ORIGINAL ARTICLE

https://doi.org/10.5005/jp-journals-11010-1117
Indian Journal of Respiratory Care
Volume 13 | Issue 2 | Year 2024

Prognostic Indicators for Prolonged Hospital Stay in Acute Exacerbation of Chronic Obstructive Pulmonary Disease: An Observational Study

Manju Bala¹, Akhlesh Rajpoot² https://orcid.org/0000-0003-2160-4914, Dinesh C Punera³, Suyash S Rathore⁴

^1–3Department of Respiratory Medicine, Soban Singh Jeena Government Institute of Medical Sciences and Research (SSJGIMSR), Almora, Uttarakhand, India

⁴Department of Pulmonary Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India

Corresponding Author: Akhlesh Rajpoot, Department of Respiratory Medicine, Soban Singh Jeena Government Institute of Medical Sciences and Research (SSJGIMSR), Almora, Uttarakhand, India, Phone: +91 7300672922, e-mail: akhileshrajpoot855@gmail.com

Received: 29 March 2024; Accepted: 31 May 2024; Published on: 18 June 2024

ABSTRACT

Aims and background: Hospitalization for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is recognized as a major event in the natural history of COPD. Besides hurting lung function, survival, risk of readmission, and quality of life, it tremendously increases healthcare costs associated with hospitalization. Information on the time course and recovery from AECOPD is important in standardizing the length of treatment, planning appropriate follow-up, and decreasing the loss of working days of the patient. Hence, this study aimed to identify predictive parameters for length of hospitalization in AECOPD patients.

Materials and methods: It was a prospective and longitudinal clinical-based descriptive study conducted at a tertiary care center in northern India. After applying the exclusion criteria and obtaining informed consent, 200 consecutive AECOPD patients were enrolled over 1 year. The Rome Proposal classifies AECOPD severity as mild, moderate, or severe, and the term prolonged length of hospital stay (LHS) refers to a stay lasting for 7 or more days.

Results: The mean age of the 200 AECOPD patients was 63.9 ± 8.2 years, the mean LHS was 10.9 ± 5.2 days, and prolonged LHS (≥7 days) was seen in 140 (70%) patients. Advanced age, previous hospitalizations for AECOPD, arterial hypoxemia, the need for noninvasive ventilation (NIV), and severe AECOPD upon admission were found to be significantly correlated with the LHS (p < 0.05). However, only severe AECOPD upon admission was identified as an independent factor predicting prolonged hospitalization (p < 0.05).

Conclusion: Older patients with a prior hospitalization for AECOPD, arterial hypoxemia, severe exacerbation of COPD, and need for NIV at the time of admission are more likely to have a longer hospitalization.

How to cite this article: Bala M, Rajpoot A, Punera DC, et al. Prognostic Indicators for Prolonged Hospital Stay in Acute Exacerbation of Chronic Obstructive Pulmonary Disease: An Observational Study. Indian J Respir Care 2024;13(2):101–106.

Source of support: Nil

Conflict of interest: None

Keywords: Acute respiratory failure, Chronic obstructive pulmonary disease, Noninvasive ventilation, Steroid therapy

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) is a chronic lung condition that causes respiratory symptoms including breathlessness, cough, sputum production, and exacerbations. This condition occurs due to abnormalities in the airways and alveoli, which result in persistent and often progressive airflow obstruction. It is caused by gene-environment interactions that occur throughout an individual’s lifetime.¹^,² COPD is the third leading cause of death worldwide, with 90% of related deaths occurring in low- to middle-income countries, and hospitalization due to acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a major event in the disease’s natural progression.³^,⁴ The diagnosis of AECOPD is based on the COPD management guidelines, which entail a comprehensive evaluation of symptoms such as dyspnea, cough, and increased sputum.⁵ This process involves a meticulous examination of the patient’s medical history, physical findings, and diagnostic tests such as arterial blood gas (ABG), C-reactive protein (CRP), and chest X-rays. Adherence to the severity criteria of AECOPD guides evidence-based interventions, ensuring timely, personalized care. Early recognition and management of AECOPD prevent adverse outcomes, improve patient outcomes, and reduce healthcare costs. These events negatively impact lung function, quality of life, and survival rates, highlighting the need for prompt management.

