Objective: Prognostic models aid clinical practice with decision-making on treatment and hospitalization in exacerbation of chronic obstructive lung disease (ECOPD). Although there are many studies with prognostic models, diagnostic accuracy is variable within and between models. Subjects and Methods: We compared the prognostic performance of the BAP65 score, DECAF score, PEARL score, and modified early warning score (MEWS) in hospitalized patients with ECOPD, to estimate ventilatory support need. Results: This cross-sectional study consisted of 139 patients. Patients in need of noninvasive or invasive mechanical ventilation support are grouped as ventilatory support groups (n = 54). Comparison between receiver operating characteristic curves revealed that the DECAF score is significantly superior to the PEARL score (p = 0.04) in discriminating patients in need of ventilatory support. DECAF score with a cutoff value of 1 presented the highest sensitivity and BAP65 score with a cutoff value of 2 presented the highest specificity in predicting ventilatory support need. Multivariable analysis revealed that gender played a significant role in COPD exacerbation outcome, and arterial pCO2 and RDW measurements were also predictors of ventilatory support need. Within severity indexes, only the DECAF score was independently associated with the outcome. One-point increase in DECAF score created a 1.43 times higher risk of ventilatory support need. All severity indexes showed a correlation with age, comorbidity index, and dyspnea. BAP65 and DECAF scores also showed a correlation with length of stay. Conclusion: Objective and practical classifications are needed by clinicians to assess prognosis and initiate treatment accordingly. DECAF score is a strong candidate among severity indexes.

Highlights of the Study

  • Objective and practical classifications are needed by clinicians in order to assess prognosis and initiate treatment accordingly in exacerbation of chronic obstructive lung disease.

  • DECAF score with a cutoff value of 1 presented the highest sensitivity and BAP65 score with a cutoff value of 2 presented the highest specificity in predicting the need for ventilatory support.

  • One-point increase in DECAF score created a 1.43 times higher risk of need for ventilatory support.

Exacerbation of chronic obstructive lung disease (ECOPD) is defined as episodes of acute respiratory symptom worsening in patients with COPD and is known to have a negative impact on health status, decline of lung function, and prognosis [1]. There is a distinctive variability in ECOPD outcomes between studies, ranging from 4.4% to 25% [2, 3]. This difference might be due to the variability in the available resources to treat patients and/or the criteria for hospitalization. Prognostic models can aid clinical practice with decision-making on treatment and hospitalization. Prognostic models have evaluated various endpoints in different settings, including patients with different disease severity and risk factors. Although there are many studies with prognostic models, diagnostic accuracy is variable between and within models [4]. BAP65 score, DECAF score, PEARL score, and modified early warning score (MEWS) are validated tools in ECOPD for predicting mortality. Although in-hospital mortality is frequently evaluated in ECOPD, severity scoring models and ventilation support need are not.

In this study, we aimed to compare the prognostic performance of severity scoring systems such as the BAP65 score, DECAF score, PEARL score, and MEWS in hospitalized patients with ECOPD in a tertiary care setting. We compared the predictive efficacy of these scores in estimating ventilatory support need (invasive or noninvasive mechanical ventilation) and aimed to identify one severity index with the highest accuracy in a clinical setting.

Study Population

Designed as a cross-sectional observational study based on a tertiary care pulmonary clinic, patients with acute ECOPD admitted to a non-intensive care unit (ICU) pulmonary ward were included consecutively in the study. COPD was defined according to GOLD criteria [1]. ECOPD was defined as an acute event characterized by a worsening of the patient’s respiratory symptoms beyond normal variation and leading to a change in medication. In line with the COPD definition, patients above 40 years of age were included. COPD patients with previous long-term noninvasive mechanical ventilation (NIV) treatment at home were excluded from the study. Patients with a waiting period in the emergency department for more than 72 h before admission or ICU admission before being admitted to the ward were also excluded from the study.

All patients received standard COPD exacerbation treatment including bronchodilators, intravenous antimicrobial therapy, and systemic corticosteroids as deemed necessary by the attending physician. Supplemental oxygen flow was adjusted to maintain oxygen saturation between 88 and 92% as needed. Respiratory support with NIV devices was considered if the patient was presented with acute respiratory failure leading to acute or acute-on-chronic respiratory acidosis or respiratory rate >24 breath/minute despite medical treatment [5]. Endotracheal intubation or intensive care unit transfer was considered in case of cardiac or respiratory arrest, decreased consciousness (Glasgow Coma Scale score ≤13), hemodynamic instability, discordance with NIV or oxygen saturation below 80% despite maximum oxygen supplementation, arterial pH<7.25 or pronounced increase in PaCO2 despite NIV treatment.

