Mortality and factors associated with acute exacerbation after non-cardiac surgery in patients with interstitial pneumonia: a retrospective study

Article information

Korean J Anesthesiol. 2025;78(5):453-461
Publication date (electronic) : 2025 February 3
doi : https://doi.org/10.4097/kja.24656
1Kyushu University Hospital, Fukuoka, Japan
2Intensive Care Unit, Kyushu University Hospital, Fukuoka, Japan
3Department of Anesthesiology and Critical Care Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
4Department of Anesthesiology and Critical Care Medicine, Kyushu University Hospital, Fukuoka, Japan
Corresponding author: Kazuhiro Shirozu, M.D., Ph.D. Kyushu University Hospital, Fukuoka, 812-8582, Japan Tel: +81-92-642-5714 Fax: +81-92-642-5722 Email: shirozu.kazuhiro.334@m.kyushu-u.ac.jp
Received 2024 September 19; Revised 2025 January 8; Accepted 2025 January 9.

Abstract

Background

Acute exacerbation of interstitial pneumonia (AE-IP) is associated with high mortality rates. Although the risk factors for AE-IP have been extensively studied, given the small sample sizes, only a few risk factors have been established. This study aimed to investigate the postoperative mortality and factors associated with AE-IP.

Methods

This retrospective study included 482 patients with a preoperative diagnosis of IP who underwent noncardiac surgery between December 2012 and April 2020. AE-IP was diagnosed by a radiologist using computed tomography when worsening respiratory symptoms were observed within 1 month postoperatively. The Cox proportional hazards model was used to compare mortality rates. Candidate factors associated with AE-IP were identified through logistic regression analysis using the variable selection method, followed by case-control analysis using propensity score matching to determine possible factors associated with AE-IP.

Results

The multivariable-adjusted hazard ratios for all-cause and IP-related deaths were significantly higher in patients with AE-IP than in those without AE-IP. Multivariable analysis with variable selection suggested that male sex, higher C-reactive protein (CRP) levels, fraction of inspired oxygen (FiO2) ≥ 60%, and non-lung surgery were candidate factors associated with AE-IP. Case-control analysis using propensity score matching demonstrated that patients with AE-IP had higher CRP levels (P = 0.044) and frequency of FiO2 ≥ 60% (P = 0.035) than those without AE-IP. Furthermore, a positive, nearly linear relationship was observed between FiO2 ≥ 60% duration and AE-IP incidence.

Conclusions

Intraoperative management with FiO2 ≥ 60% and high preoperative CRP levels were significantly associated with postoperative AE-IP.

Introduction

Interstitial pneumonia (IP) has an incidence of 5.6 per 100 000 person-years and an annual cumulative prevalence of approximately 18 per 100 000 people [1]. Opportunities for patients with IP to undergo surgery are common. Acute exacerbation (AE) may occur in patients with postoperative IP, and the mortality rate associated with AE-IP is extremely high [25]. However, no evidence-based prophylaxis exists, and the complete prevention of AE-IP is impossible. Therefore, the risk factors for AE-IP must be clearly understood and risk assessments should be conducted. To date, AE-IP risk factors have been reported to include male sex, preoperative steroid administration, history of AE-IP, low lung capacity, usual IP pattern on computed tomography (CT), high serum sialylated carbohydrate Krebs von den Lungen-6 (KL-6) antigens levels, elevated C-reactive protein (CRP) levels, lung surgery involving more than a segmental resection, prolonged duration of surgery, oxygen exposure, ventilation before surgery, and unilateral lung ventilation [3,518]. However, with the exception of one report [6], all studies have had small sample sizes with a limited number of events and only a few have appropriately controlled for confounding factors using adequate statistical analysis. Thus, no established risk factors have been identified. Furthermore, despite the existence of a large noteworthy study on lung resection [6], sufficient evidence has not been established for either lung or non-lung surgeries. Therefore, this study aimed to determine whether AE-IP is associated with worse mortality postoperatively and to identify the factors associated with the development of AE-IP.

