Application of a parametric model in the mortality risk analysis of ICU patients with severe COPD

Nomograms for Predicting Coexisting Cardiovascular Disease and Prognosis in Chronic Obstructive Pulmonary Disease: A Study Based on NHANES Data

Background

Chronic obstructive pulmonary disease (COPD) is a common chronic disease. Progression is further exacerbated by the coexistence of cardiovascular disease (CVD). We aim to construct a diagnostic nomogram for predicting the risk of coexisting CVD and a prognostic nomogram for predicting long-term survival in COPD.

Methods

The 540 eligible participants selected from the NHANES 2005-2010 were included in this study. Logistic regression analysis was used to construct a diagnostic nomogram for the diagnosis of coexisting CVD in COPD. Cox regression analyses were used to construct a prognostic nomogram for COPD. A risk stratification system was developed based on the total score generated from the prognostic nomogram. We used C-index and ROC curves to evaluate the discriminant ability of the newly built nomograms. The models were also validated utilizing calibration curves. Survival curves were made using the Kaplan-Meier method and compared by the Log-rank test.

Results

Logistic regression analysis showed that gender, age, neutrophil, RDW, LDH, and HbA1c were independent predictors of coexisting CVD and were included in the diagnostic model. Cox regression analysis indicated that CVD, gender, age, BMI, RDW, albumin, LDH, creatinine, and NLR were independent predictors of COPD prognosis and were incorporated into the prognostic model. The C-index and ROC curves revealed the good discrimination abilities of the models. And the calibration curves implied that the predicted values by the nomograms were in good agreement with the actual observed values. In addition, we found that coexisting with CVD had a worse prognosis compared to those without CVD, and the prognosis of the low-risk group was better than that of the high-risk group in COPD.

Conclusions

The nomograms we developed can help clinicians and patients to identify COPD coexisting CVD early and predict the 5-year and 10-year survival rates of COPD patients, which has some clinical practical values.

Low skeletal muscle area as a prognostic marker for chronic obstructive pulmonary disease in elderly patients admitted to ICU

Low L3 skeletal muscle area (SMA), which is assessed on computed tomography (CT) images, has been reported to indicate poor clinical outcomes of patients with acute exacerbation of chronic obstructive pulmonary disease (COPD). The dorsal muscle group area at the T12 vertebral level (T12DMA) was used as an alternative to L3 SMA. This study aimed to investigate whether T12DMA could be used as a predictor of in-hospital mortality and long-term survival in elderly patients with COPD admitted to the intensive care unit (ICU). This single-center retrospective case-control study was performed by analyzing the clinical information and measuring T12DMA on chest CT images of elderly patients with COPD admitted to the ICU between May 2013 and May 2018. This study included 136 patients. The multivariate logistic regression analysis showed that T12DMA, neutrophil-lymphocyte ratio, invasive mechanical ventilation, and systemic steroid therapy were independent risk factors for predicting the hospital mortality. The median survival was significantly higher in the high-T12DMA group (214 days) than in the low-T12DMA group (32 days).

Personalized medicine for patients with COPD: where are we?

Chronic airflow limitation is the common denominator of patients with chronic obstructive pulmonary disease (COPD). However, it is not possible to predict morbidity and mortality of individual patients based on the degree of lung function impairment, nor does the degree of airflow limitation allow guidance regarding therapies. Over the last decades, understanding of the factors contributing to the heterogeneity of disease trajectories, clinical presentation, and response to existing therapies has greatly advanced. Indeed, diagnostic assessment and treatment algorithms for COPD have become more personalized. In addition to the pulmonary abnormalities and inhaler therapies, extra-pulmonary features and comorbidities have been studied and are considered essential components of comprehensive disease management, including lifestyle interventions. Despite these advances, predicting and/or modifying the course of the disease remains currently impossible, and selection of patients with a beneficial response to specific interventions is unsatisfactory. Consequently, non-response to pharmacologic and non-pharmacologic treatments is common, and many patients have refractory symptoms. Thus, there is an ongoing urgency for a more targeted and holistic management of the disease, incorporating the basic principles of P4 medicine (predictive, preventive, personalized, and participatory). This review describes the current status and unmet needs regarding personalized medicine for patients with COPD. Also, it proposes a systems medicine approach, integrating genetic, environmental, (micro)biological, and clinical factors in experimental and computational models in order to decipher the multilevel complexity of COPD. Ultimately, the acquired insights will enable the development of clinical decision support systems and advance personalized medicine for patients with COPD.

The Relationship Between Work Commitment, Dynamic, and Medication Error

Incidence of medication errors in intensive care unit (ICU) can cause irreparable damage for ICU patients. Therefore, it seems necessary to find the causes of medication errors in this section. Work commitment and dynamic might affect the incidence of medication errors in ICU. To assess the mentioned hypothesis, we performed a descriptive-analytical study which was carried out on 117 nurses working in ICU of educational hospitals in Tehran. Minick et al., Salyer et al., and Wakefield et al. scales were used for data gathering on work commitment, dynamic, and medication errors, respectively. Findings of the current study revealed that high work commitment in ICU nurses caused low number of medication errors, including intravenous and nonintravenous. We controlled the effects of confounding variables in detection of this relationship. In contrast, no significant association was found between work dynamic and different types of medication errors. Although the study did not observe any relationship between the dynamics and rate of medication errors, the training of nurses or nursing students to create a dynamic environment in hospitals can increase their interest in the profession and increase job satisfaction in them. Also they must have enough ability in work dynamic so that they don’t confused and distracted result in frequent changes of orders, care plans, and procedures.