Measurements and Severity Scoring Systems

BAP65, DECAF, PEARL, and MEWS scores were calculated upon admission by the clinician. A structured form including risk factors, smoking status, disease history, and comorbid conditions was completed for each patient. Biochemical results and blood cell count upon admission were recorded. Prognostic scores and their components are summarized in Table 1.

Table 1.

Components of prognostic scores

DECAFPEARLBAP-65NEWSMEWS
Dyspnea eMRCD score eMRCD score 
Blood measurements Eosinophil count <0.05 × 109/L Urea nitrogen ≥25 mg/dL 
Chest X-ray Consolidation 
Blood gas analysis pH <7.30 Oxygen saturation 
Comorbidities Atrial fibrillation Right heart failure 
Left heart failure 
Age Age >80 Age >65 
Previous exacerbation Previous admission >2 
Vital signs and mental status Heart rate Systolic blood pressure Systolic blood pressure 
Heart rate Heart rate 
Respiratory rate Respiratory rate 
Altered mental status (GKS score) Temperature Temperature 
AVPU score AVPU score 
DECAFPEARLBAP-65NEWSMEWS
Dyspnea eMRCD score eMRCD score 
Blood measurements Eosinophil count <0.05 × 109/L Urea nitrogen ≥25 mg/dL 
Chest X-ray Consolidation 
Blood gas analysis pH <7.30 Oxygen saturation 
Comorbidities Atrial fibrillation Right heart failure 
Left heart failure 
Age Age >80 Age >65 
Previous exacerbation Previous admission >2 
Vital signs and mental status Heart rate Systolic blood pressure Systolic blood pressure 
Heart rate Heart rate 
Respiratory rate Respiratory rate 
Altered mental status (GKS score) Temperature Temperature 
AVPU score AVPU score 

The BAP65 score was developed by Tabak et al. [6] and studied in different settings. BAP65 score consists of serum BUN measurement, altered mental status, pulse, and age parameters. While Shor et al. validated the BAP65 score within hospitalized ECOPD patients [7]. Germini et al. were not able to achieve this in an emergency setting [8].

The DECAF score consists of an extended Modified Medical Research Council (eMRC) Dyspnea Scale, eosinopenia, consolidation, acidemia, and atrial fibrillation parameters and is derived from the predictors of mortality in hospitalized ECOPD patients [9]. DECAF score is validated in hospitalized patients for predicting in-hospital mortality, 30-day mortality [10], and 90-day all-cause mortality [11].

The PEARL score was developed and externally validated by Echevarria et al. to predict 90-day readmission or death after hospitalization for ECOPD [12]. PEARL prognostic score comprises previous admissions, eMRC score, age, right-sided heart failure, and left-sided heart failure.

The National Early Warning Score (NEWS) was developed with the aim to standardize clinical practice using physiological parameters. Numerous studies evaluated different versions of NEWS [13]. MEWS is validated in medical admissions [14] using systolic blood pressure, heart rate, respiratory rate, temperature, and AVPU score for consciousness.

Statistical Analysis

Statistical analysis was performed using IBM SPSS Statistics for Windows, version 22.0 software program (IBM Corp., Armonk, NY, USA) and MedCalc statistics. Variables were evaluated using histogram and analytical methods (Kolmogorov-Smirnov/Shapiro-Wilk test) to determine distribution. Continuous data are defined as the mean ± standard deviation or median (interquartile range) if normally distributed or non-normally distributed, respectively. Continuous outcome variables were compared by two-sample t test and by Mann-Whitney U test, according to the distribution of the variables. Categorical characteristics are defined as numbers and percentages (%). Comparisons between categorical variables between patient groups were made by ki square test. The ability of severity indexes to discriminate patients with respiratory support need during admission was analyzed using receiver operating characteristic curve analysis. Possible risk factors were evaluated by multivariable logistic regression analysis to determine independent predictors of patient clinical outcome. Hosmer-Lemeshow goodness of fit statistics were used to assess model fit. Values of p < 0.05 were considered statistically significant.

Hospitalized patients with a diagnosis of COPD exacerbation between June 2021 and September 2022 consisted of 178 patients. Among these patients, 39 (21.9%) had been using home noninvasive ventilation (NIV) support and were therefore excluded from the analysis. Our final study population had 139 patients; the most frequent symptoms upon admission were worsened dyspnea (98.6%) and increased cough (65.5%). Fifty-four (38.8%) patients used long-term oxygen supplement treatment at home and 109 (78.4%) patients were under inhaled corticosteroid treatment. Bacterial cultures revealed 16 (11.5%) Pseudomonas aeruginosa and 26 (18.7%) non-Pseudomonas aeruginosa growth in the study population. Clinical characteristics and laboratory measurements upon admission are presented in Table 2. Correlation within severity indexes is calculated as follows: BAP65 and DECAF (r = 0.316, p = 0.005), BAP65 and PEARL (r = 0.316, p < 0.001), BAP65 and modified news (r = 0.218, p = 0.01), and DECAF and PEARL (r = 0.312, p < 0.001). All severity indexes showed a positive correlation with age, Charlson comorbidity index, and dyspnea measured by eMRC. BAP65 and DECAF scores also showed a significant correlation with length of stay; r = 0.181, p = 0.03, and r = 0.275, p = 0.002, respectively.