Materials and Methods

The Clinical Research Ethics Committee of Kyushu University, Fukuoka, Japan, approved this observational retrospective study (research approval number: 2019-251) on August 5, 2020, and the need for individual written informed consent was waived due to its retrospective design. This study was conducted in compliance with the Declaration of Helsinki, 2013 and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Overall, 492 patients with a preoperative diagnosis of IP who underwent noncardiac surgery at Kyushu University Hospital between December 2012 and April 2020 were included in this study. IP was either already diagnosed and followed up by a respiratory physician or incidentally diagnosed by a radiologist on preoperative CT. After excluding five patients aged < 18 years and five identical patients, 482 participants were enrolled in this study. None of the participants had preoperative AE-IP.

We extracted surgery and anesthesia data from the participants’ electronic anesthetic charts and preoperative, postoperative, and survival data were collected manually by reviewing each participant’s electronic medical records individually. Data on sex, age, height, weight, Brinkman index (calculated by multiplying the number of cigarettes by the number of years), preoperative supplemental oxygen, and preoperative ventilator use were collected for the study participants. Additionally, we collected data on KL-6, CRP, and lactate dehydrogenase (LDH) levels; percent vital capacity (%VC); and forced expiratory volume in 1 s (FEV1) on spirometry measured within 1 month preoperatively. The following surgical and anesthesia data were collected: type of surgery (lung surgery or other), anesthesia method (general or local anesthesia), presence of differential lung ventilation, surgery duration, anesthesia duration, urine volume, blood loss volume, infusion volume, in-out balance, volume of oxygen used, presence of intraoperative blood transfusion, and duration of fraction of inspired oxygen (FiO2) ≥ 60%. Continuous intraoperative data, such as the FiO2 were automatically stored in electronic anesthetic charts, and minute-by-minute data were used for the analysis. The threshold of 60% FiO2 was established based on a previous report [9]. Although no protocol for FiO2 during anesthesia has been established at our facility, FiO2 is generally adjusted at the discretion of the individual anesthesiologist so that SpO2 does not fall below 90% for both lung and non-lung surgeries when anesthetizing patients with IP.

The primary outcome of this study was the incidence of postoperative AE-IP. We defined AE-IP as the worsening of respiratory symptoms within 1 month postoperatively, with an AE-IP diagnosis confirmed by a radiologist on CT. Postoperative mortality information was collected from medical records, and the association between AE-IP and postoperative mortality was examined. AE-IP-related deaths were defined as deaths for which IP was listed as the cause of mortality in the medical record. The follow-up period for death was calculated from the date of surgery to the date of death confirmed in the medical record or to the last date recorded (e.g., the date of the last outpatient visit).

Statistical analysis

The baseline characteristics of the participants in the AE and non-AE groups were compared. Continuous variables are presented as mean ± SD or median (Q1, Q3) values and categorical variables as percentages. We used the Student’s t test for normally distributed continuous variables, Mann–Whitney U test for non-normally distributed continuous variables, and chi-square test for frequencies. We calculated the cumulative survival rates for all-cause and IP-related deaths between the AE and non-AE groups using the Kaplan–Meier method and compared them using a log-rank test. The Cox proportional hazards model was used to estimate hazard ratios (HRs) with 95% CIs for all-cause and IP-related deaths. The risk estimates in the multivariable analysis were adjusted for potential confounding factors at baseline, including age, sex, body mass index, preoperative supplemental oxygen, preoperative ventilator use, and type of surgery (lung surgery or other). Logistic regression was used to estimate odds ratios (ORs) with 95% CIs for AE-IP to identify factors associated with AE-IP. The backward method was used to select significant variables that could be candidate factors associated with AE-IP, and P < 0.20 was used as the selection criteria. In the variable selection model, we included potential confounding factors previously reported as AE-IP risk factors and those with P < 0.20 in the univariate analysis. A total of 270 participants, excluding 212 participants with missing data, were included in the multivariable analysis using the variable selection model and the subsequent case-control study using propensity score matching. A logistic regression analysis was performed for sensitivity analysis to examine the validity of the factors associated with AE-IP obtained from the variable selection, including the 212 participants who were excluded due to missing data. Owing to the insufficient number of events and overall number of participants, case-control studies with propensity score matching were subsequently conducted for each of the variables selected as candidate factors associated with AE-IP. For each factor selected through variable selection, propensity scores for AE-IP with other factors and potential confounding factors previously reported as AE-IP risk factors were generated, and 1:5 matching was performed using conditional logistic regression analysis to examine whether the factors of interest differed. Additionally, to visualize the relationship between the duration of FiO2 ≥ 60% and AE-IP, a generalized additive model was used to calculate the predicted AE-IP incidence and establish the spline curves. Spline curves showing these associations were drawn for both lung and non-lung surgeries. All statistical analyses were performed using SAS software package (version 9.4; SAS Institute). Two-sided P values < 0.05 were considered statistically significant for all analyses.

