ABSTRACT
Background and Objectives
Asthma is the most common chronic disease in children. Difficulty in diagnosis can lead to decreased quality of life and increased morbidity and mortality. Children with asthma have increased intraoperative bronchospasm; however, it is unclear whether intraoperative bronchospasm predicts future asthma. We explored intraoperative bronchospasm and subsequent asthma diagnosis.
Methods
We retrospectively analyzed 44,284 children aged 2–18 years who underwent non‐cardiac surgery under general anesthesia between 2014 and 2020. We collected demographic and peri‐operative data, including the occurrence of bronchospasm. We then conducted a subgroup analysis of 35 770 patients that received positive pressure ventilation, using logistic regression to assess the relationship between bronchospasm and airway pressures. The association of bronchospasm and subsequent asthma diagnosis was estimated using generalized estimating equations.
Results
Intraoperative bronchospasm occurred in 128 patients (0.3%) and was associated with increased risk of asthma (OR 2.29, 95% CI 1.10–4.74, p = 0.03). Asthma was diagnosed in 1238 patients (2.8%); 8 had intraoperative bronchospasm (8 of 1238, 0.7%). After adjustment for confounders, male sex (OR 1.57, 95% CI 1.39–1.76, p < 0.001) and younger age (OR 0.96, 95% CI 0.94–0.97, p < 0.001) were also associated with future asthma diagnosis. In the subgroup analysis, Mean PIP (OR 1.50, 95% CI 1.30–1.74, p < 0.001) was associated with asthma.
Conclusions
This study shows intraoperative bronchospasm is associated with an increased risk of future asthma in children. Enhanced collaboration between pediatric anesthesiologists and pediatricians, and further research, is essential to improve asthma detection, risk stratification, and overall care for pediatric patients.
Keywords: asthma, bronchospasm, general anesthesia, pediatrics
1. Introduction
Asthma is the most common chronic disease among the pediatric population, with an overall prevalence of 6.5% according to the Centers for Disease Control and Prevention [1], with up to 17% of children in the US afflicted by asthma [2]. It is typically characterized by respiratory symptoms, specifically wheezing, shortness of breath, chest tightness, and cough [3]. In infants and toddlers, symptoms can present slightly differently with tachypnea, chest retractions, nostril flaring, persistent cough, difficulty with feeding, and fatigue. Despite its prevalence, asthma remains challenging to diagnose and there are likely many children who remain undiagnosed [4, 5, 6]. Undiagnosed asthma can lead to increased psychosocial and medical co‐morbidities including chronic obstructive pulmonary disease (COPD), higher rates of absences from school, increased hospitalizations and emergency department visits, and an increased risk of pulmonary complications related to irritants, exercise, or other environmental triggers. These airway irritants include volatile anesthetics and airway manipulation such as an endotracheal intubation, which can lead to bronchospasm during procedures that require anesthesia [7, 8, 9, 10, 11]. Early identification, diagnosis, and treatment of asthma/bronchospasm is important in order to minimize both short‐and long‐term negative impacts on health outcomes [12, 13].
Perioperative bronchospasm in the pediatric population has an incidence between 0.3% and 3.2%, with considerable variation across different centers, with the majority occurring intra‐operatively [13, 14]. A previous study has demonstrated that asthmatic patients have a higher incidence of intraoperative bronchospasm compared to non‐asthmatic patients [15]. However, it has not been shown whether intraoperative bronchospasm is a predictor for future diagnosis of asthma. We aimed to better understand the relationship between intraoperative bronchospasm and postoperative diagnosis of asthma. We hypothesized that intraoperative bronchospasm is associated with an increased incidence of subsequent asthma diagnosis in pediatric patients.
2. Methods
We obtained Institutional Review Board approval for this single‐center, retrospective cohort study, which waived patient or guardian consent for the use of deidentified data. Using the institution's data warehouse, we identified pediatric patients ages 2–18 years who underwent surgery with general anesthesia between July 1, 2014, and June 30, 2020. We obtained basic demographic and pre‐operative data including age, gender, height, weight, procedure, and comorbidities, such as recent respiratory infection, obstructive sleep apnea (OSA), asthma, bronchopulmonary dysplasia (BPD), prematurity, eczema, and allergies. We also obtained details pertaining to the anesthetic, including inhalational versus intravenous induction, use of endotracheal tube, medications administered, and intra‐operative complications.
