Developing an adapted Charlson comorbidity index for ischemic stroke outcome studies

Age-adjusted Charlson comorbidity index is associated with the risk of osteoporosis in older fall-prone men: a retrospective cohort study

BACKGROUND

There is growing evidence linking the age-adjusted Charlson comorbidity index (aCCI), an assessment tool for multimorbidity, to fragility fracture and fracture-related postoperative complications. However, the role of multimorbidity in osteoporosis has not yet been thoroughly evaluated. We aimed to investigate the association between aCCI and the risk of osteoporosis in older adults at moderate to high risk of falling.

METHODS

A total of 947 men were included from January 2015 to August 2022 in a hospital in Beijing, China. The aCCI was calculated by counting age and each comorbidity according to their weighted scores, and the participants were stratified into two groups by aCCI: low (aCCI < 5), and high (aCCI ≥5). The Kaplan Meier method was used to assess the cumulative incidence of osteoporosis by different levels of aCCI. The Cox proportional hazards regression model was used to estimate the association of aCCI with the risk of osteoporosis. Receiver operating characteristic (ROC) curve was adapted to assess the performance for aCCI in osteoporosis screening.

RESULTS

At baseline, the mean age of all patients was 75.7 years, the mean BMI was 24.8 kg/m2, and 531 (56.1%) patients had high aCCI while 416 (43.9%) were having low aCCI. During a median follow-up of 6.6 years, 296 participants developed osteoporosis. Kaplan-Meier survival curves showed that participants with high aCCI had significantly higher cumulative incidence of osteoporosis compared with those had low aCCI (log-rank test: P < 0.001). When aCCI was examined as a continuous variable, the multivariable-adjusted model showed that the osteoporosis risk increased by 12.1% (HR = 1.121, 95% CI 1.041-1.206, P = 0.002) as aCCI increased by one unit. When aCCI was changed to a categorical variable, the multivariable-adjusted hazard ratios associated with different levels of aCCI [low (reference group) and high] were 1.00 and 1.557 (95% CI 1.223-1.983) for osteoporosis (P <  0.001), respectively. The aCCI (cutoff ≥5) revealed an area under ROC curve (AUC) of 0.566 (95%CI 0.527-0.605, P = 0.001) in identifying osteoporosis in older fall-prone men, with sensitivity of 64.9% and specificity of 47.9%.

CONCLUSIONS

The current study indicated an association of higher aCCI with an increased risk of osteoporosis among older fall-prone men, supporting the possibility of aCCI as a marker of long-term skeletal-related adverse clinical outcomes.

Age-Specific Association of Co-Morbidity With Home-Time After Acute Stroke

OBJECTIVE

To examine the association of co-morbidity with home-time after acute stroke and whether the association is influenced by age.

METHODS

We conducted a province-wide study using linked administrative databases to identify all admissions for first acute ischemic stroke or intracerebral hemorrhage between 2007 and 2018 in Alberta, Canada. We used ischemic stroke-weighted Charlson Co-morbidity Index of 3 or more to identify those with severe co-morbidity. We used zero-inflated negative binomial models to determine the association of severe co-morbidity with 90-day and 1-year home-time, and logistic models for achieving ≥ 80 out of 90 days of home-time, assessing for effect modification by age and adjusting for sex, stroke type, comprehensive stroke center care, hypertension, atrial fibrillation, year of study, and separately adjusting for estimated stroke severity. We also evaluated individual co-morbidities.

RESULTS

Among 28,672 patients in our final cohort, severe co-morbidity was present in 27.7% and was associated with lower home-time, with a greater number of days lost at younger age (-13 days at age < 60 compared to -7 days at age 80+ years for 90-day home-time; -69 days at age < 60 compared to -51 days at age 80+ years for 1-year home-time). The reduction in probability of achieving ≥ 80 days of home-time was also greater at younger age (-22.7% at age < 60 years compared to -9.0% at age 80+ years). Results were attenuated but remained significant after adjusting for estimated stroke severity and excluding those who died. Myocardial infarction, diabetes, and cancer/metastases had a greater association with lower home-time at younger age, and those with dementia had the greatest reduction in home time.

CONCLUSION

Severe co-morbidity in acute stroke is associated with lower home-time, more strongly at younger age.

Machine learning-based models for prediction of the risk of stroke in coronary artery disease patients receiving coronary revascularization

BACKGROUND

To construct several prediction models for the risk of stroke in coronary artery disease (CAD) patients receiving coronary revascularization based on machine learning methods.

METHODS

In total, 5757 CAD patients receiving coronary revascularization admitted to ICU in Medical Information Mart for Intensive Care IV (MIMIC-IV) were included in this cohort study. All the data were randomly split into the training set (n = 4029) and testing set (n = 1728) at 7:3. Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO) regression model were applied for feature screening. Variables with Pearson correlation coefficient<9 were included, and the regression coefficients were set to 0. Features more closely related to the outcome were selected from the 10-fold cross-validation, and features with non-0 Coefficent were retained and included in the final model. The predictive values of the models were evaluated by sensitivity, specificity, area under the curve (AUC), accuracy, and 95% confidence interval (CI).