Results

Baseline characteristics of participants

Of the 482 participants included in the analysis, 19 developed AE-IP postoperatively. Participants who had AE-IP were more likely to be male. The mean values for weight, median values for KL-6 and CRP levels, and frequencies of FiO2 ≥ 60% were greater in the AE group than in the non-AE group (Table 1). Details regarding the surgical sites are provided in Supplementary Table 1.

Baseline Characteristics of Participants

Crude cumulative survival rates

The median (Q1, Q3) follow-up periods for the AE and non-AE groups were 212 (29, 550) and 729 (306, 1702) days, respectively. During the follow-up period, 10 and 119 patients died in the AE and non-AE groups, respectively. Additionally, five and 28 IP-related deaths occurred in the AE and non-AE groups, respectively (Table 2). A significant difference was found in the crude cumulative survival rates for all-cause (A) and IP-related (B) deaths between the AE and non-AE groups (Fig. 1).

Hazard Ratios for All-cause and IP-related Deaths

Fig. 1.

Crude cumulative survival rates for all-cause (A) and IP-related (B) deaths. This figure illustrates the survival curves for the AE and non-AE groups. AE: acute exacerbation, IP: interstitial pneumonia.

Hazard ratios for all-cause and IP-related deaths in the AE and non-AE groups

The crude HR for all-cause death was significantly higher in the AE group (HR: 4.82, 95% CI [2.51−9.26]) than in the non-AE group. In the multivariable-adjusted analysis, this association remained significant even after adjusting for potential confounding factors (HR: 5.16, 95% CI [2.62−10.14]). Similar results were observed for IP-related deaths.

Odds ratios for AE-IP in the crude and variable selection analyses

The crude OR for AE-IP was higher in males (OR: 10.64, 95% CI [2.17−192.15]) than in females, and higher CRP levels significantly increased the risk of AE-IP (OR: 1.12, 95% CI [1.03−1.22]). Multivariable analysis using the variable selection method showed that the candidate factors associated with AE-IP were male sex, higher CRP levels, FiO2 ≥ 60%, and lung surgery; however, statistical significance was observed only for CRP levels (OR: 1.21, 95% CI [1.05−1.40], P = 0.006), FiO2 ≥ 60% (OR: 5.22, 95% CI [1.37−22.68], P = 0.018), and lung surgery (OR: 0.24, 95% CI [0.06−0.96], P = 0.047) (Table 3). The results of the sensitivity analysis, which included the 212 participants who were excluded due to missing values, showed that the ORs for AE-IP after multivariable adjustment were 14.54 (95% CI [1.32−159.70]) for male vs. female, 1.17 (95% CI [1.07−1.28]) for every 1 mg/dl elevation in CRP and 5.26 (95% CI [1.74−15.89]) for FiO2 ≥ 60% vs. FiO2 < 60% (Supplementary Table 2); these findings were almost identical to the main results of multivariable analysis in Table 3. A positive relationship also existed between the duration of FiO2 ≥ 60% and AE-IP incidence: the predicted AE-IP incidence increased linearly with the duration of FiO2 ≥ 60% (Fig. 2). This linear relationship was similar for both lung and non-lung surgeries (Supplementary Fig. 1).