Inclusion criteria comprised the following: (1) Pediatric surgical patients aged 2–18 years who underwent general anesthesia, as younger patients have a known predisposition for bronchospasm and respiratory adverse events in the perioperative period compared to older children [14, 16, 17]. (2) No prior history of asthma, and (3) Received at least one follow‐up visit with a University of Michigan primary care physician (PCP) prior to August 1, 2020. Exclusion criteria included the following: (1) Previous diagnosis of asthma, (2) History of lung disease, including obstructive sleep apnea (OSA), bronchopulmonary dysplasia (BPD), prematurity defined as < 30 weeks gestational age (GA) at birth, as these children have the highest risk of BPD and physiologically tend to have the most respiratory issues related to decreased surfactant [18], congenital diaphragmatic hernias (CDH), congenital pulmonary airway malformation/congenital cystic adenomatous malformation (CPAM/CCAM) or other lesions with significant pulmonary hypoplasia, (3) History of airway defects, (4) Cystic Fibrosis, (5) Airway surgery specific to the larynx and distal to the larynx, (6) Open heart procedures to exclude any airway manipulation or defects affecting the airway, such as vascular rings or prolonged endotracheal intubation, and (7) Allergies, specifically food and seasonal allergies, given the predisposition to reactive airway disease [19]. Our outcome was new postoperative asthma diagnosis.
2.1. Case and Control Definitions
The main analysis was performed on intra‐operatively documented “bronchospasm” defined by the following criteria: documentation of bronchospasm in the anesthetic record and/or intraoperative use of albuterol and/or intravenous epinephrine. To confirm the existence of bronchospasm in patients where the etiology was unclear, individual charts were reviewed by a pediatric anesthesiologist who was blinded to the asthma diagnosis, examining multifactorial markers such as peak inspiratory pressures (PIP), oxygen saturation, medication administration, and timing in conjunction with the clinical findings and clinician notes. The first sensitivity analysis included cases with recorded bronchospasm, intraoperative use of an albuterol metered dose inhaler or intravenous epinephrine at dosages ranging from 0.1 to 1 mcg/kg, with or without the administration of intravenous magnesium, and without documentation indicating another etiology, such as hypotension or anaphylaxis. Since bronchospasm was suspected to be under‐reported in the medical record, we created two additional bronchospasm variables (Highest PIP and Mean PIP). Highest PIP was defined as the highest PIP between the time when PIP was first > 5 cmH2O after induction and the first PIP that was ≤ 5 cmH20 within 30 min before anesthesia end. Mean PIP was determined over the same time interval encompassing all nonfiltered breaths. To do this, we created a subgroup of patients who received positive pressure ventilation. We then used logistic regression to estimate based on both peak and mean airway pressures patients those who had versus those who did not have bronchospasm by the main analysis. Of note, the default mode of ventilation on the anesthesia machines at our pediatric hospital is pressure control ventilation.
Fragility index was determined by calculating the number of events that would need to be non‐events in order to no longer have a statistically significant p‐value [20].
2.2. Statistical Analysis
Initial exploratory data analysis was conducted to obtain descriptive statistics. The balance of covariates and confounders between the asthma and no asthma groups was assessed using standardized differences (StDiff).
In addition to the exposure variable presence of bronchospasm, variables selected a priori for consideration in multivariable modeling included the following: patient age, gender, race, anesthesia induction type, presence of an endotracheal tube, anesthesia time, American Society of Anesthesiologists physical status, body mass index (BMI), and gestational age. All variables were assessed for multicollinearity prior to model construction using Pearson correlation coefficients and variance inflation factors.
To identify Highest and Mean PIP values which might be associated with bronchospasm in patients receiving intraoperative positive pressure ventilation, those without bronchospasm were matched based on age, sex, ASA physical status, and emergency status 5:1 to those with bronchospasm. Then, using logistic regression, we used Youden's index to identify a threshold of both Highest and Mean PIP suggestive of bronchospasm.
Multiple imputation using chained equations to impute missing values was used to generate five completed datasets, and results of subsequent analyses were pooled using Rubin's Rules.