Although only a minority of COPD patients (about 10–15%) experience severe exacerbations requiring hospitalization, the associated expenses for AECOPD account for >70% of all COPD-related medical care costs.⁶ The cost of hospitalization for AECOPD is directly related to the duration of hospital stay. Previous studies have shown that the length of hospital stay (LHS) for patients with AECOPD varies significantly, typically ranging from 3 to 16 days.⁷^-⁹ Additionally, researchers have identified that baseline clinical variables, such as high arterial partial pressure of carbon dioxide (PaCO₂) levels, symptoms for >1 day, and prior antibiotic treatment, were associated with longer hospital stay.¹⁰^,¹¹ Understanding the predictors of prolonged hospital stay can inform the implementation of corrective measures for cost reduction and improved patient management. Hence, the present study aims to identify factors contributing to prolonged LHS in AECOPD patients for better management and care by healthcare providers.

MATERIALS AND METHODS

Study Design and Sample Size

This prospective, longitudinal, and descriptive study was conducted at a tertiary care center in northern India over 8 months, from May to December 2023. The study evaluated the factors contributing to prolonged hospitalization for AECOPD patients while ensuring ethical guidelines and participant safety. COPD was diagnosed following the global initiative for chronic obstructive lung disease (GOLD) criteria, and AECOPD severity was classified using ”The Rome Proposal.”¹² Based on the prevalence of COPD (7.2–10.1%) in past studies and AECOPD patients (10–15%) requiring hospitalization,⁶^,¹³^,¹⁴ a sample size of a minimum of 138 AECOPD patients was required to detect a 10% prevalence of AECOPD with a 5% margin of error at a 95% confidence level.

Inclusion Criteria

The AECOPD patients with age >40 years, who were willing to participate and provide written informed consent were enrolled in the study.

Exclusion Criteria

Chronic obstructive pulmonary disease patients who were hospitalized due to other causes such as pulmonary embolism, pneumothorax, lung cancer, lower respiratory tract infections, pleural effusion, or cardiac insufficiency and those who refused consent were excluded. After considering the inclusion and exclusion criteria, a total of 200 consecutive patients admitted for AECOPD were enrolled. The study was approved by the Institutional Ethics Committee of our teaching institute (IEC/NEW/INST/2021/1921).

Methodology

After hospitalization, the AECOPD patients underwent a thorough evaluation, including a detailed medical history and clinical examination. Appropriate investigations were conducted to rule out differentials of AECOPD, and various parameters of patients were noted at the time of admission. These parameters included age, sex, body mass index (BMI), smoking history, previous AECOPD hospitalizations, comorbidities (e.g., diabetes, hypertension), recent spirometry, baseline blood tests (ABG, complete blood count, kidney/liver function, pro-B-type natriuretic peptide, CRP), chest X-ray, electrocardiogram, and echocardiography. The severity of AECOPD was classified as mild, moderate, or severe, and patients were managed accordingly following established guidelines.¹² The treatment plan involved a combination of pharmacological and non-pharmacological therapies to manage AECOPD. Pharmacological therapy included inhaled bronchodilators, inhaled steroids, systemic steroids, and parenteral antibiotics. Additionally, nonpharmacological therapy, including noninvasive ventilation (NIV) with supportive care, was provided as required. Fortunately, none of our patients required invasive mechanical ventilation, and all patients successfully recovered from AECOPD. Thereafter, factors such as patient age, AECOPD severity, comorbidities, and therapy-related factors were studied for their association with LHS. Based on a previous study, LHS was divided into prolonged (≥7 days) and usual stay (<7 days).¹⁵

Statistical Analysis

Quantitative variables were represented as mean, median, and standard deviation after checking their distribution, and categorical variables were expressed as frequency or percentage. The association of various parameters with LHS was tested using the t-test and logistic regression analysis. A p-value < 0.05 with a confidence level of 95% was considered significant. All statistical tests were performed using Statistical Package for the Social Sciences version 26.0.

