Measuring stroke outcomes for 74 501 patients using linked administrative data: System-wide estimates and validation of 'home-time' as a surrogate measure of functional status

Association Between Time to Treatment With Endovascular Thrombectomy and Home-Time After Acute Ischemic Stroke

BACKGROUND AND OBJECTIVES

Home-time is a patient-prioritized stroke outcome that can be derived from administrative data linkages. The effect of faster time-to-treatment with endovascular thrombectomy (EVT) on home-time after acute stroke is unknown.

METHODS

We used the Quality Improvement and Clinical Research registry to identify a cohort of patients who received EVT for acute ischemic stroke between 2015 and 2022 in Alberta, Canada. We calculated days at home in the first 90 days after stroke. We used ordinal regression across 6 ordered categories of home-time to evaluate the association between onset-to-arterial puncture and higher home-time, adjusting for age, sex, rural residence, NIH Stroke Scale, comorbidities, intravenous thrombolysis, and year of treatment. We used restricted cubic splines to assess the nonlinear relationship between continuous variation in time metrics and higher home-time, and also reported the adjusted odds ratios within time categories. We additionally evaluated door-to-puncture and reperfusion times. Finally, we analyzed home-time with zero-inflated models to determine the minutes of earlier treatment required to gain 1 day of home-time.

RESULTS

We had 1,885 individuals in our final analytic sample. There was a nonlinear increase in home-time with faster treatment when EVT was within 4 hours of stroke onset or 2 hours of hospital arrival. There was a higher odds of achieving more days at home when onset-to-puncture time was <2 hours (adjusted odds ratio 2.36, 95% CI 1.77-3.16) and 2 to <4 hours (1.37, 95% CI 1.11-1.71) compared with ≥6 hours, and when door-to-puncture time was <1 hour (aOR 2.25, 95% CI 1.74-2.90), 1 to <1.5 hours (aOR 1.89, 95% CI 1.47-2.41), and 1.5 to <2 hours (1.35, 95% CI 1.04-1.76) compared with ≥2 hours. Results were consistent for reperfusion times. For every hour of faster treatment within 6 hours of stroke onset, there was an estimated increase in home-time of 4.7 days, meaning that approximately 1 day of home-time was gained for each 12.8 minutes of faster treatment.

DISCUSSION

Faster time-to-treatment with EVT for acute stroke was associated with greater home-time, particularly within 4 hours of onset-to-puncture and 2 hours of door-to-puncture time. Within 6 hours of stroke onset, each 13 minutes of faster treatment is associated with a gain of 1 day of home-time.

Days at Home After Transcatheter Versus Surgical Aortic Valve Replacement in Low-Risk Patients

BACKGROUND

Days at home (DAH) represents an important patient-oriented outcome that quantifies time spent at home after a medical event; however, this outcome has not been fully evaluated for low-surgical-risk patients undergoing transcatheter aortic valve replacement (TAVR). We sought to compare 1- and 2-year DAH (DAH365 and DAH730) among low-risk patients participating in a randomized trial of TAVR with a self-expanding bioprosthesis versus surgical aortic valve replacement (SAVR).

METHODS

Using Medicare-linked data from the Evolut Low Risk trial, we identified 619 patients: 606 (322 TAVR/284 SAVR) and 593 (312 TAVR/281 SAVR) were analyzed at 1 and 2 years, respectively. DAH was calculated as days alive and spent outside a hospital, inpatient rehabilitation, skilled nursing facility, long-term acute care hospital, emergency department, or observation stay. Mean DAH was compared using the t test.

RESULTS

The mean (SD) age and female sex were 74.7 (5.1) and 74.3 (4.9) years and 34.6% (115/332) and 30.3% (87/287) in TAVR and SAVR, respectively. Postprocedural discharge to rehabilitation occurred in ≤3.0% (≤10/332) in TAVR and 4.5% (13/287) in SAVR. The mean DAH365 was comparable in TAVR versus SAVR (352.2±45.4 versus 347.8±39.0; difference in days, 4.5 [95% CI, 2.3-11.2]; P=0.20). DAH730 was also comparable in TAVR versus SAVR (701.6±106.0 versus 699.6±94.5; difference in days, 2.0 [-14.1 to 18.2]; P=0.81). Secondary outcomes DAH30 and DAH90 were higher in TAVR (DAH30, 26.0±3.6 versus 20.7±6.4; difference in days, 5.3 [4.5-6.2]; P<0.001; DAH90, 85.1±8.3 versus 78.7±13.6; difference in days, 6.4 [4.6-8.2]; P<0.001).