To assess the association between bronchospasm and the primary outcome of asthma diagnoses, we used generalized estimating equations models both for the main analysis of all patients and for the subgroup sensitivity analysis of patients receiving positive pressure ventilation. Both analyses adjusted bronchospasm for the confounders. A parsimonious model was decided upon using variables with a p < 0.1 from the full model. Odds ratios and 95% confidence intervals were calculated, and goodness‐of‐fit was assessed using areas under the receiver operating characteristics (AUROC) and precision recall curves (AUPRC) [21]. p‐values < 0.05 and 95% confidence intervals of the odds ratios that excluded 1 were considered statistically significant. Variables with a StDiff > 20% represented clinical relevance and p‐values < 0.05 signify statistical significance. Analysis was performed using statistical analysis system programming (SAS) v. 9.4 (SAS Institute, Cary, NC).
3. Results
In our main analysis, after excluding 5209 patients, we studied a total of 44 284 patients undergoing non‐cardiac surgery under general anesthesia (Figure 1). Most patients were male (n = 22 814, 51.5%), White (n = 35 848, 81.0%), and ASA 1 or 2 (n = 33 535, 75.7%) [Table 1]. Only 3114 (7%) were emergency cases. Patients' ages ranged from 2 to 18 years with a mean (standard deviation) age of 10 years. (5). About half (n = 20 761, 46.9%) of patients had an endotracheal tube. Bronchospasm occurred in 128 patients (0.3%). Asthma was subsequently diagnosed in 1238 patients (2.8%) at a mean follow‐up of 1.55 years. (1.34). Patients with a new asthma diagnosis were more likely to be male (60.8% vs. 51.3%, StDiff = 19.4%, p < 0.001), ASA 3 or higher (43.2% vs. 23.7%, StDiff = 57%, p < 0.001) and less likely to have an endotracheal tube (37.7% vs. 47.1%, StDiff = 19.2%, p < 0.001). Bronchospasm was present in eight patients who subsequently were diagnosed with asthma and in 120 patients who did not receive a diagnosis of asthma (8 of 1238, 0.7% vs. 120 of 43 046, 0.3%, Stdiff = 5.4%, p = 0.02).
FIGURE 1.
Flowchart of patient inclusion and exclusion criteria in the main and subgroup analysis. *including Bronchopulmonary dysplasia (BPD), prematurity, congenital diaphragmatic hernia. **including obstructive sleep apnea (OSA).
TABLE 1.
Descriptive characteristics of the sample: main analysis.
| Total (N = 44 284) | Asthma (n = 1238) | No asthma (n = 43 046) | StDiff | |||||
|---|---|---|---|---|---|---|---|---|
| Variable | Mean | SD | Mean | SD | Mean | SD | % | p |
| Age (years) | 10.0 | 5.3 | 9.4 | 5.2 | 10.0 | 5.3 | 11.6 | < 0.001 |
| BMI (kg/m2) | 20.0 | 5.6 | 20.3 | 6.0 | 20.0 | 5.6 | 5.2 | 0.06 |
| Total Anesthesia time (min) | 119.1 | 109.7 | 101.2 | 103.7 | 119.6 | 109.8 | 17.3 | < 0.001 |
| N | % | N | % | N | % | |||
|---|---|---|---|---|---|---|---|---|
| Sex | ||||||||
| Male | 22 814 | 51.5 | 753 | 60.8 | 22 061 | 51.3 | 19.4 | < 0.001 |
| Female | 21 470 | 48.5 | 485 | 39.2 | 20 985 | 48.8 | ||
| Race/Ethnicity | ||||||||
| White + Middle Eastern | 35 848 | 81 | 1007 | 81.3 | 34 841 | 80.9 | 2.1 | 0.91 |
| Black + biracial | 3745 | 8.5 | 100 | 8.1 | 3645 | 8.5 | ||
| Asian + American Indian | 1615 | 3.7 | 48 | 3.9 | 1567 | 3.6 | ||
| Unknown race | 3076 | 7.0 | 83 | 6.7 | 2993 | 7.0 | ||
| ASA classification | ||||||||
| 1 | 15 483 | 35.0 | 176 | 14.2 | 15 307 | 35.6 | 57.0 | < 0.001 |
| 2 | 18 052 | 40.8 | 527 | 42.6 | 17 525 | 40.7 | ||
| 3 | 9851 | 22.3 | 473 | 38.2 | 9378 | 21.8 | ||
| 4 & 5 | 898 | 2.0 | 62 | 5.0 | 836 | 1.9 | ||
| Emergency | 3114 | 7.0 | 64 | 5.2 | 3050 | 7.1 | 8.0 | 0.01 |
| Induction type | ||||||||
| Intravenous | 25 683 | 58 | 750 | 60.6 | 24 933 | 57.9 | 5.4 | 0.06 |
| Mask | 18 601 | 42 | 488 | 39.4 | 18 113 | 42.1 | ||
| Endotracheal tube present | 20 761 | 46.9 | 467 | 37.7 | 20 294 | 47.1 | 19.2 | < 0.001 |
| Intra‐operative bronchospasm | 128 | 0.3 | 8 | 0.7 | 120 | 0.3 | 5.4 | 0.02 |
Abbreviations: ASA, American Society of Anesthesiologists; BMI, body mass index; SD, standard deviation; StDiff, standardized differences.
