Abstract
Aims
Both hypercapnia and hypocapnia are common in patients with acute heart failure (AHF), but the association between partial pressure of arterial carbon dioxide (PaCO2) and AHF prognosis remains unclear. The objective of this study was to investigate the connection between PaCO2 within 24 h after admission to the intensive care unit (ICU) and mortality during hospitalization and at 1 year in AHF patients.
Methods and results
AHF patients were enrolled from the Medical Information Mart for Intensive Care IV database. The patients were divided into three groups by PaCO2 values of <35, 35–45, and >45 mmHg. The primary outcome was to investigate the connection between PaCO2 and in‐hospital mortality and 1 year mortality in AHF patients. The secondary outcome was to assess the prediction value of PaCO2 in predicting in‐hospital mortality and 1 year mortality in AHF patients. A total of 2374 patients were included in this study, including 457 patients in the PaCO2 < 35 mmHg group, 1072 patients in the PaCO2 = 35–45 mmHg group, and 845 patients in the PaCO2 > 45 mmHg group. The in‐hospital mortality was 19.5%, and the 1 year mortality was 23.9% in the PaCO2 < 35 mmHg group. Multivariate logistic regression analysis showed that the PaCO2 < 35 mmHg group was associated with an increased risk of in‐hospital mortality [hazard ratio (HR) 1.398, 95% confidence interval (CI) 1.039–1.882, P = 0.027] and 1 year mortality (HR 1.327, 95% CI 1.020–1.728, P = 0.035) than the PaCO2 = 35–45 mmHg group. The PaCO2 > 45 mmHg group was associated with an increased risk of in‐hospital mortality (HR 1.387, 95% CI 1.050–1.832, P = 0.021); the 1 year mortality showed no significant difference (HR 1.286, 95% CI 0.995–1.662, P = 0.055) compared with the PaCO2 = 35–45 mmHg group. The Kaplan–Meier survival curves showed that the PaCO2 < 35 mmHg group had a significantly lower 1 year survival rate. The area under the receiver operating characteristic curve for predicting in‐hospital mortality was 0.591 (95% CI 0.526–0.656), and the 1 year mortality was 0.566 (95% CI 0.505–0.627) in the PaCO2 < 35 mmHg group.
Conclusions
In AHF patients, hypocapnia within 24 h after admission to the ICU was associated with increased in‐hospital mortality and 1 year mortality. However, the increase in 1 year mortality may be influenced by hospitalization mortality. Hypercapnia was associated with increased in‐hospital mortality.
Keywords: Acute heart failure, Arterial blood gas, Partial pressure of arterial carbon dioxide, Medical Information Mart for Intensive Care IV
Introduction
Acute heart failure (AHF) is a common and life‐threatening medical condition that requires urgent evaluation and management, with an overall in‐hospital mortality of 4–10% and 1 year mortality of 25–30%. 1 , 2 Dyspnoea is a fundamental clinical sign in AHF patients due to decreased cardiac output and pulmonary oedema, which leads to inadequate ventilation and reduced tissue perfusion, resulting in acid–base disturbances. 3 , 4 , 5 , 6 In AHF patients, the level of partial pressure of arterial carbon dioxide (PaCO2) is an important reference for clinical diagnosis and treatment to distinguish the type of respiratory failure and to explore the pathogenesis of dyspnoea. Evidence suggests that one‐third of AHF patients present with hypercapnia, and another third present with hypocapnia. 7
Hypercapnia, which is defined as PaCO2 > 45 mmHg, is a hallmark of respiratory failure and is associated with poor prognosis in a variety of diseases, including AHF. 8 , 9 It was shown that hypercapnia was associated with higher acute care unit admission rates. 10 Hypocapnia (PaCO2 < 35 mmHg) was significantly correlated with the mortality of patients after cardiac arrest and linked to poor prognosis in patients with traumatic brain injury. 2 A recent study showed that hypocapnia was an independent predictor of in‐hospital mortality in AHF patients, but this study did not examine the effect of hypocapnia on long‐term mortality. 11 The objective of this study was to investigate the association between PaCO2 within 24 h after admission to the intensive care unit (ICU) and mortality during hospitalization and 1 year in AHF patients.
Methods
Data source
Data from this retrospective observational study were extracted from a public medical database called the Medical Information Mart for Intensive Care IV (MIMIC‐IV) database. The construction of the database was approved by the Institutional Review Committee of Beth Israel Deaconess Medical Center and Massachusetts Institute of Technology. Due to the continuity, integrity, and reliability of its records, it has been widely used to study clinical problems in recent years. 12 , 13 , 14 Permission was obtained to use the database after online training at the National Institutes of Health (Record ID 36622864). The database contains all the information of each patient hospitalized, including basic vital signs, drugs used, laboratory examinations, notes recorded by medical staff, quantity of fluid, diagnostic code of the International Classification of Diseases, image report, length of stay, follow‐up, and survival data of patients. The requirement for individual patient consent was waived because the study did not impact clinical care, and all protected health information was deidentified.
