Analysis of the pathogenic bacteria, drug resistance, and risk factors of postoperative infection in patients with non-small cell lung cancer
Introduction
According to relevant reports, lung cancer is the leading cause of cancer-related mortality worldwide, and the incidence of lung cancer in China is high. In recent decades, the incidence of lung cancer has continued to rise, and the mortality and incidence of malignant tumors are ranked first (1). Approximately 80% of primary bronchial lung cancers are non-small cell lung cancer (NSCLC), with the rest being small cell lung cancer. At present, surgical treatment is still the main treatment for small cell lung cancer. However, these patients often have basic diseases, and the body is in a state of consumption during the treatment process, which leads to a further decline in the patient’s resistance, and is more easily combined with infections, which are more common in lung infections (2). Understanding the postoperative complications of NSCLC patients and analyzing its characteristics and related factors are effective means to improve the therapeutic effect and prognosis of patients. At present, there are few studies on the distribution of pathogens and related drug resistance in NSCLC. Based on this, we collected the clinical data of NSCLC patients treated in our hospital, analyzed their infections and the distribution of pathogens, and understood the risk factors affecting the infection of patients, so as to provide a basis for reducing and preventing hospital infections. The report is as follows. We present the following article in accordance with the STROBE reporting checklist (available at https://dx.doi.org/10.21037/apm-21-2364).
Methods
General information
A total of 119 patients with NSCLC who were admitted to our hospital from January 2017 to March 2020 were selected. The inclusion criteria were as follows: (I) the patients’ family members were aware of and agreed to this study, and signed the relevant informed consent; (II) patients with complete clinical data; and (III) patients diagnosed with NSCLC by clinical manifestations and imaging examinations. Patients were excluded based on the following criteria: (I) patients with other tumors; (II) patients with infection before treatment; (III) patients who were lost to follow-up; and (IV) patients with mental illnesses, such as depressive disorder and schizophrenia. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by medical ethics committee of Sichuan Provincial People’s Hospital [Lunshen (Research) No. 390, 2020]. The patients’ family members were aware of and agreed to this study, and signed the relevant informed consent.
Data collection
The clinical data of patients was collected, including age, gender, length of hospital stay, comorbid diseases (hypertension, diabetes, hyperlipidemia, etc.), TNM staging (stage I–II, stage III), pathological classification (adenocarcinoma, squamous cell carcinoma), surgery time (≥3 h, <3 h), hospital stay (≥30 d, <30 d), invasive procedures, hemoglobin, serum albumin, etc.
Grouping
The diagnostic criteria for infection were as follows: (I) all patients underwent surgical treatment; (II) no infection occurred preoperatively; and (III) all patients were infected postoperatively. According to the relevant standards in the Diagnostic Standards for Nosocomial Infections, the diagnosis was confirmed by sputum bacterial culture, clinical manifestations, CT, and other examinations. The patients were divided into infected and uninfected groups according to whether they had a postoperative infection (3).
Identification of pathogenic bacteria and drug resistance detection
The specimens were collected from the infected sites of patients who had postoperative infection. Strict aseptic operation was carried out during specimen collection. Following collection, the specimens were sent for inspection, and an VITEK 2 Compact automatic microbial identification system (Bio Mérieux, Shanghai, China) was used for detection to analyze the distribution of pathogenic bacteria. For drug resistance, the minimum inhibitory concentration was used for drug susceptibility experiments (4).
Observation indicators
The pathogenic bacteria and drug resistance of postoperatively infected NSCLC patients were analyzed. The risk factors leading to postoperative infection were analyzed.
Statistical methods
The data in this study were statistically analyzed by SPSS22.0 software (SPSS, Chicago, Illinois, USA). Measurement data were described by the mean ± standard deviation (x̅±s), and the t-test was used. Counting data were described by pass rate or composition ratio, and χ2 test was used. Multivariate logistic regression analysis was used to analyze the risk factors of postoperative infection in patients with NSCLC. The difference was statistically significant when P<0.05.
