ABSTRACT
Background
Surgery under general anaesthesia is generally safe, although some patients are vulnerable to postoperative complications. Identifying predictors of poor outcomes after general anaesthesia in all settings is relevant for preoperative risk assessment, postoperative monitoring and patient counselling. The aim of this study was to identify patient groups with poor outcomes after general anaesthesia in Denmark.
Methods
This was a nationwide, registry‐based, observational cohort study of patients aged 18 years and above undergoing general anaesthesia in Denmark. Associations between patient characteristics (age, sex, body mass index, ASA classification and 23 comorbidities) and outcomes were analysed. The primary outcome was 30‐day mortality. Secondary outcomes included acute kidney injury within 7 and 30 days, hospital length of stay, any ICU stay, length of ICU stay, 90‐day mortality, in‐hospital cardiac arrest within 30 days, and need for mechanical ventilation within 7 days.
Results
A total of 328,951 unique patients undergoing 453,133 cases of general anaesthesia in Denmark during 2020 and 2021 were identified. The adjusted odds of 30‐day mortality were higher for cases with higher age, male sex and higher ASA classification. Compared with ASA II, the adjusted odds ratio for 30‐day mortality was 0.19 (CI: 0.13–0.29) for ASA I, 7.00 (CI: 5.28–9.29) for ASA III, 40.7 (CI: 29.5–56.0) for ASA IV, and 223 (CI: 161–307) for ASA V.
Conclusion
In this nationwide observational cohort study, higher ASA classification, higher age and male sex were independently associated with increased odds of 30‐day mortality and several secondary outcomes after general anaesthesia. This study helps identify at‐risk patient groups suitable for further studies investigating ways to reduce the risk of complications.
Editorial Comment
From a national cohort, this analysis presents patient factors which have associations with postoperative mortality. This supports a simple classification for patient grouping where focus for complication prevention or mitigation can be applied.
1. Introduction
Worldwide, more than 300 million surgeries are performed each year, of which the majority require general anaesthesia [1, 2, 3], with 75% of all cases of anaesthesia in Denmark during 2021 requiring general anaesthesia [4]. Although surgery under general anaesthesia is considered safe for most patients, certain patient groups have an increased risk of postoperative complications. For example, studies have shown that American Society of Anesthesiologists (ASA) classification, higher age, comorbidity and frailty are associated with postoperative complications [5, 6, 7, 8]. However, many studies are limited to specific settings or surgery types; thus, patient characteristics predisposing to poor outcomes in patients undergoing general anaesthesia, irrespective of setting and surgery type, are not well described.
Understanding the patient population undergoing general anaesthesia and possible predictors of poor outcomes is important for preoperative risk assessment, patient counselling, degree of postoperative monitoring, and for informing future research studies. Large databases with comprehensive data on patient characteristics and outcomes after general anaesthesia are needed to identify potential patient groups with worse outcomes. In this context, the rich tradition for registries in Scandinavia offers a unique opportunity for registry‐based research, as multiple comprehensive, nationwide registries and databases collect information on patients within the health care systems, as seen in studies from Sweden [9] and Denmark [10, 11].
The aim of this study was to identify patient characteristics associated with worse outcomes after general anaesthesia in Denmark.
2. Methods
2.1. Design, Data Source and Setting
This was a national, registry‐based, observational cohort study of patients undergoing general anaesthesia in Denmark in 2020 and 2021. The study leveraged data from multiple nationwide Danish registries and databases to describe patient characteristics and outcomes. The setting and data sources have been described in a previous publication on the same cohort [11]. In brief, this study used data from the Danish Anesthesia Database to identify cases of general anaesthesia [4, 12, 13]. Data from the National Patient Registry were used to define comorbidities and length of hospital stay. For other outcomes, the Danish Civil Registration System, the Register of Laboratory Results for Research, the Danish In‐hospital Cardiac Arrest Registry (DANARREST), the Danish Intensive Care Database, and the Danish Stroke Registry were used. The databases were linked through the unique personal identification number assigned to all Danish residents (i.e., the Civil Personal Register number) [14]. The databases have been described elsewhere [10, 13, 15, 16, 17, 18, 19]. Further details are available in the supplemental material (Table S1). This study adheres to the STROBE guidelines. Ethical approval is not required for observational registry‐based studies in Denmark [20].
2.2. Population
The study population consisted of adult patients (≥ 18 years) who underwent general anaesthesia and were registered in the Danish Anesthesia Database from January 1, 2020, to December 31, 2021. Patients were included in our analyses if they had a valid unique civil personal register number and had a registered time and date of general anaesthesia. The same patient could be included multiple times, as the population consisted of unique cases of general anaesthesia. Data on unique patients, defined as the first general anaesthesia within the study period, and data stratified based on non‐cardiac and cardiac procedures were also reported in the Supporting Information.
Duplicate cases and dead organ donors were excluded. In addition, cases where general anaesthesia was expected to be of very short duration, that is, general anaesthesia for direct current cardioversion and electroconvulsive therapy, were excluded (Figure S1). These exclusions were based on procedure codes reported by the clinicians.
2.3. Data Variables
2.3.1. Patient Characteristics
Data on age and sex were obtained from the Danish Civil Registration System. Pre‐operative risk factors were obtained from the Danish Anesthesia Database. Pre‐operative risk factors included smoking, drinking status, body mass index (BMI) and ASA classification. Patient age was categorised into 8 groups: 18–29 years, 30–39 years, 40–49 years, 50–59 years, 60–69 years, 70–79 years, 80–89 years and ≥ 90 years. BMI was calculated from patient height and weight reported by the clinicians and subdivided according to World Health Organization (WHO) guidelines into 6 groups: < 18.5 kg/m2, 18.5–24.9 kg/m2, 25–29.9 kg/m2, 30–34.9 kg/m2, 35–39.9 kg/m2 and > 40 kg/m2 [21].
Data on comorbidities were obtained from the Danish National Patient Registry. All comorbidities were defined using the International Classification of Disease System (ICD‐10) codes from hospital contacts up to 10 years prior to the date of general anaesthesia. If a patient underwent more than one general anaesthesia, the patient would count accordingly in the study population. In this context, the date of each case of general anaesthesia ensured precise reporting of any newly acquired comorbidities. Comorbidities included a total of 181 disease entities grouped into 23 comorbidities across cardiovascular disease, neurological disease, pulmonary disease, metabolic disease, gastrointestinal disease, renal disease, cancer and psychiatric disorders. The specific ICD codes used to define comorbidities have been described previously [22] and are available in the supplemental materials (Table S2).
