Charlson Comorbidity Index as a predictor of repeated hospital admission and mortality among older women diagnosed with cardiovascular disease

Effectiveness of pharmacist-led medication reconciliation on medication errors at hospital discharge and healthcare utilization in the next 30 days: a pragmatic clinical trial

Transitions of care often lead to medication errors and unnecessary healthcare utilization. Medication reconciliation has been repeatedly shown to reduce this risk. However, the great majority of evidence is limited to the provision of medication reconciliation within clinical trials and countries with well-established clinical pharmacy. Thus, this pragmatic, prospective, controlled trial evaluated the effectiveness of routine pharmacist-led medication reconciliation compared to standard care on medication errors and unplanned healthcare utilization in adult general medical patients hospitalized in a teaching hospital in Slovenia. All patients hospitalized in a ward where medication reconciliation was integrated into routine clinical practice were included in the intervention group and received admission and discharge medication reconciliation, coupled with patient counselling. The control group consisted of randomly selected patients from the remaining medical wards. The primary study outcome was unplanned healthcare utilization within 30 days of discharge, and the secondary outcomes were clinically important medication errors at hospital discharge and serious unplanned healthcare utilization within 30 days of discharge. Overall, 414 patients (53.4% male, median 71 years) were included-225 in the intervention group and 189 in the control group. In the intervention group, the number of patients with clinically important medication errors at discharge was significantly lower (intervention vs control group: 9.3% vs 61.9%). Multiple logistic regression revealed that medication reconciliation reduced the likelihood of a clinically important medication error by 20-fold, while a higher number of medications on admission was associated with an increased likelihood. However, no significant differences were noted in any and serious unplanned healthcare utilization (intervention vs control group: 33.9% vs 27.8% and 20.3% vs 14.6%, respectively). The likelihood of serious healthcare utilization increased with the age of the patient, the number of medications on admission and being hospitalized for an acute medical condition. Our pragmatic trial confirmed that medication reconciliation, even when performed as part of routine clinical practice, led to a substantial reduction in the risk of clinically important medication errors at hospital discharge but not to a reduction in healthcare utilization. Medication reconciliation is a fundamental, albeit not sufficient, element to ensure patient safety after hospital discharge. Clinical Trial Registration: https://clinicaltrials.gov/search?id=NCT06207500, identifier NCT06207500.

A Population-Based Outcome-Wide Association Study of the Comorbidities and Sequelae Following COVID-19 Infection

BACKGROUND

Immense attention has been given to the outcome of COVID-19 infection. However, comprehensive studies based on large populational cohort with long-term follow-up are still lacking. This study aimed to investigate the risk of various short-term comorbidities (within one month) and long-term sequelae (above one month) after COVID-19 infection.

METHODS

In this large prospective cohort study with 14 months follow-up information based on UK biobank, we included 16,776 COVID-19-positive participants and 58,281 COVID-19-negative participants matched for comparison. The risk of each comorbidity and sequela was evaluated by multivariable logistic regression analysis and presented as hazard ratio (HR) and 95% confidence interval (95% CI).

RESULTS

COVID-19-positive individuals had a higher risk of 47 types of comorbidities within one month following COVID-19 infection, especially those who were older, male, overweight/obese, ever-smoked, with more pre-existing comorbidities and hospitalized. About 70.37% of COVID-19 patients with comorbidities had more than one co-occurring comorbidities. Additionally, only 6 high-risk sequelae were observed after one month of COVID-19 infection, and the incidence was relatively low (< 1%).

CONCLUSION

In addition to long-term sequelae following COVID-19 infection, plenty of comorbidities were observed, especially in patients with older age, male gender, overweight/obese, more pre-existing comorbidities and severe COVID-19, indicating that more attention should be given to these susceptible persons within this period.

A nomogram to predict in-hospital mortality of gastrointestinal bleeding patients in the intensive care unit

Background

Gastrointestinal bleeding (GIB) is a common condition in clinical practice, and predictive models for patients with GIB have been developed. However, assessments of in-hospital mortality due to GIB in the intensive care unit (ICU), especially in critically ill patients, are still lacking. This study was designed to screen out independent predictive factors affecting in-hospital mortality and thus establish a predictive model for clinical use.

Methods

This retrospective study included 1,442 patients with GIB who had been admitted to the ICU. They were selected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) 1.0 database and divided into a training group and a validation group in a ratio of 7:3. The main outcome measure was in-hospital mortality. Least absolute shrinkage and section operator (LASSO) regression was used to screen out independent predictors and create a nomogram.