Study population
Patients admitted to the ICU from 2008 to 2019 were identified in the MIMIC‐IV database. Patients diagnosed with AHF were selected according to the ninth edition of the International Classification of Diseases‐9 (ICD‐9), including 42 821, 42 823, 42 831, 42 833, 42 841, and 42 843. We screened patients who were over 18 years old and had entered the ICU for the first time. Patients who stayed in the ICU for <24 h and who lacked PaCO2 data within 24 h after entering the ICU were excluded.
Data extraction
Structured query language (SQL) with PostgreSQL (Version 14) was applied to extract the following data from the MIMIC‐IV database (if there were multiple records, the average value was taken). Demographic characteristics and comorbidities included age, gender, ethnicity, weight, hypertension, coronary heart disease, diabetes, atrial fibrillation, pneumonia, chronic obstructive pulmonary disease (COPD), prior heart failure history, cardiogenic shock, congestive heart failure (CHF), and acute myocardial infarction (AMI). Laboratory examination indicators included PaCO2, potassium, sodium, chlorine, calcium, blood urea nitrogen (BUN), blood creatinine, pH, N‐terminal pro‐brain natriuretic peptide (NT‐proBNP), blood glucose, and blood lactic acid. Vital signs and other indicators include mean arterial pressure (MAP), heart rate, respiratory rate (RR), arterial oxyhaemoglobin saturation (SpO2), body temperature, and oxygenation index. Treatment included vasopressors, mechanical ventilation, continuous renal replacement therapy (CRRT), dialysis, chlorthalidone, furosemide, torsemide, digoxin, nitroprusside, nitroglycerin, and nitrates. The disease severity scores include Sequential Organ Failure Assessment (SOFA), Simplified Acute Physiology Score II (SAPSII), and the Glasgow Coma Scale (GCS). All laboratory data were extracted from the data generated within the first 24 h after the patient entered the ICU. The endpoints of our study were in‐hospital mortality and 1 year mortality. In‐hospital mortality was defined as survival status at hospital discharge; it was determined by the time of death as recorded in the database ≤ the time of discharge. The 1 year mortality was defined as survival status at 1 year after admission to the hospital; it was determined by the time of death recorded in the database ≤ the time of 1 year after admission to the hospital. In addition, the 1 year mortality for hospitalized survivors was defined as the survival status of hospitalized survivors at 1 year after admission to the hospital; it was determined by the time of death of the hospitalized survivors ≤ the time of 1 year after admission to the hospital.
Patients were divided into three groups according to PaCO2 values of <35, 35–45, and >45 mmHg. Hypercapnia and hypocapnia were defined as PaCO2 > 45 mmHg and PaCO2 < 35 mmHg, respectively.
Outcomes
The primary outcome was to investigate the connection between PaCO2 and in‐hospital mortality and 1 year mortality in AHF patients. The secondary outcome was to assess the predictive value of PaCO2 in predicting in‐hospital mortality and 1 year mortality in AHF patients.
Statistical analysis
Categorical variables are expressed as frequencies and percentages and were compared by χ 2 tests or Fisher's exact tests. Normally distributed continuous variables are expressed as the means ± standard deviations (SDs) and were compared by one‐way ANOVA. Non‐normally distributed continuous variables were expressed by medians with inter‐quartile ranges (IQRs) and compared using the Kruskal–Wallis test. The difference in mortality among the three groups was analysed by the χ 2 test. Multiple interpolation was used to estimate and fill in the missing data. Variables with >20% of missing data were excluded. 15 Lactate was converted to a dummy variable in the model to avoid possible bias caused by the filled missing values. All the time records from the extracted data were converted to a common time format. The association between PaCO2 levels and in‐hospital and 1 year mortality was assessed using the Cox proportional hazards regression model. Kaplan–Meier analysis was used to plot the cumulative survival curves of the AHF patients in different groups. The log‐rank test was used to analyse the significant differences among the three groups. The discrimination of PaCO2 for in‐hospital mortality and 1 year mortality was assessed by receiver operating characteristic (ROC) curve analysis. The area under the ROC curve (AUC) usually ranges from 0.5 to 1, with 0.5 indicating no discrimination and 1 indicating perfect discrimination. 16 Statistical analyses were completed using IBM SPSS Statistics software (Version 26.0, IBM Corp., Armonk, NY, USA) and STATA software (Version 16.0, StataCorp LLC, College Station, TX, USA). P < 0.05 was considered statistically significant.
Results
A total of 524 520 patients admitted to the ICU from 2008 to 2019 in the MIMIC‐IV database were selected (Figure 1 ), of whom 61 628 aged <18 years and 449 086 diagnosed with non‐AHF were excluded. A total of 13 806 patients were diagnosed with AHF, of whom 9896 patients were admitted to the ICU for <24 h and 1536 patients with missing PaCO2 data were excluded. Finally, 2374 patients were enrolled in this study, including 2043 survivors and 331 non‐survivors. Of the 2374 patients, 457 were in the PaCO2 < 35 mmHg group, 1072 were in the PaCO2 = 35–45 mmHg group, and 845 were in the PaCO2 > 45 mmHg group. Details of the missing data are shown in Supporting Information, Table S1 .
Figure 1.
Flow chart of the distribution of patients in the Medical Information Mart for Intensive Care IV (MIMIC‐IV) database and inclusion and exclusion criteria of patients. AHF, acute heart failure; ICD‐9, International Classification of Diseases‐9; ICU, intensive care unit; PaCO2, partial pressure of arterial carbon dioxide.
