Emergency admission parameters for predicting in-hospital mortality in patients with acute exacerbations of chronic obstructive pulmonary disease with hypercapnic respiratory failure

A nomogram for predicting short-term mortality in ICU patients with coexisting chronic obstructive pulmonary disease and congestive heart failure

OBJECTIVE

This study aimed to develop and validate a nomogram for predicting 28-day and 90-day mortality in intensive care unit (ICU) patients who have chronic obstructive pulmonary disease (COPD) coexisting with congestive heart failure (CHF).

METHODS

An extensive analysis was conducted on clinical data from the Medical Information Mart for Intensive Care IV database, covering patients over 18 years old with both COPD and CHF, who were were first-time ICU admissions between 2008 and 2019. The least absolute shrinkage and selection operator (LASSO) regression method was employed to screen clinical features, with the final model being optimized using backward stepwise regression guided by the Akaike Information Criterion (AIC) to construct the nomogram. The predictive model's discrimination and clinical applicability were evaluated via receiver operating characteristic (ROC) curves, calibration curves, the C-index, and decision curve analysi s (DCA).

RESULTS

This analysis was comprised of a total of 1948 patients. Patients were separated into developing and validation cohorts in a 7:3 ratio, with similar baseline characteristics between the two groups. The ICU mortality rates for the developing and verification cohorts were 20.8 % and 19.5 % at 28 days, respectively, and 29.4 % and 28.3 % at 90 days, respectively. The clinical characteristics retained by the backward stepwise regression include age, weight, systolic blood pressure (SBP), respiratory rate (RR), oxygen saturation (SpO2), red blood cell distribution width (RDW), lactate, partial thrombosis time (PTT), race, marital status, type 2 diabetes mellitus (T2DM), malignant cancer, acute kidney failure (AKF), pneumonia, immunosuppressive drugs, antiplatelet agents, vasoactive agents, acute physiology score III (APS III), Oxford acute severity of illness score (OASIS), and Charlson comorbidity index (CCI). We developed two separate models by assigning weighted scores to each independent risk factor: nomogram A excludes CCI but includes age, T2DM, and malignant cancer, while nomogram B includes only CCI, without age, T2DM, and malignant cancer. Based on the results of the AUC and C-index, this study selected nomogram A, which demonstrated better predictive performance, for subsequent validation. The calibration curve, C-index, and DCA results indicate that nomogram A has good accuracy in predicting short-term mortality and demonstrates better discriminative ability than commonly used clinical scoring systems, making it more suitable for clinical application.

CONCLUSION

The nomogram developed in this study offers an effective assessment of short-term mortality risk for ICU patients with COPD and CHF, proving to be a superior tool for predicting their short-term prognosis.

A Novel Facet of In-Hospital Food Consumption Associated with Hospital Mortality in Patients with Scheduled Admission-Addition of a Study Protocol to Test the Existence of Effects of COVID-19 in the Same Study in the Post-COVID-19 Period

BACKGROUND

Humankind has faced unexperienced pandemic events since 2020. Since the COVID-19 pandemic has calmed down, we felt the need to verify whether in-hospital mortality had worsened compared to pre-pandemic conditions due to the COVID-19 pandemic.

OBJECTIVE

To test the hypothesis that daily food consumption is associated with in-hospital mortality during hospitalization and to provide baseline data to examine whether the effects of COVID-19 exist or not in post-pandemic period.

METHODS

All hospitalized patients staying in a single institution on the third Thursday of May, August, November, and the following February were included. Compared data: (1) among four seasons, (2) between age < 75 vs. ≥75 years, (3) between <75% vs. ≥75% of in-hospital food, and (4) logistic regression analysis to identify factors associated with in-hospital mortality.

RESULTS

In 365 inpatients, the following results were obtained: (1) no seasonality or age effect in in-hospital mortality, (2) the novel cutoff value of 75% of the hospital food requirement was used to identify poor in-hospital survivors, (3) logistic regression analysis showed low food consumption, with <75% of the hospital food requirement as the predictor of high in-hospital mortality.