2.3.2. Outcomes
The primary outcome of interest was 30‐day mortality. Secondary outcomes included length of hospital stay after general anaesthesia, any stay in an intensive care unit (ICU) within 30 days and AKI within 7 days. Additional outcomes reported in the Supporting Information include number of days in an ICU within 30 days, 90‐day mortality, AKI within 30 days, in‐hospital cardiac arrest within 30 days, and mechanical ventilation within 7 days of general anaesthesia. All outcomes were established a priori.
Mortality at 30 and 90 days after general anaesthesia was identified through data from the Danish Civil Registration System [10]. AKI was based on creatinine values obtained from The Clinical Laboratory Information Register and ICD‐10 codes for new renal replacement therapy (haemodialysis or peritoneal dialysis) using the Kidney Disease Improving Global Outcomes (KDIGO) criteria [23]. In‐depth description and definitions of secondary and supplementary outcomes are available in the Supporting Information.
2.4. Statistical Analysis
Descriptive statistics were used to describe patient characteristics and assess the distribution of data.
To identify potential patient characteristics associated with worse outcomes, logistic regression was performed for binary outcomes to obtain odds ratios (ORs) with 95% confidence intervals (CIs). Univariable logistic regression analysis was used to perform unadjusted analyses. A multivariable logistic regression model was constructed for the adjusted analyses. The adjusted model included the following variables: age, sex, BMI, ASA classification and comorbidities. Smoking and alcohol use were not included in the model due to a large proportion of missing data. We performed a post hoc analysis of 30‐day mortality adjusting for smoking and alcohol use. A post hoc analysis of 30‐day mortality adjusted for urgency was performed. Cases with missing values for BMI, ASA and length of hospital stay were not included in the respective adjusted analyses.
For the continuous outcomes of length of hospital stay after general anaesthesia and number of days in the ICU within 30 days, we used linear regression with univariable and multivariable models as described above. Results from the linear regression analyses are reported as mean difference (MD) in days with 95% CI.
For all models, generalised estimating equations were used to account for multiple cases of general anaesthesia for the same patient and for within‐hospital clustering [24].
Data management and analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA).
3. Results
A total of 453,133 cases of general anaesthesia administered to 328,951 unique patients in Denmark during 2020 and 2021 were included in this study. This included 444,748 cases of general anaesthesia for patients undergoing non‐cardiac procedures and 8385 cases for patients undergoing cardiac procedures. Patient characteristics and data on the procedure, duration, location and anaesthesia characteristics were described previously [11]. Table 1 provides descriptive data on post‐anaesthesia outcomes for all cases, unique patients and cases stratified into cardiac and non‐cardiac procedures.
TABLE 1.
Outcome summary.
| All cases (n = 453,133) | Unique patients (n = 328,951) | Non‐cardiac cases (n = 444,748) | Cardiac cases (n = 8385) | |
|---|---|---|---|---|
| Primary outcome | ||||
| Mortality at 30 days | 8172 (1.8) | 4814 (1.5) | 7924 (1.8) | 248 (3.0) |
| Secondary outcomes | ||||
| Acute kidney injury within 7 days a | 12,822 (2.8) | 8043 (2.5) | 11,387 (2.6) | 1435 (17) |
| Length of hospital stay b | 0.7 [0.2 to 2.3] | 0.5 [0.2 to 1.9] | 0.6 [0.2 to 2.2] | 5.1 [1.1 to 8.3] |
| Any ICU stay within 30 days b | 17,847 (3.9) | 10,107 (3.1) | 14,086 (3.2) | 3761 (44.9) |
| Additional outcomes | ||||
| Number of days in ICU c | 2 [0.9 to 6.4] | 1.2 [0.9 to 3.9] | 2.6 [0.9 to 7.8] | 1.1 [1.0 to 2.0] |
| Mortality at 90 days | 14,225 (3.1) | 8223 (2.5) | 13,908 (3.1) | 317 (3.8) |
| Acute kidney injury within 30 days b | 19,851 (4.4) | 11,615 (3.5) | 18,176 (4.1) | 1675 (20) |
| In‐hospital cardiac arrest within 30 days | 769 (0.2) | 447 (0.1) | 669 (0.2) | 100 (1.2) |
| Mechanical ventilation within 7 days | 4664 (1.0) | 2962 (0.9) | 3862 (0.8) | 802 (9.6) |
| Stroke within 30 days d | 338 (0.09) | 262 (0.08) | 344 (0.08) | 44 (0.5) |
| Myocardial injury d | 3470 (0.8) | 2499 (0.8) | 2567 (0.6) | 903 (11) |
Note: Categorical data are presented as counts with frequencies (%). Continuous data are presented as medians [IQR].
AKI diagnosis based on KDIGO criteria. Imputed data were used when no baseline creatinine values were available. Further description in supplement.
Measured after administration of general anaesthesia.
Data for patients who had a stay in an ICU within 30 days of general anaesthesia.
Counts and frequencies for stroke and myocardial injury are reported here. There were not enough cases with these outcomes to allow for meaningful multivariable analyses.
A total of 1076 (0.2%) and 1250 (0.3%) cases had incomplete follow‐up until 30 and 90 days after general anaesthesia, respectively, due to emigration or disappearance [10]. If patients did not have outcomes before emigration or disappearance, it was assumed that they did not have the outcome. A total of 35,403 (7.8%), 2274 (0.5%), and 48,237 (11%) cases had missing data on BMI, ASA classification and length of hospital stay, respectively. The case population for the adjusted analyses consisted of 417,730 cases (372,801 cases for the outcome of length of hospital stay). Smoking and alcohol status were missing in 81,288 (18%) and 171,947 (38%) cases.
3.1. Thirty‐Day Mortality
Mortality at 30 days after general anaesthesia was 1.8%. In the adjusted analyses, the odds of 30‐day mortality were higher for cases with greater age, male sex and higher ASA classification, whereas the odds were lower for cases with higher BMI. Results varied for the different comorbidities. Specific ORs with 95% CI for 30‐day mortality for all cases of general anaesthesia are presented in Table 2 and Figure 1. ORs with 95% CI for 30‐day mortality for unique patients and non‐cardiac cases are available in Tables S8 and S17.
TABLE 2.