ORs for AE-IP in Crude and Multivariable-adjusted Analyses with Variable Selection

Fig. 2.

Relationship between duration of FiO2 ≥ 60% and incidence of AE-IP. The gray line indicates the predicted value of AE-IP and the blue range shows 95% CIs. Multivariable adjustments were made for CRP levels. AE: acute exacerbation, CRP: C-reactive protein, FiO2 ≥ 60%: fraction of inspired oxygen ≥ 60%, IP: interstitial pneumonia.

Case-control analysis using propensity score matching

Multivariable analysis using the variable selection method was used to detect candidate factors associated with AE-IP. However, since many variables existed for the number of AE-IP cases, a case-control analysis was subsequently performed using propensity score matching. After matching with the propensity scores created using potential confounding factors previously reported as AE-IP risk factors and three additional factors other than CRP, CRP levels were significantly higher in the AE group than in the non-AE group (P = 0.044). Similarly, for FiO2 ≥ 60%, after matching other factors, frequency of FiO2 ≥ 60% was significantly higher in the AE group than in the non-AE group (P = 0.035). Sex and type of surgery did not differ significantly between the groups (Table 4).

Case-control Analysis with Propensity Score Matching

Discussion

In this study, we found that postoperative AE-IP was associated with a higher risk of mortality, particularly IP-related deaths. Furthermore, variable selection analysis showed higher CRP levels, male sex, non-lung surgery, and FiO2 ≥ 60% as candidate factors associated with AE-IP, and a subsequent propensity score matching analysis revealed that higher CRP levels and FiO2 ≥ 60% were the most likely factors associated with AE-IP. We also showed that the risk of AE-IP increased linearly with the duration of FiO2 ≥ 60%.

The frequency of postoperative AE-IP in this study was 3.9%. Although various values for this incidence have been reported, 3.9% is generally consistent with previous reports [9,10,15,19,20]. Notably, overall (34.5%) and IP-related (20.8%) deaths were higher in patients with AE-IP than in those without AE-IP. These results suggest that identifying the risk factors for AE-IP and predicting and preventing AE-IP are clinically important. In this context, the clinical relevance of this study, which identified higher CRP levels and FiO2 ≥ 60% as factors associated with AE-IP based on data from 482 participants at a single institution, is highly significant. In particular, the finding that high intraoperative FiO2 is associated with AE-IP incidence is clinically significant for anesthesiologists. The results of this study could have profound clinical implications as they may influence future perioperative management of patients with IP.

Although many studies on risk factors for AE-IP exist, only a few have focused on FiO2 during anesthesia. The incidence of AE-IP on the non-operative side after lung surgery has been reported in a few studies, suggesting a relationship between high FiO2 levels and AE-IP. However, no studies have provided statistical analyses to support this relationship. The mechanism by which high FiO2 levels are associated with AE-IP may be explained by endogenous production of oxygen radicals by some cell types, including inflammatory cells [21]. Furthermore, oxygen radicals can inactivate various enzymes within alveolar epithelial and capillary endothelial cells to damage cellular membranes and intranuclear genes [22]. Production of various cytokines by activated neutrophils and alveolar macrophages is associated with the pathogenesis of lung injury [21,22]. The administration of higher oxygen concentrations to model mice with peplomycin-induced IP has been reported to result in more severe pulmonary fibrosis, demonstrating the pulmonary toxicity of high supplemental oxygen concentrations [23]. Furthermore, although atelectasis and small airway closure normally does not occur until 100 min of FiO2 at 30%, this can occur within 10 min at 100% FiO2 [24]. This mechanism may be related to an increase in the time-dependent risk of AE-IP due to the production of reactive oxygen species and increased atelectasis. However, the possibility of reverse causation in the relationship between FiO2 and AE-IP should also be considered, though further prospective studies are required to confirm this association.