CONCLUSIONS

A small eater of in-hospital food < 75% during hospitalization was associated with significantly higher in-hospital mortality in patients with scheduled hospitalization in the pre-pandemic period. Then, a study protocol is proposed to test the existence of the effects of COVID-19 in the same study in the post-COVID-19 period. This study protocol is, to our knowledge, the first proposal to test the effects of food consumption in the post-COVID-19 period on in-hospital mortality in the clinical nutritional areas.

Clinical efficacy and safety of the self-developed Zangsiwei Qingfei Mixture combined with conventional treatment in patients with acute exacerbation of chronic obstructive pulmonary disease

OBJECTIVES

Chronic obstructive pulmonary disease (COPD) is a significant global public health issue. Modern medical treatments have both benefits and limitations, prompting increasing attention from scholars worldwide on traditional ethnic medicine, and the Zangsiwei Qingfei Mixture is a newly developed formula derived from the effective components of classical Tibetan medicine to treat chronic respiratory diseases. This study aims to investigate the clinical efficacy and safety of the Zangsiwei Qingfei Mixture combined with conventional treatment in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD).

METHODS

Sixty AECOPD patients admitted to the Second Xiangya Hospital of Central South University from May 2021 to May 2023 were enrolled and randomly divided into 2 groups, with 30 patients in each group. The control group received conventional treatment, including bronchodilators, anti-infection agents, expectorants, and oxygen therapy. The experimental group received the Zangsiwei Qingfei Mixture in addition to conventional treatment. The treatment duration was 7 d for both groups. Baseline data such as gender, age, body mass index (BMI), smoking status, Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification, COPD course, and the number of COPD exacerbations in the past year were collected. The primary efficacy indicators were assessed using the modified Medical Research Council (mMRC) dyspnea scale and the modified Borg scale. Secondary indicators included arterial lactic acid (LAC) and serum tumor necrosis factor alpha (TNF-α) levels. Safety indicators included liver and kidney function [alanine transaminase (ALT), aspartate transaminase (AST), serum creatinine (SCr), serum uric acid (SUA)], coagulation function [activated partial thromboplastin time (APTT), prothrombin time (PT), fibrinogen (FIB), and D-dimer]. The generalized linear mixed model (GLMM) was used to evaluate the clinical efficacy and safety of the Zangsiwei Qingfei Mixture.

RESULTS

Before treatment, there were no statistically significant differences in general baseline data, grading of mMRC dyspnea scale, score of modified Borg scale, arterial LAC, ALT, AST, SCr, SUA, APTT, FIB, and D-dimer between the 2 groups (all P>0.05). However, serum TNF-α and PT levels in the experimental group were significantly lower than those in the control group (both P<0.05). GLMM analysis showed that after adjusting for pre- and post-treatment, gender, age, BMI, smoking status, GOLD classification, COPD course, and the number of COPD exacerbations in the past year, the experimental group demonstrated significantly lower grading of mMRC dyspnea scale (coefficient=-0.329, P=0.036), score of modified Borg scale (coefficient=-1.077, P=0.001), serum TNF-α level (coefficient=-14.378, P<0.001), and arterial LAC level (coefficient=-0.409, P=0.012) compared to the control group. The Zangsiwei Qingfei Mixture had no significant effect on liver, kidney, or coagulation function indicators (all P>0.05).

CONCLUSIONS

The Zangsiwei Qingfei Mixture combined with conventional treatment can improve clinical symptoms and promote homeostasis in AECOPD patients, demonstrating safety and reliability. Combining modern medicine with traditional ethnic medicine offers a feasible approach to treating chronic respiratory diseases in the future.

Development and Validation of an In-Hospital Mortality Prediction Model for Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Purpose

Patients with chronic obstructive pulmonary disease (COPD) often face unknown risks during acute exacerbation of the disease (AECOPD), which could potentially result in mortality. This study aimed to develop and validate a nomogram model for predicting the risk of in-hospital mortality in AECOPD patients.