RESULTS

The Catboost model presented the best predictive performance with the AUC of 0.831 (95%CI: 0.811-0.851) in the training set, and 0.760 (95%CI: 0.722-0.798) in the testing set. The AUC of the logistic regression model was 0.789 (95%CI: 0.764-0.814) in the training set and 0.731 (95%CI: 0.686-0.776) in the testing set. The results of Delong test revealed that the predictive value of the Catboost model was significantly higher than the logistic regression model (P<0.05). Charlson Comorbidity Index (CCI) was the most important variable associated with the risk of stroke in CAD patients receiving coronary revascularization.

CONCLUSION

The Catboost model was the optimal model for predicting the risk of stroke in CAD patients receiving coronary revascularization, which might provide a tool to quickly identify CAD patients who were at high risk of postoperative stroke.

Minimally invasive epicardial surgical left atrial appendage exclusion for atrial fibrillation patients at high risk for stroke and for bleeding

BACKGROUND

Atrial fibrillation (AF) patients at high risk for stroke and for bleeding may be unsuitable for either oral anticoagulation or endocardial left atrial appendage (LAA) occlusion. However, minimally invasive, epicardial left atrial appendage exclusion (LAAE) may be an option.

OBJECTIVE

The purpose of this study was to evaluate outcomes of LAAE in high-risk AF patients not receiving oral anticoagulation.

METHODS

A retrospective analysis of Medicare claims data was conducted to evaluate thromboembolic events in AF patients who underwent LAAE compared to a 1:4 propensity score-matched group of patients who did not receive LAAE (control). Neither group was receiving any oral anticoagulation at baseline or follow-up. Fine-Gray models estimated hazard ratios and evaluated between-group differences. Bootstrapping was applied to generate 95% confidence intervals (CIs).

RESULTS

The LAAE group (n = 243) was 61% male (mean age 75 years). AF was nonparoxysmal in 70% (mean CHA2DS2-VASc score 5.4; mean HAS-BLED score 4.2). The matched control group (n = 972) had statistically similar characteristics. One-year adjusted estimates of thromboembolic events were 7.3% (95% CI 4.3%-11.1%) in the LAAE group and 12.1% (95% CI 9.5%-14.8%) in the control group. Absolute risk reduction was 4.8% (95% CI 0.6%-8.9%; P = .028). Adjusted hazard ratio for thromboembolic events for LAAE vs non-LAAE was 0.672 (95% CI 0.394-1.146).

CONCLUSION

In AF patients not taking oral anticoagulation who are at high risk for stroke and for bleeding, minimally invasive, thoracoscopic, epicardial LAAE was associated with a lower rate of thromboembolic events.

Developing 60-Day Readmission Risk Score among Home Healthcare Patients with Heart Failure

Heart failure (HF) readmissions are common, costly, and often preventable. Despite the implementation of HF programs across clinical settings, rehospitalization is still common. Efforts to identify risk factors for 60-day rehospitalization among HF patients exist, but risk scoring has not been utilized in home healthcare. The purpose of this study was to develop a 60-day rehospitalization risk score for home care patients with HF. This study is a secondary data analysis of a retrospective cross-sectional dataset that was composed of data using the Outcome Assessment Information Set (OASIS)-C version for patients with HF. We computed the Charlson Comorbidity Index (CCI) to use as a confounder. The risk score was computed from the final logistic regression model regression coefficients. The median age was 78 years old, 45.4% were male, and 81.0% were White. We identified 10 significant risk factors including CCI score. The risk score achieved a c-statistic of 0.70 in this patient sample. This risk score could prove useful in clinical practice for guiding attention and decision-making for personalized care of patients with unrecognized or under-treated health needs.

Ability of the DANCAMI to predict the risk ischemic stroke and mortality in patients with atrial fibrillation/flutter

OBJECTIVES

Comparison of the danish comorbidity index for acute myocardial infarction (DANCAMI), the charlson comorbidity index (CCI), the elixhauser comorbidity index (ECI), and the CHA2DS2-VASc score to predict ischemic stroke, cardiovascular mortality, and all-cause mortality after atrial fibrillation/flutter.

MATERIALS AND METHODS

A population-based cohort study of all Danish patients with incident atrial fibrillation/flutter during 2000-2020 (n=361,901). C-Statistics were used to evaluate the discriminatory performance for predicting 1 and 5-year risks of the outcomes for a baseline model (including age and sex) +/- the individual indices.