Thirty‐day mortality after general anaesthesia.
| All cases (n = 453,133) counts with frequencies (%) | Unadjusted odds ratio (95% confidence interval) | Adjusted a odds ratio (95% confidence interval) | |
|---|---|---|---|
| Overall | 8172/453,133 (1.8) | ||
| Demographics | |||
| Age (years) | |||
| 18–29 (ref) | 69/54,512 (0.1) | 1.00 (reference) | 1.00 (reference) |
| 30–39 | 119/50,976 (0.2) | 1.85 (1.19 to 2.86) | 1.49 (0.87 to 2.55) |
| 40–49 | 207/62,026 (0.3) | 2.64 (1.60 to 4.35) | 1.52 (0.95 to 2.42) |
| 50–59 | 688/81,100 (0.9) | 6.75 (3.81 to 11.9) | 2.39 (1.35 to 4.23) |
| 60–69 | 1502/81,948 (1.8) | 14.7 (7.66 to 28.3) | 3.53 (1.99 to 6.26) |
| 70–79 | 2657/85,678 (3.1) | 25.3 (11.8 to 54.6) | 4.86 (2.68 to 8.83) |
| 80–89 | 2196/32,578 (6.7) | 57.0 (23.1 to 141) | 9.05 (4.85 to 16.9) |
| ≥ 90 | 734/4315 (17) | 162 (65.1 to 402) | 21.8 (12.2 to 39.0) |
| Sex | |||
| Female (ref) | 3583/242,679 (1.5) | 1.00 (reference) | 1.00 (reference) |
| Male | 4589/210,454 (2.2) | 1.49 (1.32 to 1.68) | 1.16 (1.07 to 1.25) |
| BMI (kg/m2) | |||
| < 18.5 | 687/12,118 (5.7) | 2.96 (2.48 to 3.52) | 1.75 (1.55 to 1.97) |
| 18.5–24.9 (ref) | 3222/161,650 (2) | 1.00 (reference) | 1.00 (reference) |
| 25–29.9 | 2047/142,772 (1.4) | 0.72 (0.61 to 0.84) | 0.77 (0.69 to 0.85) |
| 30–34.9 | 928/65,239 (1.4) | 0.71 (0.59 to 0.85) | 0.77 (0.66 to 0.89) |
| 35–39.9 | 280/23,532 (1.2) | 0.59 (0.48 to 0.72) | 0.64 (0.53 to 0.78) |
| > 40 | 172/12,419 (1.4) | 0.69 (0.50 to 0.95) | 0.64 (0.47 to 0.88) |
| Missing | 836/35,403 (2.4) | ||
| ASA classification | |||
| I | 38/105,715 (0.04) | 0.10 (0.07 to 0.18) | 0.19 (0.13 to 0.29) |
| II (ref) | 762/221,199 (0.3) | 1.00 (reference) | 1.00 (reference) |
| III | 4342/109,657 (4) | 11.9 (9.00 to 15.8) | 7.00 (5.28 to 9.29) |
| IV | 2714/13798 (20) | 70.8 (46.8 to 107) | 40.7 (29.5 to 56.0) |
| V | 232/490 (47) | 260 (164 to 413) | 223 (161 to 307) |
| Missing | 84/2274 (3.7) | ||
| Comorbidities | |||
| Cardiovascular disease | |||
| Ischemic heart disease | 1616/40,067 (4) | 2.61 (2.26 to 3.00) | 0.76 (0.70 to 0.82) |
| Heart failure | 1174/16219 (7.2) | 4.79 (3.87 to 5.93) | 1.20 (1.07 to 1.35) |
| Hypertension | 3322/85,961 (3.9) | 3.00 (2.58 to 3.50) | 0.99 (0.94 to 1.06) |
| Atrial fibrillation/flutter | 1858/35,505 (5.2) | 3.60 (2.91 to 4.44) | 0.95 (0.87 to 1.04) |
| Other cardiac dysrhythmias | 792/21,884 (3.6) | 2.16 (1.80 to 2.59) | 0.89 (0.77 to 1.03) |
| Peripheral vascular disease | 1225/19,065 (6.4) | 4.22 (3.43 to 5.20) | 1.25 (1.16 to 1.35) |
| Hypercholesterolemia | 952/29,359 (3.2) | 1.93 (1.74 to 2.15) | 0.76 (0.67 to 0.86) |
| Venous thromboembolism | 794/19,680 (4) | 2.43 (2.02 to 2.91) | 1.18 (1.04 to 1.33) |
| Pulmonary hypertension | 97/1385 (7) | 4.14 (2.85 to 6.00) | 1.13 (0.89 to 1.42) |
| Neurological disease | |||
| Cerebrovascular disease | 1704/32,778 (5.2) | 3.51 (3.16 to 3.89) | 1.07 (0.88 to 1.32) |
| Other neurological disease | 889/21,036 (4.2) | 2.57 (1.90 to 3.48) | 1.17 (1.00 to 1.36) |
| Pulmonary disease | |||
| Chronic obstructive pulmonary disease | 1320/24,621 (5.4) | 3.48 (2.83 to 4.30) | 1.15 (1.03 to 1.28) |
| Asthma | 395/23,226 (1.7) | 0.94 (0.80 to 1.11) | 0.91 (0.74 to 1.12) |
| Metabolic disease | |||
| Diabetes mellitus | 1403/34,598 (4.1) | 2.57 (2.19 to 3.03) | 1.09 (0.96 to 1.23) |
| Gastrointestinal disease | |||
| Liver disease | 877/15,468 (5.7) | 3.55 (3.01 to 4.17) | 1.57 (1.45 to 1.70) |
| Peptic ulcer | 571/10,034 (5.7) | 3.46 (2.73 to 4.38) | 1.39 (1.19 to 1.62) |
| Pancreatitis | 377/8003 (4.7) | 2.77 (2.22 to 3.46) | 1.47 (1.15 to 1.88) |
| Renal disease | 1241/19,326 (6.4) | 4.23 (3.59 to 4.97) | 1.39 (1.22 to 1.59) |
| Cancer | 3141/95,437 (3.3) | 2.39 (1.76 to 3.23) | 1.18 (1.09 to 1.29) |
| Psychiatric disorder | |||
| Affective disorders | 634/46,853 (1.4) | 0.73 (0.43 to 1.23) | 0.88 (0.63 to 1.23) |
| Mental and behavioural disorders due to use of alcohol | 641/19,778 (3.2) | 1.89 (1.49 to 2.41) | 1.26 (1.09 to 1.47) |
| Mental and behavioural disorder due to psychoactive substance use | 319/20,907 (1.5) | 0.84 (0.66 to 1.07) | 0.77 (0.67 to 0.88) |
| Schizophrenia, schizotypal and delusional disorders | 175/17,375 (1) | 0.54 (0.27 to 1.10) | 1.21 (0.87 to 1.67) |
Model adjusted for age, sex, BMI, ASA classification and comorbidities.