RESULTS

A total of 200 AECOPD patients were enrolled in the study, of which 132 (66%) were aged 60 years or older, with a mean age of 63.9 ± 8.2 years. The majority of the patients were male (n = 180, 90%) and ever-smokers (n = 188, 94 current smokers). The mean BMI was 24.3 ± 3.7 kg/m², while only eight patients (n = 8) had a BMI <18.5 kg/m². Upon admission for AECOPD, 64 (32%) patients had systemic hypertension, 24 (12%) had diabetes mellitus, 36 (18%) had a history of pulmonary tuberculosis, and 80 (40%) had cor pulmonale. According to the spirometry test results, COPD patients were classified into four stages based on the percentage of predicted forced expiratory volume in 1 second (FEV₁) values (%FEV₁). GOLD stage I, which indicates mild airflow limitation, was observed in 22 (11%) patients with FEV₁ values above 80% of the predicted value. GOLD stage II, representing moderate airflow limitation, was seen in 62 (31%) patients with FEV₁ values between 50 and 80% of predicted. GOLD stage III, indicating severe airflow limitation, was observed in 84 (42%) patients with FEV₁ values between 30 and 50% of predicted. Finally, GOLD stage IV, which indicates very severe airflow limitation, was seen in 32 (16%) patients with FEV₁ values below 30% of the predicted value. Thus, based on spirometry, the majority of the AECOPD patients (n = 146, 73%) belonged to GOLD stages II and III of COPD (Table 1). Before hospitalization, a significant proportion of this cohort, 116 (58%) patients, were receiving maintenance triple therapy, with a long-acting β-agonist (LABA), a long-acting muscarinic antagonist (LAMA), and an inhaled corticosteroid (ICS). The remaining 84 (42%) patients were receiving dual therapy with LAMA and LABA. At admission, 32 (16%) patients had leukocytosis, 96 (48%) patients had an eosinophil count ≥300/µL, and all 200 patients had respiratory failure on ABG. However, only 136 (68%) patients among those 200 were experiencing type II respiratory failure. Out of these 136 patients, 64 (32%) had severe exacerbation or acidemia on ABG, which is a pH level below 7.35. The severity of AECOPD varied among patients, 64 (32%) had mild, 72 (36%) had moderate, and 64 (32%) had severe exacerbation.

**Table 1:** Clinical and demographic profile of AECOPD patients at admission
Parameters	Value (n = 200)
Age >60 years	132 (66%)
Mean age (years)	63.9 ± 8.2
Male gender	180 (90%)
Ever smokers	188 (94%)
Current smokers	44 (22%)
Never smokers	12 (06%)
Previous hospitalization for AECOPD	118 (59%)
Mean BMI (kg/m²)	24.3 ± 3.7
Hypertension	64 (32%)
Diabetes mellitus	24 (12%)
Treated PTB	36 (18%)
Cor pulmonale	80 (40%)
COPD (GOLD) stage I	22 (11%)
COPD (GOLD) stage II	62 (31%)
COPD (GOLD) stage III	84 (42%)
COPD (GOLD) stage IV	32 (16%)
NIV required	104 (52%)
Mean LHS (days)	10.9 ± 5.2
LHS ≥7 days	140 (70%)

AECOPD, Acute exacerbation of chronic obstructive pulmonary disease; BMI, body mass index; COPD, chronic obstructive pulmonary disease; data presented as n (%), number (percentage); GOLD, global initiative for chronic obstructive lung disease; n, number; NIV, noninvasive ventilation; PTB, pulmonary tuberculosis; LHS, length of hospital stay

Of this cohort of 200 patients, 136 (68%) patients were administered intravenous steroids, with a mean steroid duration of 5.4 ± 1.2 days, and the remaining 64 (32%) patients did not receive either parenteral or oral steroids. A total of 104 (52%) patients were found to require NIV during their hospitalization. Among these, 64 (32%) patients were diagnosed with severe AECOPD (ABG: pH <7.35, PaCO₂ >45 mm Hg), and the remaining 40 patients exhibited accessory respiratory muscle use and failed to maintain adequate oxygenation with a venturi mask or nasal prongs. Additionally, 80 (40%) patients were treated with low-dose diuretics due to coexisting cor pulmonale. All the patients under treatment recovered from AECOPD and were discharged from the hospital, with a mean LHS of 10.9 ± 5.2 days (clinical profiles of patients are presented in Tables 1 and 2).