Baseline characteristics of the study population
The demographic characteristics, treatment, comorbidities, severity scores, and biochemical indicators are shown in Table 1 . The median age was 76.1 (62.9–85.1) years in the PaCO2 < 35 mmHg group; there was no significant difference among the three groups (P = 0.577), and 1163 (49%) patients were female. Most of the study population was White [1675 (70.6%)]. In the PaCO2 < 35 mmHg group, patients had lower body weight and PaCO2 [31.0 (28.0–33.0), 40.0 (37.0–42.0), and 53.0 (48.5–63.0)] and higher RR and heart rate compared with the other two groups (P < 0.001). The SpO2 and SAPSII scores in the PaCO2 < 35 mmHg group were higher than those in the PaCO2 > 45 mmHg group. The PaCO2 > 45 mmHg group had lower vasopressor (3.4% vs. 6.1%, P = 0.03), nitroprusside (2.1% vs. 4.1%, P = 0.045), and nitroglycerin use than the PaCO2 = 35–45 mmHg group (45.3% vs. 57.1%, P < 0.001). The mechanical ventilation ratio in the PaCO2 < 35 mmHg group was lower than that in the other two groups (32.4% vs. 53.9% vs. 51.1%, P < 0.001). Patients in the PaCO2 < 35 mmHg group had a lower incidence of diabetes mellitus (35.4% vs. 44.4%, P < 0.001) and coronary heart disease (40.0% vs. 48.7%, P < 0.001) than those in the PaCO2 = 35–45 mmHg group. The percentages of patients with COPD (5.3% vs. 24.3%, P < 0.001), prior heart failure (69.1% vs. 79.1%, P < 0.001), and CHF (96.7% vs. 98.7%, P = 0.04) in the PaCO2 < 35 mmHg group were significantly lower than those in the PaCO2 > 45 mmHg group. The percentages of patients with cardiogenic shock (23% vs. 11%, P < 0.001) and AMI (3.9% vs. 0.9%, P = 0.001) in the PaCO2 < 35 mmHg group were higher than those in the PaCO2 > 45 mmHg group. Creatinine in the PaCO2 < 35 mmHg group was higher than that in the PaCO2 = 35–45 mmHg group (P < 0.001). BUN in the PaCO2 < 35 mmHg group was higher than that in the other two groups (P < 0.001). The PaCO2 < 35 mmHg group had lower sodium, potassium, and calcium levels than the PaCO2 > 45 mmHg group (P < 0.001). The rate of lactate ≥1.6 mmol/L was higher in the PaCO2 < 35 mmHg group than in the PaCO2 > 45 mmHg group (50.5% vs. 29.9%, P < 0.001). The other variables had no significant differences.
Table 1.
Baseline characteristics of the study population
| Characteristics | Total (n = 2374) | PaCO2 (mmHg) | P value | ||
|---|---|---|---|---|---|
| <35 (n = 457) | 35–45 (n = 1072) | >45 (n = 845) | |||
| Age (years) | 74.9 (64.5–83.8) | 76.1 (62.9–85.1) | 74.8 (64.6–83.5) | 74.3 (64.5–83.6) | 0.577 |
| Female, n (%) | 1163 (49.0) | 220 (48.1) | 497 (46.4) | 446 (52.8)* | 0.019 |
| Ethnicity, n (%) | 0.009 | ||||
| White | 1675 (70.6) | 319 (69.8) | 769 (71.7) | 587 (69.5) | |
| Black | 254 (10.7) | 53 (11.6) | 89 (8.3) | 112 (13.3)* | |
| Other | 445 (18.7) | 85 (18.6) | 214 (20.0) | 146 (17.3) | |
| Weight (kg) | 81.6 (67.6–91.0) | 75.8 (65.0–88.0)* , ** | 80.7 (67.4–96.2) | 85.7 (70.0–106.0)* | <0.001 |
| MAP (mmHg) | 75.0 ± 9.7 | 75.1 ± 9.6 | 75.2 ± 9.6 | 74.6 ± 9.9 | 0.419 |
| Heart rate (b.p.m.) | 85.4 ± 15.7 | 87.9 ± 17.9* , ** | 85.2 ± 15.2 | 84.3 ± 15.0 | <0.001 |
| RR (b.p.m.) | 20.4 ± 4.0 | 21.5 ± 4.4* , ** | 20.0 ± 3.9 | 20.5 ± 3.9* | <0.001 |
| Temperature (°C) | 36.8 ± 0.6 | 36.8 ± 0.6 | 36.8 ± 0.6 | 36.8 ± 0.6 | 0.428 |
| SpO2 (%) | 96.9 (95.2–98.2) | 96.9 (95.3–98.2)* , ** | 97.3 (95.8–98.6) | 96.1 (94.5–97.8)* | <0.001 |
| PaCO2 (mmHg) | 41.5 (36.0–49.0) | 31.0 (28.0–33.0)* , ** | 40.0 (37.0–42.0) | 53.0 (48.5–63.0)* | <0.001 |
| Scoring systems | |||||
