and Technology Journal Database (VIP), were searched from inception to April 30, 2021. Gray literature as well as the references of the relevant articles were also retrieved when possible. The search was conducted by using a combination of relevant subject headings and keywords including “stroke/acute ischemic stroke/cerebral infarction/transient ischemic attack (TIA)/cerebral vascular accident” and “re*hospital*/re*admission*”.

Inclusion and exclusion criteria

The inclusion criteria were as follows: (I) the article was a retrospective or prospective observational study or interventional study; (II) the subjects were patients with radiologically (cranial computed tomography or magnetic resonance imaging) confirmed ischemic stroke or identified according to the International Classification of Diseases, regardless of stroke type, lesion location, disease course, or comorbidity; (III) participants were aged ≥18 years; and (IV) the study focused on risk factors for 30-day readmission in patients with ischemic stroke. The exclusion criteria were as follows: (I) studies that were not available in full text; (II) literature for which complete data were not available; (III) among repeated articles, the article had the least comprehensive data set; and (IV) review articles, case reports, and qualitative studies. Some of the articles on 30-day unplanned readmissions or that focused on 28- or 31-day readmissions were also included, as we believed they were equally valuable for our analysis. We also included some articles that examined patients with different stroke types and articles in which patients with ischemic stroke accounted for more than 70% of all the participants. However, similar articles not involving ischemic stroke survivors or with a low proportion of ischemic stroke survivors were excluded. A few articles that did not appear suitable for our analysis were still included if we could find or calculate the data we needed from these articles, though information from these articles was typically quite limited.

Data extraction and quality assessment

Two researchers (DZQ and WXY) independently screened the literature based on the inclusion and exclusion criteria. Using a predesigned table, these 2 researchers independently extracted data including: (I) first author, publication year, country, study type, and sample size; (II) basic characteristics of the study population including age, stroke type, readmission time, readmission type, and 30-day readmission rate; and (III) outcome indicators including risk factors for 30-day readmissions. These 2 investigators also independently assessed study quality using methods developed by the US Agency for Healthcare Research and Quality (AHRQ), while the Newcastle-Ottawa Scale was applied for observational studies. Study quality scores were defined as poor [0–3], fair [4–6], or good [7–9]. Discrepancies encountered during literature screening, data extraction, and quality assessment were discussed and resolved in consultation with a third author (YR), if necessary. Where data were not available or were unclear from the reports, we contacted the corresponding authors for further information.

Data synthesis and statistical analysis

Review Manager version 5.3 (Cochrane Library) was used for outcome analysis. As all the included articles in the final analysis were retrospective observational studies, the pooled effect size was estimated using odds ratio (OR), and the 95% confidence interval (CI) was also calculated. A P value of <0.05 was considered statistically significant. Heterogeneity was assessed by the χ² test and I² value. If the heterogeneity of the study was acceptable (P>0.10 and I²<50%), a fixed-effects model was applied, while the robustness of the test was validated using a random-effects model. If heterogeneity was present among the studies, the sources of heterogeneity were further analyzed. First, any possible errors that occurred during data extraction, recording, and input were checked for. Second, sensitivity analysis was performed to exclude studies that might have caused heterogeneity, which was followed by a re-performing of the meta-analysis to eliminate heterogeneity. If the heterogeneity was large (P≤0.10 and I²>50% for outcome indicators) and the source of heterogeneity could not be determined, the meta-analysis could not be performed and only descriptive analysis was conducted. For missing or erroneous data in the original articles, we added them ourselves if they could be interpreted according to the main text. Otherwise, the corresponding authors of these articles were contacted for clarification via email. The search flowchart, basic information table, and quality evaluation table were created using Microsoft Word (Microsoft Corporation, Redmond, WA, USA), and the forest plots and inverted funnel plots were created using RevMan version 5.3. Publication bias was assessed using inverted funnel plots.