In the main analysis, we found several factors to be independently associated with an increased likelihood of a subsequent diagnosis of asthma [Table 2]. After adjustment for confounders, we found that intraoperative bronchospasm was associated with a doubling of the risk of asthma (OR 2.29, 95% CI 1.10–4.74, p = 0.03). We also found that male sex (OR 1.57, 95% CI 1.39–1.76, p < 0.001) and younger age (OR 0.96, 95% CI 0.94–0.97, p < 0.001) were associated with future asthma diagnosis, while Black race was not. This model had fair discrimination (area under the receiver characteristic operator curve = 0.69 (0.008)) and fair relevance, being 20 times better than a random classifier (area under the precision recall curve = 0.06 compared to 0.003 for a random classifier).
TABLE 2.
Parsimonious model of factors associated with future diagnosis of asthma: main analysis.
| Parameter | Odds ratio | 95% CI | p |
|---|---|---|---|
| Age (years) | 0.96 | 0.94–0.97 | < 0.001 |
| Body mass index (kg/m2) | 1.03 | 1.01–1.04 | < 0.001 |
| Total anesthesia time (h) | 0.87 | 0.83–0.91 | < 0.001 |
| Male sex (ref female) | 1.57 | 1.39–1.76 | < 0.001 |
| ASA classification (ref 1) | |||
| 2 | 2.73 | 2.29–3.24 | < 0.001 |
| 3 | 4.50 | 3.77–5.38 | < 0.001 |
| 4 and 5 | 7.96 | 5.84–10.85 | < 0.001 |
| Induction‐type mask (ref intravenous) | 0.89 | 0.78–1.03 | 0.11 |
| Endotracheal tube present (ref not present) | 0.85 | 0.74–0.98 | 0.02 |
| Intra‐operative bronchospasm (ref without bronchospasm) | 2.29 | 1.10–4.74 | 0.03 |
Abbreviation: CI, confidence interval.
A subgroup sensitivity analysis was performed using mean and peak inspiratory pressure suggestive of bronchospasm among the 35 770 patients who received intraoperative positive pressure ventilation [Figure 1]. Patient demographics were similar to the main analysis [Table 3]. The Mean PIP was 15 mmHg (5), and the Highest PIP was 23 mmHg (9). Subsequently, 950 patients (2.7%) were diagnosed with asthma. The mean time to diagnosis of asthma was 1.60 years (1.32) compared to 3.55 years (1.70) in those without a diagnosis of asthma. Youden's point was 16.6 cmH20 for Mean PIP and 30 cmH20 for Highest PIP. These criteria identified 9781 patients with Mean PIP ≥ 16.6 cmH2O and 4603 had a Highest PIP ≥ 30 cmH2O. Patients who subsequently developed asthma were more likely to have Mean PIP ≥ 16.6 cmH2O (359 of 950, 37.8% vs. 9422 of 34 820, 27.1%, StDiff = 23.1%, p < 0.001), while the proportions of patients with Highest PIP were similar between the two groups (133 of 950, 14% vs. 4470 of 34 820, 12.8%, StDiff = 3.4%, p = 0.29).
TABLE 3.