CONCLUSIONS

In the Evolut Low Risk trial linked to Medicare, low-risk patients undergoing TAVR spend a similar number of days at home at 1 and 2 years compared with SAVR. Days spent at home at 30 and 90 days were higher in TAVR. In contrast to higher-risk patients studied in prior work, there is no clear advantage of TAVR versus SAVR for DAH in the first 2 years after AVR in low-surgical-risk patients.

Days at home after transcatheter or surgical aortic valve replacement in high-risk patients

BACKGROUND

Days at home (DAH) quantifies time spent at home after a medical event but has not been fully evaluated for TAVR. We sought to compare 1- and 5-year DAH (DAH₃₆₅, DAH₁₈₂₅) among high-risk patients participating in a randomized trial of transcatheter aortic valve replacement (TAVR) with a self-expanding bioprosthesis versus surgical aortic valve replacement (SAVR).

METHODS

We linked data from the U.S. CoreValve High Risk Trial to Medicare Fee-for-Service claims in 456 patients with 450 (234 TAVR/216 SAVR) and 427 (222 TAVR/205 SAVR) analyzed at 1 and 5 years. DAH was calculated as the number of days alive and spent outside of a hospital, skilled nursing facility, rehabilitation, long-term acute care hospital, emergency department, or observation stay.

RESULTS

Mean DAH₃₆₅ was higher in patients who underwent TAVR compared with SAVR (295.1 ± 106.9 vs 267.8 ± 122.3, difference in days 27.2 [95% CI 6.0, 48.5], P = .01). Compared with SAVR, TAVR patients had a shorter index length of stay (LOS) (7.4 ± 4.5 vs 12.5 ± 9.0, difference in days -5.1 [-6.5, -3.8], P < .001). The largest contributions to decreased DAH₃₆₅ were mortality days and total facility days after discharge from the index hospitalization (mortality days-TAVR: 34.7 ± 93.1 vs SAVR: 48.0 ± 108.8, difference in days -13.3 [95% CI -32.1, 5.5], P = .17; total facility days-TAVR: 27.9 ± 47.4 vs SAVR: 36.7 ± 48.9, difference in days -8.8 [95% CI -17.8, 0.1], P = .05). Mean DAH₁₈₂₅ was numerically but not statistically significantly higher in TAVR (TAVR: 1154.2 ± 659.0 vs SAVR: 1067.6 ± 697.3, difference in days 86.6 [95% CI -42.3, 215.6], P = .19). Landmark analysis showed no difference in DAH from years 1 to 5 (TAVR: 1040.4 ± 477.5 vs SAVR: 1022.9 ± 489.3, P = .74).

CONCLUSIONS

In the U.S. CoreValve High Risk Trial linked to Medicare, high-risk patients undergoing TAVR spend an average of 27 additional DAH compared with SAVR in the first year after the procedure due to a shorter index LOS and the additive effect of fewer but nonsignificantly different mortality and total facility days after discharge from the index hospitalization compared with SAVR. After the first year, both groups spend a similar number of DAH. These results describe the postprocedural course of high-risk patients from a patient-centered perspective, which may guide expectations regarding longitudinal health care needs and inform shared decision-making.

Clinical Significance and Value of Serum Homocysteine and Urine 11 Dehydrothromboxane B2 Combined with Transferrin-Specific Peptide in the Diagnosis of Cerebral Apoplexy

Objective

To explore the clinical significance and value of serum homocysteine (Hcy) and urine 11 dehydrothromboxane B2 (urine 11-DH-TXB2) combined with transferrin-specific peptide (TF-UP) in the diagnosis of stroke.

Methods

One hundred stroke patients treated from January 2019 to June 2021 were enrolled in our hospital as the study group. All the patients in the study group met the diagnostic criteria of stroke. The focus of stroke was confirmed by CT or MRI, and the first onset was less than 48 hours. One hundred healthy persons who went through physical examination in our hospital were enrolled as the control group. The comparison was taken to explore the clinical significance and value of Hcy and urine 11-DH-TXB2 combined with TF-UP in the diagnosis of stroke.