Patients and Methods

Clinical data of patients hospitalized at The Second People's Hospital of Wuhu City for AECOPD between January 2013 and December 2022 were retrospectively collected. Variables underwent selection through LASSO regression and multivariable logistic regression to develop a nomogram model. The model's predictive performance was assessed using the concordance index, calibration curve, and decision curve analysis (DCA), with internal validation conducted using the bootstrap method.

Results

A total of 1224 patients were included in this study, with 98 (8%) deaths occurring during hospitalization. LASSO regression identified 11 variables, used to construct model A. Further multivariable logistic regression was conducted to select variables with P < 0.05 to establish model B. model B was selected as the final model based on discrimination, calibration, and clinical utility, encompassing variables including acute respiratory failure, lung cancer, heart rate, hemoglobin, absolute neutrophil count, serum albumin, blood urea nitrogen, and serum chloride. The nomogram model achieved a concordance index of 0.858. Internal validation of the model was conducted using the bootstrap method with 500 repetitions, resulting in a concordance index of 0.851 (95% CI: 0.805, 0.893). The calibration curve demonstrated a good fit, with a Hosmer-Lemeshow goodness-of-fit test P-value of 0.520. Moreover, DCA findings suggested patient benefit within a threshold probability range of 0.02 to 0.73, with a maximum net benefit of 0.07.

Conclusion

The model constructed in this study has good predictive performance, which helps clinical doctors identify patients at high risk of death early.

A Diagnostic Nomogram for Predicting Hypercapnic Respiratory Failure in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Purpose

To develop and validate a nomogram for assessing the risk of developing hypercapnic respiratory failure (HRF) in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD).

Patients and Methods

From January 2019 to August 2023, a total of 334 AECOPD patients were enrolled in this research. We employed the Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression to determine independent predictors and develop a nomogram. This nomogram was appraised by the area under the receiver operating characteristic curve (AUC), calibration curve, Hosmer-Lemeshow goodness-of-fit test (HL test), decision curve analysis (DCA), and clinical impact curve (CIC). The enhanced bootstrap method was used for internal validation.

Results

Sex, prognostic nutritional index (PNI), hematocrit (HCT), and activities of daily living (ADL) were independent predictors of HRF in AECOPD patients. The developed nomogram based on the above predictors showed good performance. The AUCs for the training, internal, and external validation cohorts were 0.841, 0.884, and 0.852, respectively. The calibration curves and HL test showed excellent concordance. The DCA and CIC showed excellent clinical usefulness. Finally, a dynamic nomogram was developed (https://a18895635453.shinyapps.io/dynnomapp/).

Conclusion

This nomogram based on sex, PNI, HCT, and ADL demonstrated high accuracy and clinical value in predicting HRF. It is a less expensive and more accessible approach to assess the risk of developing HRF in AECOPD patients, which is more suitable for primary hospitals, especially in developing countries with high COPD-related morbidity and mortality.

Prognostic value of early warning scores in patients presenting to the emergency department with exacerbation of COPD

OBJECTIVE

Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a condition that frequently presents to the emergency department (ED) and its prognosis is not very well understood. Risk tools that can be used rapidly in the ED are needed to predict the prognosis of these patients.

METHODS

This study comprised a retrospective cohort of AECOPD patients presenting to a single center between 2015 and 2022. The prognostic accuracy of several clinical early warning scoring systems, Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), NEWS‑2, Systemic Inflammatory Response Syndrome (SIRS) and the quick Sepsis-related Organ Failure Assessment (qSOFA), were compared. The outcome variable was determined as one-month mortality.

RESULTS

Of the 598 patients, 63 (10.5%) had died within 1 month after presenting to the ED. Patients who died had more often congestive heart failure, altered mental status, and admission to intensive care, and they were older. Although the MEWS, NEWS, NEWS‑2, and qSOFA scores of those who died were higher than those who survived, there was no difference between the SIRS scores of these two groups. The score with the highest positive likelihood ratio for mortality estimation was qSOFA (8.5, 95% confidence interval [CI] 3.7-19.6). The negative likelihood ratios of the scores were similar, the NEWS score had a negative likelihood ratio of 0.4 (95% CI 0.2-0.8) with the highest negative predictive value of 96.0%.