Results

Results of literature search

A total of 366 articles were retrieved from the 7 databases, and 25 documents were found through other resources (Figure 1). Seventeen retrospective observational studies from the United States (n=10), China (n=2), Republic of Korea (n=2), Norway (n=2), and Australia (n=1), comprising a total of 1,829,964 patients, were entered into the final meta-analysis. In contrast, the number of prospective observational and interventional studies (e.g., RCTs) was small. In addition, these articles covered a wide range of topics that did not focus on a specific number of risk factors. The number of articles addressing the same risk factor was ≤3, and many factors were only described in just a single article. Thus, they were not deemed suitable for meta-analysis or descriptive systematic evaluation. The 30-day readmission rates of ischemic stroke survivors ranged from 1.41% to 27.64%, with a mean value of 10.66% (SD 6.87%). The results varied among countries and regions, with the highest reported 30-day readmission rate from China and the lowest from the United States (Table 1).

Figure 1 Flowchart of the review process.

Quality evaluation

The included articles were of moderate quality (n=13) or high quality (n=4) (Table 2).

Statistical analysis

We screened about 30 of the most frequently mentioned risk factors in these 17 articles and finally identified 6 risk factors (Figures 2-6): history of stroke (OR, 1.33; 95% CI: 1.08–1.64; P=0.007), diabetes mellitus (OR, 1.15; 95% CI: 1.13–1.17; P<0.001), hypertension (OR, 1.10; 95% CI: 1.07–1.13; P<0.001), atrial fibrillation (OR, 1.26; 95% CI: 1.23–1.29; P<0.001), heart failure (OR, 1.59; 95% CI: 1.56–1.63; P<0.001), and age, among which age was determined by descriptive analysis. Four risk factors were ruled out: hyperlipidemia (OR, 1.01; 95% CI: 0.87–1.17; P=0.91), coronary artery disease (OR, 0.83; 95% CI: 0.73–0.96; P=0.009), smoking (OR, 0.97; 95% CI: 0.83–1.14; P=0.71), and gender (female, OR, 0.97; 95% CI: 0.96–0.98; P<0.001; Figures 7-10). Five possible risk factors requiring further investigation included duration of hospitalization, treatment modality (thrombolysis and thrombectomy), discharge disposition (home, rehabilitation facility, nursing home, home nursing, and others), health care payment model (Medicare, NHS, Medicaid, private insurance, and others), and etiology (atherosclerosis, cardiogenic cerebral embolism, small vessel disease, other definite causes, and other unknown causes). Intravenous thrombolysis (OR, 0.93; 95% CI: 0.91–0.96; P<0.001) and post-discharge rehabilitation (OR, 0.78; 95% CI: 0.65–0.93; P=0.007) were protective factors for 30-day readmissions in ischemic stroke survivors (Figures 11-14). Due to insufficient data reported in the studies, 17 factors could not be assessed, including epilepsy, peripheral arterial disease, deep vein thrombosis, dementia, infection, obesity, hospital region, ethnicity, renal failure, depression, admission to a non-neurological department, admission to an emergency department, admission on weekends, alcohol consumption, marriage, admission to a teaching hospital, and hospital ownership. Sensitivity analysis was performed for all analysis results, and there was no significant heterogeneity. Heterogeneity might have arisen from differences in geography, sample size, and study population across studies.

Figure 2 Influence of prior stroke on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 3 Influence of diabetes mellitus on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 4 Influence of hypertension on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 5 Influence of atrial fibrillation on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 6 Influence of heart failure on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 7 Influence of hyperlipidemia on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 8 Influence of coronary heart disease on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 9 Influence of smoking on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 10 Influence of gender (female) on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 11 Influence of treatment modality on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 12 Influence of discharge destination on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 13 Influence of health care payment model on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Figure 14 Influence of etiology on 30-day readmission in patients with ischemic stroke (Fixed effects model, Random effects model).

Publication bias

Inverted funnel plots for assessing publication bias are shown in the Appendix (Figures 15-27). Except for diabetes mellitus (Figure 16), hyperlipidemia (Figure 17), and intravenous thrombolysis (Figure 24), which might have involved some publication bias, none of the other factors showed significant publication bias.

Figure 15 Publication bias of prior stroke.

Figure 16 Publication bias of diabetes mellitus.

Figure 17 Publication bias of hypertension.

Figure 18 Publication bias of atrial fibrillation.

Figure 19 Publication bias of heart failure.

Figure 20 Publication bias of hyperlipidemia.

Figure 21 Publication bias of coronary heart disease.

Figure 22 Publication bias of smoking.

Figure 23 Publication bias of gender (female).