Results

There exhibited no significant difference in the history of smoking, drinking, and atrial fibrillation (P > 0.05). There were significant differences in systolic blood pressure, diastolic blood pressure, eGFR, history of hypertension, diabetes, and coronary heart disease (P < 0.05). In terms of the levels of Hcy, urine 11-DH-TXB2, and TF-UP, the levels of Hcy and urine 11-DH-TXB2 in the study group were higher compared to the control group, while the level of TF-UP in the study group was lower compared to the control group (P < 0.05). The results of logistic regression analysis indicated that there was a significant correlation between Hcy, urine 11-DH-TXB2, TF-UP, and stroke, and Hcy and urine 11-DH-TXB2 indicated positive correlation with stroke disease, while TF-UP level was negatively correlated with stroke disease (P < 0.05). The levels of Hcy, urine 11-DH-TXB2, and TF-UP were adopted as evaluation indexes to draw ROC curve. The results show that the area under the curve (AUC) of Hcy is 0.760 (95% CI 0.670~0.850). The best critical point was 3342.5 pg/mg Ucr, the sensitivity was 65.6%, and the specificity was 77.1%. The AUC of urine 11-DH-TXB2 was 0.773 (95% CI 0.685~0.861). The best critical point was 3354.44 pg/mg Ucr, the sensitivity was 71.2%, and the specificity was 78.3%. The AUC of TF-UP was 0.735 (95% CI 0.641~0.829). The best critical point was 3365.43 pg/mg Ucr, the sensitivity was 68.4%, and the specificity was 80.5%. If Hcy was detected in combination with other indexes, AUC increased to 0.749 when combined with urine 11-DH-TXB2, and AUC increased to 0.797 when combined with TF-UP. When the three are combined, the AUC can reach 0.836, the sensitivity is 79.1%, and the specificity is 80%. It shows that the combined detection of Hcy, urine 11-DH-TXB2, and TF-UP is of higher diagnostic value. The difference of data exhibited statistically significant (P < 0.05).

Conclusion

There is imbalance between Hcy, urine 11-DH-TXB2, and TF-UP in patients with acute stroke. High Hcy, urine 11-DH-TXB2, and low TF-UP are closely related to the occurrence of cerebral infarction. Hcy, urine 11-DH-TXB2, and TF-UP may be the risk factors of stroke and positively correlated with the degree of neurological impairment. Effective monitoring of Hcy and urine 11-DH-TXB2 combined with TF-UP levels and positive intervention measures may effectively prevent the occurrence and development of cerebral infarction, reduce Hcy and urine 11-DH-TXB2, or increase the level of TF-UP, which may provide new ideas for the treatment of cerebrovascular diseases.

External validation of the Passive Surveillance Stroke Severity Indicator

BACKGROUND

The Passive Surveillance Stroke Severity (PaSSV) Indicator was derived to estimate stroke severity from variables in administrative datasets but has not been externally validated.

METHODS

We used linked administrative datasets to identify patients with first hospitalization for acute stroke between 2007-2018 in Alberta, Canada. We used the PaSSV indicator to estimate stroke severity. We used Cox proportional hazard models and evaluated the change in hazard ratios and model discrimination for 30-day and 1-year case fatality with and without PaSSV. Similar comparisons were made for 90-day home time thresholds using logistic regression. We also linked with a clinical registry to obtain National Institutes of Health Stroke Scale (NIHSS) and compared estimates from models without stroke severity, with PaSSV, and with NIHSS.

RESULTS

There were 28,672 patients with acute stroke in the full sample. In comparison to no stroke severity, addition of PaSSV to the 30-day case fatality models resulted in improvement in model discrimination (C-statistic 0.72 [95%CI 0.71-0.73] to 0.80 [0.79-0.80]). After adjustment for PaSSV, admission to a comprehensive stroke center was associated with lower 30-day case fatality (adjusted hazard ratio changed from 1.03 [0.96-1.10] to 0.72 [0.67-0.77]). In the registry sample (N = 1328), model discrimination for 30-day case fatality improved with the inclusion of stroke severity. Results were similar for 1-year case fatality and home time outcomes.

CONCLUSION

Addition of PaSSV improved model discrimination for case fatality and home time outcomes. The validity of PASSV in two Canadian provinces suggests that it is a useful tool for baseline risk adjustment in acute stroke.

The Allure of Big Data to Improve Stroke Outcomes: Review of Current Literature

PURPOSE OF REVIEW

To critically appraise literature on recent advances and methods using "big data" to evaluate stroke outcomes and associated factors.

RECENT FINDINGS

Recent big data studies provided new evidence on the incidence of stroke outcomes, and important emerging predictors of these outcomes. Main highlights included the identification of COVID-19 infection and exposure to a low-dose particulate matter as emerging predictors of mortality post-stroke. Demographic (age, sex) and geographical (rural vs. urban) disparities in outcomes were also identified. There was a surge in methodological (e.g., machine learning and validation) studies aimed at maximizing the efficiency of big data for improving the prediction of stroke outcomes. However, considerable delays remain between data generation and publication. Big data are driving rapid innovations in research of stroke outcomes, generating novel evidence for bridging practice gaps. Opportunity exists to harness big data to drive real-time improvements in stroke outcomes.

Perspectives on Home Time and Its Association With Quality of Life After Inpatient Surgery Among US Veterans

IMPORTANCE

Home time, defined as time spent at home after hospital discharge, is emerging as a novel, patient-oriented outcome in stroke recovery and end-of-life care. Longer home time is associated with lower mortality and higher patient satisfaction. However, a knowledge gap exists in the measurement and understanding of home time in the population undergoing surgery.