RESULTS

For the DANCAMI, the 5-year risk did not increase with comorbidity burden for ischemic stroke (5.9% for low vs. 5.6% for severe) but did increase for cardiovascular mortality (10% for low vs. 16% for severe) and all-cause mortality (33% for low vs. 61% for severe). C-Statistics for predicting 5-year ischemic stroke risk were similar for all models (0.64). C-Statistics for predicting 5-year cardiovascular mortality risk were also similar for the baseline (0.76), the DANCAMI (0.77), the CCI (0.76), the ECI (0.76), and the CHA2DS2-VASc (0.76) models. C-Statistics for predicting 5-year all-cause mortality risk were lower for the baseline (0.71) and the CHA2DS2-VASc (0.71) models than for the DANCAMI (0.75), the CCI (0.74), and the ECI (0.74) models. The 1-year C-Statistics were comparable.

CONCLUSION

The DANCAMI predicted ischemic stroke and cardiovascular mortality risks similar to the CCI, the ECI, and the CHA2DS2-VASc. The DANCAMI predicted all-cause mortality risk similar to the CCI and the ECI, but better than the baseline and the CHA2DS2-VASc.

Association of co-morbidity with acute stroke mortality by age and time since stroke: A population-based study

OBJECTIVE

To examine whether the association of co-morbidity with mortality after acute stroke is influenced by stroke type, age, sex, or time since stroke.

MATERIALS AND METHODS

We conducted a province-wide population-based study using linked administrative databases to identify all admissions for acute stroke between 2007-2018 in Alberta, Canada. We used Cox proportional hazard models to determine the association of severe co-morbidity based on the Charlson Co-morbidity Index with 1-year mortality after stroke, assessing for effect modification by stroke type, age, and sex, and with adjustment for estimated stroke severity, comprehensive stroke centre care, hypertension, atrial fibrillation, and year of study. We used a piecewise model to analyze the impact of co-morbidity across four time periods.

RESULTS

We had 28,672 patients in our final cohort (87.8% ischemic stroke). The hazard of mortality with severe co-morbidity was higher for individuals with ischemic stroke (adjusted hazard ratio [aHR] 2.20, 95% CI 2.07-2.32) compared to those with intracerebral hemorrhage (aHR 1.70, 95% CI 1.51-1.92; pint<0.001), and higher in individuals under age 75 (aHR 3.20, 95% CI 2.90-3.53) compared to age ≥75 (aHR 1.93, 95% CI 1.82-2.05, pint<0.001). There was no interaction by sex. The hazard ratio increased in a graded fashion at younger ages and was higher after the first 30 days of acute stroke.

CONCLUSION

There was a stronger association between co-morbidity and mortality at younger age and in the subacute phase of stroke. Further research is needed to determine the reason for these findings and identify ways to improve outcomes among those with stroke and co-morbid conditions at young age.

The Ability of Comorbidity Indices to Predict Mortality After Heart Transplantation: A Validation of the Danish Comorbidity Index for Acute Myocardial Infarction, Charlson Comorbidity Index, and Elixhauser Comorbidity Index

Advanced heart failure patients often have comorbidities of prognostic importance. However, whether total pretransplantation comorbidity burden predicts mortality in patients treated with heart transplantation (HTx) is unknown. We used population-based hospital and prescription data to examine the ability of the Danish Comorbidity Index for Acute Myocardial Infarction (DANCAMI), DANCAMI restricted to noncardiovascular diseases, Charlson Comorbidity Index, and Elixhauser Comorbidity Index to predict 30-d, 1-y, 5-y, and 10-y all-cause and cardiovascular mortality after HTx.

Methods

We identified all adult Danish patients with incident HTx from the Scandiatransplant Database between March 1, 1995, and December 31, 2018 (n = 563). We calculated Harrell's C-Statistics to examine discriminatory performance.

Results

The C-Statistic for predicting 1-y all-cause mortality after HTx was 0.58 (95% confidence interval [CI], 0.50-0.65) for a baseline model including age and sex. Adding comorbidity score to the baseline model did not increase the C-Statistics for DANCAMI (0.58; 95% CI, 0.50-0.65), DANCAMI restricted to noncardiovascular diseases (0.57; 95% CI, 0.50-0.64), Charlson Comorbidity Index (0.59; 95% CI, 0.51-0.66), or Elixhauser Comorbidity Index (0.58; 95% CI, 0.51-0.65). The results for 30-d, 5-y, and 10-y all-cause and cardiovascular mortality were consistent.

Conclusions

After accounting for patient age and sex, none of the commonly used comorbidity indices added predictive value to short- or long-term all-cause or cardiovascular mortality after HTx.

Comparative Effectiveness and Safety of Seizure Prophylaxis Among Adults After Acute Ischemic Stroke

BACKGROUND

Older adults occasionally receive seizure prophylaxis in an acute ischemic stroke (AIS) setting, despite safety concerns. There are no trial data available about the net impact of early seizure prophylaxis on post-AIS survival.