A large multicenter study involving 1763 patients at 61 centers found that a history of AE-IP, male sex, preoperative steroid use, high KL6 levels, and low %VC were significantly associated with AE-IP [6]. Furthermore, a meta-analysis of 2655 patients across 12 studies identified male sex, high KL6 and LDH levels, elevated white blood cell counts, low oxygen pressure in arterial blood (PaO2) levels, and prolonged surgery as risk factors for AE-IP [19].

Several previous reports, despite their small sample sizes, have reported high CRP levels as a risk factor for postoperative AE-IP, which is consistent with the findings of this study [7,10,13,16,22]. High preoperative CRP levels have been reported to reflect a strong inflammatory state, and the induction of inflammatory cytokines is considered a possible trigger for AE-IP [10]. Notably, the two large studies mentioned earlier reported that male sex, high %VC, high KL6 and LDH levels, and prolonged surgery were risk factors for AE-IP [6,19]. However, we did not observe similar results in our study. The most likely explanation is that we had an insufficient number of participants and AE-IP cases; therefore, our study lacked the statistical power to identify all factors in every case. Previous studies have also reported similar observations that not all risk factors can be identified [4,25]. Therefore, as this exploratory analysis was designed only to generate hypotheses about relationships, it provides no conclusive evidence about these associations.

Strengths and limitations

Our results are valuable because this is the first study that uses appropriate statistical methods to show that intraoperative FiO2 ≥ 60% is associated with AE-IP and suggest a time-response relationship wherein the incidence of AE-IP increases with time of administration. Another strength of this study, compared with previous reports, is the large number of participants at a single institution. In multicenter studies, differences in perioperative management among centers may hinder the identification of risk factors, whereas in a single-center study, these extraneous factors do not need to be considered, and consistent results are more likely to be obtained.

However, a limitation of this study is that even though the number of participants was large for a single center, it was not sufficient to identify all the factors associated with AE-IP, as previously noted. Second, even though the risk estimates were adjusted for possible confounding factors, residual confounders may exist. Third, as this was an observational study, the FiO2 levels during surgery were arbitrarily set by the respective anesthesiologists based on the clinical situation. Additionally, as we had insufficient data regarding PaO2, it was impossible to determine whether AE-IP was attributable to FiO2 or PaO2 and whether it was the use of or need for FiO2 ≥ 60% that was a risk factor for AE-IP in this study. Fourth, insufficient information on the participants’ IP diagnosis prevented separate analyses of each type of IP, and the lack of data on AE-IP classification as unilateral or bilateral prevented its inclusion in the study. Furthermore, information on the history of AE-IP and preoperative steroid use was lacking. Finally, this study was conducted on a single race at one institution; therefore, the generalizability of our findings is limited.

In conclusion, this study demonstrates that, in addition to elevated preoperative CRP levels, anesthesia management with a higher FiO2 during surgery is associated with postoperative AE-IP.

Acknowledgements

We would like to express our deepest appreciation to Mrs. Yoko Kondo, who works at the Kyushu University Hospital, for her assistance in this study.

Notes

Funding

None.

Conflicts of Interest

No potential conflict of interest relevant to this article was reported.

Data Availability

The data associated with this study are not publicly available but are available from the corresponding author on reasonable request.