**Table 2:** Blood investigation parameters and severity of AECOPD at admission
Parameters	Value (n = 200)
Mean hemoglobin (gm/dL)	13.4 ± 2.2
Leukocytosis	32 (16%)
Absolute eosinophil count < 300 (cells/μL)	104 (52%)
Absolute eosinophil count ≥ 300 (cells/μL)	96 (48%)
pH (ABG)	7.33 ± 0.07
Mean PaO₂ (mm Hg)	59.4 ± 23.3
Mean PaCO₂ (mm Hg)	51.3 ± 15.9
Type II respiratory failure	136 (68%)
AECOPD severity
Mild	64 (32%)
Moderate	72 (36%)
Severe (ABG: pH <7.35 and PaCO₂ >45 mm Hg)	64 (32%)

ABG, arterial blood gas; AECOPD, acute exacerbation of chronic obstructive pulmonary disease; data presented as n (%), number (percentage); n, number; PaCO₂, arterial carbon dioxide pressure; PaO₂, arterial oxygen pressure

According to our study, 140 (70%) patients stayed in the hospital for at least 7 days, while 60 (30%) were discharged in <7 days. To analyze the association of different variables with LHS, we set a cutoff of ≥7 days for prolonged hospitalization, based on a previous study.¹⁵ The results indicate that LHS is significantly correlated (p < 0.05) with advanced age, prior hospitalizations for AECOPD, arterial hypoxemia, severe AECOPD, and the need for NIV at admission (Table 3).

**Table 3:** Binary logistic regression analysis of different variables with LHS
Variable	Pearson coefficient (r)	p-value
Age	0.25	0.04*
Male gender	0.09	0.50
BMI	0.07	0.62
Smoking status	−0.14	0.32
Hypertension	−0.18	0.20
Diabetes mellitus	−0.07	0.08
Cor pulmonale	0.38	0.43
Previous hospitalizations	0.30	0.03*
Old PTB	0.22	0.12
Hemoglobin	0.04	0.75
Leukocytosis	0.12	0.40
pH	−0.11	0.42
PaO2	−0.27	0.045*
PaCO₂	0.19	0.20
Type II respiratory failure	0.18	0.19
COPD (GOLD) stage	0.53	0.24
Severe AECOPD	0.40	0.004*
NIV requirement	0.34	0.01*

AECOPD, acute exacerbation of chronic obstructive pulmonary disease; BMI, body mass index; LHS, length of hospital stay; NIV, noninvasive ventilation; PaO₂, arterial oxygen pressure at ambient air; PaCO₂, arterial carbon dioxide pressure; *, significant p-value < 0.05; Bold values indicate statistically significant values

However, when multiple logistic regression analysis was used to analyze the association between the clinical variables and LHS, the results showed that severe AECOPD at admission was the only independent factor that predicted prolonged LHS [odds ratio (OR): 5.0; 95% confidence interval (CI): 1.4–18.2; p = 0.01]. These findings are presented in Table 4.

**Table 4:** Multiple logistic regression analysis of different variables with LHS
Variable	Unstandardized coefficients		Standardized coefficients	t	Significance
Variable	B	Standard error	β	t	Significance
(Constant)	20.996	127.073		0.165	0.870
Age	−0.101	0.078	−0.162	−1.303	0.202
Male gender	4.321	2.757	0.253	1.567	0.127
BMI	0.652	1.482	0.60	0.429	0.626
Smoking status	0.092	0.111	0.152	0.835	0.410
Hypertension	0.283	0.315	0.113	0.849	0.359
Diabetes mellitus	1.033	2.920	0.048	0.354	0.726
Cor pulmonale	0.596	1.833	0.047	0.325	0.747
Previous hospitalizations	0.241	0.528	0.058	0.456	0.652
Old treated PTB	0.686	1.614	0.051	0.425	0.674
Hemoglobin	0.306	0.336	0.130	0.909	0.370
Leukocytosis	0.454	0.286	0.210	1.588	0.122
pH	−3.575	16.271	−0.047	−0.220	0.827
PaO₂	0.421	1.235	0.025	0.356	0.245
PaCO₂	−0.097	0.063	−0.300	−1.537	0.134
Type II respiratory failure	0.261	0.324	0.128	0.645	0.452
COPD (GOLD) stage	4.113	5.343	0.113	0.770	0.447
Severe AECOPD	0.577	0.112	0.742	5.157	0.001*
NIV requirement	1.137	2.019	0.104	0.563	0.577