Results
Postoperative infection of 119 patients
Among the 119 included patients, 33 patients (27.73%) had postoperative infections, and 86 patients (72.28%) had no infections.
Distribution of infectious pathogens after surgery
The secretions from the infected sites of the 33 infected patients were cultured and treated, and 81 strains pathogenic bacteria were isolated. Of these, 43 strains (53.09%) were gram-negative bacteria, 34 strains (41.98%) were gram-positive bacteria, and four strains (4.94%) were fungi. The specific distribution is shown in Table 1.
Table 1
| Pathogenic bacteria | Strains | Rate (%) |
|---|---|---|
| Gram-positive bacteria | 43 | 53.09 |
| |
18 | 22.22 |
| Coagulase-negative |
14 | 17.28 |
| |
7 | 8.64 |
| Other | 4 | 4.94 |
| Gram-negative bacteria | 34 | 41.98 |
| |
15 | 18.52 |
| |
9 | 11.11 |
| |
4 | 4.94 |
| |
3 | 3.70 |
| Other | 3 | 3.70 |
| Fungus | 4 | 4.94 |
| Total | 81 | 100.00 |
Analysis of drug resistance of infectious pathogens after surgery
Analysis of drug resistance of gram-negative bacteria after postoperative infection
As shown in Table 2, the highest rate of resistance to ciprofloxacin in gram-negative bacteria after surgery was 81.39%, and the lowest rates of resistance to drug-resistant imipenem and meropenem were 9.30% and 4.65%, respectively.
Table 2
| Antibacterial agents | Gram-negative bacteria (n=43) | |
|---|---|---|
| Strains | Drug resistance rate (%) | |
| Ciprofloxacin | 35 | 81.39 |
| Ceftazidime | 24 | 55.81 |
| Ceftriaxone | 20 | 46.51 |
| Levofloxacin | 19 | 44.18 |
| Macrodantin | 8 | 18.60 |
| Imipenem | 4 | 9.30 |
| Meropenem | 2 | 4.65 |
Analysis of drug resistance of gram-positive bacteria after postoperative infection
As shown in Table 3, the highest rate of resistance to erythromycin after postoperative infection of gram-positive bacteria was 82.35%, and the lowest rate of resistance to vancomycin was 5.88%.
Table 3
| Antibacterial agents | Gram-positive bacteria (n=34) | |
|---|---|---|
| Strains | Drug resistance rate (%) | |
| Erythrocin | 28 | 82.35 |
| Penicillin G | 19 | 55.88 |
| Levofloxacin | 16 | 47.59 |
| Gentamicin | 8 | 23.53 |
| Cefoxitin | 4 | 11.76 |
| Vancomycin | 2 | 5.88 |
Single-factor analysis of postoperative infection in patients with NSCLC
According to the univariate analysis, there were differences between the two groups in terms of age, hospital stay, comorbid diseases, operation time, invasive procedures, hemoglobin, and serum albumin (P<0.05). However, there were no differences between the two groups in terms of gender, TNM staging, and pathological classification (P<0.05), as shown in Table 4.