Figure 24 Publication bias of treatment modality.

Figure 25 Publication bias of discharge destination.

Figure 26 Publication bias of health care payment model.

Figure 27 Publication bias of etiology.

Discussion

To our knowledge, this is the first systematic review and meta-analysis of risk factors for 30-day readmission in patients with ischemic stroke. Although several systematic reviews and meta-analyses (8-10) have investigated the risk factors for readmission in stroke survivors, our current study possesses the following distinct strengths: (I) all the literature (including Chinese-language literature, English-language literature, gray literature, and references to relevant articles) as of April 30, 2021 was searched, and thus high-quality articles in the past 5 years were included in the analysis; (II) a total of 7 electronic databases (including Chinese-language databases) were searched, which were not examined in the previous meta-analyses; (III) only high-quality or moderate-quality studies were included for analysis, and some of these studies had large sample sizes, which increased the persuasiveness and scientific validity of our conclusions; and (IV) about 30 possible risk factors were considered, and detailed subgroup analyses were performed for some of the risk factors, with the results for some of these risk factors being reported for the first time.

Research on 30-day readmission in patients with ischemic stroke is a priority, and identifying the risk factors of readmissions is essential to implementing effective interventions and reducing the 30-day readmission rate. However, the exact risk factors remain controversial and have eluded exact study. The 30-day readmission rates of ischemic stroke survivors ranged from 1.41% to 27.64%, with a mean value of 10.66% (SD 6.87%). The results varied across countries and regions, with the highest reported 30-day readmission rate from China (11) and the lowest from the United States (12), which is consistent with the results of previous systematic reviews and meta-analyses (2,4,7,13-27). Many risk factors can contribute to 30-day readmission in patients with ischemic stroke. We screened about 30 of the most frequently mentioned risk factors in these 17 articles and finally identified 6 risk factors: history of stroke, diabetes mellitus, hypertension, atrial fibrillation, heart failure, and age. Among these, age was determined by descriptive analysis. Four risk factors were excluded, including hyperlipidemia, coronary heart disease, smoking, and gender, while 5 possible risk factors require further investigation, including duration of hospitalization, treatment modality, discharge disposition, health care payment model, and etiology. Intravenous thrombolysis and post-discharge rehabilitation showed protective effects. To our surprise, some of these risk factors have been shown to increase the risk of ischemic stroke, but our current study suggested that they did not increase the risk of 30-day readmission in patients with ischemic stroke.

We confirmed that a history of stroke, diabetes mellitus, hypertension, atrial fibrillation, or heart failure is a risk factor for 30-day readmission in patients with ischemic stroke. In our current analysis, “history of stroke” had different meanings across the included studies (4,17,18,22,28-30) and was not explicitly defined in each study. Nevertheless, it could be definitively concluded that patients with a history of stroke are more likely to be readmitted within 30 days after discharge than those who experienced stroke for the first time. The possible explanation for this is that patients with previous ischemic stroke episodes have more risk factors, such as worse vascular condition, older age, or more comorbidities. However, it is unclear how a different, complex stroke history affects 30-day readmission. Whether diabetes mellitus, hypertension, atrial fibrillation, and heart failure are risk factors for 30-day readmission in patients with ischemic stroke remains controversial, even in some multicenter studies that had large sample sizes (2,5,7,18,23,31,32). Our current analysis confirmed the associations of these 4 comorbidities with 30-day readmission. It is possible that when patients have these comorbidities, the inner walls of blood vessels are often damaged and blood is more likely to be in a hypercoagulable state, leading to thrombus formation or dislodgement of existing thrombus, which ultimately cause stroke recurrence. Stroke recurrence is the leading cause of 30-day readmission in patients with ischemic stroke (2,4,7,17,24), and these comorbidities themselves may also directly lead to readmission (15,16,24,31). In addition, the outcomes of recovery from these comorbidities were closely related to medications, outpatient follow-up, and patients' dietary habits and exercise. Furthermore, the patients’ conditions and health care capacity varied from region to region, which may explain the inconsistent results across multiple studies. Therefore, for patients with ischemic stroke with a history of stroke, diabetes, hypertension, atrial fibrillation, and/or heart failure, tailored health care should be offered within 30 days after discharge, which may benefit more patients and lower the 30-day readmission rate.