COPD, Chronic obstructive pulmonary disease; GOLD, global initiative for chronic obstructive lung disease; LHS, length of hospital stay; NIV, noninvasive ventilation; PaCO₂, arterial carbon dioxide pressure; PaO₂, arterial oxygen pressure; SaO₂, oxygen saturation of arterial blood; *, significant p-value < 0.05; Bold values indicate statistically significant values

DISCUSSION

The present study analyzed different clinical variables for their association with the LHS in patients with AECOPD. The term ”prolonged” LHS refers to a stay that lasts for ≥7 days and a usual stay for <7 days.¹⁵ The results showed that advanced age (r = 0.25, p = 0.04), previous hospitalizations for AECOPD (r = 0.30; p = 0.03), arterial hypoxemia (r = −0.28, p = 0.05), need for NIV (r = 0.34; p = 0.01), and severe exacerbations at admission (r = 0.40; p = 0.004) had a statistically significant correlation with the LHS. These results are in coherence with a previous study done by Diamantea et al. which developed the AECOPD-F score for predicting the LHS by including seven parameters including the number of exacerbations in the previous years, and it seems logical that the LHS may be affected by the severity of AECOPD.⁹ The duration of hospitalization is a crucial determinant of the overall medical expenses incurred during the hospital stay. In the present study, the patients had a mean duration of hospital stay of 10.9 ± 5.2 days, which is almost similar to the previous studies done in China (9.38 days), North West England (9.8 days), and Spain (11.9 days), respectively.¹⁶^-¹⁸ However, few studies from the United States (5.9 days) and European countries (8.7 days) had lower durations of hospital stay.¹⁹^,²⁰ This discordance in the duration of LHS might be due to heterogeneity of disease severity, geographical location, and the level of hospital care provided to patients.

Our study showed a statistically significant correlation between advancing age and prolonged LHS. This relationship is consistent with earlier studies and can be attributed to the compromised functional capacity of these patients, leading to a slower rate of clinical recovery.¹⁷^,²¹^,²² Therefore, when dealing with older patients, it’s crucial to focus on comprehensive care, including respiratory treatments, physical activity within limits, and emotional support. Discussing a care plan with the medical team and involving family in decision-making can be beneficial. Our findings emphasize the significance of prior hospitalizations for AECOPD as a reliable marker to predict prolonged LHS and disease severity, as stated in the GOLD guidelines.¹² This is in coherence with a Spanish study done by Crisafulli et al., which showed that patients with prolonged LHS had more hospitalizations for AECOPD previously.²³ The observed phenomenon may be attributed to the exacerbation of COPD, causing a deterioration of lung functionality and a more rapid decline in lung volume, necessitating hospitalization.

In contrast to our findings, a few studies showed that an elevated arterial PaCO₂ level is highly indicative of prolonged hospital stay (>11 days), instead of previous COPD-related admission.⁹^,²⁴ The difference might be due to differences in the study design, particularly the cutoff value of 11 days for prolonged stay in previous studies, or the presence of compensated type-II respiratory failure in many patients at the time of hospitalization in our study. These factors may impact results and need consideration in future investigations. Our research highlights the vital role of arterial hypoxemia during AECOPD and found a significant inverse correlation (r = −0.28, p = 0.05) between arterial hypoxemia and LHS, which emphasizes the clinical relevance of arterial hypoxemia as a prognostic indicator in AECOPD. These findings are supported by previous studies that have shown longer hospital stays among AECOPD patients with arterial hypoxemia while breathing ambient air.²³^,²⁵ Therefore, early management and treatment of hypoxemia are crucial to mitigate the length of hospitalization in AECOPD patients.