METHODS

Using a stroke registry (American Heart Association's Get With The Guidelines) individually linked to electronic health records, we examined the effect of initiating seizure prophylaxis (ie, epilepsy-specific antiseizure drugs) within 7 days of an AIS admission versus not initiating in patients ≥65 years admitted for a new, nonsevere AIS (National Institutes of Health Stroke Severity score ≤20) between 2014 and 2021 with no recorded use of epilepsy-specific antiseizure drugs in the previous 3 months. We addressed confounding by using inverse-probability weights. We performed standardization accounting for pertinent clinical and health care factors (eg, National Institutes of Health Stroke Severity scale, prescription counts, seizure-like events).

RESULTS

The study sample included 151 patients who received antiseizure drugs and 3020 who did not. The crude 30-day mortality risks were 219 deaths per 1000 patients among epilepsy-specific antiseizure drugs initiators and 120 deaths per 1000 among noninitiators. After standardization, the estimated mortality was 251 (95% CI, 190-307) deaths per 1000 among initiators and 120 (95% CI, 86-144) deaths per 1000 among noninitiators, corresponding to a risk difference of 131 (95% CI, 65-200) excess deaths per 1000 patients. In the prespecified subgroup analyses, the risk difference was 52 (95% CI, 11-72) among patients with minor AIS and 138 (95% CI, 52-222) among moderate-to-severe AIS patients. Similarly, the risk differences were 86 (95% CI, 18-118) and 157 (95% CI, 57-219) among patients aged 65 to 74 years and ≥75 years, respectively.

CONCLUSIONS

There was a higher risk of 30-day mortality associated with initiating versus not initiating seizure prophylaxis within 7 days post-AIS. This study does not support the role of seizure prophylaxis in reducing 30-day poststroke mortality.

Clinicopathological differences, risk factors and prognostic scores for western patients with intestinal and diffuse-type gastric cancer

BACKGROUND

In the molecular era, the Laurén system is still a cost-effective and widely implemented classification for gastric cancer (GC) and it has been recently associated with clinical, histological and molecular features of these tumors. Despite recent advances in the understanding of the molecular biology of GC, there is a need to develop new prognostic tools for patient stratification in clinical practice. Thus, the identification of easily available prognostic factors in patients with intestinal and diffuse-type tumors can significantly improve risk assessment and patient stratification in GC.

AIM

To identify clinicopathological differences, risk factors, and to develop cost-effective prognostic scores for patients with intestinal and diffuse-type GC.

METHODS

Retrospective study of all patients undergoing surgery for GC at a tertiary referral center from 2001 to 2019. 286 cases met inclusion criteria (intestinal: 190, diffuse: 96). Clinical data and gross findings were collected. All specimens were reviewed by two independent pathologists and a detailed protocol for histologic evaluation was followed. Five tissue microarrays (TMAs) were constructed and sections of the TMA block were immunostained for HERCEPTEST, MSH2, MSH6, MLH1 and PMS2. Statistical analyses were performed and prognostic scores were developed based on hazard ratios.

RESULTS

Intestinal and diffuse-type GC showed different epidemiological, clinicopathological and prognostic features. Diffuse tumors were significantly associated with younger age, less symptomatology, flat morphology, deeper invasion, perineural infiltration, advanced stage at diagnosis, administration of adjuvant therapy and poorer prognosis. Intestinal lesions were fungoid or polypoid, showed necrosis, desmoplasia, microsatellite instability and HERCEPTEST positivity and were diagnosed at earlier stages. Tumor depth, desmoplasia, macroscopic type and lymph node involvement were independently related to the Laurén subtype. Furthermore, intestinal and diffuse GC were associated with different risk factors for progression and death. Vascular invasion, perineural infiltration and growth pattern were important prognostic factors in intestinal-type GC. On the contrary, tumor size and necrosis were significant prognosticators in diffuse-type GC. Our recurrence and cancer-specific death scores for patients with intestinal and diffuse-type GC showed an excellent patient stratification into three (diffuse GC) or four (intestinal) prognostic groups.

CONCLUSION

Our findings support that Laurén subtypes represent different clinicopathological and biological entities. The development of specific prognostic scores is a useful and cost-effective strategy to improve risk assessment in GC.

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.