OBJECTIVES

To examine the association between postoperative home time and quality of life (QoL), functional status, and decisional regret and to identify themes regarding the meaning of time spent at home after surgery.

DESIGN, SETTING, AND PARTICIPANTS

This mixed-methods study including a survey and qualitative interviews used an explanatory sequential design involving 152 quantitative surveys followed by in-depth interviews with 12 participants from February 26, 2020, to December 17, 2020. US veterans older than 65 years who underwent inpatient surgery at a single-center veterans hospital within the prior 6 to 12 months were studied.

EXPOSURES

Quality of life, measured by the Veterans RAND 12-item Health Survey and 19-item Control, Autonomy, Self-realization, and Pleasure scale; functional status, measured by activities of daily living (ADL) and instrumental ADL scales; and regret, measured by the Decision Regret Scale.

MAIN OUTCOMES AND MEASURES

Home time, standardized as percentage of total time spent at home from the time of surgery to the time of survey administration. Associations between home time and QoL, function, and decisional regret in the survey data were analyzed using Spearman correlation in the overall cohort and in operative stress score subcohorts (1-2 [low] vs 3-5 [high]) in a stratified analysis. The 12 semistructured interviews were analyzed to elicit patients' perspectives on home time in postoperative recovery. Qualitative data were coded and analyzed using content and thematic analysis and integrated with quantitative data in joint displays.

RESULTS

A total of 152 patients (mean [SD] age, 72.3 [4.4] years; 146 [96.0%] male) were surveyed, and 12 patients (mean [SD] age, 72.3 [4.8] years; 11 [91.7%] male) were interviewed. The median time to survey completion was 307 days (IQR, 265-344 days). The median home time was 97.8% (IQR, 94.6%-98.6%; range, 22.2%-99.5%). Increased home time was associated with better physical health-related QoL in the Veterans RAND 12-item Health Survey (r = 0.33; 95% CI, 0.18-0.47; P < .001) and higher ADL scores (r = 0.21; 95% CI, 0.06-0.36; P = .008) and instrumental ADL functional scores (r = 0.21; 95% CI, 0.04-0.37; P = .009). Decisional regret was inversely associated with home time in only the high operative stress score subcohort (r = -0.22; 95% CI, -0.47 to -0.04; P = .047). Home was perceived as a safe and familiar environment that accelerated recovery through nurturing support of loved ones.

CONCLUSIONS AND RELEVANCE

In this mixed-methods study including a survey and qualitative interviews, increased home time in the first year after major surgery was associated with improved daily function and physical QoL among US veterans. Interviewees considered the transition to home to be an indicator of recovery, suggesting that home time may be a promising, patient-oriented quality outcome measure for surgical recovery that warrants further study.

Population-based stroke surveillance using big data: state-wide epidemiological trends in admissions and mortality in New South Wales, Australia

OBJECTIVES

Epidemiological trends for major causes of death and disability, such as stroke, may be monitored using administrative data to guide public health initiatives and service delivery.

METHODS

We calculated admissions rates for ischaemic stroke, intracerebral haemorrhage and subarachnoid haemorrhage between 1 January 2005 and December 31^st, 2013 and rates of 30-day mortality and 365-day mortality in 30-day survivors to 31 December 2014 for patients aged 15 years or older from New South Wales, Australia. Annual Average Percentage Change in rates was estimated using negative binomial regression.

RESULTS

Of 81,703 eligible admissions, 64,047 (78.4%) were ischaemic strokes and 13,302 (16.3%) and 4,778 (5.8%) were intracerebral and subarachnoid haemorrhages, respectively. Intracerebral haemorrhage admissions significantly declined by an average of 2.2% annually (95% Confidence Interval = -3.5% to -0.9%) (p < 0.001). Thirty-day mortality rates significantly declined for ischaemic stroke (Average Percentage Change -2.9%, 95% Confidence Interval = -5.2% to -1.0%) (p = 0.004) and subarachnoid haemorrhage (Average Percentage Change = -2.6%, 95% Confidence Interval = -4.8% to -0.2%) (p = 0.04). Mortality at 365-days amongst 30-day survivors of ischaemic stroke and intracerebral haemorrhage was stable over time and increased in subarachnoid haemorrhage (Annual Percentage Change 6.2%, 95% Confidence Interval = -0.1% to 12.8%), although not significantly (p = 0.05).

DISCUSSION

Improved prevention may have underpinned declining intracerebral haemorrhage rates while survival gains suggest that innovations in care are being successfully translated. Mortality in patients surviving the acute period is unchanged and may be increasing for subarachnoid haemorrhage warranting investment in post-discharge care and secondary prevention.