The present study showed significant correlation coefficients, r = 0.34 (p = 0.01) for NIV requirement, and r = 0.40 (p = 0.004) for severe AECOPD at admission, with prolonged LHS. These findings suggest a positive correlation between NIV requirement and exacerbation severity upon admission with the duration of hospitalization, which is in line with previous studies.¹⁸^,²³^,²⁶ The statistical significance (p < 0.05) of these associations reinforces their robustness. It emphasizes the clinical relevance of NIV requirement and severity of AECOPD as potential indicators influencing the LHS in patients with AECOPD. Such insights can facilitate a more comprehensive understanding of the factors that impact patient outcomes and guide healthcare professionals in optimizing care strategies and resource allocation. Our research showed that advanced age, previous hospitalizations for AECOPD, arterial hypoxemia, the need for NIV, and severe AECOPD at admission had a significant correlation with the LHS on binary logistic regression analysis. However, on multiple logistic regression analysis, only severe AECOPD was independently associated with prolonged hospital stay (OR: 5.0; 95% CI: 1.4–18.2, p = 0.01). In other words, patients who were admitted with severe AECOPD had a longer hospital stay compared to patients who had mild or moderate exacerbations (10.5 vs 5.3 days, p = 0.001).

The present study did not reveal any significant correlation between gender, respiratory rate, heart rate, comorbidities, GOLD stages of COPD, leukocytosis, and eosinophil counts with prolonged LHS, which coincides with previous studies.¹⁸^,²³^,²⁵ However, some studies revealed a significant correlation of comorbidities with prolonged LHS.²⁶^,²⁷ Such associations might be attributed to pathophysiologic changes due to comorbidities compromising lung function, leading to an increased risk of complications and other diseases. Most of the patients in our study were ever smokers (n = 188, 94%); hence, its association with the LHS could not be evaluated. There is no data on the association of pack years with LHS in AECOPD. However, a previous study by Kessler et al. did not find any differences between smoking and the risk of COPD readmission. Only eight patients in our study were underweight with BMI <18.5 kg/m²; hence, its association with LHS could also not be elicited. A study conducted by Jo et al. discovered that underweight patients had more frequent clinic visits and hospitalization, while an increase in BMI did not correlate significantly with increased COPD-related healthcare utilization.²⁸^,²⁹

When assessing LHS in patients with AECOPD, several factors should be taken into consideration. These factors may include advanced age, prior hospitalizations for AECOPD, arterial hypoxemia, severe AECOPD, and the requirement of NIV during admission. By taking these factors into account, clinicians can make well-informed decisions and enhance the overall management of patients with AECOPD. The study contributes significantly to clinical practice, specifically in enhancing care for patients with AECOPD. The findings have important implications for medical professionals and may inform the development of new treatment strategies. Overall, this research is a valuable addition to the existing knowledge on AECOPD and may lead to improved outcomes for patients.

MAIN POINTS

Elderly patients who have been previously hospitalized for AECOPD.
Exhibit arterial hypoxemia,
Experience severe exacerbation of COPD.
Require NIV at the time of admission, and are more likely to have an extended hospital stay.

Limitations

This study has a few limitations that may have influenced the findings—(1) the small sample size of 200 patients, (2) the study population recruited from a single hospital in North India, thus ethnicity and geographical variance may affect the LHS, and (3) in this study, etiologies of AECOPD were not investigated, which are potentially associated with prognosis and LHS. Therefore, the results of this study should be viewed within the context of these limitations. To gain a more comprehensive understanding of the factors that affect LHS, further studies with larger sample sizes and in-depth analysis of these limitations are required.

CONCLUSION

This study aims to investigate the topic of LHS in AECOPD by evaluating comprehensive patient, disease, and therapy-related factors. The analysis was performed using t-test, binary, and multiple logistic regression models. The study finds that a significant proportion of AECOPD patients experience prolonged LHS (>7 days). Furthermore, advanced age, the number of previous hospitalizations, arterial hypoxemia at ambient air, the need for NIV, and severe AECOPD, are identified as important factors that predict longer hospital stays. However, there is no significant association between spirometry-based COPD severity and LHS. This study suggests that the reasons for prolonged LHS are likely to be multidimensional, and future studies should explore both patient and nonpatient-related factors to provide a comprehensive understanding of the issue.