Author Contributions

Kaoru Umehara (Conceptualization; Formal analysis; Investigation; Methodology; Visualization; Writing – original draft; Writing – review & editing)

Kazuhiro Shirozu (Conceptualization; Data curation; Investigation; Methodology; Project administration; Supervision; Writing – original draft; Writing – review & editing)

Taichi Ando (Data curation; Investigation; Writing – original draft; Writing – review & editing)

Kentaro Tokuda (Conceptualization; Investigation; Writing – original draft; Writing – review & editing)

Kei Makishima (Data curation; Investigation; Writing – review & editing)

Kazuya Imura (Data curation; Investigation; Writing – review & editing)

Shota Tsumura (Data curation; Investigation; Writing – review & editing)

Shinnosuke Takamori (Data curation; Investigation; Writing – review & editing)

Ken Yamaura (Conceptualization; Funding acquisition; Supervision; Writing – review & editing)

Supplementary Materials

Supplementary Table 1.

Classification of surgical site.

kja-24656-Supplementary-Table-1.pdf
Supplementary Table 2.

ORs for AE-IP in sensitivity analysis including participants initially excluded by missing values. ORs: odds ratios, AE-IP: acute exacerbation of interstitial pneumonia.

kja-24656-Supplementary-Table-2.pdf
Supplementary Fig. 1.

Relationship between duration of FiO2 ≥ 60% and incidence of AE-IP in lung (A) and non-lung (B) surgeries. FiO2: fraction of inspired oxygen, AE-IP: acute exacerbation of interstitial pneumonia.

kja-24656-Supplementary-Fig-1.pdf

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Article information Continued

Fig. 1.

Crude cumulative survival rates for all-cause (A) and IP-related (B) deaths. This figure illustrates the survival curves for the AE and non-AE groups. AE: acute exacerbation, IP: interstitial pneumonia.

Fig. 2.

Relationship between duration of FiO2 ≥ 60% and incidence of AE-IP. The gray line indicates the predicted value of AE-IP and the blue range shows 95% CIs. Multivariable adjustments were made for CRP levels. AE: acute exacerbation, CRP: C-reactive protein, FiO2 ≥ 60%: fraction of inspired oxygen ≥ 60%, IP: interstitial pneumonia.

Table 1.

Baseline Characteristics of Participants

Variable AE group (n = 19) Non-AE group (n = 463) P value
Male (%) 94.7 62.9 0.003
Age (yr) 71.2 ± 10.0 69.7 ± 10.6 0.567
Height (cm) 162.9 ± 7.4 159.8 ± 8.7 0.123
Weight (kg) 64.2 ± 11.2 58.7 ± 11.8 0.0
Body mass index (kg/m2) 24.1 ± 3.5 22.9 ± 3.9 0.181
KL-6 (U/ml) 893 (481, 1593) 529 (356, 854) 0.019
CRP (mg/dl) 2.00 (0.21, 5.71) 0.27 (0.09, 0.95) 0.001
LDH (U/L) 220 (168, 294) 209 (182, 246) 0.347
Brinkman index 400 (0, 1200) 450 (0, 960) 0.925
%VC (%) 81.9 ± 21.1 87.7 ± 19.7 0.270
FEV1.0% (%) 76.6 ± 8.2 76.6 ± 10.6 0.993
Preoperative supplemental oxygen (%) 15.8 4.3 0.056
Preoperative ventilator use (%) 5.3 2.2 0.361
General anesthesia (%) 84.2 87.7 0.719
DLV (%) 52.6 25.7 0.015
Lung surgery (%) 26.3 22.5 0.779
Duration of operation (min) 237 (82, 323) 153 (82, 270) 0.417
Duration of anesthesia (min) 361 (238, 414) 256 (170, 378) 0.110
Volume of urine (ml) 400 (200, 650) 275 (100, 600) 0.249
Volume of blood loss (g) 50 (0, 284) 37 (0, 150) 0.334
Volume of blood loss (g/kg) 0.79 (0.00, 4.66) 0.65 (0.00, 2.78) 0.371
Volume of infusion (ml) 2039 (715, 3047) 1566 (906, 2467) 0.357
In-out balance (ml) 1330 (426, 2077) 1034 (615, 1685) 0.634
Volume of oxygen use (L) 549 (279, 650) 269 (180, 456) 0.009
Transfusion (%) 21.1 11.0 0.256
FiO2 ≥ 60% (%) 63.2 29.1 0.004