Table 2.

Clinical characteristics and laboratory measurements upon admission (n = 139)

Age, years 68.1±8.9 
Male gender, n (%) 120 (86.3) 
Smoking status, n (%) 
 Current smoker 24 (17.3) 
 Ex-smoker 87 (62.6) 
 Never smoker 11 (7.9) 
Smoking, pack/year 50.0 [30.0–70.0] 
Comorbidities, n (%) 
 CAD 30 (21.6) 
 HT 51 (36.7) 
 AF 9 (6.5) 
 HF 26 (18.8) 
 DM 28 (20.1) 
 CVD 6 (4.3) 
 CRF 16 (11.5) 
 Bronchiectasis 7 (5.0) 
 Malignancy 12 (8.6) 
 OSA 3 (2.2) 
Charlson comorbidity index 2.0 [1.0–4.0] 
Duration of COPD diagnosis, years 7.0 [3.0–10.0] 
All ECOPD episodes in the last year 2.0 [1.0–3.0] 
 Hospitalization in the last year 1.0 [0.0–1.7] 
 ED visit in the last year 2.5 [1.0–4.0] 
Home LTOT, n (%) 54 (38.8) 
eMRC 3.0 [2.0–4.0] 
Laboratory measurements 
 White blood cell count, 109/L 9.15 [6.86–12.98] 
 Eosinophil count, 106/L 68.5 [13.0–194.2] 
 RDW 13.3 [12.0–15.0] 
 BNP, ng/L 82.0 [36.2–385.0] 
 Albumin, g/L 34.8±5.2 
Arterial blood gas analysis 
 pH 7.39±0.07 
 pO2, mm Hg 65.0 [50.4–82.7] 
 pCO2, mm Hg 47.0 [37.4–59.0] 
 HCO3, mmol/L 26.9 [24.0–30.8] 
CRP at admission, mg/L 13.4 [4.6–90.7] 
Procalcitonin at admission, µg/L 0.07 [0.03–0.23] 
Severity indexes 
 BAP 65 score 1.0 [1.0–2.0] 
  Class 1 20 (14.4) 
  Class 2 47 (33.8) 
  Class 3 34 (24.5) 
  Class 4 10 (7.2) 
  Class 5 1 (0.7) 
 PEARL score 2.0 [1.0–4.0] 
  Low risk, n (%) 52 (37.4) 
  Intermediate risk, n (%) 51 (36.7) 
  High risk, n (%) 20 (14.4) 
 DECAF score 1.0 [1.0–2.0] 
 MEWS score 1.0 [0.0–2.0] 
NIV support during hospitalization, n (%) 52 (37.4) 
IMV support, n (%) 7 (5.0) 
Length of stay, days 8.0 [6.0–12.0] 
In hospital mortality, n (%) 6 (4.3) 
Age, years 68.1±8.9 
Male gender, n (%) 120 (86.3) 
Smoking status, n (%) 
 Current smoker 24 (17.3) 
 Ex-smoker 87 (62.6) 
 Never smoker 11 (7.9) 
Smoking, pack/year 50.0 [30.0–70.0] 
Comorbidities, n (%) 
 CAD 30 (21.6) 
 HT 51 (36.7) 
 AF 9 (6.5) 
 HF 26 (18.8) 
 DM 28 (20.1) 
 CVD 6 (4.3) 
 CRF 16 (11.5) 
 Bronchiectasis 7 (5.0) 
 Malignancy 12 (8.6) 
 OSA 3 (2.2) 
Charlson comorbidity index 2.0 [1.0–4.0] 
Duration of COPD diagnosis, years 7.0 [3.0–10.0] 
All ECOPD episodes in the last year 2.0 [1.0–3.0] 
 Hospitalization in the last year 1.0 [0.0–1.7] 
 ED visit in the last year 2.5 [1.0–4.0] 
Home LTOT, n (%) 54 (38.8) 
eMRC 3.0 [2.0–4.0] 
Laboratory measurements 
 White blood cell count, 109/L 9.15 [6.86–12.98] 
 Eosinophil count, 106/L 68.5 [13.0–194.2] 
 RDW 13.3 [12.0–15.0] 
 BNP, ng/L 82.0 [36.2–385.0] 
 Albumin, g/L 34.8±5.2 
Arterial blood gas analysis 
 pH 7.39±0.07 
 pO2, mm Hg 65.0 [50.4–82.7] 
 pCO2, mm Hg 47.0 [37.4–59.0] 
 HCO3, mmol/L 26.9 [24.0–30.8] 
CRP at admission, mg/L 13.4 [4.6–90.7] 
Procalcitonin at admission, µg/L 0.07 [0.03–0.23] 
Severity indexes 
 BAP 65 score 1.0 [1.0–2.0] 
  Class 1 20 (14.4) 
  Class 2 47 (33.8) 
  Class 3 34 (24.5) 
  Class 4 10 (7.2) 
  Class 5 1 (0.7) 
 PEARL score 2.0 [1.0–4.0] 
  Low risk, n (%) 52 (37.4) 
  Intermediate risk, n (%) 51 (36.7) 
  High risk, n (%) 20 (14.4) 
 DECAF score 1.0 [1.0–2.0] 
 MEWS score 1.0 [0.0–2.0] 
NIV support during hospitalization, n (%) 52 (37.4) 
IMV support, n (%) 7 (5.0) 
Length of stay, days 8.0 [6.0–12.0] 
In hospital mortality, n (%) 6 (4.3) 