Table 4
| Factor | Infections group (n=33) | No infections group (n=86) | χ2 | P |
|---|---|---|---|---|
| Age | 27.413 | <0.001 | ||
| <60 years | 5 | 59 | ||
| ≥60 years | 28 | 27 | ||
| Gender | 0.057 | 0.810 | ||
| Man | 18 | 49 | ||
| Woman | 15 | 37 | ||
| Comorbid diseases | 26.971 | <0.001 | ||
| Yes | 27 | 25 | ||
| No | 6 | 61 | ||
| TNM staging | 1.544 | 0.214 | ||
| I–II staging | 17 | 55 | ||
| III staging | 16 | 31 | ||
| Pathological classification | 1.058 | 0.303 | ||
| Adenocarcinoma | 19 | 54 | ||
| Squamous carcinoma | 14 | 32 | ||
| Operation time | 27.997 | <0.001 | ||
| >3 h | 29 | 29 | ||
| ≤3 h | 4 | 57 | ||
| Hospital stay | 41.089 | <0.001 | ||
| >30 d | 28 | 18 | ||
| ≤30 d | 5 | 68 | ||
| Invasive procedures | 35.243 | <0.001 | ||
| Yes | 30 | 26 | ||
| No | 3 | 60 | ||
| Hemoglobin (g/L) | 8.760 | 0.003 | ||
| >90 | 12 | 57 | ||
| ≤90 | 21 | 29 | ||
| Serum albumin (g/L) | 18.007 | <0.001 | ||
| >30 | 6 | 53 | ||
| ≤30 | 27 | 33 |
Analysis of multiple factors leading to postoperative infection in patients with NSCLC
The significance and assignment of the factors to be analyzed are shown in Table 5. The unconditional multivariate logistic regression model analysis showed that age ≥60 years old, hospitalization time >30 days, comorbid diseases, operation time ≥3 hours, hospitalization time >30 days, invasive operation, hemoglobin ≤90 g/L, and serum albumin ≤30 g/L were independent risk factors leading to postoperative infection in patients with NSCLC (P<0.05), as shown in Table 6.
Table 5
| Factors | Significance | Assignment |
|---|---|---|
| X1 | Age | 0= <60 years; 1= ≥60 years |
| X2 | Hospital stay | 0= ≤30 d; 1= >30 d |
| X3 | Comorbid diseases | 0= no; 1= yes |
| X4 | Operation time | 0= <3 h; 1= ≥3 h |
| X5 | Invasive procedures | 0= no; 1= yes |
| X6 | Hemoglobin | 0= >90 g/L; 1= ≤90 g/L |
| X7 | Serum albumin | 0= >30 g/L; 1= ≤30 g/L |
Table 6
| Factors | Regression coefficient | Standard error | Wald χ2 | P | OR (95% CI) |
|---|---|---|---|---|---|
| X1=1 (Reference =0) | 0.915 | 0.205 | 8.459 | <0.001 | 2.496 (1.670–3.731) |
| X2=1 (Reference =0) | 0.889 | 0.316 | 9.184 | <0.001 | 2.432 (1.309–4.519) |
| X3=1 (Reference =0) | 0.649 | 0.311 | 3.526 | 0.002 | 1.913 (1.000–3.661) |
| X4=1 (Reference =0) | 0.711 | 0.334 | 3.157 | 0.018 | 2.036 (1.057–3.918) |
| X5=1 (Reference =0) | 0.619 | 0.284 | 4.595 | 0.001 | 1.913 (1.096–3.338) |
| X6=1 (Reference =0) | 0.705 | 0.236 | 8.715 | <0.01 | 2.024 (1.274–3.214) |
| X7=1 (Reference =0) | 0.613 | 0.228 | 9.514 | <0.01 | 1.846 (1.181–2.886) |
Discussion
Most patients with NSCLC are at an advanced stage when first diagnosed, with a high malignancy stage and poor chemotherapy sensitivity, and thus, early treatment is crucial (5). Understanding the postoperative infection status can help to improve the prognosis and treatment effect of patients. In this study, 33 of the 119 included patients (27.73%) developed postoperative infections. Through bacterial culture and drug susceptibility test analysis, it was found that gram-negative bacteria infections accounted for the majority, indicating that the pathogenic bacteria of patients with infection were invasive. The high resistance rate to erythromycin indicates that in clinical practice, appropriate antibiotics should be selected for treatment according to the drug sensitivity results after postoperative infection in NSCLC patients to avoid the abuse of antibiotics and reduce the occurrence of drug resistance (6).