Charlson Comorbidity Index: A Critical Review of Clinimetric Properties

The present critical review was conducted to evaluate the clinimetric properties of the Charlson Comorbidity Index (CCI), an assessment tool designed specifically to predict long-term mortality, with regard to its reliability, concurrent validity, sensitivity, incremental and predictive validity. The original version of the CCI has been adapted for use with different sources of data, ICD-9 and ICD-10 codes. The inter-rater reliability of the CCI was found to be excellent, with extremely high agreement between self-report and medical charts. The CCI has also been shown either to have concurrent validity with a number of other prognostic scales or to result in concordant predictions. Importantly, the clinimetric sensitivity of the CCI has been demonstrated in a variety of medical conditions, with stepwise increases in the CCI associated with stepwise increases in mortality. The CCI is also characterized by the clinimetric property of incremental validity, whereby adding the CCI to other measures increases the overall predictive accuracy. It has been shown to predict long-term mortality in different clinical populations, including medical, surgical, intensive care unit (ICU), trauma, and cancer patients. It may also predict in-hospital mortality, although in some instances, such as ICU or trauma patients, the CCI did not perform as well as other instruments designed specifically for that purpose. The CCI thus appears to be clinically useful not only to provide a valid assessment of the patient's unique clinical situation, but also to demarcate major diagnostic and prognostic differences among subgroups of patients sharing the same medical diagnosis.

Association of material deprivation with discharge location and length of stay after inpatient stroke rehabilitation in Ontario: a retrospective, population-based cohort study

BACKGROUND

Low socioeconomic status is associated with increased risk of stroke and worse poststroke functional status. The aim of this study was to determine whether socioeconomic status, as measured by material deprivation, is associated with direct discharge to long-term care or length of stay after inpatient stroke rehabilitation.

METHODS

We performed a retrospective, population-based cohort study of people admitted to inpatient rehabilitation in Ontario, Canada, after stroke. Community-dwelling adults (aged 19-100 yr) discharged from acute care with a most responsible diagnosis of stroke between Sept. 1, 2012, and Aug. 31, 2017, and subsequently admitted to an inpatient rehabilitation bed were included. We used a multivariable logistic regression model to examine the association between material deprivation quintile (from the Ontario Marginalization Index) and discharge to long-term care, and a multivariable negative binomial regression model to examine the association between material deprivation quintile and rehabilitation length of stay.

RESULTS

A total of 18 736 people were included. There was no association between material deprivation and direct discharge to long-term care (most v. least deprived: odds ratio [OR] 1.07, 95% confidence interval [CI] 0.89-1.28); however, people living in the most deprived areas had a mean length of stay 1.7 days longer than that of people in the least deprived areas (p = 0.004). This difference was not significant after adjustment for other baseline differences (relative change in mean 1.02, 95% CI 0.99-1.04).

INTERPRETATION

People admitted to inpatient stroke rehabilitation in Ontario had similar discharge destinations and lengths of stay regardless of their socioeconomic status. In future studies, investigators should consider further examining the associations of material deprivation with upstream factors as well as potential mitigation strategies.

[A comparative analysis of the clinical and anamnestic status of patients with chronic occlusion of the carotid arteries based on the data of observational registries]

OBJECTIVE

To study the clinical and anamnestic status of patients with chronic carotid artery occlusion (CCAO) based on the analysis of risk factors, demographic and clinical and anatomical characteristics, the dynamics of the disease; to evaluate ongoing drug therapy, the incidence of strokes (MI) and deaths (according to the local registry compared with the results of other observational studies).

MATERIAL AND METHODS

PubMed and eLibrary searches for a systematic review were performed from October 24 to December 10, 2021 independently by two investigators. Out of 870 articles, based on inclusion/exclusion criteria, 8 studies were selected and included in the systematic review.

RESULTS

A comparative analysis of the clinical and anamnestic status of patients with CCAO according to the present review showed the following data on the prevalence of the main risk factors/diseases: hypertension - 79.1%; male gender - 83.7%; smoking - 46%; diabetes mellitus - 30.5%. Of the entire of own Duplex registry group (n=2548), 7 patients were identified with CCAO (0.27%). All patients were male (mean age 71.3±9.4 years). Endpoints were recorded in 5 of 7 participants during the follow-up period (8.9 years): 5 deaths, 2 fatal MI, 1 non-fatal MI, 1 myocardial infarction. A significant impact of the fact of MI on the survival of patients was confirmed using the standard log-rank test (p=0.02 and the Cox-Mendel test (p=0.04). The incidence of MI during the prospective follow-up according to the analyzed studies ranged from 4.3% (within a month of follow-up) to 42.8% (with a follow-up of 8.9 years), and averaged 12%.

CONCLUSIONS

A comparative analysis of the clinical and anamnestic status of patients with CCAO based on data from observational registers showed that the probability of detecting this pathology is associated with age and male gender. Data obtained from prospective observation of patients with CCAO in our own study show that the development of MI is one of the main factors affecting the survival of this category of patients.

Predicting Stroke Complications in Hospital and Functional Status at Discharge by Clustering of Cardiovascular Diseases a Multi-Centre Registry-Based Study of Acute Stroke

OBJECTIVE

Indicators for outcomes following acute stroke are lacking. We have developed novel evidence-based criteria for identifying outcomes of acute stroke using the presence of clusters of coexisting cardiovascular disease (CVD).