Descriptive characteristics of the sample: subgroup analysis of patients receiving positive pressure ventilation.
| Total (N = 35 770) | Asthma (n = 950) | No asthma (n = 34 820) | StDiff | |||||
|---|---|---|---|---|---|---|---|---|
| Variable | Mean | SD | Mean | SD | Mean | SD | % | p |
| Age (years) | 9.8 | 5.2 | 9.2 | 5.1 | 9.9 | 5.2 | 13.5 | < 0.001 |
| BMI (kg/m2) | 20.0 | 5.6 | 20.4 | 6.2 | 19.9 | 5.6 | 8.2 | 0.01 |
| Total anesthesia time (min) | 128.5 | 108.1 | 108.8 | 100.6 | 129.0 | 108.2 | 19.4 | < 0.001 |
| N | % | N | % | N | % | |||
|---|---|---|---|---|---|---|---|---|
| Sex | ||||||||
| Male | 18 718 | 52.3 | 581 | 61.2 | 18 137 | 52.1 | 18.7 | < 0.001 |
| Female | 17 052 | 47.7 | 369 | 38.8 | 16 683 | 47.9 | ||
| Race/Ethnicity | ||||||||
| White + Middle Eastern | 28 909 | 80.8 | 775 | 81.6 | 28 134 | 80.8 | 3.7 | 0.76 |
| Black + biracial | 3025 | 8.5 | 80 | 8.4 | 2945 | 8.5 | ||
| Asian + American Indian | 1341 | 3.8 | 37 | 3.9 | 1304 | 3.7 | ||
| Unknown race | 2495 | 7.0 | 58 | 6.1 | 2437 | 7.0 | ||
| ASA classification | ||||||||
| 1 | 13 823 | 38.6 | 157 | 16.5 | 13 666 | 39.3 | 58.4 | < 0.001 |
| 2 | 14 520 | 40.6 | 419 | 44.1 | 14 101 | 40.5 | ||
| 3 | 6701 | 18.7 | 323 | 34.0 | 6378 | 18.3 | ||
| 4 & 5 | 726 | 2.0 | 51 | 5.4 | 675 | 1.9 | ||
| Emergency | 2811 | 7.9 | 61 | 6.4 | 2750 | 7.9 | 5.7 | 0.10 |
| Induction type | ||||||||
| IV | 18 988 | 53.1 | 521 | 54.8 | 18 467 | 53.0 | 3.6 | 0.27 |
| Mask | 16 782 | 46.9 | 429 | 45.2 | 16 353 | 47.0 | ||
| Endotracheal tube present | 20 471 | 57.2 | 453 | 47.7 | 20 018 | 57.5 | 19.7 | < 0.001 |
| Bronchospasm (mean PIP > 16.5 cmH20) | 9781 | 27.3 | 359 | 37.8 | 9422 | 27.1 | 23.1 | < 0.001 |
| Bronchospasm (highest PIP > 30 cmH20) | 4603 | 12.9 | 133 | 14.0 | 4470 | 12.8 | 3.4 | 0.29 |
Abbreviations: ASA, American Society of Anesthesiologists; BMI, body mass index; PIP, peak inspiratory pressure; StDiff, standardized differences.
In this subgroup analysis, several factors were independently associated with an increased likelihood of a future diagnosis of asthma [Table 4]. After adjusting for confounders, we found that Mean PIP was associated with an increased risk of asthma (OR 1.50, 95% CI 1.30–1.74, p < 0.001), but not Highest PIP. We also found that male sex (OR 1.60, CI 1.40–1.83, p < 0.001) and BMI (OR 1.03, 95% CI 1.01–1.04, p < 0.001) were associated with future asthma diagnosis. This model had fair discrimination (area under the receiver characteristic operator curve = 0.71 (0.009)) and fair relevance, being 23 times better than a random classifier (area under the precision recall curve = 0.07 compared to 0.003 for a random classifier).
TABLE 4.
Parsimonious model of factors associated with future diagnosis of asthma using bronchospasm as determined by the mean peak inspiratory pressure: subgroup analysis.
| Parameter | Odds ratio | 95% CI | p |
|---|---|---|---|
| Age (years) | 0.94 | 0.92–0.95 | < 0.001 |
| Body mass index (kg/m2) | 1.03 | 1.01–1.04 | < 0.001 |
| Total anesthesia time (min) | 1.00 | 1.00–1.00 | < 0.001 |
| Male sex (ref female) | 1.60 | 1.40–1.83 | < 0.001 |
| ASA classification (ref 1) | |||
| 2 | 2.65 | 2.20–3.20 | < 0.001 |
| 3 | 4.83 | 3.97–5.87 | < 0.001 |
| 4 and 5 | 8.08 | 5.72–11.41 | < 0.001 |
| Induction‐type mask (ref IV) | 0.79 | 0.67–0.93 | 0.006 |
| Endotracheal tube present (ref not present) | 0.74 | 0.64–0.86 | < 0.001 |
| Intra‐operative bronchospasm (by PIP mean) (ref without bronchospasm) | 1.50 | 1.30–1.74 | < 0.001 |
Abbreviation: CI, confidence interval.