CAD, Coronary artery disease; HT, hypertension; AF, atrial fibrillation; DM, diabetes mellitus; CVD, cerebrovascular disease; CRF, chronic renal failure; OSA, obstructive sleep apnea; ECOPD, exacerbation of COPD; LTOT, long-term oxygen therapy; eMRC, extended Modified Medical Research Council Dyspnea Scale; RDW, red cell distribution width; BNP, B-type natriuretic peptide; CRP, C-reactive protein; NIV, noninvasive ventilation; IMV, invasive mechanical ventilation.

In order to evaluate the difference between severity index scores, patients were divided into two groups. Patients in need of NIV or invasive mechanical ventilation (IMV) support are grouped as ventilatory support groups (n = 54). The differences between patients with and without ventilatory support are presented in Table 3. Patients with ventilatory support needs were more frequently lethargic (20.3% vs. 1.1%, p < 0.001) upon admission. Patients with ventilatory support need had significantly higher dyspnea score, BAP65 score, DECAF score, and MEWS score. However, there is no difference in symptoms at admission, bacterial growth in cultures, CRP, and procalcitonin change on day 3 and day 6 between the two groups.

Table 3.

Comparison of patient groups according to the need for ventilatory support

NIV + IV support (n = 54)Without respiratory support need (n = 85)p value
Age, years 68.3±8.7 68.0±9.1 0.99 
Female gender, n (%) 15 (27.7) 4 (4.7) <0.001 
Smoking status, n (%) 0.09 
 Current smoker 8 (14.8) 16 (18.8)  
 Ex-smoker 32 (59.2) 55 (64.7)  
 Never smoker 8 (14.8) 3 (3.5)  
Smoking pack/year 45.0 [22.5–85.0] 50.0 [30.0–65.5] 0.24 
Comorbidities, n (%) 
 CAD 8 (14.8) 22 (25.8) 0.14 
 HT 25 (46.2) 26 (30.5) 0.07 
 AF 7 (12.9) 2 (2.3) 0.02 
 HF 11 (20.3) 15 (17.6) 0.66 
 DM 17 (31.4) 11 (12.9) 0.01 
 Bronchiectasis 3 (5.5) 4 (4.7) 0.99 
 Malignancy 5 (9.2) 7 (8.2) 0.99 
 OSA 3 (5.5) 0 (0.0) 0.05 
Charlson comorbidity index 2.0 [1.0–4.0] 2.0 [1.0–4.0] 0.99 
Duration of COPD diagnosis, years 7.0 [2.5–15.0] 6.5 [3.2–10.0] 0.93 
All ECOPD episodes in the last year 1.0 [0.0–4.0] 2.0 [1.0–3.0] 0.25 
 Hospitalization in the last year 1.0 [0.0–1.0] 1.0 [0.0–2.0] 0.30 
 ED visit in the last year 2.0 [0.0–4.0] 3.0 [1.0–4.0] 0.25 
Home LTOT, n (%) 22 (40.7) 32 (37.6) 0.72 
eMRC 4.0 [3.0–5.0] 3.0 [2.0–4.0] <0.001 
Laboratory measurements 
 White blood cell count, 109/L 9.07 [6.56–13.96] 9.41 [7.06–12.51] 0.97 
 Eosinophil count, 106/L 68.0 [17.0–158.5] 68.0 [9.0–227.0] 0.88 
 RDW 14.0 [12.9–16.0] 12.8 [11.6–14.0] <0.001 
 BNP, ng/L 129.0 [57.5–536.5] 69.0 [31.3–360.7] 0.15 
 Albumin, g/L 35.0 [32.2–39.0] 34.0 [31.0–38.0] 0.65 
Arterial blood gas analysis 
 pH 7.34±0.06 7.42±0.06 <0.001 
 pO2, mm Hg 68.3 [46.5–88.0] 64.8 [52.2–81.8] 0.79 
 pCO2, mm Hg 60.0 [55.8–66.5] 39.6 [35.0–46.9] <0.001 
 HCO3, mmol/L 30.0 [25.0–32.9] 26.0 [24.0–28.4] 0.002 
CRP at admission, mg/L 9.0 [4.8–77.0] 17.0 [4.1–96.5] 0.20 
Procalcitonin at admission, µg/L 0.07 [0.03–0.23] 0.07 [0.03–0.20] 0.71 