| SOFA | 6.0 (4.0–9.0) | 6.0 (4.0–9.0) | 6.0 (4.0–9.0) | 6.0 (4.0–8.0) | 0.30 |
| SAPSII | 40.0 (32.0–50.0) | 41.0 (33.0–51.0) ** | 40.0 (32.0–50.0) | 39.0 (32.0–49.0) | 0.049 |
| GCS | 15.0 (15.0–15.0) | 15.0 (15.0–15.0) | 15.0 (15.0–15.0) | 15.0 (15.0–15.0) | 0.238 |
| Treatment | |||||
| Vasopressor, n (%) | 117 (4.9) | 23 (5.0) | 65 (6.1) | 29 (3.4)* | 0.03 |
| Ventilation, n (%) | 1149 (48.4) | 148 (32.4)* , ** | 578 (53.9) | 423 (51.1) | <0.001 |
| CRRT, n (%) | 138 (5.8) | 25 (5.5) | 72 (6.7) | 41 (4.9) | 0.210 |
| Dialysis, n (%) | 72 (3.0) | 12 (2.6) | 35 (3.3) | 25 (3.0) | 0.791 |
| Chlorthalidone, n (%) | 28 (1.2) | 2 (0.4) | 17 (1.6) | 9 (1.1) | 0.152 |
| Furosemide, n (%) | 2257 (95.1) | 432 (94.5) | 1020 (95.2) | 805 (95.3) | 0.832 |
| Torsemide, n (%) | 577 (24.3) | 105 (23.0) | 257 (24.0) | 215 (25.4) | 0.577 |
| Digoxin, n (%) | 418 (17.6) | 81 (17.7) | 180 (16.8) | 157 (18.6) | 0.592 |
| Nitroprusside, n (%) | 80 (3.4) | 18 (3.9) | 44 (4.1) | 18 (2.1)* | 0.045 |
| Nitroglycerin, n (%) | 1206 (50.8) | 211 (46.2)* | 612 (57.1) | 383 (45.3)* | <0.001 |
| Nitrates, n (%) | 516 (21.7) | 90 (19.7) | 234 (21.8) | 192 (22.7) | 0.447 |
| Comorbidities | |||||
| Atrial fibrillation, n (%) | 1137 (47.9) | 207 (45.3) | 528 (49.3) | 402 (47.6) | 0.356 |
| Hypertension, n (%) | 1018 (42.9) | 178 (38.9) | 486 (45.3) | 354 (41.9) | 0.053 |
| Diabetes, n (%) | 1030 (43.4) | 162 (35.4)* , ** | 476 (44.4) | 392 (46.4) | <0.001 |
| Pneumonia, n (%) | 127 (5.3) | 22 (4.8) | 62 (5.8) | 43 (5.0) | 0.68 |
| Coronary heart disease, n (%) | 1000 (42.1) | 183 (40.0)* | 522 (48.7) | 295 (34.9)* | <0.001 |
| COPD, n (%) | 311 (13.1) | 24 (5.3) ** | 82 (7.6) | 205 (24.3)* | <0.001 |
| Prior heart failure, n (%) | 1371 (57.8) | 316 (69.1) ** | 747 (69.7) | 668 (79.1)* | <0.001 |
| Cardiogenic shock, n (%) | 402 (16.9) | 105 (23.0) ** | 204 (19.0) | 93 (11.0)* | <0.001 |
| CHF, n (%) | 2329 (98.1) | 442 (96.7) ** | 1053 (98.2) | 834 (98.7) | 0.04 |
| AMI, n (%) | 57 (2.4) | 18 (3.9) ** | 31 (2.9) | 8 (0.9)* | 0.001 |
| Laboratory tests | |||||
| Creatinine (mg/dL) | 1.3 (0.9–2.0) | 1.5 (1.0–2.3)* | 1.2 (0.9–1.9) | 1.3 (0.9–1.9)* | <0.001 |
| BUN (mg/dL) | 28.0 (18.6–44.4) | 32.5 (21.0–50.7)* , ** | 26.3 (18.0–41.0) | 28.0 (19.0–44.8)* | <0.001 |
| Glucose (mg/dL) | 135.7 (111.5–174.0) | 138.0 (114.0–177.5) | 134.5 (111.0–171.8) | 136.0 (111.0–174.0) | 0.524 |
| Sodium (mmol/L) | 138.5 (135.5–141.0) | 137.7 (134.6–140.3) ** | 138.0 (135.5–140.3) | 139.7 (136.5–142.0)* | <0.001 |
| Potassium (mmol/L) | 4.2 (3.8–4.6) | 4.2 (3.8–4.6) ** | 4.2 (3.8–4.6) | 4.3 (3.9–4.7)* | <0.001 |
| Chloride (mmol/L) | 102.9 ± 6.2 | 104.4 ± 6.7 ** | 103.8 ± 5.7 | 101.0 ± 6.0* | <0.001 |
| Calcium (mg/dL) | 8.4 ± 0.7 | 8.2 ± 0.7* , ** | 8.3 ± 0.7 | 8.5 ± 0.7* | <0.001 |
| pH | 7.4 ± 0.1 | 7.4 ± 0.1* , ** | 7.4 ± 0.1 | 7.3 ± 0.1* | <0.001 |
| Lactate, n (%) | <0.001 | ||||
| <1.6 mmol/L | 910 (38.3) | 141 (30.9) ** | 349 (32.6) | 420 (49.7)* | |
| ≥1.6 mmol/L | 1016 (42.8) | 231 (50.5) ** | 532 (49.6) | 253 (29.9)* | |
| No test | 448 (18.9) | 85 (18.6) | 191 (17.8) | 172 (20.4) | |
AMI, acute myocardial infarction; BUN, blood urea nitrogen; CHF, congestive heart failure; COPD, chronic obstructive pulmonary disease; CRRT, continuous renal replacement therapy; GCS, Glasgow Coma Scale; MAP, mean arterial pressure; PaCO2, partial pressure of arterial carbon dioxide; RR, respiration rate; SAPSII, Simplified Acute Physiology Score II; SOFA, Sequential Organ Failure Assessment; SpO2, arterial oxyhaemoglobin saturation.
