Activity of daily living upon admission is an independent predictor of in-hospital mortality in older patients with community-acquired pneumonia

Activities of daily living limitation and functional decline during hospitalization predict 180-day readmission and mortality in older patients with pneumonia: A single-center, retrospective cohort study

BACKGROUND

The role of activities of daily living (ADL) as a predictor of adverse outcomes in patients with pneumonia is unclear. This study aimed to assess the association between ADL, including physical and cognitive function, and death or readmission in older inpatients with pneumonia.

METHODS

This retrospective, single-center, observational study included consecutive older inpatients with pneumonia between October 2018 and December 2019. ADL was assessed using the Functional Independence Measure (FIM). Functional decline during hospitalization was defined as a decrease of at least 1 point in FIM at discharge from admission. The primary outcome was the time to composite 180-day mortality and readmission from any cause after discharge.

RESULTS

In total, 363 patients (median [interquartile range] age: 80 [73-86] years, male: 68 %) were divided according to the median FIM scores (≥100, n = 183 and < 100, n = 180). Among the patients, 25 experienced functional decline during hospitalization, 69 were readmitted, and 17 died. In the Kaplan-Meier analysis, both the lower FIM group and the functional decline group had significantly lower event-free rates than the higher FIM groups and the non-functional decline groups (log-rank test, p < 0.001), respectively. After multivariate analysis, both the lower FIM (adjusted HR, 2.11; 95 % CI, 1.24-3.58; p = 0.006) and functional decline (adjusted HR, 3.18; 95 % CI, 1.44-7.05; p = 0.005) were significantly associated with the primary outcome.

CONCLUSIONS

In older patients hospitalized with pneumonia, ADL limitations at discharge and a decline in ADL were associated with poor outcomes.

Analysis of risk factors for pneumonia in patients with catatonia: a cross-sectional analysis

Objective

The clinical management of catatonia has always been a focus of psychiatric nursing. Unfortunately, there is still limited research on the risk factors and nursing methods for patients with catatonia and bacterial pneumonia. Few studies have identified and analyzed the clinical risk factors for catatonia patients with bacterial pneumonia. This study aims to explore the risk factors and preventive nursing measures for pneumonia in patients with catatonia.

Methods

A total of 88 patients with catatonia treated in the emergency department of a psychiatric hospital from January 2019 to October 2021 were selected. They were divided into bacterial pneumonia group (n=17) and non-pneumonia group (n=71) based on whether they had pneumonia. The demographic data and clinical characteristics of the two groups were compared. Logistic regression analysis and point-biserial correlation were used to analyze the risk factors for developing pneumonia in patients with catatonia.

Results

The incidence of pneumonia in patients with catatonia was 19.32%. Correlation analysis showed that age (r=0.216, p=0.043), The Activities of Daily Living Scale (ADL) score (r=0.265, p=0.013), cell count of white blood (r=0.591, p<0.001), neutrophil count (r=0.599, p<0.001), percentage of neutrophils (r=0.311, p=0.003), C-reactive protein (r=0.558, p<0.001), bedridden days (r=0.470, p<0.001), and albumin level (r=-0.288, p=0.007) were significantly associated with pneumonia. Multivariate logistic regression analysis showed that smoking, bedridden days, family support, and nutritional status were risk factors for pneumonia in patients with catatonia.

Conclusion

Reducing smoking and bedridden days, improving nutrition, and providing timely preventive nursing care by family members can reduce the occurrence of pneumonia in patients with catatonia.

Establishment of risk model for elderly CAP at different age stages: a single-center retrospective observational study

Community-acquired pneumonia (CAP) is one of the main reasons of mortality and morbidity in elderly population, causing substantial clinical and economic impacts. However, clinically available score systems have been shown to demonstrate poor prediction of mortality for patients aged over 65. Especially, no existing clinical model can predict morbidity and mortality for CAP patients among different age stages. Here, we aimed to understand the impact of age variable on the establishment of assessment model and explored prognostic factors and new biomarkers in predicting mortality. We retrospectively analyzed elderly patients with CAP in Minhang Hospital, Fudan University. We used univariate and multiple logistic regression analyses to study the prognostic factors of mortality in each age-based subgroup. The prediction accuracy of the prognostic factors was determined by the Receiver Operating Characteristic curves and the area under the curves. Combination models were established using several logistic regressions to save the predicted probabilities. Four factors with independently prognostic significance were shared among all the groups, namely Albumin, BUN, NLR and Pulse, using univariate analysis and multiple logistic regression analysis. Then we built a model with these 4 variables (as ABNP model) to predict the in-hospital mortality in all three groups. The AUC value of the ABNP model were 0.888 (95% CI 0.854-0.917, p < 0.000), 0.912 (95% CI 0.880-0.938, p < 0.000) and 0.872 (95% CI 0.833-0.905, p < 0.000) in group 1, 2 and 3, respectively. We established a predictive model for mortality based on an age variable -specific study of elderly patients with CAP, with higher AUC value than PSI, CURB-65 and qSOFA in predicting mortality in different age groups (66-75/ 76-85/ over 85 years).