Results

LASSO regression picked out nine independent predictors: heart rate (HR), activated partial thromboplastin time (aPTT), acute physiology score III (APSIII), sequential organ failure assessment (SOFA), cerebrovascular disease, acute kidney injury (AKI), norepinephrine, vasopressin, and dopamine. Our model proved to have excellent predictive value with regard to in-hospital mortality (the area under the receiver operating characteristic curve was 0.906 and 0.881 in the training and validation groups, respectively), as well as a good outcome on a decision curve analysis to assess net benefit.

Conclusion

Our model effectively predicts in-hospital mortality in patients with GIB, indicating that it may prove to be a valuable tool in future clinical practice.

The value of distinguishing patients with isolated subsegmental pulmonary embolism presenting to two tertiary hospitals in Australia: an observational study

Isolated-subsegmental-pulmonary-embolism (SSPE) is increasingly diagnosed with the use of computed-tomography-pulmonary-angiogram (CTPA). There remains clinical equipoise for management of SSPE with previous studies not accounting for frailty while determining clinical outcomes. Clinical outcomes among patients with isolated SSPE were compared with those with a more proximal PE after accounting for frailty and other risk-factors. This study included all patients with a positive CTPA for pulmonary embolism (PE) admitted between 2017 and 2021 to two Australian-tertiary-hospitals. Frailty was determined by use of the hospital-frailty-risk-score (HFRS). Competing-risk-analysis and Cox-proportional hazard models determined the cumulative-risk of VTE and mortality within 3 months and 1 year of index PE event after adjustment for frailty and other variables. Of 334 patients with positive CTPA for PE, 111 (33.2%) had isolated-SSPE. The mean (SD) age was 64.3 (17.7) years, 50.9% were males and 9.6% were frail. The risk of recurrent VTE within 3-months (0.9% vs. 1.8%, P = 0.458) and within 1-year of follow-up (2.7% vs. 6.3%, P = 0.126) did not differ significantly between patients with isolated SSPE and those with more proximal PE. After adjusted analyses, the cumulative-incidence of recurrent VTE was not different among patients with isolated SSPE within 1 year of index event [subdistribution-hazard-ratio (HR) 0.84, 95% CI 0.19 to 3.60]. Similarly, mortality within 1 year of index event was also not different between the two groups (aHR 1.72, 95% CI 0.92-3.23). The prevalence of SSPE was 33.2% and even after adjustment for frailty these patients had no different clinical outcomes than those with proximal PE.

Age‑adjusted Charlson comorbidity index and in‑hospital mortality in critically ill patients with cardiogenic shock: A retrospective cohort study

Evidence regarding the relationship between age-adjusted Charlson comorbidity index (ACCI) and in-hospital mortality is limited. Therefore, the present study investigated whether there was an independent association between ACCI and in-hospital mortality in critically ill patients with cardiogenic shock (CS) after adjusting for other covariates (age, sex, history of disease, scoring system, in-hospital management, vital signs at presentation, laboratory findings and vasopressors). ACCI, calculated retrospectively after hospitalization between 2008 and 2019, was derived from intensive care unit (ICU) admissions at the Beth Israel Deaconess Medical Center (Boston, MA, USA). Patients with CS were classified into two categories based on predefined ACCI scores (low, <8; high, ≥8). Based on baseline ACCI, the risk of in-hospital mortality in patients with CS was calculated using a multivariate Cox proportional risk model, and the threshold effect was calculated using a two-piece linear regression model. The in-hospital mortality rate was ~1.5 times greater in the ACCI high group compared with that in the ACCI low group [hazard ratio (HR)=1.45; 95% confidence interval (CI), 1.14-1.86]. Additional analysis showed that ACCI had a curvilinear association with in-hospital mortality risk in patients with CS, with a saturation effect predicted at 4.5. When ACCI was >4.5, the risk of in-hospital CS death increased significantly with increasing ACCI (HR=1.122; 95% CI, 1.054-1.194). Overall, ACCI was an independent predictor of in-hospital mortality in ICU patients with CS. A non-linear relationship was revealed between ACCI and in-hospital mortality, where in-hospital mortality increased significantly when ACCI was >4.5.