P < 0.05 vs. PaCO2 = 35–45 mmHg.
P < 0.05 vs. PaCO2 > 45 mmHg.
Primary outcome
The in‐hospital mortality of patients was 19.5% (89 deaths of 457 cases) in the PaCO2 < 35 mmHg group, which was significantly higher than 11.7% (125 deaths of 1072 cases) in the PaCO2 = 35–45 mmHg group and 13.8% (117 deaths of 845 cases) in the PaCO2 > 45 mmHg group (P < 0.001, Figure 2 ). The 1 year mortality of patients was 23.9% (109 deaths of 457 cases) in the PaCO2 < 35 mmHg group, which was significantly higher than the 15.2% (163 deaths of 1072 cases) in the PaCO2 = 35–45 mmHg group (P < 0.05), but not significantly different from the 18.3% (155 deaths of 845 cases) in the PaCO2 > 45 mmHg group (P > 0.05). The 1 year mortality among hospitalized survivors was not significantly different among the three groups (P = 0.39, Supporting Information, Table S4 ).
Figure 2.
In‐hospital mortality and 1 year mortality among the three groups. In‐hospital mortality was significantly higher in the partial pressure of arterial carbon dioxide (PaCO2) <35 mmHg group than those in the other two groups (19.5% vs. 11.7% vs. 13.8%, P < 0.001); 1 year mortality was significantly higher in the PaCO2 < 35 mmHg group than those in the PaCO2 = 35–45 mmHg group, but not significantly different from the PaCO2 > 45 mmHg group (23.9% vs. 15.2% vs. 18.3%, P < 0.001). P < 0.05 was statistically significant. *P < 0.05 vs. PaCO2 = 35–45 mmHg. # P < 0.05 vs. PaCO2 > 45 mmHg.
Variables (P < 0.05) screened by univariate Cox regression analysis for association with in‐hospital mortality included age, ethnicity, weight, MAP, heart rate, RR, SpO2, SOFA score, SAPSII score, GCS score, vasopressor use, mechanical ventilation ratios, CRRT use, furosemide, torsemide, nitroglycerin, atrial fibrillation, hypertension, diabetes, pneumonia, cardiogenic shock, PaCO2, blood creatinine, BUN, glucose, potassium, pH, and lactate (Supporting Information, Table S2 ). After adjusting for confounding factors, the association between PaCO2 levels and in‐hospital mortality is shown in Table 2 . Compared with the PaCO2 = 35–45 mmHg group, the PaCO2 < 35 mmHg group and the PaCO2 > 45 mmHg group were associated with higher in‐hospital mortality [hazard ratio (HR) 1.398, 95% confidence interval (CI) 1.039–1.882, P = 0.027; HR 1.387, 95% CI 1.050–1.832, P = 0.021]. The same method was used to filter out variables (P < 0.05) on 1 year mortality (Supporting Information, Table S3 ). After adjusting for confounding factors (Table 3 ), the PaCO2 < 35 mmHg group was associated with higher 1 year mortality than the PaCO2 = 35–45 mmHg group (HR 1.327, 95% CI 1.020–1.728, P = 0.035), while the PaCO2 > 45 mmHg group showed no significant difference in 1 year mortality compared with the PaCO2 = 35–45 mmHg group (HR 1.286, 95% CI 0.995–1.662, P = 0.055). The Kaplan–Meier survival curves showed that AHF patients in the PaCO2 < 35 mmHg group had a significantly lower 1 year survival rate (76.5% vs. 85.2% vs. 81.9%, log‐rank P < 0.001) than those in the PaCO2 = 35–45 mmHg group and the PaCO2 > 45 mmHg group (Figure 3 ).
Table 2.