Development and validation of a survival prediction model in elder patients with community-acquired pneumonia: a MIMIC-population-based study

BACKGROUND

To develop a prediction model predicting in-hospital mortality of elder patients with community-acquired pneumonia (CAP) admitted to the intensive care unit (ICU).

METHODS

In this cohort study, data of 619 patients with CAP aged ≥ 65 years were obtained from the Medical Information Mart for Intensive Care III (MIMIC III) 2001-2012 database. To establish the robustness of predictor variables, the sample dataset was randomly partitioned into a training set group and a testing set group (ratio: 6.5:3.5). The predictive factors were evaluated using multivariable logistic regression, and then a prediction model was constructed. The prediction model was compared with the widely used assessments: Sequential Organ Failure Assessment (SOFA), Pneumonia Severity Index (PSI), systolic blood pressure, oxygenation, age and respiratory rate (SOAR), CURB-65 scores using positive predictive value (PPV), negative predictive value (NPV), accuracy (ACC), area under the curve (AUC) and 95% confidence interval (CI). The decision curve analysis (DCA) was used to assess the net benefit of the prediction model. Subgroup analysis based on the pathogen was developed.

RESULTS

Among 402 patients in the training set, 90 (24.63%) elderly CAP patients suffered from 30-day in-hospital mortality, with the median follow-up being 8 days. Hemoglobin/platelets ratio, age, respiratory rate, international normalized ratio, ventilation use, vasopressor use, red cell distribution width/blood urea nitrogen ratio, and Glasgow coma scales were identified as the predictive factors that affect the 30-day in-hospital mortality. The AUC values of the prediction model, the SOFA, SOAR, PSI and CURB-65 scores, were 0.751 (95% CI 0.749-0.752), 0.672 (95% CI 0.670-0.674), 0.607 (95% CI 0.605-0.609), 0.538 (95% CI 0.536-0.540), and 0.645 (95% CI 0.643-0.646), respectively. DCA result demonstrated that the prediction model could provide greater clinical net benefits to CAP patients admitted to the ICU. Concerning the pathogen, the prediction model also reported better predictive performance.

CONCLUSION

Our prediction model could predict the 30-day hospital mortality in elder patients with CAP and guide clinicians to identify the high-risk population.

Combination of the Barthel Index at Discharge with GRACE Leads to Improved One-Year Mortality Prediction in Older Patients with Acute Myocardial Infarction

Purpose

Many older patients with acute myocardial infarction (AMI) have impaired ability for activities of daily living (ADL). Impaired ADL leads to poor prognosis in elderly patients. The Global Registry of Acute Coronary Events (GRACE) score is widely used for risk stratification in AMI patients but does not consider physical performance, which is an important prognosis predictor for older adults. This study assessed whether the Barthel Index (BI) score combine the GRACE score would achieve improved one-year mortality prediction in older AMI patients.

Patients and Methods

This single-center retrospective study included 688 AMI patients aged ≥65 years who were divided into an impaired ADL group (BI ≤60, n = 102) and a normal ADL group (BI >60, n = 586) based on BI scores at discharge. The participants were followed up for one year. Cox survival models were constructed for BI score, GRACE score, and BI score combined GRACE score for one-year mortality prediction.

Results

Patients had a mean age of 76.29 ± 7.42 years, and 399 were men (58%). A lower BI score was associated with more years of hypertension and diabetes, less revascularization, longer hospital stays, and higher one-year mortality after discharge. Multivariable Cox regression analysis identified BI as a significant risk factor for one-year mortality in older AMI patients (HR 0.977, 95% CI, 0.963-0.992, P = 0.002). BI (0.774, 95% CI: 0.731-0.818) and GRACE (0.758, 95% CI: 0.704-0.812) scores had similar predictive power, but their combination outperformed either score alone (0.810, 95% CI: 0.770-0.851).

Conclusion

BI at discharge is a significant risk factor for one-year mortality in older AMI patients, which can be better predicted by the combination of BI and GRACE scores.

A nomogram for predicting risk of death during hospitalization in elderly patients with Alzheimer's disease at the time of admission

Background and objectives

Elderly patients with Alzheimer's disease (AD) often have multiple underlying disorders that lead to frequent hospital admissions and are associated with adverse outcomes such as in-hospital mortality. The aim of our study was to develop a nomogram to be used at hospital admission for predicting the risk of death in patients with AD during hospitalization.

Methods

We established a prediction model based on a dataset of 328 patients hospitalized with AD -who were admitted and discharged from January 2015 to December 2020. A multivariate logistic regression analysis method combined with a minimum absolute contraction and selection operator regression model was used to establish the prediction model. The identification, calibration, and clinical usefulness of the predictive model were evaluated using the C-index, calibration diagram, and decision curve analysis. Internal validation was evaluated using bootstrapping.