Crosswalk between Charlson Comorbidity Index and the American Society of Anesthesiologists Physical Status Score for Geriatric Trauma Assessment

The American Society of Anesthesiologists Physical Status (ASA-PS) grade better risk stratifies geriatric trauma patients, but it is only reported in patients scheduled for surgery. The Charlson Comorbidity Index (CCI), however, is available for all patients. This study aims to create a crosswalk from the CCI to ASA-PS. Geriatric trauma cases, aged 55 years and older with both ASA-PS and CCI values (N = 4223), were used for the analysis. We assessed the relationship between CCI and ASA-PS, adjusting for age, sex, marital status, and body mass index. We reported the predicted probabilities and the receiver operating characteristics. A CCI of zero was highly predictive of ASA-PS grade 1 or 2, and a CCI of 1 or higher was highly predictive of ASA-PS grade 3 or 4. Additionally, while a CCI of 3 predicted ASA-PS grade 4, a CCI of 4 and higher exhibited greater accuracy in predicting ASA-PS grade 4. We created a formula that may accurately situate a geriatric trauma patient in the appropriate ASA-PS grade after adjusting for age, sex, marital status, and body mass index. In conclusion, ASA-PS grades can be predicted from CCI, and this may aid in generating more predictive trauma models.

Comorbidity among inpatients with dementia: a preliminary cross-sectional study in West China

OBJECTIVE

To investigate comorbidities among hospitalized patients with dementia.

METHOD

Data were extracted from the discharge records in our hospital. Comorbidities based on ICD-10 were selected from the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI). The distributions of these comorbidities were described in dementia inpatients and age- and sex-matched nondementia controls, as well as in inpatients with Alzheimer's disease and vascular dementia. A logistic regression model was applied to identify dementia-specific morbid conditions.

RESULTS

A total of 3355 patients with dementia were included, with a majority of 1503 (44.8%) having Alzheimer's disease, 395 (11.8%) with vascular dementia, and 441 (13.1%) with mixed dementia. The mean number of comorbidities was 3.8 in dementia patients (vs. 2.9 in controls). The most prevalent comorbidities in inpatients with dementia compared with those without dementia were cerebral vascular disease (73.0% vs. 35.9%), hypertension (62.8% vs. 56.2%), and peripheral vascular disease (53.7% vs. 31.2%). Comorbidities associated with dementia included epilepsy (OR 4.8, 95% CI 3.5-6.8), cerebral vascular disease (OR 4.1, 95% CI 3.7-4.5), depression (OR 4.0, 95% CI 3.2-5.0), uncomplicated diabetes (OR 1.5, 95% CI 1.4-1.7), peripheral vascular disease (OR 1.8, 95% CI 1.6-2.0), rheumatoid arthritis collagen vascular disease (OR 1.7, 95% CI 1.3-2.3), and anemia (OR 1.2, 95% CI 1.04-1.3). Some comorbidities suggested a protective effect against dementia. They were hypertension (OR 0.8, 95% CI 0.7-0.9), COPD (OR 0.6, 95% CI 0.5-0.6), and solid tumor without metastasis (OR 0.4, 95% CI 0.3-0.4). Vascular dementia has more cardiovascular and cerebrovascular comorbidities than Alzheimer's disease.

CONCLUSION

Patients with dementia coexisted with more comorbidities than those without dementia. Comorbidities (esp. cardio-cerebral vascular risks) in patients with vascular dementia were more than those in patients with AD. Specifically, vascular and circulatory diseases, epilepsy, diabetes and depression increased the risk of dementia.

Association between dysglycemia and the Charlson Comorbidity Index among hospitalized patients with diabetes

AIM

Inpatient dysglycemia has been linked to short-term mortality, but longer-term mortality data are lacking. Our aim was to evaluate the association between inpatient dysglycemia and one-year mortality risk.

METHODS

Retrospective chart review of adults with diabetes hospitalized between 2015 and 2019. The Charlson Comorbidity Index (CCI) was used to estimate 1-year mortality risk, stratified into low (CCI ≤ 5) and high risk (CCI ≥6). Simple and multivariable logistic regression was used to evaluate the association between dysglycemic measures and high mortality risk.

RESULTS

Among 22,639 unique admissions, BG ≥ 180, ≥300, ≤70, <54 and <40 mg/dL were associated with adjusted odds of 1.43 (95 % CI, 1.33, 1.54), 1.58 (95 % CI, 1.48, 1.68), 2.16 (95 % CI, 2.01, 2.32), 2.58 (95 % CI, 2.32, 2.86), and 2.56 (95 % CI, 2.19, 2.99) for high mortality risk, respectively. Older age and Black race were positively associated with hyperglycemia and hypoglycemia. Myocardial infarction, congestive heart failure (CHF), and moderate to severe liver disease were most strongly associated with hyperglycemia, while renal disease, CHF, peripheral vascular disease, and peptic ulcer disease were most strongly associated with hypoglycemia.

CONCLUSIONS

Inpatient hypoglycemia and hyperglycemia were both positively associated with higher one-year mortality risk, with stronger magnitude of association observed for hypoglycemia. The association appears to be mediated mainly by presence of diabetes-related complications.

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.