Multivariate Cox regression analysis for the association between the risk factors and in‐hospital mortality
| Variables | Multivariate model a | ||
|---|---|---|---|
| HR | 95% CI | P value | |
| Age | 1.025 | 1.013–1.037 | <0.001 |
| Weight | 0.991 | 0.986–0.997 | 0.004 |
| MAP | 0.983 | 0.970–0.997 | 0.016 |
| Creatinine | 0.860 | 0.753–0.981 | 0.025 |
| Potassium | 1.246 | 1.019–1.524 | 0.032 |
| BUN | 1.012 | 1.006–1.019 | <0.001 |
| PaCO2 | 0.024 | ||
| PaCO2 < 35 mmHg | 1.398 | 1.039–1.882 | 0.027 |
| PaCO2 = 35–45 mmHg | Reference | ||
| PaCO2 > 45 mmHg | 1.387 | 1.050–1.832 | 0.021 |
| SpO2 | 0.917 | 0.876–0.959 | <0.001 |
| SOFA | 1.112 | 1.059–1.167 | <0.001 |
| SAPSII | 1.016 | 1.005–1.028 | 0.005 |
| Cardiogenic shock | 1.711 | 1.308–2.239 | <0.001 |
| Torsemide | 0.425 | 0.296–0.612 | <0.001 |
| Nitroglycerin | 0.676 | 0.530–0.861 | 0.002 |
BUN, blood urea nitrogen; CI, confidence interval; GCS, Glasgow Coma Scale; HR, hazard ratio; MAP, mean arterial pressure; PaCO2, partial pressure of arterial carbon dioxide; RR, respiration rate; SAPSII, Simplified Acute Physiology Score II; SOFA, Sequential Organ Failure Assessment; SpO2, arterial oxyhaemoglobin saturation.
Variables (P < 0.05) screened by univariate Cox regression analysis for association with in‐hospital mortality included in the multivariate Cox regression analysis, including age, ethnicity, weight, MAP, heart rate, RR, SpO2, SOFA score, SAPSII score, GCS score, vasopressor, mechanical ventilation, atrial fibrillation, hypertension, diabetes, pneumonia, PaCO2, blood creatinine, BUN, glucose, potassium, pH, and lactate.
Table 3.
Multivariate Cox regression analyses for the association between the risk factors and 1 year mortality
| Variables | Multivariate model a | ||
|---|---|---|---|
| HR | 95% CI | P value | |
| Age | 1.021 | 1.011–1.032 | <0.001 |
| Weight | 0.990 | 0.985–0.995 | <0.001 |
| RR | 1.046 | 1.019–1.075 | 0.001 |
| BUN | 1.009 | 1.003–1.015 | 0.001 |
| Chloride | 0.980 | 0.963–0.996 | 0.016 |
| PaCO2 | 0.045 | ||
| PaCO2 < 35 mmHg | 1.327 | 1.020–1.728 | 0.035 |
| PaCO2 = 35–45 mmHg | Reference | ||
| PaCO2 > 45 mmHg | 1.286 | 0.995–1.662 | 0.055 |
| SpO2 | 0.942 | 0.903–0.983 | 0.006 |
| SOFA | 1.098 | 1.054–1.144 | <0.001 |
| SAPSII | 1.013 | 1.002–1.023 | 0.017 |
| Cardiogenic shock | 1.710 | 1.338–2.185 | <0.001 |
| AMI | 0.114 | 0.016–0.816 | 0.031 |
| Torsemide | 0.562 | 0.424–0.747 | <0.001 |
AMI, acute myocardial infarction; BUN, blood urea nitrogen; CI, confidence interval; GCS, Glasgow Coma Scale; HR, hazard ratio; MAP, mean arterial pressure; PaCO2, partial pressure of arterial carbon dioxide; RR, respiration rate; SAPSII, Simplified Acute Physiology Score II; SOFA, Sequential Organ Failure Assessment; SpO2, arterial oxyhaemoglobin saturation.
Variables (P < 0.05) screened by univariate Cox regression analysis for association with 1 year mortality included in the multivariate Cox regression analysis, including age, weight, MAP, heart rate, RR, temperature, SpO2, SOFA score, SAPSII score, GCS score, vasopressor, mechanical ventilation ratios, atrial fibrillation, hypertension, pneumonia, PaCO2, blood creatinine, BUN, glucose, potassium, pH, and lactate.
Figure 3.
Kaplan–Meier survival curves for acute heart failure patients based on partial pressure of arterial carbon dioxide (PaCO2). The PaCO2 < 35 mmHg group had significantly lower 1 year survival rate (76.5% vs. 85.2% vs. 81.9%, log‐rank P < 0.001) than those in the other two groups.
Secondary outcome
The ROC curve of PaCO2 for predicting in‐hospital mortality showed that the cutoff value was 31.75 mmHg, the sensitivity was 67.4%, the specificity was 47.8%, and the AUC was 0.591 (95% CI 0.526–0.656) in the PaCO2 < 35 mmHg group. The AUC of the PaCO2 = 35–45 mmHg group was 0.536 (95% CI 0.485–0.486), and that of the PaCO2 > 45 mmHg group was 0.506 (95% CI 0.449–0.563, Figure 4 A ). In addition, the ROC curve of PaCO2 for predicting 1 year mortality showed that the cutoff value was 29.25 mmHg, the sensitivity was 44.2%, the specificity was 69.3%, and the AUC was 0.566 (95% CI 0.505–0.627) in the PaCO2 < 35 mmHg group. The AUC of the PaCO2 = 35–45 mmHg group was 0.536 (95% CI 0.491–0.582), and that of the PaCO2 > 45 mmHg group was 0.517 (95% CI 0.467–0.567, Figure 4 B ).
Figure 4.