Values are presented as percentage, mean ± SD or median (Q1, Q3). AE: acute exacerbation, KL-6: sialylated carbohydrate Krebs von den Lungen-6 antigens, CRP: C-reactive protein, LDH: lactate dehydrogenase, %VC: percent vital capacity, FEV1.0%: forced expiratory volume 1.0 (s) percent, DLV: differential lung ventilation, FiO2 ≥ 60%: fraction of inspired oxygen ≥ 60%.

Table 2.

Hazard Ratios for All-cause and IP-related Deaths

Outcome No. of participants No. of events Crude HR (95% CI) P value Multivariable-adjusted* HR (95% CI) P value
All-cause death
 Non-AE group 463 119 1.00 (reference) < 0.001 1.00 (reference) < 0.001
 AE group 19 10 4.82 (2.51−9.26) 5.16 (2.62−10.14)
IP-related death
 Non-AE group 463 28 1.00 (reference) < 0.001 1.00 (reference) < 0.001
 AE group 19 5 9.47 (3.59−25.02) 9.32 (3.36−25.83)

*Multivariable adjustment for age, sex, body mass index, preoperative supplemental oxygen, preoperative ventilator use, and type of surgery (lung or other). IP: interstitial pneumonia, HR: hazard ratio, AE: acute exacerbation.

Table 3.

ORs for AE-IP in Crude and Multivariable-adjusted Analyses with Variable Selection

Variable Crude OR (95% CI) P value Multivariable-adjusted* OR (95% CI) P value
Male (vs. female) 10.64 (2.17−192.15) 0.022 8.41 (1.44−161.68) 0.051
Age (per 1 year) 1.01 (0.97−1.07) 0.566
Body mass index (kg/m2) 1.08 (0.96−1.21) 0.181
KL-6 (per 100 U/ml) 1.03 (0.98−1.07) 0.120
CRP (per 1 mg/dl) 1.12 (1.03−1.22) 0.009 1.21 (1.05−1.40) 0.006
LDH (per 1 U/L) 1.07 (0.86−1.20) 0.315
Brinkman index (per 100) 1.01 (0.94−1.07) 0.834
%VC (per 1%) 0.99 (0.96−1.01) 0.269
FEV1.0% (per 1%) 1.00 (0.95−1.05) 0.994
Preoperative supplemental oxygen 4.15 (0.91−13.79) 0.033
Preoperative ventilator use 2.51 (0.13−14.26) 0.391
General anesthesia (vs. regional anesthesia) 0.75 (0.24−3.29) 0.653
DLV (vs. two-lung ventilation) 3.21 (1.27−8.27) 0.013
Lung surgery (vs. others) 1.22 (0.39−3.31) 0.694 0.24 (0.06−0.96) 0.047
Duration of operation (per 1 h) 1.08 (0.91−1.24) 0.322
Duration of anesthesia (per 1 h) 1.10 (0.94−1.27) 0.208
Volume of urine (per 100 ml) 1.03 (0.95−1.09) 0.427
Volume of blood loss (per 100 g) 0.99 (0.84−1.05) 0.779
Volume of blood loss (per 10 g/kg) 0.93 (0.38−1.40) 0.803
Volume of infusion (per 1 L) 1.07 (0.79−1.34) 0.609
In-out balance (per 1 L) 1.13 (0.69−1.68) 0.595
Volume of oxygen use (per 100 L) 1.22 (1.05−1.40) 0.005
Transfusion 2.16 (0.60−6.21) 0.187
FiO2 ≥ 60% 4.18 (1.65−11.46) 0.003 5.22 (1.37−22.68) 0.018

*Multivariable adjustment with variable selection was performed using the backward method. In total, 270 participants with no missing data were included in the multivariate analysis. OR: odds ratio, AE: acute exacerbation, IP: interstitial pneumonia, KL-6: sialylated carbohydrate Krebs von den Lungen-6 antigens, CRP: C-reactive protein, LDH: lactate dehydrogenase, %VC: percent vital capacity, FEV1.0%: forced expiratory volume 1.0 (s) percent, DLV: differential lung ventilation, FiO2 ≥ 60%: fraction of inspired oxygen ≥ 60%.