Length of hospital stay and age have been explored in many studies, but the type of data reported varied widely across studies. Boehme et al., Vahidy et al., Lichtman et al., Qiu et al., and Han et al. (5,7,18,28,33) presented the means and SDs of length of hospital stay. Bjerkreim et al., Wen et al., Mittal et al., Khanevski et al., and Kilkenny et al. (4,11,30,34,35) reported the medians and quartiles, while Crispo et al. and Lee et al. (12,36) performed subgroup comparisons. The same was true for age, with means and SD (4,5,7,17,18,22,28,30,34), medians and quartiles (11,35), and subgroup comparisons (12,18,29,33,36) being reported in different articles, which proved problematic in allowing us to obtain accurate quantitative results via meta-analysis. We believe that advanced age is largely a risk factor for 30-day readmission, while the length of hospital stay is still a controversial factor. According to the studies performed by Bambhroliya et al. (3) (n=2,078,854) and by Hirayama et al. (37) (n=620,788), advanced age is a risk factor for 30-day readmission in patients with ischemic stroke, which is consistent with the results of a study in China (2) that included 50,912 patients from 375 hospitals in 29 provinces. Hirayama et al. (37) noted that the 30-day readmission rate was significantly higher in patients older than 65 years compared with those younger than 65 years (65–74 years: OR 1.19, 95% CI: 1.16–1.21; 75–84 years: OR 1.29, 95% CI: 1.27–1.31; >85 years: OR 1.24, 95% CI: 1.22–1.27; all P<0.001). Nouh et al. (29) also showed that the 30-day readmission rate was higher in patients >75 years. Qureshi et al. (17) reported a 19% increase in the odds of readmission for each decade of older age. Compared to young and middle-aged patients, older adult patients had more comorbidities, as well as worse vascular condition, higher blood viscosity, and lower cardiac function, which could lead to hemodynamic deficiencies. As a result, patients with advanced age are more likely to be readmitted. A question then arises: what is the cutoff age for “advanced age”? There was no definite answer in our current analysis. In terms of length of hospital stay, some Korean and American studies (7,12,33,36) suggested that the length of hospital stay affects the 30-day readmission in patients with ischemic stroke, which was corroborated by the results of a few prospective cohort studies (32,38). Conversely, other studies from Norway (4), Australia (35), and China (28) reported opposing results. Unfortunately, some of the prospective studies with large sample sizes did not analyze the length of hospital stay (4,37). A study by Wen et al. (2) showed that a length of hospital stay longer than 7 days was associated with a reduced risk of 30-day readmission. In another study by Wen et al. (11), however, the risk of 30-day readmission was lowest in patients hospitalized for about 10 days, and longer or shorter length of hospital stay increased the risk of readmission. The controversy over the length of hospital stay may be due to differences in region, sample size, study type, medical resources, and level of care, though one of the key considerations may be as follows: a longer length of hospital stay indicates that the disease is more severe and more difficult to treat; however, the patients receive more medical resources and high-quality care, which theoretically leads to better outcomes and thus lowers readmission rates. A shorter length of hospital stay may have the opposite effect. We hope that multicenter prospective studies with larger sample sizes can further clarify the role of the length of hospital stay.

In our current analysis, 4 risk factors were excluded, including hyperlipidemia, coronary heart disease, smoking, and gender. These 4 factors are known to be risk factors for the development of ischemic stroke. Interestingly, however, they were not associated with 30-day readmission in patients with ischemic stroke. In some previous studies (4,11,32,39), abnormal lipid metabolism and heart-related diseases differed between two groups of patients, but the investigators did not analyze hyperlipidemia and coronary heart disease separately. In addition, although studies with large sample sizes performed by Crispo et al. and Lichtman et al. (12,18) suggested that gender might increase the likelihood of 30-day readmission in patients with ischemic stroke, our analysis did find a basis for this association (1.3 million participants in 13 articles), which was supported by a prospective study performed by Terman et al. (32). This may be due to the fact that, within 30 days of discharge, patients have good medication compliance, their disease is effectively controlled, and acute conditions due to hyperlipidemia and coronary artery disease are relatively rare. For smoking and gender, a period of 30 days may be too short to reflect the impact these factors on readmission, and perhaps a longer period would have shown a difference. It is also possible that the included studies had some limitations in data analysis. For instance, gender was not analyzed in subgroups based on age or disease condition, and no accurate or specific data on smoking were collected.