Severity indexes 
 BAP 65 score 2.0 [1.0–2.0] 1.0 [1.0–2.0] 0.04 
  Class 1, n (%) 8 (14.8) 12 (14.1) 0.03 
  Class 2, n (%) 14 (25.9) 33 (38.8) 
  Class 3, n (%) 16 (29.6) 18 (21.1) 
  Class 4, n (%) 7 (12.9) 3 (3.5) 
  Class 5, n (%) 1 (1.8) 0 (0.0) 
 PEARL score 2.0 [1.0–3.5] 2.0 [0.0–4.0] 0.53 
  Low risk, n (%) 19 (35.1) 33 (38.8) 0.22 
  Intermediate risk, n (%) 19 (35.1) 32 (37.6) 
  High risk, n (%) 11 (20.3) 9 (10.5) 
 DECAF score 2.0 [1.0–3.0] 1.0 [1.0–2.0] 0.001 
 MEWS 1.5±1.4 1.1±1.2 0.06 
Length of stay, days 8.0 [6.0–12.0] 8.0 [6.0–11.0] 0.41 
In-hospital mortality, n (%) 6 (11.1) 0 (0.0) 0.003 
NIV + IV support (n = 54)Without respiratory support need (n = 85)p value
Age, years 68.3±8.7 68.0±9.1 0.99 
Female gender, n (%) 15 (27.7) 4 (4.7) <0.001 
Smoking status, n (%) 0.09 
 Current smoker 8 (14.8) 16 (18.8)  
 Ex-smoker 32 (59.2) 55 (64.7)  
 Never smoker 8 (14.8) 3 (3.5)  
Smoking pack/year 45.0 [22.5–85.0] 50.0 [30.0–65.5] 0.24 
Comorbidities, n (%) 
 CAD 8 (14.8) 22 (25.8) 0.14 
 HT 25 (46.2) 26 (30.5) 0.07 
 AF 7 (12.9) 2 (2.3) 0.02 
 HF 11 (20.3) 15 (17.6) 0.66 
 DM 17 (31.4) 11 (12.9) 0.01 
 Bronchiectasis 3 (5.5) 4 (4.7) 0.99 
 Malignancy 5 (9.2) 7 (8.2) 0.99 
 OSA 3 (5.5) 0 (0.0) 0.05 
Charlson comorbidity index 2.0 [1.0–4.0] 2.0 [1.0–4.0] 0.99 
Duration of COPD diagnosis, years 7.0 [2.5–15.0] 6.5 [3.2–10.0] 0.93 
All ECOPD episodes in the last year 1.0 [0.0–4.0] 2.0 [1.0–3.0] 0.25 
 Hospitalization in the last year 1.0 [0.0–1.0] 1.0 [0.0–2.0] 0.30 
 ED visit in the last year 2.0 [0.0–4.0] 3.0 [1.0–4.0] 0.25 
Home LTOT, n (%) 22 (40.7) 32 (37.6) 0.72 
eMRC 4.0 [3.0–5.0] 3.0 [2.0–4.0] <0.001 
Laboratory measurements 
 White blood cell count, 109/L 9.07 [6.56–13.96] 9.41 [7.06–12.51] 0.97 
 Eosinophil count, 106/L 68.0 [17.0–158.5] 68.0 [9.0–227.0] 0.88 
 RDW 14.0 [12.9–16.0] 12.8 [11.6–14.0] <0.001 
 BNP, ng/L 129.0 [57.5–536.5] 69.0 [31.3–360.7] 0.15 
 Albumin, g/L 35.0 [32.2–39.0] 34.0 [31.0–38.0] 0.65 
Arterial blood gas analysis 
 pH 7.34±0.06 7.42±0.06 <0.001 
 pO2, mm Hg 68.3 [46.5–88.0] 64.8 [52.2–81.8] 0.79 
 pCO2, mm Hg 60.0 [55.8–66.5] 39.6 [35.0–46.9] <0.001 
 HCO3, mmol/L 30.0 [25.0–32.9] 26.0 [24.0–28.4] 0.002 
CRP at admission, mg/L 9.0 [4.8–77.0] 17.0 [4.1–96.5] 0.20 
Procalcitonin at admission, µg/L 0.07 [0.03–0.23] 0.07 [0.03–0.20] 0.71 
Severity indexes 
 BAP 65 score 2.0 [1.0–2.0] 1.0 [1.0–2.0] 0.04 
  Class 1, n (%) 8 (14.8) 12 (14.1) 0.03 
  Class 2, n (%) 14 (25.9) 33 (38.8) 
  Class 3, n (%) 16 (29.6) 18 (21.1) 
  Class 4, n (%) 7 (12.9) 3 (3.5) 
  Class 5, n (%) 1 (1.8) 0 (0.0) 
 PEARL score 2.0 [1.0–3.5] 2.0 [0.0–4.0] 0.53 
  Low risk, n (%) 19 (35.1) 33 (38.8) 0.22 
  Intermediate risk, n (%) 19 (35.1) 32 (37.6) 
  High risk, n (%) 11 (20.3) 9 (10.5) 
 DECAF score 2.0 [1.0–3.0] 1.0 [1.0–2.0] 0.001 
 MEWS 1.5±1.4 1.1±1.2 0.06 
Length of stay, days 8.0 [6.0–12.0] 8.0 [6.0–11.0] 0.41 
In-hospital mortality, n (%) 6 (11.1) 0 (0.0) 0.003 