Table 4.

Case-control Analysis with Propensity Score Matching

Variable Matching other than sex* Matching other than CRP Matching other than type of surgery Matching other than FiO2 ≥ 60%
AE (+) (n = 11) AE (-) (n = 43) P value AE (+) (n = 12) AE (-) (n = 49) P value AE (+) (n = 11) AE (-) (n = 40) P value AE (+) (n = 14) AE (-) (n = 53) P value
Male (%) 90.9 65.1 0.145 91.7 89.8 0.845 90.9 77.5 0.995 92.9 86.7 0.996
CRP (mg/dl) 1.10 (0.19, 5.04) 0.46 (0.16, 3.73) 0.475 2.25 (0.30, 5.34) 0.58 (0.13, 1.68) 0.044 1.10 (0.20, 5.04) 0.73 (0.20, 3.96) 0.246 2.70 (0.41, 5.71) 1.06 (0.23, 3.34) 0.872
Lung surgery (%) 36.4 32.6 0.504 33.3 36.7 0.944 36.4 52.5 0.374 28.6 35.9 0.932
FiO2 ≥ 60% (%) 63.6 51.2 0.392 58.3 59.2 0.681 63.6 57.5 0.840 64.3 37.7 0.035
KL-6 (U/ml) 1036 (595, 1767) 463 (322, 748) 0.343 893 (538, 1680) 499 (358, 928) 0.508 1036 (595, 1767) 492 (356, 770) 0.145 893 (481, 1593) 837 (460, 1430) 0.950
LDH (U/L) 220 (188, 279) 208 (184, 247) 0.845 220 (178, 264) 206 (178, 251) 0.937 220 (188, 279) 208 (188, 236) 0.631 220 (168, 279) 213 (188, 246) 0.848
%VC (%) 89.3 ± 18.9 87.4 ± 22.4 0.793 87.0 ± 19.8 83.1 ± 21.1 0.491 89.3 ± 18.9 90.4 ± 23.4 0.981 87.0 ± 19.8 82.1 ± 19.3 0.242
Preoperative supplemental oxygen (%) 0.0 2.3 0.995 8.3 10.2 0.650 0.0 2.5 0.996 14.3 11.3 0.942
Duration of operation (min) 285 (82, 323) 211 (115, 317) 0.833 261 (88, 320) 243 (102, 321) 0.739 285 (82, 323) 214 (91, 331) 0.853 194 (82, 317) 213 (87, 298) 0.828
In-out balance (ml) 1420 (426, 2336) 1260 (891, 1772) 0.762 1421 (521, 2074) 1278 (900, 1852) 0.804 1420 (426, 2336) 1070 (801, 1988) 0.881 1375 (426, 1812) 1328 (812, 1855) 0.569

Values are presented as percentage, median (Q1, Q3) or mean ± SD. *Propensity score for AE was generated by potential AE-IP risk factors other than sex, namely, CRP, type of surgery, FiO2 ≥ 60%, KL-6, LDH, %VC, preoperative supplemental oxygen, duration of operation, and in-out balance. Other propensity scores were calculated in the same manner. In total, 270 participants with no missing data were included in the analysis. P values were calculated using conditional logistic regression analysis. AE: acute exacerbation, CRP: C-reactive protein, FiO2 ≥ 60%: fraction of inspired oxygen ≥ 60%, KL-6: sialylated carbohydrate Krebs von den Lungen-6 antigen, LDH: lactate dehydrogenase, %VC: percentage vital capacity, IP: interstitial pneumonia..