FIGURE 1.
Thirty‐day mortality for all cases of general anaesthesia (n = 417,730). Adjusted odds ratios for 30‐day mortality for all patient characteristics. The x‐axis is logarithmic. Model adjusted for age, sex, BMI, ASA classification and comorbidities. Abbreviations: alcohol use disorder, mental and behavioural disorders due to use of alcohol; ASA, American Society of Anesthesiologists; BMI, body mass index; COPD, chronic obstructive pulmonary disease; schizophrenia, schizophrenia, schizotypal and delusional disorders; substance use disorder, mental and behavioural disorder due to psychoactive substance abuse.
3.2. Secondary Outcomes
A total of 2.8% of cases had AKI within 7 days after general anaesthesia. For AKI within 7 days after general anaesthesia, the adjusted odds were higher for cases with higher age, male sex, higher BMI, and higher ASA classification among all cases (Table 3). Adjusted ORs with 95% CI for AKI within 7 days for unique patients and non‐cardiac cases are available in Tables S9 and S18.
TABLE 3.
Acute kidney injury within 7 days a .
| All cases (n = 453,133) counts with frequencies (%) | Unadjusted odds ratio (95% confidence interval) | Adjusted b odds ratio (95% confidence interval) | |
|---|---|---|---|
| Overall | 12,822/453,133 (2.8) | ||
| Demographics | |||
| Age (years) | |||
| 18–29 (ref) | 242/54,512 (0.4) | 1.00 (reference) | 1.00 (reference) |
| 30–39 | 334/50,976 (0.7) | 1.48 (1.23 to 1.78) | 1.21 (1.00 to 1.46) |
| 40–49 | 703/62,026 (1.1) | 2.58 (2.17 to 3.04) | 1.53 (1.32 to 1.77) |
| 50–59 | 1771/81,100 (2.2) | 5.01 (4.25 to 5.89) | 2.10 (1.62 to 2.70) |
| 60–69 | 2933/81,948 (3.6) | 8.32 (6.73 to 10.3) | 2.53 (1.84 to 3.49) |
| 70–79 | 4317/85,678 (5.0) | 11.9 (8.42 to 16.8) | 2.90 (1.91 to 4.41) |
| 80–89 | 2078/32,578 (6.4) | 15.3 (8.60 to 27.2) | 3.10 (1.75 to 5.51) |
| ≥ 90 | 444/4315 (10) | 25.7 (13.5 to 49.0) | 4.44 (2.33 to 8.48) |
| Sex | |||
| Female (ref) | 4978/242,679 (2.1) | 1.00 (reference) | 1.00 (reference) |
| Male | 7844/210,454 (3.7) | 1.85 (1.60 to 2.14) | 1.35 (1.26 to 1.44) |
| BMI (kg/m2) | |||
| < 18.5 | 449/12,118 (3.7) | 1.47 (1.27 to 1.69) | 0.97 (0.88 to 1.07) |
| 18.5–24.9 (ref) | 4133/161,650 (2.6) | 1.00 (reference) | 1.00 (reference) |
| 25–29.9 | 3942/142,772 (2.8) | 1.08 (0.99 to 1.18) | 1.03 (0.97 to 1.10) |
| 30–34.9 | 2042/65,239 (3.1) | 1.23 (1.11 to 1.36) | 1.10 (1.02 to 1.19) |
| 35–39.9 | 810/23,532 (3.4) | 1.36 (1.22 to 1.51) | 1.17 (1.06 to 1.30) |
| > 40 | 467/12,419 (3.8) | 1.49 (1.24 to 1.79) | 1.11 (0.85 to 1.43) |
| Missing | 979/35,403 (2.8) | ||
| ASA classification | |||
| I | 295/105,715 (0.3) | 0.22 (0.16 to 0.30) | 0.31 (0.24 to 0.40) |
| II (ref) | 2740/221,199 (1.2) | 1.00 (reference) | 1.00 (reference) |
| III | 6675/109,657 (6.1) | 5.17 (4.18 to 6.39) | 3.48 (2.60 to 4.66) |
| IV | 2875/13798 (21) | 21.0 (15.3 to 28.9) | 13.1 (8.52 to 20.1) |
| V | 160/490 (33) | 38.7 (24.7 to 60.5) | 25.4 (14.5 to 44.4) |
| Missing | 77/2274 (3.4) | ||
| Comorbidities | |||
| Cardiovascular disease | |||
| Ischemic heart disease | 2844/40,067 (7.1) | 3.09 (2.66 to 3.59) | 1.05 (0.94 to 1.17) |
| Heart failure | 1630/16219 (10) | 4.25 (3.66 to 4.94) | 1.13 (1.04 to 1.22) |
| Hypertension | 5332/85,961 (6.2) | 3.18 (2.80 to 3.60) | 1.21 (1.12 to 1.31) |
| Atrial fibrillation/flutter | 2400/35,505 (6.8) | 2.83 (2.39 to 3.35) | 0.91 (0.86 to 0.97) |
| Other cardiac dysrhythmias | 1144/21,884 (5.2) | 1.98 (1.75 to 2.24) | 0.93 (0.88 to 0.99) |
| Peripheral vascular disease | 1586/19,065 (8.3) | 3.41 (2.91 to 4.01) | 1.11 (1.02 to 1.20) |
| Hypercholesterolemia | 1594/29,359 (5.4) | 2.11 (1.89 to 2.35) | 0.81 (0.76 to 0.87) |
| Venous thromboembolism | 974/19,680 (5.0) | 1.85 (1.61 to 2.13) | 0.96 (0.87 to 1.06) |
| Pulmonary hypertension | 140/1385 (10) | 3.89 (3.15 to 4.82) | 1.26 (1.12 to 1.42) |
| Neurological disease | |||
| Cerebrovascular disease | 1884/32,778 (5.8) | 2.28 (1.99 to 2.61) | 0.86 (0.82 to 0.94) |
| Other neurological disease | 775/21,036 (3.7) | 1.33 (1.05 to 1.69) | 0.81 (0.74 to 0.90) |
| Pulmonary disease | |||
| Chronic obstructive pulmonary disease | 1531/24,621 (6.2) | 2.45 (2.01 to 2.99) | 0.97 (0.86 to 1.10) |
| Asthma | 606/23,226 (2.6) | 0.92 (0.84 to 1.00) | 0.83 (0.76 to 0.90) |
| Metabolic disease | |||
| Diabetes mellitus | 2400/34,598 (6.9) | 2.92 (2.60 to 3.28) | 1.08 (1.01 to 1.16) |