ETHICAL APPROVAL

This study was approved by the Institutional Ethics Committee of Soban Singh Jeena Government Institute of Medical Sciences and Research (SSJGIMSR), Almora, Uttarakhand, India, IEC/NEW/INST/2021/1921.

ORCID

Akhlesh Rajpoot https://orcid.org/0000-0003-2160-4914

REFERENCES

1. Celli B, Fabbri L, Criner G, et al. Definition and nomenclature of chronic obstructive pulmonary disease: time for its revision. Am J Respir Crit Care Med 2022;206(11):1317–1325. DOI: 10.1164/rccm.202204-0671PP

2. Agusti A, Melen E, DeMeo DL, et al. Pathogenesis of chronic obstructive pulmonary disease: understanding the contributions of gene-environment interactions across the lifespan. Lancet Respir Med 2022;10(5):512–524. DOI: 10.1016/S2213-2600(21)00555-5

3. Halpin DMG, Celli BR, Criner GJ, et al. The GOLD summit on chronic obstructive pulmonary disease in low- and middle-income countries. Int J Tuber Lung Dis 2019;23(11):1131–1141. DOI: 10.5588/ijtld.19.0397

4. Seemungal TA, Donaldson GC, Paul EA, et al. Effect of exacerbation on quality of life in patients with chronic obstructive pulmonary disease. Am J Res Crit Care Med 1998;157(5):1418–1422. DOI: 10.1164/ajrccm.157.5.9709032

5. Celli BR, Fabbri LM, Aaron SD, et al. An updated definition and severity classification of chronic obstructive pulmonary disease exacerbations: the Rome proposal. Am J Respir Crit Care Med 2021;204(11):1251–1258. DOI: 10.1164/rccm.202108-1819PP

6. Sullivan SD, Ramsey SD, Lee TA. The economic burden of COPD. Chest 2000;117(2 Suppl):5S–9S. DOI: 10.1378/chest.117.2_suppl.5s

7. De la Iglesia F, Valino P, Pita S, et al. Factors predicting a hospital stay of over 3 days in patients with acute exacerbation of chronic obstructive pulmonary disease. Int J Med 2002;251(6):500–507. DOI: 10.1046/j.1365-2796.2002.00989.x

8. Nowiński A, Kamiński D, Korzybski D, et al. The impact of comorbidities on the length of hospital treatment in patients with chronic obstructive pulmonary disease. Resp Med 2011;79(6):388–396. DOI: 10.5603/ARM.27622

9. Diamantea F, Kostikas K, Bartziokas K, et al. Prediction of hospitalization stay in COPD exacerbations: the AECOPD-F score. Resp Care 2014;59(11):1679–1686. DOI: 10.4187/respcare.03171

10. Quintana JM, Unzurrunzaga A, Garcia-Gutierrez S, et al. Predictors of hospital length of stay in patients with exacerbations of COPD: a cohort study. JGIM 2015;30(6):824–831. DOI: 10.1007/s11606-014-3129-x

11. Mushlin AI, Black ER, Connolly AC, et al. The necessary length of hospital stay for chronic pulmonary disease. JAMA 1991;266(1):80–83. DOI: 10.1001/jama.1991.03470010084035

12. Global Initiative for Chronic Obstructive Lung Disease (GOLD): Global Strategy for the Diagnosis, Management, and Prevention of COPD 2023. www.goldcopd.org (last accessed on February 20, 2024).