CAD, coronary artery disease; HT, hypertension; AF, atrial fibrillation; DM, diabetes mellitus; CVD, cerebrovascular disease; CRF, chronic renal failure; OSA, obstructive sleep apnea; ECOPD, exacerbation of COPD; LTOT, long-term oxygen therapy; eMRC, extended Modified Medical Research Council Dyspnea Scale; RDW, red cell distribution width; BNP, B-type natriuretic peptide; CRP, C reactive protein; NIV, noninvasive ventilation; IMV, invasive mechanical ventilation.

Comparison between receiver operating characteristic curves (Fig. 1) revealed that the DECAF score is significantly superior to the PEARL score (p = 0.04) in discriminating patients in need of ventilatory support. However, there are no other statistically significant differences between diagnostic performance of severity indexes, in pairwise comparisons. Diagnostic performances of different severity indexes for discriminating patients with ventilatory support need are presented in Table 4. Within severity indexes, the DECAF score with a cutoff value of 1 presented the highest sensitivity and the BAP65 score with a cutoff value of 2 presented the highest specificity.

Fig. 1.

Comparison between ROC curves of severity scores. ROC, receiver operating characteristic.

Fig. 1.

Comparison between ROC curves of severity scores. ROC, receiver operating characteristic.

Close modal
Table 4.

Diagnostic performance of severity indexes with selected cutoff values

Cutoff valueSensitivitySpecificityNPVPPV
BAP65 
 >1 58.4 [44.1–71.9] 59.0 [47.7–69.7] 69.0 [60.7–76.3] 47.7 [39,3–56,3] 
 >2 18.8 [9.4–32.0] 92.7 [84.9–97.3] 64.2 [60.8–67.4] 62.5 [39.2–81.2] 
DECAF 
 >1 68.6 [54.1–80.9] 64.5 [53.0–75.0] 76.1 [67.3–83.2] 55.6 [46.8–64.0] 
 >2 27.4 [15.9–41.7] 88.6 [79.5–94.7] 65.4 [61.1–69.5] 60.9 [42.1–76.9] 
PEARL 
 >1 57.1 [42.2–71.2] 44.5 [3.0–56.6] 61.1 [51.0–70.3] 40.6 [33.2–48.4] 
 >2 40.8 [27.0–55.8] 56.7 [44.7–68.2] 59.2 [51.6–56.3] 38.5 [29.0–48.9] 
 >3 24.4 [13.3–38.9] 74.3 [62.8–83.8] 59.8 [54.7–64.7] 38.7 [25.2–54.2] 
MEWS 
 >1 44.2 [30.5–58.7] 69.5 [58.4–79.2] 66.3 [59.7–72.3] 47.9 [37.0–59.0] 
 >2 21.1 [11.1–34.7] 82.9 [73.0–90.3] 62.4 [58.3–66.3] 44.0 [27.9–61.5] 
Cutoff valueSensitivitySpecificityNPVPPV
BAP65 
 >1 58.4 [44.1–71.9] 59.0 [47.7–69.7] 69.0 [60.7–76.3] 47.7 [39,3–56,3] 
 >2 18.8 [9.4–32.0] 92.7 [84.9–97.3] 64.2 [60.8–67.4] 62.5 [39.2–81.2] 
DECAF 
 >1 68.6 [54.1–80.9] 64.5 [53.0–75.0] 76.1 [67.3–83.2] 55.6 [46.8–64.0] 
 >2 27.4 [15.9–41.7] 88.6 [79.5–94.7] 65.4 [61.1–69.5] 60.9 [42.1–76.9] 
PEARL 
 >1 57.1 [42.2–71.2] 44.5 [3.0–56.6] 61.1 [51.0–70.3] 40.6 [33.2–48.4] 
 >2 40.8 [27.0–55.8] 56.7 [44.7–68.2] 59.2 [51.6–56.3] 38.5 [29.0–48.9] 
 >3 24.4 [13.3–38.9] 74.3 [62.8–83.8] 59.8 [54.7–64.7] 38.7 [25.2–54.2] 
MEWS 
 >1 44.2 [30.5–58.7] 69.5 [58.4–79.2] 66.3 [59.7–72.3] 47.9 [37.0–59.0] 
 >2 21.1 [11.1–34.7] 82.9 [73.0–90.3] 62.4 [58.3–66.3] 44.0 [27.9–61.5] 