| Gastrointestinal disease | |||
| Liver disease | 1038/15,468 (6.7) | 2.60 (2.25 to 3.00) | 1.29 (1.15 to 1.44) |
| Peptic ulcer | 681/10,034 (6.8) | 2.58 (2.07 to 3.23) | 1.19 (1.03 to 1.37) |
| Pancreatitis | 443/8003 (5.5) | 2.05 (1.66 to 2.53) | 1.14 (0.98 to 1.32) |
| Renal disease | 2691/19,326 (14) | 6.77 (5.96 to 7.67) | 2.78 (2.40 to 3.23) |
| Cancer | 4145/95,437 (4.3) | 1.82 (1.27 to 2.62) | 0.98 (0.80 to 1.20) |
| Psychiatric disorder | |||
| Affective disorders | 757/46,853 (1.6) | 0.54 (0.31 to 0.92) | 0.63 (0.43 to 0.92) |
| Mental and behavioural disorders due to use of alcohol | 754/19,778 (3.8) | 1.38 (1.00 to 1.91) | 1.00 (0.74 to 1.35) |
| Mental and behavioural disorder due to psychoactive substance use | 555/20,907 (2.7) | 0.93 (0.74 to 1.18) | 1.00 (0.90 to 1.11) |
| Schizophrenia, schizotypal and delusional disorders | 228/17,375 (1.3) | 0.45 (0.23 to 0.88) | 0.82 (0.57 to 1.18) |
AKI diagnosis based on KDIGO criteria. Imputed data were used when no baseline creatinine values were available. Further description in supplement.
Model adjusted for age, sex, BMI, ASA classification and comorbidities.
The mean and median length of hospital stay after general anaesthesia for all cases was 3.4 ± 10 days and 0.7 [0.2–2.3] days, respectively. In the adjusted analyses of all cases, the mean hospital length of stay was longer for cases with male sex and higher ASA classification (Table 4). MDs in length of hospital stay after general anaesthesia for unique patients and non‐cardiac cases are available in Tables S10 and S19.
TABLE 4.
Length of hospital stay in days after general anaesthesia.
| All cases a (n = 404,896) medians [IQR] | Unadjusted mean difference in days (95% confidence interval) | Adjusted b mean difference in days (95% confidence interval) | |
|---|---|---|---|
| Overall | 0.7 [2.3 to 0.2] | ||
| Demographics | |||
| Age (years) | |||
| 18–29 (ref) | 0.3 [0.2 to 0.9] | Reference | Reference |
| 30–39 | 0.3 [0.2 to 1.0] | 0.2 (0.1 to 0.4) | 0.1 (−0.1 to 0.2) |
| 40–49 | 0.3 [0.2 to 1.2] | 0.7 (0.3 to 1.1) | 0.1 (−0.1 to 0.3) |
| 50–59 | 0.4 [0.2 to 2.0] | 1.8 (0.9 to 2.7) | 0.5 (0.3 to 0.7) |
| 60–69 | 1.0 [0.2 to 3.2] | 2.7 (1.6 to 3.9) | 0.5 (0.3 to 0.8) |
| 70–79 | 1.1 [0.3 to 4.3] | 3.2 (2.4 to 4.) | 0.3 (−0.2 to 0.7) |
| 80–89 | 2.1 [0.8 to 6.1] | 3.3 (2.8 to 3.9) | −0.5 (−1.8 to 0.9) |
| ≥ 90 | 4.1 [1.3 to 7.5] | 4.1 (3.4 to 4.9) | −0.7 (−2.7 to 1.3) |
| Sex | |||
| Female (ref) | 0.6 [0.2 to 2.1] | Reference | Reference |
| Male | 0.8 [0.2 to 3.0] | 1.0 (0.4 to 1.6) | 0.2 (0.1 to 0.4) |
| BMI (kg/m2) | |||
| < 18.5 | 1.1 [0.2 to 5.2] | 1.5 (1.1 to 2.0) | −0.2 (−0.8 to 0.3) |
| 18.5–24.9 (ref) | 0.5 [0.2 to 2.3] | Reference | Reference |
| 25–29.9 | 0.6 [0.2 to 2.1] | −0.3 (−0.4 to −0.1) | −0.3 (−0.4 to −0.1) |
| 30–34.9 | 0.8 [0.2 to 2.2] | −0.2 (−0.5 to 0.1) | −0.5 (−0.9 to −0.1) |
| 35–39.9 | 0.9 [0.2 to 2.2] | 0.1 (−0.2 to 0.4) | −0.5 (−0.9 to −0.2) |
| > 40 | 1.0 [0.3 to 2.3] | 0.9 (0.3 to 1.5) | −1.3 (−2.2 to −0.5) |
| Missing | 0.9 [0.2 to 3.1] | ||
| ASA classification | |||
| I | 0.3 [0.2 to 0.9] | −1.1 (−1.4 to −0.8) | −1.2 (−1.7 to −0.7) |
| II (ref) | 0.4 [0.2 to 1.3] | Reference | Reference |
| III | 2.0 [0.4 to 6.4] | 4.3 (3.1 to 5.5) | 4.5 (3.0 to 5.9) |
| IV | 7.4 [3.0 to 20] | 15.4 (11.1 to 19.7) | 15.3 (11.0 to 20.0) |
| V | 12 [2.0 to 29] | 22.1 (14.9 to 29.2) | 20.7 (14.9 to 26.6) |
| Missing | 1.1 [0.2 to 3.6] | ||
| Comorbidities | |||
| Cardiovascular disease | |||
| Ischemic heart disease | 1.3 [0.3 to 5.6] | 2.1 (1.5 to 2.7) | −0.9 (−1.4 to −0.3) |
| Heart failure | 2.0 [0.5 to 7.2] | 3.2 (2.2 to 4.2) | −0.5 (−1.0 to 0.0) |
| Hypertension | 1.2 [0.3 to 5.1] | 2.0 (1.6 to 2.5) | −0.2 (−0.4 to 0.0) |
| Atrial fibrillation/flutter | 1.2 [0.3 to 5.5] | 2.0 (1.5 to 2.5) | −0.5 (−0.8 to −0.2) |
| Other cardiac dysrhythmias | 1.1 [0.3 to 4.3] | 1.2 (0.9 to 1.6) | −0.4 (−0.6 to −0.2) |
| Peripheral vascular disease | 2.4 [0.6 to 7.5] | 3.6 (3.0 to 4.2) | 0.6 (−0.0 to 1.1) |
| Hypercholesterolemia | 1.2 [0.3 to 5.1] | 2.0 (1.3 to 2.6) | −0.3 (−0.6 to 0.0) |
| Venous thromboembolism | 1.2 [0.3 to 5.1] | 1.7 (1.3 to 2.1) | 0.0 (−0.4 to 0.4) |
| Pulmonary hypertension | 2.0 [0.5 to 7.6] | 3.5 (2.1 to 4.9) | −0.1 (−0.8 to 0.6) |
| Neurological disease | |||
| Cerebrovascular disease | 1.9 [0.3 to 6.7] | 4.9 (2.5 to 7.3) | 2.3 (0.3 to 4.3) |
