Readmission Patterns in Patients with Spontaneous Intracerebral Hematoma: A Retrospective Analysis

doi:10.21203/rs.3.rs-5225687/v1

Introduction: Hospital readmissions following spontaneous intracerebral hemorrhage (sICH) represent a significant concern in healthcare, particularly in Ghana. The objective of this paper is to investigate the readmission rates of patients with sICH in Ghana and to identify the factors influencing these rates.

Methods: A retrospective study at the University of Ghana Medical Centre analyzed sICH patient data (January 2021-June 2023), comparing readmitted and non-readmitted groups using Wilcoxon rank-sum and chi-square tests to assess differences in clinical features, treatments, and outcomes.

Results: The study involved 84 non-readmitted patients and 18 re-admitted patients. Among the readmitted patients, 50.0% were females and 50.0% were males, compared to 27.4% and 72.6% in the non-readmitted group, respectively. The mean age of the non-readmitted patients was 51.5 years (SD = 12.2), while the mean age of the readmitted patients was 61.3 years (SD = 21.0). A higher proportion of readmitted patients had diabetes (22.2%) compared to non-readmitted patients (6.0%) (p = 0.049). The mean MRS 1 month and 3 months post-discharge were significantly higher in the readmitted group (p=0.004 and p=0.005, respectively). Patients who were readmitted had a lower GCS (10.9, SD = 3.4) compared with the non-readmitted group (p= 0.082).

Conclusion: These findings underscore the importance of comprehensive discharge planning and post-discharge support for patients with sICH, particularly those with diabetes and higher mRS scores, to mitigate readmission risks and improve long-term outcomes.

Spontaneous Intracerebral Hemorrhage

Stroke and Readmission.

Patient readmission, also known as hospital readmission, refers to the situation where a patient is admitted to a hospital again, specifically within 30 or 90 days after being discharged from the same or different hospital.¹ The rate and duration of readmissions vary depending on the health condition. In 2011, there were approximately 3.3 million adult 30-day all-cause readmissions in the United States with about $41.3 billion in hospital costs proposing hospital readmissions as one of the most expensive to tackle in the country.² Risk factors for hospital readmissions include age, sex, pre-existing comorbidities and socioeconomic constraints.^1,3,4 Various causes and effects can be enumerated in patient readmissions, some arising from the healthcare personnel or facility and others from the patients themselves. Unplanned readmissions can be caused by several factors including: premature discharge and poor discharge planning, medication errors, inadequate patient counsel or education amongst many others.^5,6 Studies by Hernandez et al.⁷ and Jencks et al.⁸ revealed poor follow-up care as a crucial cause of increased hospital readmissions.

Studies on readmission rates among neurologic patients have primarily focused on ischemic stroke, with limited data available on spontaneous intracerebral hemorrhage (sICH).⁹ The existing studies, which are based on Medicare data, indicate that patients with ICH have a high readmission rate of over 15% within 30 days, even in specialized stroke centers.¹⁰ The rate of readmission after intracerebral hemorrhage (ICH) is not well understood.¹⁰ Most studies on ischemic stroke readmissions have relied on large administrative databases, which have limitations such as non-specific diagnostic codes and indirect measures of disease severity.^11,12 The few hospital-based studies on this topic have only provided limited information on disease severity, hospital course, and outcomes.¹³ While large administrative databases can detect small associations with readmission, they may not be able to fully investigate these associations or determine their clinical significance, making it challenging for individual institutions to develop effective strategies to reduce readmission rates.¹³

This study aims to offer valuable insights into hospital readmissions following sICH in the University of Ghana Medical Center. By employing a hospital-based approach, the study provides a more detailed and nuanced understanding of the factors associated with sICH readmission. The findings will contribute significantly to the development of targeted strategies for reducing readmission rates within Ghanaian healthcare settings.

Study Design

This research was a retrospective study carried out at the University of Ghana Medical Centre, a major hospital in Accra. We received ethical approval from the facility's review board (UGMC-IRB/MSRC/041/2023). Since the study was retrospective and posed minimal risk to patients, informed consent was waived. All eligible patients were included in the study. We reviewed patient records from January 2021 to June 2023, encompassing patients treated in the Emergency Department, Neurosurgery, General Intensive Care, and Internal Medicine Units. Data collected included patient demographics, initial symptoms, risk factors, initial blood pressure readings, time to reach target blood pressure, CT scan findings (including hematoma volume using the ABC/2 formula,¹⁴ location, and complications), treatment approaches, and patient outcomes, readmission status and ICU admission events.