Results

The independent risk factors included in our nomogram were diabetes, coronary heart disease (CHD), heart failure, hypotension, chronic obstructive pulmonary disease (COPD), cerebral infarction, chronic kidney disease (CKD), anemia, activities of daily living (ADL) and systolic blood pressure (SBP). The C-index and AUC of the model were both 0.954 (95% CI: 0.929-0.978), suggesting that the model had accurate discrimination ability and calibration. Internal validation achieved a good C-index of 0.940.

Conclusion

The nomogram including the comorbidities (i.e., diabetes, CHD, heart failure, hypotension, COPD, cerebral infarction, anemia and CKD), ADL and SBP can be conveniently used to facilitate individualized identification of risk of death during hospitalization in patients with AD.

Exploration of Aging-Care Parameters to Predict Mortality of Patients Aged 80-Years and Above with Community-Acquired Pneumonia

Purpose

The study explores a clinical model based on aging-care parameters to predict the mortality of hospitalized patients aged 80-year and above with community-acquired pneumonia (CAP).

Patients and methods

In this study, four hundred and thirty-five CAP patients aged 80-years and above were enrolled in the Central Hospital of Minhang District, Shanghai during 01,01,2018–31,12,2021. The clinical data were collected, including aging-care relevant factors (ALB, FRAIL, Barthel Index and age-adjusted Charlson Comorbidity Index) and other commonly used factors. The prognostic factors were screened by multivariable logistic regression analysis. Receiver operating characteristic (ROC) curves were used to predict the mortality risk.

Results

Univariate analysis demonstrated that several factors, including gender, platelet distribution width, NLR, ALB, CRP, pct, pre-albumin, CURB-65, low-density, lipoprotein, Barthel Index, FRAIL, leucocyte count, neutrophil count, lymphocyte count and aCCI, were associated with the prognosis of CAP. Multivariate model analyses further identified that CURB-65 (p < 0.0001, OR = 5.44, 95% CI = 3.021–10.700), FRAIL (p < 0.0001, OR = 5.441, 95% CI = 2.611–12.25) and aCCI (p = 0.003, OR = 1.551, 95% CI = 1.165–2.099) were independent risk factors, whereas ALB (p = 0.005, OR = 0.871, 95% CI = 0.788–0.957) and Barthel Index (p = 0.0007, OR = 0.958, 95% CI = 0.933–0.981) were independent protective factors. ROC curves were plotted to further predict the in-hospital mortality and revealed that combination of three parameters (Barthel Index+ FRAI +CURB-65) showed the best performance.

Conclusion

This study showed that CURB-65, frailty and aCCI were independent risk factors influencing prognosis. In addition, ALB and Barthel Index were protective factors for in CAP patients over 80-years old. AUC was calculated and revealed that combination of three parameters (Barthel Index+ FRAI +CURB-65) showed the best performance.

Comparison of Different Scoring Systems for Prediction of Mortality and ICU Admission in Elderly CAP Population

Background

The incidence and mortality rate of community-acquired pneumonia (CAP) in elderly patients were higher than the younger population. Different scoring systems, including The quick Sequential Organ Function Assessment (qSOFA), Combination of Confusion, Urea, Respiratory Rate, Blood Pressure, and Age ≥65 (CURB-65), Modified Early Warning Score (MEWS) and National Early Warning Score (NEWS), were used widely for predicting mortality and ICU admission of patients with community-acquired pneumonia (CAP). This study aimed to identify the most suitable score system for better hospitalization.

Methods

We retrospectively analyzed elderly patients with CAP in Minhang Hospital, Fudan University from 1 January 2018 to 1 January 2020. We recorded information of the patients including age, gender, underlying disease, consciousness state, vital signs, physiological and laboratory variables and further calculated the qSOFA, CURB-65, MEWS, and NEWS scores. Receiver operating characteristic (ROC) curves were used to predict the mortality risk and ICU admission. Kaplan–Meier survival curves were used in survival rate.

Results

In total, 1044 patients were selected for analysis and divided into two groups, namely survivor groups (902 cases) and non-survivor groups (142 cases). Depending on ICU admission enrolled patients were classified into ICU admission (n = 102) and non-ICU admission (n = 942) groups. Mortality expressed as AUC values were 0.844 (p < 0.001), 0.868 (p < 0.001), 0.927 (p < 0.001) and 0.892 (p < 0.001) for qSOFA, CURB 65, MEWS and NEWS, respectively. There were clear differences in MEWS vs CURB-65 (p < 0.0001), MEWS vs NEWS (p < 0.001), MEWS vs qSOFA (p < 0.0001). For ICU-admission, the AUC values of qSOFA, CURB-65, MEWS and NEWS scores were 0.866 (p < 0.001), 0.854 (p < 0.001), 0.922 (p < 0.001), 0.976 (p < 0.001), respectively. There were significant differences in NEWS vs CURB-65 (p < 0.0001), NEWS vs MEWS (p < 0.001), NEWS vs qSOFA (p < 0.0001).

Conclusion

We explored the outcome prediction values of CURB65, qSOFA, MEWS and NEWS for patients aged 65-years and older with community-acquired pneumonia. We found that MEWS showed superiority over the other severity scores in predicting hospital mortality, and NEWS showed superiority over the other scores in predicting ICU admission.