| Other neurological disease | 1.2 [0.3 to 5.2] | 1.9 (1.1 to 2.7) | −0.4 (−1.1 to 0.3) |
| Pulmonary disease | |||
| Chronic obstructive pulmonary disease | 1.2 [0.3 to 6.0] | 2.1 (1.7 to 2.6) | −0.7 (−1.1 to −0.2) |
| Asthma | 0.7 [0.2 to 2.2] | −0.2 (−0.4 to 0.0) | −0.5 (−0.7 to −0.2) |
| Metabolic disease | |||
| Diabetes mellitus | 1.2 [0.3 to 6.0] | 2.1 (1.67 to 2.5) | −0.4 (−0.8 to 0.1) |
| Gastrointestinal disease | |||
| Liver disease | 1.3 [0.3 to 6.1] | 2.5 (2.1 to 3.0) | −1.0 (−2.1 to 0.1) |
| Peptic ulcer | 2.0 [0.3 to 6.3] | 2.7 (2.2 to 3.2) | 0.5 (0.1 to 0.9) |
| Pancreatitis | 1.1 [0.3 to 6.0] | 3.8 (1.5 to 6.0) | 2.3 (0.2 to 4.3) |
| Renal disease | 1.6 [0.3 to 7.1] | 3.3 (2.5 to 4.1) | 0.3 (−0.2 to 0.8) |
| Cancer | 1.1 [0.3 to 4.2] | 1.2 (0.5 to 1.8) | −0.2 (−0.7 to 0.3) |
| Psychiatric disorder | |||
| Affective disorders | 0.6 [0.2 to 2.3] | 0.0 (−0.4 to 0.4) | −0.3 (−0.6 to 0.0) |
| Mental and behavioural disorders due to use of alcohol | 1.1 [0.2 to 5.7] | 2.5 (1.9 to 3.0) | 0.7 (0.1 to 1.2) |
| Mental and behavioural disorder due to psychoactive substance use | 0.5 [0.2 to 3.2] | 0.7 (0.3 to 1.1) | −0.1 (−0.5 to 0.2) |
| Schizophrenia, schizotypal and delusional disorders | 0.5 [0.2 to 2.9] | 0.6 (−0.1 to 1.3) | 0.3 (−0.4 to 1.0) |
About 48,237 cases had missing values for length of stay after general anaesthesia and were not included in the model.
Model adjusted for age, sex, BMI, ASA classification and comorbidities.
A total of 17,847 (3.9%) of all cases had an ICU stay within 30 days of general anaesthesia. The mean number of days admitted to an ICU within 30 days of general anaesthesia was 5.4 ± 7.6 days for all cases with an ICU admission. The adjusted ORs with 95% CI for any ICU stay within 30 days of general anaesthesia are available in Table 5. The mean number of days in ICU was longer for cases with higher ASA classification and decreased in the oldest patient groups (Table S3). Adjusted ORs for any ICU stay within 30 days of general anaesthesia and MDs in number of days admitted to an ICU within 30 days of general anaesthesia for unique patients and non‐cardiac cases are available in Tables S11, S12, S20 and S21.
TABLE 5.
Any ICU stay within 30 days of general anaesthesia.
| All cases (n = 453,133) counts with frequencies (%) | Unadjusted odds ratio (95% confidence interval) | Adjusted a odds ratio (95% confidence interval) | |
|---|---|---|---|
| Overall | 17,847/453,133 (3.9) | ||
| Demographics | |||
| Age (years) | |||
| 18–29 (ref) | 714/54,512 (1.3) | 1.00 (reference) | 1.00 (reference) |
| 30–39 | 805/50,976 (1.6) | 1.21 (1.08 to 1.35) | 1.01 (0.90 to 1.13) |
| 40–49 | 1290/62,026 (2.1) | 1.60 (1.30 to 1.97) | 0.96 (0.80 to 1.16) |
| 50–59 | 3009/81,100 (3.7) | 2.90 (2.39 to 3.53) | 1.16 (0.97 to 1.38) |
| 60–69 | 4533/81,948 (5.5) | 4.41 (3.49 to 5.57) | 1.23 (0.96 to 1.57) |
| 70–79 | 5514/85,678 (6.4) | 5.18 (3.76 to 7.15) | 1.13 (0.78 to 1.63) |
| 80–89 | 1780/32,578 (5.5) | 4.35 (2.41 to 7.87) | 0.74 (0.39 to 1.38) |
| ≥ 90 | 202/4315 (4.7) | 3.70 (1.84 to 7.45) | 0.47 (0.24 to 0.93) |
| Sex | |||
| Female (ref) | 6836/242,679 (2.8) | 1.00 (reference) | 1.00 (reference) |
| Male | 11,011/210,454 (5.2) | 1.90 (1.53 to 2.37) | 1.31 (1.13 to 1.53) |
| BMI (kg/m2) | |||
| < 18.5 | 605/12,118 (5) | 1.36 (1.00 to 1.86) | 0.75 (0.62 to 0.90) |
| 18.5–24.9 (ref) | 6001/161,650 (3.7) | 1.00 (reference) | 1.00 (reference) |
| 25–29.9 | 5598/142,772 (3.9) | 1.06 (0.93 to 1.20) | 1.02 (0.96 to 1.09) |
| 30–34.9 | 2708/65,239 (4.2) | 1.12 (1.02 to 1.24) | 0.98 (0.92 to 1.04) |
| 35–39.9 | 961/23,532 (4.1) | 1.10 (0.99 to 1.24) | 0.81 (0.73 to 0.91) |
| > 40 | 579/12,419 (4.7) | 1.27 (1.02 to 1.58) | 0.59 (0.45 to 0.77) |
| Missing | 1395/35,403 (3.9) | ||
| ASA classification | |||
| I | 435/105,715 (0.4) | 0.32 (0.24 to 0.43) | 0.28 (0.20 to 0.39) |
| II (ref) | 2800/221,199 (1.3) | 1.00 (reference) | 1.00 (reference) |
| III | 8317/109,657 (7.6) | 6.40 (4.79 to 8.55) | 7.42 (4.98 to 11.1) |
| IV | 5787/13798 (42) | 56.3 (32.9 to 96.4) | 64.5 (34.0 to 122) |
| V | 339/490 (69) | 175 (83.1 to 369) | 167 (76 to 367) |
| Missing | 169/2274 (7.4) | ||
| Comorbidities | |||
| Cardiovascular disease | |||
| Ischemic heart disease | 4204/40,067 (10) | 3.43 (2.42 to 4.87) | 1.43 (0.95 to 2.15) |
| Heart failure | 1831/16219 (11) | 3.34 (2.85 to 3.92) | 0.93 (0.85 to 1.01) |