MATERIALS AND METHODS

Analysis of prospectively collected data from the Sentinel Stroke National Audit Programme (SSNAP). A total of 1656 men (mean age ±SD=73.1yrs±13.2) and 1653 women (79.3yrs±13.0) were admitted with acute stroke (83.3% ischaemic, 15.7% intracranial haemorrhagic), 1.0% unspecified) in four major UK hyperacute stroke units (HASU) between 2014 and 2016. Four categories from cardiovascular disease Congestive heart failure, Atrial fibrillation, pre-existing Stroke and Hypertension (CASH).were constructed: CASH-0 (no coexisting CVD); CASH-1 (any one coexisting CVD); CASH-2 (any two coexisting CVD); CASH-3 (any three or all four coexisting CVD). These were tested against outcomes, adjusted for age and sex.

RESULTS

Compared to CASH-0, individuals with CASH-3 had greatest risks of in-hospital mortality (11.1% vs 24.5%, OR=1.8, 95%CI=1.3-2.7) and disability (modified Rankin Scale score ≥4) at discharge (24.2% vs 46.2%, OR=1.9, 95%CI=1.4-2.7), urinary tract infection (3.8% vs 14.6%, OR= 3.3, 95%CI= 1.9-5.5), and pneumonia (7.1% vs 20.6%, OR= 2.6, 95%CI= 1.7-4.0); length of stay on HASU >14 days (29.8% vs 39.3%, OR=1.8, 95%CI=1.3-2.6); and joint-care planning (20.9% vs 29.8%, OR=1.4, 95%CI=1.0-2.0).

CONCLUSIONS

We present a simple tool for estimating the risk of adverse outcomes of acute stroke including death, disability at discharge, nosocomial infections, prolonged length of stay, as well as any joint care planning. CASH-0 indicates a low level and CASH-3 indicates a high level of risk of such complications after stroke.

Sex differences in the outcomes of adults admitted to inpatient rehabilitation after stroke

INTRODUCTION

Several differences have been reported between male and female patients with stroke in clinical and sociodemographic features, treatment, and outcomes. Potential effects in the inpatient rehabilitation population are unclear.

OBJECTIVE

To evaluate the differences between male and female patients in discharge functional status, length of stay, and discharge home after inpatient rehabilitation for stroke.

DESIGN

Retrospective, population-based cohort study.

SETTING

Inpatient rehabilitation centers in Ontario, Canada.

PARTICIPANTS

Male (N = 10,684) and female (N = 9459) patients discharged from acute care between September 1, 2012 and August 31, 2017, with a diagnosis of stroke and subsequently admitted to inpatient rehabilitation.

EXPOSURE VARIABLE

Female sex.

MAIN OUTCOME MEASURES

Discharge Functional Independence Measure (FIM) score, length of stay, and discharge home.

RESULTS

Female patients had a lower functional status at discharge (mean FIM score 94.1 vs. 97.8, p < .001) and a lower proportion were discharged home (81.1% vs. 82.9%, p = .001). Female and male patients had similar rehabilitation length of stay (mean 31.8 vs. 31.7 days, p = .90). In the adjusted analyses, there was no difference in discharge functional status between male and female patients (FIM score β -.20 [95% confidence interval [CI] -0.64 to 0.25]). Female patients had a mean length of stay 2% shorter (0.98 [95% CI 0.96-0.99]) and a higher odds of discharge home (odds ratio [OR] 1.14 [95% CI 1.05-1.24]).

CONCLUSIONS

There were no clinically significant sex differences in outcomes after inpatient rehabilitation for stroke. Observed sex disparities in the general stroke population may not be directly applicable to individuals undergoing inpatient rehabilitation.

Travel time to emergency care not by geographic time, but by optimal time: A nationwide cross-sectional study for establishing optimal hospital access time to emergency medical care in South Korea

Increase in travel time, beyond a critical point, to emergency care may lead to a residential disparity in the outcome of patients with acute conditions. However, few studies have evaluated the evidence of travel time benchmarks in view of the association between travel time and outcome. Thus, this study aimed to establish the optimal hospital access time (OHAT) for emergency care in South Korea. We used nationwide healthcare claims data collected by the National Health Insurance System database of South Korea. Claims data of 445,548 patients who had visited emergency centers between January 1, 2006 and December 31, 2014 were analyzed. Travel time, by vehicle from the residence of the patient, to the emergency center was calculated. Thirteen emergency care-sensitive conditions (ECSCs) were selected by a multidisciplinary expert panel. The 30-day mortality after discharge was set as the outcome measure of emergency care. A change-point analysis was performed to identify the threshold where the mortality of ECSCs changed significantly. The differences in risk-adjusted mortality between patients living outside of OHAT and those living inside OHAT were evaluated. Five ECSCs showed a significant threshold where the mortality changed according to their OHAT. These were intracranial injury, acute myocardial infarction, other acute ischemic heart disease, fracture of the femur, and sepsis. The calculated OHAT were 71-80 min, 31-40 min, 70-80 min, 41-50 min, and 61-70 min, respectively. Those who lived outside the OHAT had higher risks of death, even after adjustment (adjusted OR: 1.04-7.21; 95% CI: 1.03-26.34). In conclusion, the OHAT for emergency care with no significant increase in mortality is in the 31-80 min range. Optimal travel time to hospital should be established by optimal time for outcomes, and not by geographic time, to resolve the disparities in geographical accessibility to emergency care.

