Prognostic indicators for in-hospital mortality in COPD with acute exacerbation in Thailand: a retrospective cohort study

Morasert, Thotsaporn; Jantarapootirat, Methus; Phinyo, Phichayut; Patumanond, Jayanton

doi:10.1136/bmjresp-2019-000488

Cited by 13 publications

(13 citation statements)

References 49 publications

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“…Consistent with previously reported studies on mortality in AECOPD, advanced age was recognized as a significant predictor for mortality in our study ( 18 , 20 ). Respiratory failure emerged as a strong risk factor for in-hospital mortality, which is similar to a recent research on hypercapnia during respiratory failure increased the risk of mortality ( 21 , 22 ).…”

Section: Discussionsupporting

confidence: 93%

“…Respiratory failure emerged as a strong risk factor for in-hospital mortality, which is similar to a recent research on hypercapnia during respiratory failure increased the risk of mortality ( 21 , 22 ). The increase in mortality risk was also observed in patients with respiratory failure in a cohort in Thailand ( 20 ). Respiratory failure is a serious complication in severe exacerbations.…”

Section: Discussionmentioning

confidence: 71%

“…It reflects disease severity with a manifestation of dramatical drop in lung function. This condition can be modified through early interventions, for example, blood gas and proper management when admitted and utilization of ventilation or supplemental oxygen ( 20 , 23 , 24 ). Co-existing morbidities have been regarded as mortality predicting factors after hospital admission ( 4 , 25 , 26 ).…”

Section: Discussionmentioning

confidence: 99%

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Development and Validation of Risk Prediction Model for In-hospital Mortality Among Patients Hospitalized With Acute Exacerbation Chronic Obstructive Pulmonary Disease Between 2015 and 2019

et al. 2021

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Background: In patients with chronic obstructive pulmonary disease (COPD), acute exacerbations affect patients' health and can lead to death. This study was aimed to develop a prediction model for in-hospital mortality in patients with acute exacerbations of COPD (AECOPD).Method: A retrospective study was performed in patients hospitalized for AECOPD between 2015 and 2019. Patients admitted between 2015 and 2017 were included to develop model and individuals admitted in the following 2 years were included for external validation. We analyzed variables that were readily available in clinical practice. Given that death was a rare outcome in this study, we fitted Firth penalized logistic regression. C statistic and calibration plot quantified the model performance. Optimism-corrected C statistic and slope were estimated by bootstrapping. Accordingly, the prediction model was adjusted and then transformed into risk score.Result: Between 2015 and 2017, 1,096 eligible patients were analyzed, with a mean age of 73 years and 67.8% male. The in-hospital mortality was 2.6%. Compared to survivors, non-survivors were older, more admitted from emergency, more frequently concomitant with respiratory failure, pneumothorax, hypoxic-hypercarbic encephalopathy, and had longer length of stay (LOS). Four variables were included into the final model: age, respiratory failure, pneumothorax, and LOS. In internal validation, C statistic was 0.9147, and the calibration slope was 1.0254. Their optimism-corrected values were 0.90887 and 0.9282, respectively, indicating satisfactory discrimination and calibration. When externally validated in 700 AECOPD patients during 2018 and 2019, the model demonstrated good discrimination with a C statistic of 0.8176. Calibration plot illustrated a varying discordance between predicted and observed mortality. It demonstrated good calibration in low-risk patients with predicted mortality rate ≤10% (P = 0.3253) but overestimated mortality in patients with predicted rate >10% (P < 0.0001). The risk score of 20 was regarded as a threshold with an optimal Youden index of 0.7154.Conclusion: A simple prediction model for AECOPD in-hospital mortality has been developed and externally validated. Based on available data in clinical setting, the model could serve as an easily used instrument for clinical decision-making. Complications emerged as strong predictors, underscoring an important role of disease management in improving patients' prognoses during exacerbation episodes.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 71%

Section: Discussionmentioning

confidence: 99%

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Development and Validation of Risk Prediction Model for In-hospital Mortality Among Patients Hospitalized With Acute Exacerbation Chronic Obstructive Pulmonary Disease Between 2015 and 2019

et al. 2021

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“…Kim et al showed that, after grouping the population by age quartiles, the rate of FEV1 decline was faster among older patients than younger ones [ 43 ]. Other studies have also shown that COPD patients had higher odds of inpatient mortality and morbidity, particularly if they were more than 80 years of age [ 44 , 45 ]. So, we included age in the logistic regression as a confounder.…”