| Hypertension | 5496/85,961 (6.4) | 1.96 (1.71 to 2.26) | 0.92 (0.87 to 0.98) |
| Atrial fibrillation/flutter | 2659/35,505 (7.5) | 2.15 (1.74 to 2.64) | 0.89 (0.80 to 0.98) |
| Other cardiac dysrhythmias | 1395/21,884 (6.4) | 1.72 (1.48 to 1.99) | 0.91 (0.80 to 1.03) |
| Peripheral vascular disease | 1642/19,065 (8.6) | 2.43 (1.74 to 3.39) | 0.82 (0.62 to 1.06) |
| Hypercholesterolemia | 1876/29,359 (6.4) | 1.74 (1.58 to 1.93) | 0.74 (0.66 to 0.84) |
| Venous thromboembolism | 1121/19,680 (5.7) | 1.50 (1.18 to 1.91) | 0.85 (0.72 to 1.00) |
| Pulmonary hypertension | 175/1385 (13) | 3.55 (2.68 to 4.71) | 1.20 (0.97 to 1.48) |
| Neurological disease | |||
| Cerebrovascular disease | 3192/32,778 (9.7) | 2.97 (2.44 to 3.65) | 1.26 (0.96 to 1.66) |
| Other neurological disease | 1031/21,036 (4.9) | 1.27 (1.01 to 1.61) | 0.69 (0.60 to 0.97) |
| Pulmonary disease | |||
| Chronic obstructive pulmonary disease | 1812/24,621 (7.4) | 0.71 (1.48 to 2.83) | 0.85 (0.68 to 1.06) |
| Asthma | 831/23,226 (3.6) | −0.10 (0.80 to 1.02) | 0.84 (0.74 to 0.97) |
| Metabolic disease | |||
| Diabetes mellitus | 2452/34,598 (7.1) | 0.69 (1.74 to 2.30) | 0.89 (0.84 to 0.95) |
| Gastrointestinal disease | |||
| Liver disease | 1321/15,468 (8.5) | 2.38 (1.81 to 3.13) | 1.02 (0.86 to 1.20) |
| Peptic ulcer | 945/10,034 (9.4) | 2.62 (1.70 to 4.03) | 1.44 (1.14 to 1.83) |
| Pancreatitis | 551/8003 (6.9) | 1.83 (1.22 to 2.74) | 0.98 (0.73 to 1.31) |
| Renal disease | 1573/19,326 (8.1) | 2.27 (1.64 to 3.15) | 0.81 (0.61 to 1.07) |
| Cancer | 4243/95,437 (4.5) | 1.18 (0.75 to 1.84) | 0.63 (0.47 to 0.85) |
| Psychiatric disorder | |||
| Affective disorders | 1144/46,853 (2.4) | 0.58 (0.34 to 1.00) | 0.70 (0.53 to 0.92) |
| Mental and behavioural disorders due to use of alcohol | 1250/19,778 (6.3) | 1.69 (1.20 to 2.40) | 1.03 (0.82 to 1.28) |
| Mental and behavioural disorder due to psychoactive substance use | 887/20,907 (4.2) | 1.08 (0.89 to 1.33) | 1.00 (0.88 to 1.13) |
| Schizophrenia, schizotypal and delusional disorders | 437/17,375 (2.5) | 0.62 (0.30 to 1.26) | 0.89 (0.61 to 1.28) |
Model adjusted for age, sex, BMI, ASA classification and comorbidities.
3.3. Additional Outcomes
The analyses of the supplementary outcomes of 90‐day mortality (Table S4), AKI within 30 days (Table S5), in‐hospital cardiac arrest within 30 days (Table S6), and need for mechanical ventilation within 7 days (Table S7), had results similar to those observed for the primary and secondary outcomes. The ORs with 95% CI for supplementary outcomes for all cases, unique patients and non‐cardiac cases are available in Tables S13–S16 and S22–S25. Post hoc analyses of 30‐day mortality adjusted for urgency and adjusted for smoking and alcohol use for all cases are available in Tables S26 and S27.
4. Discussion
In this nationwide observational cohort study, we evaluated the associations between patient characteristics and outcomes after general anaesthesia in Denmark. We found that higher ASA classification was associated with increased odds of mortality and all secondary outcomes. This association persisted when adjusting for other patient characteristics such as age, sex and comorbidities. We found that higher age and male sex were associated with increased odds of 30‐day mortality in the adjusted analyses. The findings remained consistent in the analyses of unique patients and non‐cardiac procedure cases.
Previous studies have investigated the association between ASA classification and mortality [5, 9, 25, 26, 27]. These studies consistently showed that higher ASA classification was associated with increased mortality and are thus in line with our study. Although Hackett et al. [5] studied the association between ASA and mortality in surgical cases across specialties from 2005 to 2012, other studies were conducted in small populations undergoing specific surgical procedures such as endometrial cancer surgery [25], bladder cancer surgery [26], and surgery for acute hip fracture [27] or limited to certain patient populations, that is patients aged above 80 years [9]. In comparison to previous studies, our large cohort study included cases of general anaesthesia for both surgical and non‐surgical procedures, thus comprehensively representing the contemporary population receiving general anaesthesia in Denmark.