Multivariable analysis revealed that gender played a significant role in COPD exacerbation outcome, and arterial pCO2 and RDW measurements were also predictors of ventilatory support need (online suppl. Table 1; for all online suppl. material, see https://doi.org/10.1159/000538812). Within severity indexes, only the DECAF score was independently associated with the outcome. One-point increase in DECAF score created a 1.43 times higher risk of ventilatory support need (Table 5).

Table 5.

Multivariate analysis

VariablesModel 1Model 2Model 3Model 4
p valueORp valueORp valueORp valueOR
Gender 0.04 0.12 [0.01–0.90] 0.02 0.21[0.05–0.83] 0.04 0.09 [0.01–0.90] 0.03 0.98 [0.01–0.82] 
HT 0.95 1.03 [0.31–3.35] 0.27 1.63 [0.67–3.96] 0.48 1.54 [0.45–5.19] 0.43 1.58 [0.50–5.00] 
DM 0.61 1.47 [0.32–6.66] 0.84 1.12 [0.34–3.66] 0.66 1.41 [0.29–6.93] 0.66 1.41 [0.29–6.73] 
pCO2 <0.001 1.15 [1.09–1.20] <0.001 1.16 [1.10–1.23] <0.001 1.16 [1.10–1.23] 
RDW 0.25 1.13 [0.90–1.42] 0.03 1.20 [1.01–1.44] 0.22 1.16 [0.90–1.49] 0.20 1.16 
BAP65 0.37 1.29 [0.73–2.25] 
PEARL 0.77 1.04 [0.75–1.45] 
DECAF 0.04 1.43 [1.01–2.01] 
MEWS 0.21 1.26 [0.87–1.83] 
VariablesModel 1Model 2Model 3Model 4
p valueORp valueORp valueORp valueOR
Gender 0.04 0.12 [0.01–0.90] 0.02 0.21[0.05–0.83] 0.04 0.09 [0.01–0.90] 0.03 0.98 [0.01–0.82] 
HT 0.95 1.03 [0.31–3.35] 0.27 1.63 [0.67–3.96] 0.48 1.54 [0.45–5.19] 0.43 1.58 [0.50–5.00] 
DM 0.61 1.47 [0.32–6.66] 0.84 1.12 [0.34–3.66] 0.66 1.41 [0.29–6.93] 0.66 1.41 [0.29–6.73] 
pCO2 <0.001 1.15 [1.09–1.20] <0.001 1.16 [1.10–1.23] <0.001 1.16 [1.10–1.23] 
RDW 0.25 1.13 [0.90–1.42] 0.03 1.20 [1.01–1.44] 0.22 1.16 [0.90–1.49] 0.20 1.16 
BAP65 0.37 1.29 [0.73–2.25] 
PEARL 0.77 1.04 [0.75–1.45] 
DECAF 0.04 1.43 [1.01–2.01] 
MEWS 0.21 1.26 [0.87–1.83] 

Model 1: gender, HT, DM, RDW, pCO2, BAP65 score; model 2: gender, HT, DM, RDW, DECAF score; model 3: gender, HT, DM, RDW, pCO2, PEARL score; model 4: gender, HT, DM, RDW, pCO2, MEWS.

Knowledge of the likelihood of complications in ECOPD is vital for clinicians to make management decisions. In our study population, patients with ventilatory support need had significantly higher dyspnea scores, BAP65 scores, DECAF scores, and MEWS scores. Within severity indexes, the calculated highest sensitivity is from the DECAF score and the highest specificity is from the BAP65 score. However, in multivariable analysis, only the DECAF score is a predictor of ventilatory support need in hospitalized ECOPD patients.