Inclusion and Exclusion Criteria

The study focused on adult patients (over 18 years old) who had a new, confirmed spontaneous intracerebral hemorrhage as identified by CT scans. We excluded patients whose hemorrhage was caused by trauma or surgical complications, subarachnoid hemorrhage, hemorrhagic cerebral tumors, or hemorrhagic transformation of acute ischemic stroke.

Data Analysis

Data was carefully checked for accuracy and consistency. The statistical analysis was carried out using R Studio (Version 4.3). To present the data, measures like averages and standard deviations were used for continuous data, while count and percentages were used for categorical data. We studied various variables like the mean age, clinical comorbidities, last know normal timeframe, Glasgow Coma Score (GCS), and type of management. This statistical method offered a detailed analysis of the sICH patients' medical profile, care methods, and results in a large Ghanaian hospital. To compare continuous data among different groups, we used the Wilcoxon rank-sum test. When working with categorical data, we applied the chi-square test, switching to Fisher's exact test if a group had fewer than five counts in a cell. We divided the patients into two groups: those who were readmitted to the hospital and those who were discharged and did not return to our facility as inpatients. We analyzed and compared the different clinical characteristics of sICH patients between the two groups: those who were readmitted and those who were not.

Demographics, Clinical and Comorbidity Profiles

The study involved 84 patients who were not readmitted and 18 patients who were readmitted after being hospitalized for sICH. Among the readmitted patients, 50.0% were females and 50.0% were males, compared to 27.4% and 72.6% in the non-readmitted group, respectively. The mean age of the non-readmitted patients was 51.5 years (SD = 12.2), vs. 61.3 years (SD = 21.0, p = 0.071) in the readmitted cohort.

Regarding clinical characteristics and comorbidities, 85.5% of non-readmitted patients had hypertension, compared to 83.3% of readmitted patients (p = 0.728). A higher proportion of readmitted patients had diabetes (22.2%) compared to non-readmitted patients (6.0%) (p = 0.049). Among the readmitted patients, 61.1% presented with loss consciousness, whereas 42.9% of non-readmitted patients presented with same (p = 0.25). Regarding the time of the last known normal (LKN), a higher proportion of readmitted patients (45.5%) had presented within 3-6 hours of symptom onset, compared to 5.3% of non-readmitted patients (p = 0.02). None of the non-readmitted patients had presented within 48-72 hours, while 18.2% of readmitted patients had presented within that timeframe (p = 0.146). The mean GCS score at presentation was higher for the non-readmitted patients (12.6, SD = 3.2) compared to the readmitted patients (10.9, SD = 3.4) with a p-value of 0.082. The details of the demographic, clinical and comorbidity profiles of the patients are described in Table 1.

The Association Between Hematoma Characteristics and Readmission

The anatomical location of the hematoma revealed that 35.3% of readmitted patients had lobar involvement, compared to 12% of non-readmitted patients. The presence of hydrocephalus was more common in non-readmitted patients (26.9%) than readmitted patients (12.5%). Notably, the mean hematoma volume was significantly higher in readmitted patients (48.0mls) compared to non-readmitted patients (17.4mls, p=0.362). Table 2 shows the association between various characteristics of sICH patients and hospital readmission.

Management Approaches, Outcomes and Glasgow Coma Scale (GCS) Progression.

The management type was not significantly associated with readmission (p=0.265), with 88.1% of non-readmitted patients and 77.8% of readmitted patients receiving conservative management. In terms of hospital outcomes, 94.0% of non-readmitted patients were discharged, whereas all readmitted patients were eventually discharged (p=0.583). The mean hospital length of stay (LOS) was not significantly different between the two groups (p=0.556). The mean Glasgow Coma Scale (GCS) at discharge and the mean modified Rankin Scale (MRS) at discharge showed no significant difference between the groups. However, the mean MRS 1 month and 3 months post-discharge were significantly higher in the readmitted group (p=0.004 and p=0.005, respectively). These results suggest that readmitted patients had worse outcomes 1 and 3 months after discharge. Table 3 details the management and outcomes of patients with sICH and their association with hospital readmission.