Regretfully, we failed to analyze the impact of 5 possible risk factors on 30-day readmission in patients with ischemic stroke, including discharge disposition (home, rehabilitation facility, nursing home, home nursing, and others), health care payment model (Medicare, NHS, Medicaid, private insurance, and others), treatment modality (thrombolysis and thrombectomy), and etiology (atherosclerosis, cardiogenic cerebral embolism, small vessel disease, other definite causes, and other unknown causes). Nevertheless, we were the first to perform a detailed and systematic subgroup analysis of these factors. In fact, we performed subgroup analyses for each of these factors, but the literature was insufficient due to heterogeneity. Only intravenous thrombolysis and post-discharge rehabilitation had valuable outcomes in that they were protective factors for 30-day readmission in patients with ischemic stroke. This may be because patients who complete intravenous thrombolysis are those who are sent to the hospital promptly after disease onset for treatment, where they receive excellent medical care and have good outcomes and significant recovery immediately after completion of thrombolysis, which may eliminate the impact of inadequate blood supply to the brain. Therefore, we suggest that active intravenous thrombolysis should be carried out for patients with ischemic stroke who arrive in hospital within the treatment time window according to the standard operating requirements to reduce the risk of 30-day readmission. Post-discharge rehabilitation can help patients effectively control various risk factors, receive more health care, and reduce the risk of 30-day readmission. According to Andrews et al. (40), compared with low- and medium-intensity therapy, high-intensity therapy (physical therapy, occupational therapy, and speech therapy) can lower the 30-day readmission rate. However, patients who receive higher-intensity therapy may have more comorbidities and greater illness severity relative to those who receive lower-intensity therapy. We suggest that medical staff should strengthen health education, emphasize the importance of active rehabilitation when patients are discharged from hospital and in outpatient treatment, and provide personalized rehabilitation guidance according to each patient’s condition.

Our research also has some limitations. First, some of the factors [e.g., alcohol consumption, marriage, infection, National Institutes of Health Stroke Scale (NIHSS) score, nasogastric tube feeding, and indwelling catheter] were not subjected to meta-analysis because of the limited amount of included literature (41), but they were still very common. Although they have been investigated in a few multicenter studies with large sample sizes, more studies are still needed. Second, some potential risk factors were not included because the number of prospective observational or interventional studies focusing on the same factor was too small for a meta-analysis or a descriptive analysis. Nevertheless, we took these studies into account as much as possible in the analysis. All the studies included in this analysis were case-control studies, so causality cannot be inferred. In addition, recall bias may exist. Third, most of the included articles were from the United States, which might have had an impact on the study results due to the differences in cultural background, health care services, and research capacity. Some of the included articles did not strictly meet the inclusion or exclusion criteria, which might have also affected our conclusions. Fourth, some of the databases were not searched due to the limited resources of the research institutions. However, the databases used in our current analysis are large international databases that are commonly used in academic research. In particular, we searched Chinese databases, which ensures that the vast majority of the relevant literature was retrieved.

Conclusions

The 30-day readmission rate remains high in ischemic stroke survivors, ranging from 1.41% to 27.64%. The results varied across countries and regions, with the highest reported 30-day readmission rate from China and the lowest from the United States. Special attention should be paid to patients with a history of stroke, diabetes, hypertension, atrial fibrillation, heart failure, and/or advanced age. Timely intravenous thrombolysis can alleviate the disease, and post-discharge rehabilitation should be encouraged. These interventions help to reduce 30-day readmissions and benefit more patients. In contrast, interventions based on hyperlipidemia, coronary heart disease, smoking status, or gender may not improve the current situation. Additional research is needed on the length of hospital stay, treatment modality, discharge disposition, health care payment model, and etiology to explore their impact on 30-day readmission in patients with ischemic stroke.

Acknowledgments

Funding: This work was supported by West China Nursing Discipline Development Special Fund Project, Sichuan University (grant No. HXHL19004). The funding bodies were not involved in any aspects of the study.

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://dx.doi.org/10.21037/apm-21-2884

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/apm-21-2884). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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