Receiver operating characteristic (ROC) curve of partial pressure of arterial carbon dioxide (PaCO2) for predicting in‐hospital mortality and 1 year mortality in acute heart failure patients. (A) ROC curve of PaCO2 for predicting in‐hospital mortality. The area under the ROC curve (AUC) was 0.591 [95% confidence interval (CI) 0.526–0.656] in the PaCO2 < 35 mmHg group, 0.536 (95% CI 0.485–0.486) in the PaCO2 = 35–45 mmHg group, and 0.506 (95% CI 0.449–0.563) in the PaCO2 > 45 mmHg group. (B) ROC curve of PaCO2 for predicting 1 year mortality. The AUC was 0.566 (95% CI 0.505–0.627) in the PaCO2 < 35 mmHg group, 0.536 (95% CI 0.491–0.582) in the PaCO2 = 35–45 mmHg group, and 0.517 (95% CI 0.467–0.567) in the PaCO2 > 45 mmHg group.
Discussion
This was a retrospective study of the MIMIC‐IV database to simultaneously evaluate the connection between PaCO2 and in‐hospital mortality and 1 year mortality in AHF patients and the potential predictive value of PaCO2. The analysis of blood gas values within 24 h after admission to the ICU of these patients showed that hypocapnia was associated with a higher risk of in‐hospital mortality and 1 year mortality in AHF patients. However, the effect of hypocapnia on 1 year mortality may be influenced by hospitalization mortality. Hypercapnia was associated with a higher risk of in‐hospital mortality; however, it was not associated with a higher risk of 1 year mortality in AHF patients. In addition, PaCO2 had low predictive performance for in‐hospital mortality and 1 year mortality.
Most of the effects of extracellular hypocapnia are caused by alkalosis rather than by the low PaCO2 itself. Anxiety, fear, and panic about AHF‐related symptoms may cause hyperventilation and lower PaCO2. 2 , 17 Hypocapnia may also be associated with an increased RR due to hypoxia and renal dysfunction caused by inadequate tissue perfusion, resulting in metabolic acidosis and elevated lactate levels. 18 As reported previously, hypocapnia has numerous negative effects on the heart, lungs, and brain. Hypocapnia can cause coronary arteries to contract and increase the risk of coronary artery spasms, 19 while reducing oxygen release due to the left shift of the oxygen dissociation curve, increasing the risk of myocardial ischaemia, and leading to arrhythmias. 20 Hypocapnia can cause bronchoconstriction, while hypoxic pulmonary vasoconstriction is inhibited, resulting in an imbalance in the ventilation–perfusion ratio and increased intrapulmonary shunting. Hypocapnia can also inhibit the production of pulmonary surfactants, increasing the permeability of the alveolar–capillary membrane and upper respiratory tract. 21 It can cause severe acute lung parenchymal injury and even exacerbate lung injury due to ischaemia–reperfusion. 22 Post‐traumatic cerebral vasoconstriction under hypocapnia conditions and intracranial pressure can be lowered by inducing hypocapnia, but this may lead to cerebral hypoperfusion and cerebral tissue ischaemia. 23 Therefore, poor prognosis in AHF patients may be associated with hypocapnia, leading to multiple adverse effects; we need to identify the cause of hypocapnia and provide effective treatment. In our study, patients were divided into three groups according to PaCO2 values of <35, 35–45, and >45 mmHg, which was more in line with the clinical criteria for grouping PaCO2. In addition, PaCO2 values can be easily obtained from arterial blood gases (ABGs), and using them to predict the prognosis of AHF patients is convenient. Therefore, PaCO2 can be used for instruction of the subsequent treatment.
Hypercapnia can cause pulmonary hypertension, which affects ejection of the right ventricle and causes tachycardia and hypertension. 24 In contrast, hypercapnia may have beneficial roles in the pathogenesis of inflammation and tissue injury and in increasing cerebral blood flow. Permissive hypercapnia is a strategy considered to be lung‐protective ventilation to avoid ventilator‐related lung injury. 25 Miñana et al. demonstrated that a higher level of PaCO2 (>50 mmHg) showed no significant association with all‐cause long‐term mortality. 26 A recent study showed that prehospital hypercapnia (PaCO2 > 45 mmHg) was associated with an increase in in‐hospital and 7 day mortality in AHF patients. 8 Consistent with these studies, the present study showed that hypercapnia (PaCO2 > 45 mmHg) was associated with a higher risk of in‐hospital mortality; however, it was not associated with a higher risk of 1 year mortality in AHF patients. This may be because hypercapnic patients were more likely to have higher systolic blood pressure (SBP) and diastolic blood pressure. Elevated blood pressure may increase the risk of pulmonary oedema, which reduces carbon dioxide clearance and oxygen uptake, leading to hypoxaemia and therefore increased mortality. Meanwhile, the presence of hypercapnia in AHF is acute and transient and is associated with immediate airway intervention. Non‐invasive positive pressure ventilation rapidly improves the symptoms of AHF 7 ; therefore, prompt administration of airway interventions to correct hypercapnia reduces mortality in AHF patients.