Timing to Readmission and Readmission Outcomes in Patients with sICH.

Out of 18 readmitted patients, 16.7% were readmitted within the first week, 11.1% between 1-2 weeks, and 11.1% between 2-4 weeks. The majority (27.8%) were readmitted between 1-3 months, while 16.7% were readmitted between 3-6 months, and 11.1% between 6-12 months. One patient was readmitted between 1-2 years. In terms of in-hospital outcomes of readmission, 38.9% of patients died, 55.6% were discharged, and 5.56% were referred. The timing to mortality showed that 42.9% of patients died within 3 months, 42.9% between 3-6 months, and 14.3% after 1 year. Table 4 provides information about the timing of readmission and mortality for patients with sICH.

Based on the provided data, this study compared the demographic and clinical characteristics of patients who were readmitted to the hospital and those who were not. The study suggests that readmitted patients had worse outcomes at discharge and post-discharge.

Demographics, Clinical Characteristics, Readmission and Readmission Outcomes

Our study found that hospitalized patients who were readmitted had a higher average age than those not readmitted, though this difference wasn't statistically significant. Although our study found an equal number of men and women in the readmitted group, previous research has shown conflicting results regarding gender and readmission rates. While one study reported a higher incidence of readmission among male patients,¹⁵ another study found slightly more women being readmitted.¹⁶ This inconsistency may be due to differences in patient populations, study designs, or statistical methods. Nonetheless, the finding of an equal gender distribution in the readmitted group in this study suggests that gender may not be a significant factor for hospital readmission risk in this specific patient population. Further research is needed to clarify the relationship between gender and hospital readmission risk in different patient populations. The finding of a higher mean age in the readmitted cohort, consistent with Bjerkreim et al's report,¹⁷ may be attributed to the fact that older age is often accompanied by comorbidities, which can make the management of sICH more challenging.

Short-term readmissions (<1 week to 4 weeks) accounted for 39.9% of cases, indicating that many patients in our study potentially experienced complications soon after discharge. The mortality rate is concentrated in the first six months post-readmission, with 85.8% of deaths occurring within that timeframe. This suggests that early follow-up care and monitoring could be crucial for improving outcomes. Although some studies have shown mixed results regarding the link between diabetes and readmission rates,^18,19 our study found a significant association between diabetes and readmission status. Interestingly, our results showed that Diabetes Mellitus was the only statistically significant factor associated with readmission, which aligns with a previous study that found higher frequencies of Diabetes in patients with late readmissions beyond 30 days.¹⁷ This finding could be explained by the well-known macrovascular and microvascular complications of diabetes, particularly vascular dysfunction, which can increase the risk of complications and readmission in patients with intracerebral hemorrhage.²⁰ Also, while a low GCS score at presentation showed no association with readmission risk in our study (p=0.082), this finding is similar to the findings of Liotta et al., who found no significant relationship between a low GCS score and readmission status.⁹ It is possible that we noted a low GCS score in our readmission cohort because patients with lower GCS scores might undergo more aggressive treatments, including surgeries or intensive medical interventions.²¹ These treatments could raise the likelihood of complications, thereby increasing the possibility of readmission. The significant difference in LKN timeframe between readmitted and non-readmitted patients in our study highlights the importance of considering the time course of neurological decline in managing patients with ICH. This might primarily be because a shorter LKN timeframe might indicate a more rapid progression of the ICH, potentially leading to a higher risk of complications requiring readmission.²² Another possible explanation is the fact that these patients presented to the hospital early hence why we recorded a shorter LKN timeframe. The most notable finding is the significant difference in functional outcomes at discharge and follow-up between readmitted and non-readmitted patients. Readmitted patients had worse functional outcomes at discharge after their first admission and remained significantly worse at 1- and 3-months post-discharge. Liotta et al.'s study supports our findings, as we also identified mRS as a statistically significant factor.⁹ This could be mainly because patients with higher mRS scores might require closer monitoring and additional support, which could lead to increased healthcare utilization and hospital readmissions.