CONCLUSION

In AECOPD patients, most of the early warning scores that are frequently used in the ED were found to have a moderate ability to exclude mortality and a low ability to predict mortality.

Analysis of the Current State of COPD Nursing Based on a Bibliometric Approach from the Web of Science

Background and Aim

COPD nursing plays a crucial role in alleviating disease symptoms, prolonging patient survival, and is therefore of paramount importance. However, authoritative research findings, research hotspots, and development trends in the field of COPD are still unclear. This study aimed to examine authoritative research findings, research hotspots, and trends in the field of COPD nursing. Descriptive statistics and bibliometric and visual analyses of the literature were conducted.

Methods

Bibliometric data were obtained from the Web of Science database. Citespace was used to explore publication trends, countries, institutions, journals, authors, keywords, and co-citation characteristics of the included literature in order to summarize the key research in the field of COPD nursing.

Results

In total, 693 articles on COPD nursing were published. 1998-2014 showed a rapid growth period in this research field, which stabilized in 2015-2022. The research content could mostly be summarized into five categories: acute exacerbation, quality of life, risk, evidence-based nursing, and pulmonary rehabilitation. The research hotspots in 1998-2014 included randomized controlled trials, education, elderly patients, nursing home residents, nursing homes, rehabilitation, and prevalence. Research in 2015-2022 focused on impact, palliative care, needs, and predictors. In recent years, research mainly concentrated on symptom management models, cost-effectiveness, and cumulative meta-analysis.

Conclusion

Bibliometric analysis of COPD nursing articles indicates that the focus of COPD nursing research is shifting from tertiary prevention to primary and secondary prevention. Helping patients achieve self-management of symptoms, reducing the financial burden of COPD on healthcare, and summarizing research evidence by meta-analyses will likely remain the focus of future research.

Diagnostic Accuracy of Optic Nerve Sheath Diameter Measured With Ocular Ultrasonography in Acute Attack of Chronic Obstructive Pulmonary Disease

OBJECTIVE

The study aimed to evaluate intracranial pressure changes by measuring ONSD before and after treatment in patients with chronic obstructive pulmonary disease (COPD).

METHODS

The study was designed as a prospective analysis, in which 56 COPD in acute exacerbation and 50 volunteers. COPD severity was determined by the Dyspnea Scale of Modified Medical Research Council (mMRC). Measurements were made with ocular ultrasonography and linear probe in both eyes.

RESULTS

Both the right and left ONSDs were higher in the patient compared to the control (P = .017) and regressed after the treatment (P = .021). In the ROC analysis for the predictability of COPD, right eye ONSDs showed a predictive potential for COPD with %75.7 specificity and %68.1 sensitivity at 0.455 cut-off (AUC: 0.727; P = .0001; %95CI: 0.609-0.833). Similar to the right eye, the left ONSD presented %74.4 specificity and %67 sensitivity at 0.505 cut-off value (AUC: 0.718; P = .0001; %95CI: 0.608-0.841).

CONCLUSION

The ONSD measurement that was with the help of ocular ultrasonography can be a useful diagnostic tool for symptomatic COPD presenting with an acute attack.

Acute COPD exacerbation treatment with noninvasive ventilation

The establishment of a guideline for long-term noninvasive ventilation treatment (LTH-NIV) of acute hypercapnic exacerbations of chronic obstructive pulmonary disease (AECOPD) requiring acute ventilation has proven elusive. Most studies thus far have shown no mortality benefit of long-term noninvasive ventilation treatment. Using retrospective analysis of the data of our patients (n = 143) recruited from 2012 to 2019, we aimed to compare patients discharged with and without long-term noninvasive ventilation. The follow-up results showed no significant difference (p = 0.233) between the groups [LTH-NIV (n = 83); non-NIV (n = 60)] regarding readmission due to clinical worsening. However, the first- and second-year survival rates were 82% and 72%, respectively, in the LTH-NIV group and significantly different (p = 0.023) from 67 and 55% in the non-NIV group. The statistical models showed a significant mortality risk for the non-NIV group, with a hazard ratio (HR) of 2.82 (1.31; 6.03). To the best of our knowledge, this is the first study to demonstrate the mortality benefit of long-term NIV therapy for patients with AECOPD under real-world conditions.