Hypocapnia may cause or aggravate cellular or tissue ischaemia by both decreasing the cellular oxygen supply and increasing the cellular oxygen demand. 17 Supplemental oxygen therapy is the routine treatment for AHF patients. 27 , 28 While the avoidance of hypoxia is widely practised, a growing amount of evidence has shown the potentially deleterious effects of hyperoxia. 29 , 30 , 31 In AHF patients, changes in SpO2 levels may be a precursor to the disease deterioration, and hyperoxia might decrease vigilance and delay recognition of deteriorating patients. 32 A study in the ICU reported that conservative oxygen therapy (SpO2 = 94–98%) had lower ICU mortality than usual care (SpO2 ≥ 97%). 33 Our study found that SpO2 was associated with in‐hospital mortality in AHF patients. However, the study conducted by Sepehrvand et al. showed that there was no difference in mortality within 30 days after discharge in the high SpO2 group (>96%) compared with the low SpO2 (90–92%) group. 28 This may be because the study was a pilot trial that enrolled only 50 AHF patients and used a manual SpO2 titration method, which did not induce a proper separation of SpO2 levels between the two test groups. There were some adherence issues, mainly related to healthcare professionals not following the protocol and performing low titrations on those with SpO2 levels above the specified range. Therefore, further trials are warranted to confirm the efficacy and safety of supplemental oxygen therapy in AHF patients.
Previous prediction models of mortality of heart failure patients demonstrated that the risk of in‐hospital mortality can be reliably estimated using routinely available vital signs and laboratory data obtained on hospital admission. 34 Fonarow et al. used a logistic regression model for in‐hospital mortality and suggested that BUN level, SBP, heart rate, and age were the most significant predictors of mortality risk. 35 A study conducted by Wagner et al. showed that a high SOFA score at admission was associated with a worse outcome defined as death or rehospitalization because of heart failure symptoms. 36 This reveals that quick SOFA is useful to identify the high risk of worse outcome in patients with heart failure. Consistent with previous studies, SOFA score, BUN level, MAP, RR, and age were useful predictors of mortality in AHF patients in our study.
Brain natriuretic peptide (BNP) and NT‐proBNP have been shown to be favourable prognostic markers for AHF. It has been reported that in AHF patients, decreases in NT‐proBNP concentrations both before discharge and during hospitalization are associated with post‐discharge prognosis. 37 , 38 Another trial showed that changes in NT‐proBNP concentrations during hospitalization and changes in concentrations early after discharge and at 1 month after discharge were independent prognostic factors. 39 Regretfully, NT‐proBNP was not included in our study results because of the large number of missing values, and the true prognostic impact of NT‐proBNP on AHF patients could not be shown.
There were several limitations of our study. First, AHF patients without ABG analysis or the absence of PaCO2 recording were excluded, which may cause selection bias. Second, although the ABG analysis records were obtained within 24 h after admission to the ICU, the time of the ABG analysis was not consistent in all patients, and there was no record of abnormal PaCO2 duration, which could not demonstrate whether abnormal PaCO2 duration would have an effect on mortality in AHF patients. Third, critical patients had large heterogeneity. Although multivariate regression analysis was used to adjust for confounders, there may still be some unknown factors interfering with the observed results. Fourth, because >20% of laboratory tests were excluded because of missing data, there was a lack of some important clinical indices, such as NT‐proBNP, resulting in their prognostic value for AHF not being evaluated. Fifth, it was an observational study set in a single centre, limiting the generalization of our results. Finally, all AUC values were lower than 0.6, indicating that PaCO2 had low predictive performance for in‐hospital mortality and 1 year mortality. This may be because the AHF patients included in this study were from a single centre and the number of patients was too small to find the predictive value of PaCO2. Therefore, the results need external prospective validation from other medical institutions.
Conclusions
Hypocapnia within 24 h after admission to the ICU was associated with increased in‐hospital mortality and 1 year mortality in AHF patients. However, the increase in 1 year mortality may be influenced by hospitalization mortality. Hypercapnia within 24 h after admission to the ICU was associated with increased in‐hospital mortality; however, it was not associated with increased 1 year mortality in AHF patients. The risk assessment of AHF patients should include hypocapnia.
Conflict of interest
None declared.
Funding
This study was supported by the National Natural Science Foundation of China (82171859 and 81871515 to F.H.) and Key R&D Program of Heilongjiang (2022ZX06C20 to F.H.).
Supporting information
Table S1. Details of missing values.
Table S2. Univariate Cox regression analysis for the association between the risk factors and in‐hospital mortality.
Table S3. Univariate Cox regression analyses for the association between the risk factors and one‐year mortality.
Table S4. One‐year mortality for hospitalized survivors.
Zhang, L. , Sun, Y. , Sui, X. , Zhang, J. , Zhao, J. , Zhou, R. , Xu, W. , Yin, C. , He, Z. , Sun, Y. , Liu, C. , Song, A. , and Han, F. (2024) Hypocapnia is associated with increased in‐hospital mortality and 1 year mortality in acute heart failure patients. ESC Heart Failure, 11: 2138–2147. 10.1002/ehf2.14763.
Data availability statement
The data that support the findings of this study are included in the article materials. Further inquiries can be directed to the corresponding author.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1. Details of missing values.
Table S2. Univariate Cox regression analysis for the association between the risk factors and in‐hospital mortality.
Table S3. Univariate Cox regression analyses for the association between the risk factors and one‐year mortality.
Table S4. One‐year mortality for hospitalized survivors.
Data Availability Statement
The data that support the findings of this study are included in the article materials. Further inquiries can be directed to the corresponding author.