The fragility index for the main analysis was 1, and for the subgroup analysis, the fragility index was 75.
4. Discussion
We found that intraoperative bronchospasm was associated with the development of future asthma (OR 2.29, CI 1.10–4.74, p = 0.03) Our study findings are the first that we know of to evaluate intraoperative bronchospasm being associated with future asthma diagnosis. While other factors that we also found to be associated with an asthma diagnosis, such as male sex and BMI, have been previously described [22, 23] we found no association between future asthma diagnosis and endotracheal tubes [10, 11]. This difference could be related to deeper depth of anesthetic with an endotracheal tube present or to more direct administration of volatile anesthesia contributing to more bronchodilation in our cohort. Notably, we did not find a significant association between asthma and race, potentially due to the geographic and socioeconomic composition of our patient population, which may differ from broader epidemiological studies [24, 25].
While we found that intraoperative bronchospasm is independently associated with subsequent asthma diagnosis, the sensitivity and positive predictive values are low, limiting its clinical utility. However, parents should be informed of intraoperative bronchospasm as it might prompt discussion and questions about symptoms of asthma that may have been missed or previously ignored. Utilizing this information, one could optimize pathways for those with asthma/reactive airway disease to include breathing treatments pre‐operatively, customization of airway devices, and anesthetic agents. It could also lead to improvement in follow‐up care for patients to be seen by their primary care physician, have their pulmonary status optimized, and asthma diagnosed sooner. Future studies would need to be conducted to determine the utility of this approach.
Other limitations include the retrospective nature of our study and reliance on appropriate intra‐operative documentation. Although our team individually reviewed records to assess multiple clinical factors indicative of bronchospasm, some cases may have been missed. Other differential diagnosis considerations that present similarly to bronchospasm include mucous plugging, anaphylaxis, aspiration, and laryngospasm, complicating clinical interpretation and producing an unknown bias in our results. Additionally, we did not fully explore the temporal distribution of the bronchospasm events or the techniques for maintenance of anesthesia, which could provide valuable insights for future considerations and management strategies in this patient population.
Despite pressure control ventilation being the default ventilation mode on our anesthesia machines, variability in practice and retrospective data collection made further investigation into specific ventilation details unavailable. Additionally, as our hospital is both a community hospital and a tertiary care referral center, some patients may have followed up elsewhere, potentially leading to underreporting. Our study also did not account for the potential impact of secondhand smoke exposure or a family history of asthma, which are known risk factors for bronchospasm. This information was not readily available or consistently captured in our electronic medical records but could be explored in future studies to better understand other environmental risk factors. Although we excluded participants with known respiratory diseases or infections, variability in the timing and clinical manifestations of respiratory tract infections could contribute to an increased likelihood of bronchospasm, posing another potential confounder. We also did not have access to information on exercise‐induced wheezing or wheezing associated with upper respiratory tract infections within the last 12 months, which are known to be predictors of asthma development. Furthermore, although our study suggests that intra‐operative bronchospasm is associated with future asthma diagnosis, we are unable to determine if this represents undiagnosed asthma or an increased risk of developing asthma. Either way, the occurrence of intra‐operative bronchospasm should lead to further evaluation, as prompt diagnosis of asthma would facilitate earlier treatment. Our findings highlight the need for additional research to further elucidate risk factors that could help treat and prevent respiratory events related to asthma both daily as well as in the perioperative period.
In our study, we observed 128 cases of bronchospasm in 44 284 anesthetics or 2.9 per 1000 anesthetics in the main analysis and 122 cases of bronchospasm in 35 770 anesthetics or 3.4 per 1000 anesthetics in the subgroup analysis. This incidence is higher compared to larger studies such as Olsson et al., who found a rate of 1.7 per 1000 anesthetics in a database study of over 100 000 anesthetics [14]. Our focus on pediatric patients, who have a higher incidence of bronchospasm, or differing definitions of bronchospasm may account for our higher rate. We also controlled for pre‐existing risk factors such as allergies, eczema, congenital pulmonary pathology, and prematurity. We conducted thorough chart reviews in specific cases where the database data was unclear, looking specifically for notes confirming wheezing, bronchospasm, or other dialogue that would indicate bronchospasm. We also reviewed medication administered, specifically albuterol and other adjunct medication such as magnesium and/or epinephrine, and analyzed air pressures, pressure change, and oxygen saturation during suspected events.