The Main Pulmonary Artery to the Ascending Aorta Diameter Ratio (PA/A) as a Predictor of Worse Outcomes in Hospitalized Patients with AECOPD

Purpose

The main pulmonary artery (PA) to ascending aorta diameter ratio (PA/A) greater than one is a promising indicator of pulmonary hypertension (PH) in acute exacerbation (AE) of chronic obstructive pulmonary disease (COPD) (AECOPD). This study aims to disclose the associations between the PA/A ratio and clinical outcomes in hospitalized patients with AECOPD.

Patients and Methods

Consecutive AECOPD patients admitted to the Department of Respiratory Medicine from September 2017 to July 2021 were reviewed. The treatment success of AECOPD patients was defined as improvement in the clinical condition when discharged from the hospital. Conversely, treatment failure was considered to be an event of in-hospital death or deterioration of the clinical condition prior to discharge.

Results

A total of 118 individuals were ultimately reviewed in this study: 74 individuals with a PA/A ratio <1 and 44 individuals with a PA/A ratio ≥1. The outcomes of 21 patients were treatment failure, and 97 patients were considered successes. Patients with a PA/A ratio ≥1 had significantly higher PaCO2, red cell distribution width, brain natriuretic peptide, PA diameters, RICU admission rates, and proportions of treatment failure than patients with PA/A ratios <1 (P < 0.05). The PA diameter and PA/A ratio were significantly increased in the treatment failure group compared with the success group (P < 0.05). A survival analysis indicated that patients with a PA/A ratio ≥1 had worse outcomes than patients with a PA/A ratio <1 during hospitalization (P < 0.05). A multivariate analysis showed that a PA/A ratio ≥1 was an independent risk factor for treatment failure in patients with AECOPD.

Conclusions

AECOPD patients with a PA/A ratio ≥1 may have worse outcomes during hospitalization. A PA/A ratio ≥1 may be a promising predictor of treatment failure in patients with AECOPD.

Neutrophils and Lymphocytes Can Help Distinguish Asymptomatic COVID-19 From Moderate COVID-19

Introduction

Asymptomatic coronavirus disease 2019 (COVID-19) and moderate COVID-19 may be the most common COVID-19 cases. This study was designed to develop a diagnostic model for patients with asymptomatic and moderate COVID-19 based on demographic, clinical, and laboratory variables.

Methods

This retrospective study divided the subjects into 2 groups: asymptomatic COVID-19 (without symptoms, n = 15) and moderate COVID-19 (with symptoms, n = 57). Demographic characteristics, clinical data, routine blood tests, other laboratory tests, and inpatient data were collected and analyzed to compare patients with asymptomatic COVID-19 and moderate COVID-19.

Results

Comparison of the asymptomatic COVID-19 group with the moderate COVID-19 group yielded the following results: the patients were younger (P = 0.045); the cluster of differentiation (CD)8+ (cytotoxic) T cell level was higher (P = 0.017); the C-reactive protein (CRP) level was lower (P = 0.001); the white blood cell (WBC, P < 0.001), neutrophil (NEU, P = 0.036), lymphocyte (LYM, P = 0.009), and eosinophil (EOS, P = 0.036) counts were higher; and the serum iron level (P = 0.049) was higher in the asymptomatic COVID-19 group. The multivariate analysis showed that the NEU count (odds ratio [OR] = 2.007, 95% confidence interval (CI): 1.162 - 3.715, P = 0.014) and LYM count (OR = 9.380, 95% CI: 2.382 - 36.934, P = 0.001) were independent factors for the presence of clinical symptoms after COVID-19 infection. The NEU count and LYM count were diagnostic predictors of asymptomatic COVID-19. This diagnostic prediction model showed high discriminatory power, consistency, and net clinical benefits.

Conclusions

The proposed model can distinguish asymptomatic COVID-19 from moderate COVID-19, thereby helping clinicians identify and distinguish patients with potential asymptomatic COVID-19 from those with moderate COVID-19.