Performance of Charlson and Elixhauser Comorbidity Index to Predict in-Hospital Mortality in Patients with Stroke in Sumadija and Western Serbia

BACKGROUND

Comorbidities are major predictors of in-hospital mortality in stroke patients. The Charlson comorbidity index (CCI) and the Elikhauser comorbidity index (ECI) are scoring systems for classifying comorbidities. We aimed to compare the performance of the CCI and ECI to predict in-hospital mortality in stroke patients.

METHODS

We included patients hospitalized for stroke in the Clinical Center of Kragujevac, Serbia for the last 7 years. Hospitalizations caused by stroke, were identified by the International Classification of Diseases-10 (ICD-10) codes I60.0 - I69.9. All patients were divided into two cohorts: Alive cohort (n=3297) and Mortality cohort (n=978).

RESULTS

There were significant associations between higher CCIS and increased risk of in-hospital mortality (HR = 1.07, 95% CI = 1.01-1.12) and between higher ECIS and increased risk of in-hospital mortality (HR = 1.04, 95% CI = 0.99-1.09). Almost 2/3 patients (66.9%) had comorbidities included in the CCI score and 1/3 patients (30.2%) had comorbidities included in the ECI score. The statistically significant higher CCI score (t = -3.88, df = 1017.96, P <0.01) and ECI score (t = -6.7, df = 1447.32, P <0.01) was in the mortality cohort.Area Under the Curve for ECI score was 0.606 and for CCI score was 0.549.

CONCLUSION

Both, the CCI and the ECI can be used as scoring systems for classifying comorbidities in the administrative databases, but the model's ECI Score had a better discriminative performance of in-hospital mortality in the stroke patients than the CCI Score model.

Construction and validation of a machine learning-based nomogram: A tool to predict the risk of getting severe coronavirus disease 2019 (COVID-19)

Background

Identifying patients who may develop severe coronavirus disease 2019 (COVID‐19) will facilitate personalized treatment and optimize the distribution of medical resources.

Methods

In this study, 590 COVID‐19 patients during hospitalization were enrolled (Training set: n = 285; Internal validation set: n = 127; Prospective set: n = 178). After filtered by two machine learning methods in the training set, 5 out of 31 clinical features were selected into the model building to predict the risk of developing severe COVID‐19 disease. Multivariate logistic regression was applied to build the prediction nomogram and validated in two different sets. Receiver operating characteristic (ROC) analysis and decision curve analysis (DCA) were used to evaluate its performance.

Results

From 31 potential predictors in the training set, 5 independent predictive factors were identified and included in the risk score: C‐reactive protein (CRP), lactate dehydrogenase (LDH), Age, Charlson/Deyo comorbidity score (CDCS), and erythrocyte sedimentation rate (ESR). Subsequently, we generated the nomogram based on the above features for predicting severe COVID‐19. In the training cohort, the area under curves (AUCs) were 0.822 (95% CI, 0.765–0.875) and the internal validation cohort was 0.762 (95% CI, 0.768–0.844). Further, we validated it in a prospective cohort with the AUCs of 0.705 (95% CI, 0.627–0.778). The internally bootstrapped calibration curve showed favorable consistency between prediction by nomogram and the actual situation. And DCA analysis also conferred high clinical net benefit.

Conclusion

In this study, our predicting model based on five clinical characteristics of COVID‐19 patients will enable clinicians to predict the potential risk of developing critical illness and thus optimize medical management.

Charlson comorbidity index predicts outcomes of elderly after allogeneic hematopoietic stem cell transplantation for acute myeloid leukemia and myelodysplastic syndrome

BACKGROUND/PURPOSE

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains the curative therapy for acute myeloid leukemia (AML) or high-risk myelodysplastic syndrome (MDS), but advanced age with multiple comorbidities limits the eligibility for allo-HSCT. We conducted a retrospective study to investigate the comorbidities assessments and prognostic factors that predict outcomes for these patients.

METHODS

Clinical data of patients older than 50 years who had received diagnoses of AML or MDS and underwent allo-HSCT were obtained. Information on patient characteristics, including age, gender, allogeneic transplant type, conditioning regimens, Charlson comorbidity index (CCI), and presence of acute graft-versus-host disease (GVHD) or chronic GVHD, were collected and analyzed.

