Integration of Pulmonary Function Data into Electronic Health Records: Time for Action

Inverted U-Shaped relationship Between Systemic Immune-Inflammation Index and Pulmonary Function: A Large Population-Based Study in US Adults

Background

Systemic immune-inflammation index (SII) is a novel comprehensive inflammatory marker. Inflammation is associated with impaired lung function. We aimed to explore the possible relationship between SII and lung function to examine the potential of SII in predicting lung function decline.

Methods

A cross-sectional survey was conducted using the data of the NHANES from 2007 to 2012. Multiple linear regression models were used to analyze the linear relationship between SII and pulmonary functions. Sensitivity analyses, subgroup analyses, and interaction tests were used to examine the robustness of this relationship across populations. Fitted smooth curves and threshold effect analysis were used to describe the nonlinear relationships.

Results

A total of 10,125 patients were included in this study. After adjusting for all covariates, multiple linear regression model analysis showed that high Log2-SII level was significantly associated with decreased FVC(β, -23.4061; 95% CI, -42.2805- -4.5317), FEV1(β, -46.7730; 95% CI, -63.3371- -30.2089), FEV1%(β, -0.7923; 95% CI, -1.1635- -0.4211), FEV1/FVC(β, -0.6366; 95% CI, -0.8328- -0.4404) and PEF(β, -121.4468; 95% CI,-164.1939- -78.6998). The negative correlation between Log2-SII and pulmonary function indexes remained stable in trend test and stratified analysis. Inverted U-shaped relationships between Log2-SII and FVC, FEV1, FEV1%, and PEF were observed, while a negative linear correlation existed between FEV1/FVC and Log2-SII. The cutoff values of the nonlinear relationship between Log2-SII and FVC, FEV1, FEV1%, PEF were 8.3736, 8.0688, 8.3745, and 8.5255, respectively. When SII exceeded the critical value, the lung function decreased significantly.

Conclusion

This study found a close correlation between SII and pulmonary function indicators. This study investigated the SII threshold when lung functions began to decline in the overall population. SII may become a promising serological indicator for predicting lung function decline. However, prospective studies were needed further to establish the causal relationship between these two factors.

Serum lactate dehydrogenase is associated with impaired lung function: NHANES 2011-2012

BACKGROUND

Serum lactate dehydrogenase levels reflect disease status in a variety of organs, but its role in indicating pulmonary function is not yet clear. Therefore, this study explored the correlation between pulmonary function and serum lactate dehydrogenase, and investigated thresholds for changes in pulmonary function indicators in the total population as well as in different strata of the population.

METHODS

Based on data from the National Health and Nutrition Examination Survey (NHANES) 2011-2012 (n = 3453), univariate and stratified analyses were performed to investigate factors associated with pulmonary function, and multiple regression analysis was used to further investigate the specific relationship with serum lactate dehydrogenase. Smoothed curve fitting, threshold effect and saturation effect analysis were used to explore the threshold level of serum lactate dehydrogenase at the onset of changes in pulmonary function indicators.

RESULTS

Adjusted smoothed curve fit plots showed a linear relationship between serum lactate dehydrogenase levels and forced vital capacity and forced expiratory volume in one second: for each 1 U/L increase in serum lactate dehydrogenase levels, forced vital capacity decreased by 1.24 mL (95% CI = -2.05, -0.42, P = 0.0030) and forced expiratory volume in one second by 1.11 mL (95% CI = -1.82, -0.39, P = 0.0025).

CONCLUSIONS

Serum lactate dehydrogenase was negatively and linearly correlated with pulmonary function indices in the total population analyzed. Based on the total population and different population stratifications, this study determined the threshold values of serum lactate dehydrogenase at the onset of decline of pulmonary function in different populations. This provides a new serological monitoring indicator for patients suffering from respiratory diseases and has implications for patients with possible clinical impairment of pulmonary function. However, our cross-sectional study was not able to determine a causal relationship between these two factors, and further research is needed.

Crossing the health IT chasm: considerations and policy recommendations to overcome current challenges and enable value-based care

While great progress has been made in digitizing the US health care system, today's health information technology (IT) infrastructure remains largely a collection of systems that are not designed to support a transition to value-based care. In addition, the pursuit of value-based care, in which we deliver better care with better outcomes at lower cost, places new demands on the health care system that our IT infrastructure needs to be able to support. Provider organizations pursuing new models of health care delivery and payment are finding that their electronic systems lack the capabilities needed to succeed. The result is a chasm between the current health IT ecosystem and the health IT ecosystem that is desperately needed.In this paper, we identify a set of focal goals and associated near-term achievable actions that are critical to pursue in order to enable the health IT ecosystem to meet the acute needs of modern health care delivery. These ideas emerged from discussions that occurred during the 2015 American Medical Informatics Association Policy Invitational Meeting. To illustrate the chasm and motivate our recommendations, we created a vignette from the multistakeholder perspectives of a patient, his provider, and researchers/innovators. It describes an idealized scenario in which each stakeholder's needs are supported by an integrated health IT environment. We identify the gaps preventing such a reality today and present associated policy recommendations that serve as a blueprint for critical actions that would enable us to cross the current health IT chasm by leveraging systems and information to routinely deliver high-value care.