The unconditional multivariate logistic regression model analysis showed that age ≥60 years old, hospitalization time >30 days, comorbid diseases, operation time ≥3 hours, invasive operation, hemoglobin ≤90 g/L, and serum albumin ≤30 g/L were independent risk factors leading to postoperative infection in patients with NSCLC. We speculate that this may be caused by the following factors. Firstly, the relationship between postoperative infection and age could be due to the declining function of body tissues and organs in elderly patients, as well as the declining defense ability of the bronchial mucosa of such patients, which can cause respiratory tract infection in patients. At the same time, long-term hospitalization leads to a poor anti-infection ability against pathogens in the hospital. Numerous studies have shown that age is a risk factor that results in susceptibility to infection after surgical treatment (7,8). Secondly, the relationship between postoperative infection and length of hospitalization could be attributable to the fact that patients with a longer hospitalization time have more serious illnesses, are in contact with other patients during hospitalization, and undergo an increased number of invasive operations, which can easily lead to nosocomial infection (9). Thirdly, the relationship between postoperative infection and comorbid diseases could be due to the fact that patients with underlying diseases typically have lower physical fitness and are more likely to develop infections after surgical treatment. Fourthly, the relationship between postoperative infection and operation time could be attributable to the fact that patients often choose the lateral position during surgical treatment, and intraoperative secretion retention is prone to occur in this position. Studies have shown that with the prolongation of operation time, secretion retention will increase significantly (10). Previous studies have reported that the time of anesthesia also increases after the operation time is extended. After the one-lung ventilation time increases, the time of pulmonary fistula will also increase, leading to lung damage (11). However, patients may become irritable and restless after prolonged anesthesia time, which may cause respiratory function to be inhibited after taking sedatives. Thus, the patient may have difficulty in expectoration, a weakened cough emission, and is prone to pulmonary infection. Patients may have respiratory dysfunction, which can also lead to postoperative respiratory failure (12,13). Chen et al. (14) reported that as the operation time is prolonged, the time of repeated rubbing and squeezing of the lungs is also increased, as is bronchial secretions, which significantly increases the postoperative lung infection rate (15). Fifthly, the relationship between postoperative infection and invasive operation could be due to the fact that endotracheal intubation is often required after surgery. This is an invasive operation that could easily damage the oral mucosa of the patient and destroy the balance of the oral flora. Studies have also shown that long-term pure oxygen inhalation can cause normal lung tissue damage and increase the risk of respiratory and pulmonary infections (16,17). Lastly, the relationship between postoperative infection and hemoglobin/serum albumin could be attributable to the fact that patients with low levels of hemoglobin and serum albumin levels have a poor nutritional status. Thus, the body cannot provide the consumed capacity, and the body’s impaired immunity will lead to infection (18).
From the above analysis of risk factors, it is clear that in order to reduce the risk of postoperative infection, clinical attention needs to be paid to patients who exhibit these risk factors. Older patients need to strengthen nutrition before surgery to improve their immunity. Doctors should also try to avoid prolonging the operation time and reduce surgical trauma. Furthermore, invasive operations after surgery should be reduced. During surgical treatment, doctors should avoid invasive operations and act gently. When the patient’s condition permits, the use of a ventilator should be reduced, and it is best to perform sputum suction in the operating room. The correct use of antibiotics during treatment. If the tube can be taken offline as soon as possible, the incidence of nosocomial infection can be reduced (19).
In summary, the postoperative infection rate of patients with NSCLC is high, and the main cases are gram-negative infections. There are numerous postoperative infection factors in patients, and these need to be strictly controlled in clinical practice, which is an effective means to prevent postoperative infection. However, the number of people included in this study is limited, and the follow-up sample size can be increased to expand the research scope and increase the research direction.
Acknowledgments
Funding: None.
Footnote
Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://dx.doi.org/10.21037/apm-21-2364
Data Sharing Statement: Available at https://dx.doi.org/10.21037/apm-21-2364
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/apm-21-2364). The authors have no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by medical ethics committee of Sichuan Provincial People’s Hospital [Lunshen (Research) No. 390, 2020]. The patients’ family members were aware of and agreed to this study, and signed the relevant informed consent.
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
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(English Language Editor: A. Kassem)