Limitations and Future Recommendations

This retrospective study, the first of its kind in Ghana focusing solely on sICH readmission factors, has limitations due to its single-center design. Findings may not be generalizable to all institutions, as other centers might observe unique associations related to their patient acuity and specific circumstances. Like many other African nations and lower-middle-income regions, our hospital encounters substantial resource shortages that significantly affect patient outcomes.^23,24 The shortage of specialized neurosurgery staff and insufficient ICU beds hampers our ability to provide timely and optimal care for patients requiring intensive monitoring and post-operative interventions.^23,25 These constraints can lead to inadequate management of complications, resulting in higher readmission rates. Additionally, many patients are lost to follow up after discharge and this affects the quality of post stroke rehabilitation care they can receive. This situation is further worsened by the lack of dedicated care givers in assist some families care for patients with low MRS scores.

The study's retrospective design may have compromised the quality of evidence and introduced bias, particularly in the reporting of complications due to potential underreporting. The data's dependence on clinical and procedural records, which may not have been consistently collected according to strict criteria, could also affect the results. Challenges arose from incomplete or inaccurate records despite the data being obtained from an electronic medical record system. Additionally, the absence of control over the original data collection introduced inconsistencies and the potential impact of unmeasured confounding variables. While the sample size is substantial for a single-center study, it is smaller than those used in larger-scale ischemic stroke readmission studies, potentially limiting the detection of smaller effect sizes. This reflects a balance between sample size, data detail, patient classification accuracy, and the identification of clinically significant associations.

By addressing these challenges—such as enhancing staff training, increasing ICU capacity, and improving overall healthcare delivery—we can mitigate the factors contributing to elevated readmission rates. Ultimately, improving access to quality care is essential for enhancing patient survival and reducing the burden of readmissions in our healthcare system. Nonetheless, we believe our cohort, representing several years of ICH admissions at a major medical center, is large enough to identify clinically meaningful associations for developing targeted interventions to reduce readmissions at the institutional level. Future research using larger administrative databases is needed to identify smaller epidemiologic associations between sICH and hospital readmission.

This study has explored the complexities surrounding readmission rates for patients with spontaneous intracerebral hemorrhage (sICH) in Ghana. By highlighting the relationship between these factors and increased readmission rates, it emphasizes the urgent need for targeted strategies to enhance care of patients with sICH even after discharge. Ultimately, addressing these challenges is essential for improving patient care, reducing readmission rates, and ensuring better survival outcomes in our healthcare system.

SICH: Spontaneous Intracerebral Hemorrhage; ICH: Intracerebral Hemorrhage; SD: Standard Deviation; UGMC: University of Ghana Medical Center; IRB: Institutional Review Board; MSRC: Medical and Scientific Research Center; CT: Computed Tomography; ICU: Intensive Care Unit; GCS: Glasgow Coma Score; LKN: Last Known Normal; LOS: Length of Stay; MRS: Modified Rankin Scale.

Funding Statement: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Conflict of interest Statement: The authors have no personal or institutional interest with regards to the authorship and/or publication of this manuscript

Author’s Contributions:

Conceptualization and Methodology: PT and EO. Formal Analysis: KD. Resources and Data Curation: All Authors. Writing-Original Draft: PT, EO, KD, OA, and AD. Writing - Review & Editing: EO, PT, KD, OA and TT. Supervision: PT, KD and TT.

IRB compliance statement and ethical adherence: This study was written in compliance with our institutional ethical review board. IRB approval was granted with IRB number UGMC-IRB/MSRC/041/2023

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Table 1.

Variables	Readmitted
Variables	No (N=84) N (%)	Yes (N=18) N (%)	p-value
Demographics
Mean Age in Years (SD)	51.5 (12.2)	61.3 (21.0)	0.071
Female	23 (27.4)	9 (50.0)	NA
Male	61 (72.6)	9 (50.0)	NA
Clinical Characteristics and Comorbidities
Hypertension	71 (85.5)	15 (83.3)	0.728
Diabetes	5 (6.0)	4 (22.2)	0.049
LOC	36 (42.9)	11 (61.1)	0.25
Seizures	11 (13.1)	3 (16.7)	0.709
Limb Weakness	51 (60.7)	9 (50.0)	0.566
Headache	24 (28.6)	3 (16.7)	0.387
Time to Last Known Normal
3-6 Hours	3 (5.3)	5 (45.5)	0.02
6-12 Hours	9 (15.8)	0 (0.0)
12-24 Hours	14 (24.6)	3 (27.3)
24-48 Hours	5 (8.8)	2 (18.2)
48-72 Hours	7 (12.3)	0 (0.0)
3-7 Days	14 (24.6)	1 (9.09)
Mean GCS at Presentation (SD)	12.6 (3.2)	10.9 (3.4)	0.082