Clinicians choose predictive indexes according to their needs in their clinical setting. Sensitivity represents the proportion of patients who needed respiratory support that was identified as at risk by having higher values than the threshold in the scoring system. On the other hand, specificity represents the proportion of patients who did not need respiratory support that were identified as not at risk. In a population with high risk, a prediction score with high specificity and positive predictive value is preferable while in a population with a low-risk, high sensitivity and negative predictive value is desired. The use of clinical prognostic tools in the UK for the management of COPD significantly increased between 2017 and 2019, 43.7% versus 52.1%, respectively [15]. DECAF and PEARL scores are used for admission avoidance, early discharge, and hospital-at-home (HAH) decisions. However, severity indexes are not routinely used to guide NIV treatment [15].

Comparison between severity scores in predicting adverse outcomes, especially mortality, is present in recent literature. Echevarria et al. compared the adjusted NEWS2 score to the DECAF score for predicting in-hospital mortality in hospitalized 2645 COPD exacerbation patients. DECAF score was superior to NEWS and adjusted NEWS2 score in the prediction of mortality and a good scoring system to choose patients eligible for early discharge [16]. HAH services in the UK include visits from a respiratory specialist nurse and home treatment in patients with low mortality risk. In another study, Echevarria et al. presented that ECOPD patients with a DECAF score of 0 or 1 can be treated at HAH with better anxiety control and symptom control without a change in death and readmissions [17]. These studies indicated that the DECAF score can be used as a clinical decision tool for admission and at-home treatment without adverse outcomes [16, 17].

Apart from the hospital setting, the DECAF score is also useful with 74.8% specificity in the emergency setting for predicting composite poor outcome (30-day mortality, mechanical ventilation, readmission, hospitalization for longer than 14 days) [18]. Unal et al. [18] showed there is no statistically significant difference between the DECAF score and the Ottawa COPD risk scale in emergency settings for discriminating short-term outcomes. This study pointed out that the DECAF score alone is insufficient for the decision of discharge from the emergency department but might still be useful for guidance.

Gayaf et al. [19] included 141 hospitalized ECOPD patients and compared DECAF, BAP65, CURB-65, and PSI scores in predicting 30-day and 90-day mortality. All of the severity indexes were higher in deceased patients. However, no statistical difference was found between severity indexes in terms of prognostic accuracy. In multivariate analysis for mortality, only CURB-65 presented a weak effect on mortality [19]. Shafuddin et al. [20] compared BAP65, CURB-65, and DECAF scores in predicting in-hospital and 30-day mortality within patients admitted due to COPD exacerbation without consolidation. While all the scores were correlated with mortality, prognostic performance was statistically similar between severity indexes [20]. The lack of difference might be related to the inclusion of patients without consolidation in chest imaging, and this result is an indicator that consolidation is a critically important component of the DECAF score. Most of the studies including severity scoring systems identified in-hospital mortality as a primary outcome, while to the best of our knowledge, only two studies evaluated the DECAF score and two studies evaluated the BAP65 score for predicting the need for NIV or IMV [8, 21, 22].

Gemini et al. evaluated the BAP65 score in an emergency setting to discriminate ECOPD patients who will need IMV and calculated area under curve (AUC) of 0.61 which is a result similar to our study [8]. Shorr et al. calculated the AUC for the BAP65 score as 0.81 in predicting mechanical ventilation within 34,478 ECOPD patients [22]. Son et al. [23] showed DECAF score has excellent discrimination in an emergency setting for ICU admission, need for mechanical ventilation, and in-hospital mortality. In addition, in contrast to our results, the DECAF score had better AUC values compared to BAP65 and CURB-65 scores [23].

Strengths and Limitations

A strength of this study is our comparison of BAP65, DECAF, PEARL, and MEWS scores in the same population. Our study is one of the few studies evaluating the prognostic accuracy of severity indexes in predicting ventilatory support need although these indexes are designed to predict mortality outcome. Due to the selection of hospitalized patients, we could not interpret the prognostic value of these scores in an emergency setting to aid clinical decisions such as admission, discharge, and HAH treatment. In addition, by excluding patients using long-term NIV support, we might have excluded patients with acute-on-chronic respiratory failure. Our study has moderate generalizability as it was a single-center study.

Our study showed that the DECAF score is independently associated with respiratory support need and that a one-point increase in DECAF score created a 1.43 times higher risk of ventilatory support need. These results can be used as a guide to stratify patients according to the risk of respiratory support need and aid in deciding admission to the hospital or ICU.

Approval from the Institutional Ethical Committee of Bursa Uludag University Faculty of Medicine was obtained (No: 2021-5/26). Informed consent is obtained from participants.

The authors have no conflicts of interest to disclose.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

All authors made substantial contributions to the conception and design of the work. All authors reviewed the draft and approved the final version of the manuscript. Nilüfer Aylin Acet-Öztürk is the principal investigator and takes primary responsibility for communication.

Data are available upon reasonable request.

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