Future studies could impact asthma screening protocols, aid in earlier diagnosis in pediatric populations, and pave the way for future investigations to determine other predictors for asthma diagnosis.
5. Conclusion
Asthma remains one of the most common respiratory diseases in the world and continues to be underdiagnosed. Our study indicates that intra‐operative bronchospasm is associated with an increased risk of future asthma diagnosis in pediatric patients. Further research is essential to validate these findings and identify additional risk factors for early asthma detection and management, which could improve risk stratification of patients in the peri‐operative and post‐operative period and improve overall outcomes of pediatric patients.
Ethics Statement
This study was reviewed and proved by the Institutional Review Board at the University of Michigan Medicine. Informed consent was waived due to the retrospective nature of the study and the use of de‐identified data.
Conflicts of Interest
The authors declare no conflicts of interest.
Funding: The authors received no specific funding for this work.
Article Summary: This article investigates the relationship between intraoperative bronchospasm and its association with a future diagnosis of asthma in the pediatric patient population.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
References
- 1. Centers for Disease Control and Prevention , “Asthma CDC National Data,” https://www.cdc.gov/asthma/most_recent_national_asthma_data.htm.
- 2. Seol H. Y., Sohn S., Liu H., et al., “Early Identification of Childhood Asthma: The Role of Informatics in an Era of Electronic Health Records,” Frontiers in Pediatrics 7 (2019): 113, 10.3389/fped.2019.00113. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Aaron S. D., Boulet L. P., Reddel H. K., and Gershon A. S., “Underdiagnosis and Overdiagnosis of Asthma,” American Journal of Respiratory and Critical Care Medicine 198, no. 8 (2018): 1012–1020, 10.1164/rccm.201804-0682ci. [DOI] [PubMed] [Google Scholar]
- 4. Molis W. E., Bagniewski S., Weaver A. L., Jacobson R. M., and Juhn Y. J., “Timeliness of Diagnosis of Asthma in Children and Its Predictors,” Allergy 63, no. 11 (2008): 1529–1535, 10.1111/j.1398-9995.2008.01749.x. [DOI] [PubMed] [Google Scholar]
- 5. Perez M. F. and Coutinho M. T., “An Overview of Health Disparities in Asthma,” Yale Journal of Biology and Medicine 94, no. 3 (2021): 497–507. [PMC free article] [PubMed] [Google Scholar]
- 6. Bakirtas A., “Diagnostic Challenges of Childhood Asthma,” Current Opinion in Pulmonary Medicine 23, no. 1 (2017): 27–33, 10.1097/mcp.0000000000000338. [DOI] [PubMed] [Google Scholar]
- 7. Karaatmaca B., Sahiner U. M., Sekerel B. E., and Soyer O., “Perioperative Hypersensitivity Reactions During Childhood and Outcomes of Subsequent Anesthesia,” Paediatric Anaesthesia 31, no. 4 (2021): 436–443, 10.1111/pan.14126. [DOI] [PubMed] [Google Scholar]
- 8. Pizov R., Brown R. H., Weiss Y. S., et al., “Wheezing During Induction of General Anesthesia in Patients With and Without Asthma. A Randomized, Blinded Trial,” Anesthesiology 82, no. 5 (1995): 1111–1116, 10.1097/00000542-199505000-00004. [DOI] [PubMed] [Google Scholar]
- 9. Kim E. S. and Bishop M. J., “Endotracheal Intubation, but Not Laryngeal Mask Airway Insertion, Produces Reversible Bronchoconstriction,” Anesthesiology 90, no. 2 (1999): 391–394, 10.1097/00000542-199902000-00010. [DOI] [PubMed] [Google Scholar]
- 10. von Ungern‐Sternberg B. S., Boda K., Chambers N. A., et al., “Risk Assessment for Respiratory Complications in Paediatric Anaesthesia: A Prospective Cohort Study,” Lancet 376, no. 9743 (2010): 773–783, 10.1016/S0140-6736(10)61193-2. [DOI] [PubMed] [Google Scholar]