Abbreviations

GCS: Glasgow Coma Score

LOC: Loss Of Consciousness

N: Total Number

NA: Not Applicable

SD: Standard Deviation

sICH: Spontaneous Intracerebral Haemorrhage

Table 2.

Variables	Readmitted
Variables	No (N=84) N (%)	Yes (N=18) N (%)	p-value
Topography of Hematoma
Left Hemisphere	40 (52.6)	11 (64.7)	0.526
Right Hemisphere	36 (47.4)	6 (35.3)	0.526
Infratentorial	3 (3.57)	1 (5.6)	0.546
Supratentorial	81 (96.4)	17 (94.4)	0.546
Anatomical Location of Hematoma
Basal ganglia	39 (47.0)	3 (17.6)	0.132
Cerebellar	2 (2.4)	2 (11.8)
Lobar	10 (12.0)	6 (35.3)
Thalamus	16 (19.3)	5 (29.4)
Intraventricular Extension	43 (53.1)	8 (47.1)	0.853
Presence Of Hydrocephalus	21 (26.9)	2 (12.5)	0.341
Mean ICH Score (SD)	1.28 (1.1)	1.29 (1.3)	0.982
Mean Predicted Mortality (SD)*	21.2 (24.8)	23.1 (32.4)	0.837
Mean Hematoma Volume in mls (SD)	17.4 (14.5)	48.0 (117)	0.362

*Predicted mortality rate from ICH score of included patients

Abbreviations

ICH: Intracerebral Hemorrhage

mls: Milliliters

N: Total Number

SD: Standard Deviation

Table 3.

Variables	Readmitted
Variables	No, N=84 N (%)	Yes, N=18 N (%)	p-value
Conservative Management	74 (88.1)	14 (77.8)	0.265
Surgical Management	10 (11.9)	4 (22.2)	0.265
In Hospital Outcome at First Admission
Referred	5 (6.0)	0 (0.0)	0.583
Discharged	79 (94.0)	18 (100.0)	0.583
Mean Hospital LOS in days (SD)	9.68 (10.2)	11.2 (9.9)	0.556
Mean GCS at discharge	14.0 (2.3)	13.9 (1.5)	0.853
Mean MRS at discharge	3.1 (1.5)	4.0 (0.9)	0.019
Mean MRS 1 Month Post-discharge	2.0 (1.7)	3.8 (0.8)	0.004
Mean MRS 3-Month Post-discharge	1.2 (1.5)	3.7 (1.4)	0.005

Abbreviations

BP- Blood pressure

EVD- External ventricular drainage

GCS- Glasgow coma scale

ICU- Intensive care unit

MRS- Modified ranking score

SD- Standard deviation

Table 4.

Variables	(N=18) N (%)
Timing to First Readmission
<1 Week	3 (16.7)
1-2 Weeks	2 (11.1)
2-4 Weeks	2 (11.1)
1-3 Months	5 (27.8)
3-6 Months	3 (16.7)
6-12 Months	2 (11.1)
1-2 Years	1 (5.6)
In Hospital Outcome post-First Readmission
Died	7 (38.9)
Discharged	10 (55.6)
Referred	1 (5.56)
Timing to Mortality
<3 Months	3 (42.9)
3-6 Months	3 (42.9)
>1 Year	1 (14.3)

Abbreviations

ICU: Intensive Care Unit

N: Total number

NA: Not Applicable

No competing interests reported.

Readmission Patterns in Patients with Spontaneous Intracerebral Hematoma: A Retrospective Analysis

Status:

Version 1

Abstract

Introduction

Methods

Results

Discussion

Conclusion

Abbreviations

Declarations

References

Tables

Additional Declarations

Status:

Version 1