13. Daniel RA, Aggarwal P, Kalaivani M, et al. Prevalence of chronic obstructive pulmonary disease in India: a systematic review and meta-analysis. Lung India 2021;38(6):506–513. DOI: 10.4103/lungindia.lungindia_159_21

14. Sinha B, Vibha, Singla R, et al. An epidemiological profile of chronic obstructive pulmonary disease: a community–based study in Delhi. J Postgrad Med 2017;63(1):29–35. DOI: 10.4103/0022-3859.194200

15. Kostikas K, Clemens A, Patalano F. Prediction and prevention of exacerbations and mortality in patients with COPD. Expert Rev Resp Med 2016;10(7):739–753. DOI: 10.1080/17476348.2016.1185371

16. Li M, Wang F, Chen R, et al. Factors contributing to hospitalization costs for patients with COPD in China: a retrospective analysis of medical record data. Int J Chron Obstruct Pulmon Dis 2018;13:3349–3357. DOI: 10.2147/COPD.S175143

17. Agboado G, Peters J, Donkin L, et al. Factors influencing the length of hospital stay among patients resident in blackpool admitted with COPD: a cross-sectional study. BMJ Open 2012;2(5):e000869. DOI: 10.1136/bmjopen-2012-000869

18. García-Sanz MT, González-Barcala FJ, Cánive-Gómez JC, et al. Prolonged stay predictors in patients admitted with chronic obstructive pulmonary disease acute exacerbation. Lung India 2018;35(4):316–320. DOI: 10.4103/lungindia.lungindia_469_17

19. Perera PN, Armstrong EP, Sherrill DL, et al. Acute exacerbations of COPD in the United States: inpatient burden and predictors of costs and mortality. Chronic Obstr Pulm Dis 2012;9(2):131–141. DOI: 10.3109/15412555.2011.650239

20. Ruparel M, López-Campos JL, Castro-Acosta A, et al. Understanding variation in the length of hospital stay for COPD exacerbation: European COPD audit. ERJ Open Res 2016;2(1):00034–2015. DOI: 10.1183/23120541.00034-2015

21. Connolly MJ, Lowe D, Anstey K, et al. Admissions to hospital with exacerbations of chronic obstructive pulmonary disease: effect of age-related factors and service organization. Thorax 2006;61(10):843–848. DOI: 10.1136/thx.2005.054924

22. George PM, Stone RA, Buckingham RJ, et al. Changes in NHS organization of care and management of hospital admissions with COPD exacerbations between the national COPD audits of 2003 and 2008. QJM 2011;104(10):859–866. DOI: 10.1093/qjmed/hcr083

23. Crisafulli E, Ielpo A, Barbeta E, et al. Clinical variables predicting the risk of a hospital stay for longer than 7 days in patients with severe acute exacerbations of chronic obstructive pulmonary disease: a prospective study. Respir Res 2018;19(1):261. DOI: 10.1186/s12931-018-0951-4

24. Wang Y, Stavem K, Dahl FA, et al. Factors associated with a prolonged length of stay after acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Int J Chron Obstruct Pulmon Dis 2014;9:99–105. DOI: 10.2147/COPD.S51467

25. Lüthi-Corridori G, Boesing M, Ottensarendt, N, et al. Predictors of length of stay, mortality and rehospitalization in COPD patients: a retrospective cohort study. J Clin Med 2023;12(16):5322. DOI: 10.3390/jcm12165322

26. Li M, Cheng K, Ku K, et al. Factors influencing the length of hospital stay among patients with chronic obstructive pulmonary disease (COPD) in Macao population: a retrospective study of in-patient health record. Int J Chronic Obstr Pulm Dis 2021;16:1677–1685. DOI: 10.2147/COPD.S307164

27. Alqahtani JS, Njoku CM, Bereznicki B, et al. Risk factors for all-cause hospital readmission following exacerbation of COPD: a systematic review and meta-analysis. Eur Respir Rev 2020;29(156):190166. DOI: 10.1183/16000617.0166-2019

28. Kessler R, Faller M, Fourgaut G, et al. Predictive factors of hospitalization for acute exacerbation in a series of 64 patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med 1999;159(1):158–164. DOI: 10.1164/ajrccm.159.1.9803117

29. Jo YS, Kim YH, Lee JY, et al. Impact of BMI on exacerbation and medical care expenses in subjects with mild to moderate airflow obstruction. Int J Chron Obstruct Pulmon Dis 2018;13:2261–2269. DOI: 10.2147/COPD.S163000

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