Section: Discussionmentioning

confidence: 99%

The Impact of Diabetes Mellitus in Patients with Chronic Obstructive Pulmonary Disease (COPD) Hospitalization

Gunasekaran

Murthi

Elango

et al. 2021

JCM

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(1) Background: Chronic obstructive pulmonary disease (COPD) is the leading cause of morbidity and mortality worldwide. Diabetes mellitus (DM) has been shown to have adverse inflammatory effects on lung anatomy and physiology. We investigated the impact of DM on COPD patient outcomes during inpatient hospitalization. (2) Methods: We conducted a retrospective analysis using the Nationwide Inpatient Sample (NIS) over the years 2002–2014. Three groups, COPD without diabetes, COPD with diabetes but no complication, and COPD with DM and complication, were analyzed. (3) Results: A total of 7,498,577 were COPD hospitalization; of those, 1,799,637 had DM without complications, and 483,467 had DM with complications. After adjusting for clinical, demographic, and comorbidities, the odds of increased LOS in the COPD/DM with complication were 1.37 (confidence interval (CI): 1.326–1.368), and those of DM without complication were 1.061 (1.052–1.070) when compared with COPD alone. The odds of pneumonia, respiratory failure, stroke, and acute kidney injury were also higher in COPD hospitalizations with DM. Both DM with complication (odds ratio (OR): 0.751 (CI 0.727–0.777)) and DM without complication (OR: 0.635 (CI: 0.596–0.675)) have lesser odds of mortality during hospitalization than with COPD alone. (4) Conclusions: There is a considerable inpatient burden among COPD patients with DM in the United States.

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“…Second, an arterial puncture was also required for the evaluation of acidemia. In Thailand, blood gas analysis was only performed in patients with AECOPD who were intubated and needed regular ventilation adjustment [20]. Thus, for patients with AECOPD without acute respiratory failure, blood gas analysis was not generally available for the calculation of the DECAF score.…”

Section: Introductionmentioning

confidence: 99%

The MAGENTA model for individual prediction of in-hospital mortality in chronic obstructive pulmonary disease with acute exacerbation in resource-limited countries: A development study

et al. 2021

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Background Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a common undesirable event associated with significant morbidity and mortality. Several clinical prediction tools for predicting in-hospital mortality in patients with AECOPD have been developed in the past decades. However, some issues concerning the validity and availability of some predictors in the existing models may undermine their clinical applicability in resource-limited clinical settings. Methods We developed a multivariable model for predicting in-hospitality from a retrospective cohort of patients admitted with AECOPD to one tertiary care center in Thailand from October 2015 to September 2017. Multivariable logistic regression with fractional polynomial algorithms and cluster variance correction was used for model derivation. Results During the study period, 923 admissions from 600 patients with AECOPD were included. The in-hospital mortality rate was 1.68 per 100 admission-day. Eleven potential predictors from the univariable analysis were included in the multivariable logistic regression. The reduced model, named MAGENTA, incorporated seven final predictors: age, body temperature, mean arterial pressure, the requirement of endotracheal intubation, serum sodium, blood urea nitrogen, and serum albumin. The model discriminative ability based on the area under the receiver operating characteristic curve (AuROC) was excellent at 0.82 (95% confidence interval 0.77, 0.86), and the calibration was good. Conclusion The MAGENTA model consists of seven routinely available clinical predictors upon patient admissions. The model can be used as an assisting tool to aid clinicians in accurate risk stratification and making appropriate decisions to admit patients for intensive care.

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Prognostic indicators for in-hospital mortality in COPD with acute exacerbation in Thailand: a retrospective cohort study

Cited by 13 publications

References 49 publications

Development and Validation of Risk Prediction Model for In-hospital Mortality Among Patients Hospitalized With Acute Exacerbation Chronic Obstructive Pulmonary Disease Between 2015 and 2019

Development and Validation of Risk Prediction Model for In-hospital Mortality Among Patients Hospitalized With Acute Exacerbation Chronic Obstructive Pulmonary Disease Between 2015 and 2019

The Impact of Diabetes Mellitus in Patients with Chronic Obstructive Pulmonary Disease (COPD) Hospitalization

The MAGENTA model for individual prediction of in-hospital mortality in chronic obstructive pulmonary disease with acute exacerbation in resource-limited countries: A development study

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