RESULTS

Two hundred fifty-five elderly patients with a median age at allo-HSCT of 57 years were included. The significant prognostic factors associated with worse overall survival (OS) were CCI ≥3 (hazard ratio: 1.88) and grade III-IV acute GVHD (3.18). Similar findings were noted in the non-relapse mortality analysis. To investigate the effects of chronic GVHD on patient outcomes, OS analysis was performed for those with survival >100 days after transplantation. The results revealed CCI ≥3 (1.88) and grade III-IV acute GVHD (2.73) remained poor prognostic factors for OS, whereas mild chronic GVHD (0.43) was associated with better OS.

CONCLUSION

This cohort study suggests that CCI ≥3 predicts poor outcomes, primarily due to a higher NRM risk. Careful management of GVHD after transplantation could improve outcomes in elderly patients with AML or MDS after allo-HSCT.

Proposal for a clinicopathological prognostic score for resected gastric cancer patients

BACKGROUND

Factors other than pTNM stage have been associated with gastric cancer (GC) prognosis, and several alternative prognostic scores have been constructed. Our aims are to identify prognostic factors in western GC patients and to build clinicopathological prognostic models for overall survival (OS) and disease-free survival (DFS).

METHODS

A Retrospective study of 204 cases of GC resected during the years 2000 to 2014 was conducted in our hospital. Clinicopathological features were assessed, univariate and multivariate analysis were performed and prognostic scores were constructed.

RESULTS

Most patients were diagnosed at pTNM stages II and III (36.9% and 48.1%, respectively). According to Laurén classification, tumors were intestinal (55.8%), diffuse (35.2%) and mixed (9%). During follow-up, 43.5% of patients had tumor recurrence, and 28.6% died due to tumor. Univariate analysis showed that patient age, Laurén subtype, signet-ring cell morphology, pTNM stage, tumor grade, perineural invasion, growth pattern, intratumoral inflammation, adjuvant therapy, and desmoplasia were significantly related to tumor progression or death. Multivariate analysis showed that Laurén subtype, pT stage, and lymph node ratio (LNR) were significantly and independently associated with GC recurrence. Laurén subtype and LNR were significantly related to patient survival. Prognostic scores for tumor progression and death were developed and patients were classified into four prognostic groups which showed good prognostic performance.

CONCLUSION

A prognostic model comprising histological features such as Laurén subtype can be easily applied in clinical practice, and provides more prognostic information than pTNM stage alone. These models can further stratify resected GC patients and have the potential to aid in the individualization of patient management.

Is there an agreement between self-reported medical diagnosis in the CARTaGENE cohort and the Québec administrative health databases?

BACKGROUND

Population health studies often use existing databases that are not necessarily constituted for research purposes. The question arises as to whether different data sources such as in administrative health data (AHD) and self-report questionnaires are equivalent and lead to similar information.

OBJECTIVES

The main objective of this study was to assess the level of agreement between self-reported medical conditions and medical diagnosis captured in AHD. A secondary objective was to identify predictors of agreement among medical conditions between the two data sources. Therefore, the purposes of the study were to explore the extent to which these two methods of commonly used public health data collection provide concordant records and identify the main predictors of statistical variations.

METHODS

Data were extracted from CARTaGENE, a population-based cohort in Québec, Canada, which was linked to the provincial health insurance records of the same individuals, namely the MED-ÉCHO database from the Régie de l'assurance maladie du Québec (RAMQ) and the fee-for-service billing records provided by the physician, for the time period 1998-2012. Agreement statistics (kappa coefficient) along with sensitivity, specificity and predictive positive value were calculated for 19 chronic conditions and 12 types of cancers. Logistic regressions were used to identify predictors of concordance between self-report and AHD from significant covariates (sex, age groups, education, region, income, heavy utilization of health care system and Charlson comorbidity index).

RESULTS

Agreement between self-reported data and AHD across diseases ranged from kappa of 0.09 for chronic renal failure to 0.86 for type 2 diabetes. Sensitivity of self-reported data was higher than 50% for 14 out of the 31 medical conditions studied, especially for myocardial infarction (88.62%), breast cancer (86.28%), and diabetes (85.06%). Specificity was generally high with a minimum value of 89.70%. Lower concordance between data sources was observed for higher frequency of health care utilization and higher comorbidity scores.

CONCLUSION

Overall, there was moderate agreement between the two data sources but important variations were found depending on the type of disease. This suggests that CARTaGENE's participants were generally able to correctly identify the kind of diseases they suffer from, with some exceptions. These results may help researchers choose adequate data sources according to specific study objectives. These results also suggest that Québec's AHD seem to underestimate the prevalence of some chronic conditions, which might result in inaccurate estimates of morbidity with consequences for public health surveillance.