Previous studies on the association between sex and mortality in patients undergoing specific procedures differ in their findings, as two studies found a lower mortality in women [9, 28, 29], others were neutral [30, 31], and some found a lower mortality in men [32, 33]. In our study, male sex was independently associated with higher odds of 30‐day mortality and other assessed outcomes. The inconsistencies between studies are hard to interpret. Some of the interstudy differences might be mediated by unmeasured risk factors such as smoking, alcohol use, type of surgery and the severity of comorbidities.
We found that higher BMI was associated with lower mortality. This association between higher BMI and lower mortality is a well‐described phenomenon termed the ‘obesity paradox’ [34, 35]. It is generally believed that this association may be explained by residual confounding and collider bias [35, 36]. In our study, the cohort is selected based on receiving a procedure under general anaesthesia. This may be a collider in the association between BMI and mortality. As an example, patients with higher BMI and a high comorbidity burden might never be candidates for a procedure with general anaesthesia and are therefore not included in our study. Thus, a spurious (i.e., non‐causal) association between BMI and mortality may be observed when restricting the cohort to those with a procedure with general anaesthesia [36].
The specific comorbidities in our study had varying associations with 30‐day mortality. The reduced odds of 30‐day mortality for some comorbidities, for example, ischaemic heart disease and hypercholesterolaemia, might potentially be explained by collider bias influencing the association between some comorbidities and outcomes.
Our study provides insights into the patient population undergoing general anaesthesia and identifies several patient characteristics associated with worse outcomes in Denmark. These findings carry several implications. First, the associations between patient characteristics and outcomes identified in this study may inform clinicians about high‐risk patients in need of comprehensive postoperative observation, that is, through close monitoring and frequent use of early warning systems to detect and treat any complications at an early stage. Second, they may help generate new hypotheses and lay the foundation for future observational studies investigating the associations between patient characteristics and outcomes in specific patient populations, for example, patients with high age undergoing procedures requiring general anaesthesia. Third, the data presented here create an overview of the current patient population undergoing general anaesthesia; thus, the data may inform future randomised clinical trials about suitable patients and relevant outcomes for investigation to reduce the risk of complications. Fourth, the insights of this study may provide guidance for future quality assurance projects and clinical improvement initiatives aimed at improving outcomes after general anaesthesia, as the findings of this study offer guidance on identifying relevant patient groups towards which efforts should be addressed.
Our study has several strengths. This nationwide study leveraged the rich tradition for registries in Denmark and linkage through the unique civil personal register number. This allowed us to study many individual‐level predictors and outcomes with limited loss to follow‐up [10]. In addition, this enabled us to study a large cohort of patients undergoing general anaesthesia in Denmark, thereby increasing the precision of our outcome estimates and facilitating the study of rare outcomes such as in‐hospital cardiac arrest. The universal healthcare model in Denmark ensures that the cohort is a representation of the population receiving general anaesthesia in Denmark, as patients across demographic and socioeconomic statuses are included. The Danish health care model and patient cohort are comparable to similar cohorts, that is, the Swedish cohort investigated by Eriksson et al. [9] and the American cohort by Hackett et al. [5] Caution is warranted when generalising the findings of this study to other populations, such as those from low‐and middle‐income countries. At last, our study was not limited to specific patient settings or specific surgical procedures.
The findings of our study need to be interpreted in the context of some limitations. First, we did not have access to sufficient data on some variables that are likely to affect outcomes, such as smoking and alcohol status. It was not possible to distinguish between planned and unplanned ICU admissions. Second, despite mandatory reporting to the Danish Anaesthesia Database, not all hospitals reported all cases of general anaesthesia in 2020 and 2021. Moreover, our data were collected during the COVID‐19 pandemic. These factors may potentially affect the generalisability of our results. However, the data completeness of the Danish Anaesthesia Database is estimated to be high and did not vary substantially in 2020 and 2021 [4, 12, 13]. Furthermore, the Danish health care system had a low COVID‐19 related mortality and capacity strain compared to other countries [37]. Third, we could not report multivariable analyses for myocardial injury and stroke, as these outcomes were too rare for meaningful analyses. In addition, data on other post‐operative complications, such as pneumonia and surgical site infections, and data on surgical risk assessment scores, such as Physiological and Operative Severity Score for the enumeration of Mortality and morbidity (POSSUM) or National Surgical Quality Improvement Program Surgical Risk Calculator (NSQIP), were not available. Fourth, the aim of this study was to identify patient characteristics associated with worse outcomes after general anaesthesia in Denmark. As such, we deemed information on the anaesthetic management to be outside the scope of this study.
5. Conclusion
In this nationwide registry‐based cohort study, we found that higher ASA classification, higher age and male sex were independently associated with increased risk of mortality as well as secondary outcomes.
This study might help identify patient groups suitable for further studies investigating initiatives to reduce the risk of complications and provide guidance for future quality assurance projects.
Author Contributions
Benjamin H. Risager: conceptualisation, methodology, formal analysis, investigation, data curation, writing – original draft, visualisation. Signe Ø. Mortensen: conceptualisation, methodology, formal analysis, investigation, data curation, writing – review and editing. Maria B. Pælestik: conceptualisation, methodology, writing – review and editing, supervision. Peter C. Lind: conceptualisation, methodology, writing – review and editing, supervision. Nikola Stankovic: conceptualisation, methodology, writing – review and editing, supervision. Lars W. Andersen: conceptualisation, methodology, writing – review and editing, supervision, project administration, funding acquisition.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Data S1: aas70130‐sup‐0001‐Supinfo.docx.
Risager B. H., Mortensen S. Ø., Pælestik M. B., Lind P. C., Stankovic N., and Andersen L. W., “Patient Characteristics Associated With Outcomes After General Anaesthesia in Denmark: A Nationwide Observational Study,” Acta Anaesthesiologica Scandinavica 69, no. 10 (2025): e70130, 10.1111/aas.70130.
Funding: This study was partly funded by the Independent Research Fund Denmark.
Data Availability Statement
The data used in the study can be obtained from the Danish Health Data Authority and the Danish Clinical Quality Program—National Clinical Registries (RKKP).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data S1: aas70130‐sup‐0001‐Supinfo.docx.
Data Availability Statement
The data used in the study can be obtained from the Danish Health Data Authority and the Danish Clinical Quality Program—National Clinical Registries (RKKP).