- 11. Dones F., Foresta G., and Russotto V., “Update on Perioperative Management of the Child With Asthma,” Pediatric Reports 4, no. 2 (2012): e19, 10.4081/pr.2012.e19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Lin C. S., Chang C. C., Yeh C. C., Chung C. L., Chen T. L., and Liao C. C., “Postoperative Adverse Outcomes in Patients With Asthma: A Nationwide Population‐Based Cohort Study,” Medicine 95, no. 3 (2016): e2548, 10.1097/MD.0000000000002548. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Olsson G. L., “Bronchospasm During Anaesthesia. A Computer‐Aided Incidence Study of 136 929 Patients,” Acta Anaesthesiologica Scandinavica 31, no. 3 (1987): 244–252, 10.1111/j.1399-6576.1987.tb02560.x. [DOI] [PubMed] [Google Scholar]
- 14. Habre W., Disma N., Virag K., et al., “Incidence of Severe Critical Events in Paediatric Anaesthesia (APRICOT): A Prospective Multicentre Observational Study in 261 Hospitals in Europe,” Lancet Respiratory Medicine 5, no. 5 (2017): 412–425, 10.1016/S2213-2600(17)30116-9. [DOI] [PubMed] [Google Scholar]
- 15. Woods B. D. and Sladen R. N., “Perioperative Considerations for the Patient With Asthma and Bronchospasm,” British Journal of Anaesthesia 103, no. Suppl 1 (2009): i57–i65, 10.1093/bja/aep271. [DOI] [PubMed] [Google Scholar]
- 16. Murat I., Constant I., and Maud'huy H., “Perioperative Anaesthetic Morbidity in Children: A Database of 24 165 Anaesthetics Over a 30‐Month Period,” Paediatric Anaesthesia 14, no. 2 (2004): 158–166, 10.1111/j.1460-9592.2004.01167.x. [DOI] [PubMed] [Google Scholar]
- 17. Paterson N. and Waterhouse P., “Risk in Pediatric Anesthesia,” Paediatric Anaesthesia 21, no. 8 (2011): 848–857, 10.1111/j.1460-9592.2010.03366.x. [DOI] [PubMed] [Google Scholar]
- 18. Hilgendorff A., Reiss I., Ehrhardt H., Eickelberg O., and Alvira C. M., “Chronic Lung Disease in the Preterm Infant: Lessons Learned From Animal Models,” American Journal of Respiratory Cell and Molecular Biology 50, no. 2 (2014): 233–245, 10.1165/rcmb.2013-0014TR. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Emons J. A. and Gerth van Wijk R., “Food Allergy and Asthma: Is There a Link? Curr Treat Options,” Allergy 5, no. 4 (2018): 436–444, 10.1007/s40521-018-0185-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Walsh M., Srinathan S. K., McAuley D. F., et al., “The Statistical Significance of Randomized Controlled Trial Results Is Frequently Fragile: A Case for a Fragility Index,” Journal of Clinical Epidemiology 67 (2014): 622–628, 10.1016/j.jclinepi.2013.10.019. [DOI] [PubMed] [Google Scholar]
- 21. Davis J. and Goadrich M., “The Relationship Between Precision‐Recall and ROC Curves,” in Proceedings of the 23rd International Conference on Machine Learning (Association for Computing Machinery, 2006). [Google Scholar]
- 22. Chowdhury N. U., Guntur V. P., Newcomb D. C., and Wechsler M. E., “Sex and Gender in Asthma,” European Respiratory Review 30, no. 162 (2021): 210067, 10.1183/16000617.0067-2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Vijayakanthi N., Greally J. M., and Rastogi D., “Pediatric Obesity‐Related Asthma: The Role of Metabolic Dysregulation,” Pediatrics 137, no. 5 (2016): e20150812, 10.1542/peds.2015-0812. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Drake K. A., Galanter J. M., and Burchard E. G., “Race, Ethnicity and Social Class and the Complex Etiologies of Asthma,” Pharmacogenomics 9, no. 4 (2008): 453–462, 10.2217/14622416.9.4.453. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Malleske D., Bryant‐Stephens T. C., and Montoya‐Williams D., “Childhood Asthma Disparities‐Race, Place, or Not Keeping Pace?,” JAMA Pediatrics 176, no. 8 (2022): 739–740, 10.1001/jamapediatrics.2022.1457. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.