The Evaluation of risk factors and prognostic impact of glucocorticoid therapy among non-HIV patients with Pneumocystis Jirovecii Pneumonia (PCP) Running title：Glucocorticoid therapy among non-HIV patients with PCP

The Evaluation of risk factors and prognostic impact of glucocorticoid therapy among non-HIV patients with Pneumocystis Jirovecii Pneumonia (PCP) Running title：Glucocorticoid therapy among non-HIV patients with PCP | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Evaluation of risk factors and prognostic impact of glucocorticoid therapy among non-HIV patients with Pneumocystis Jirovecii Pneumonia (PCP) Running title：Glucocorticoid therapy among non-HIV patients with PCP Jun Li, Xiangdong Mu, Haichao Li, Xinmin Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3906065/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Glucocorticoids have been shown to be very effective in the treatment of Human Immunodeficiency Virus (HIV) associated Pneumocystis jirovecii Pneumonia (PCP). However, risk factors and the impact on prognosis in non-HIV-PCP patients remain unclear. Our study aimed to early identification risk factors and prognostic impact of glucocorticoids therapy in non-HIV-PCP patients to decrease patients’ mortality. Methods A retrospective study was conducted on adult (≥ 18 years old) patients diagnosed with non-HIV-PCP in Peking University First Hospital from April 2007 to October 2022. A total of 269 patients with non-HIV-PCP were hospitalized during the period, and 200 patients were eventually included. Demographic data and related clinical data were collected. Univariate and multivariate logistic regression were used to analyze the relationship between variables and poor prognosis. Results A total of 200 non-HIV-PCP patients were included. 29% (58/200) patients died during admission. Univariate analysis showed that age, history of chemotherapy, history of glucocorticoid, autoimmune disease, organ transplantation, respiratory failure, platelet count, neutrophil/lymphocyte ratio, highly sensitive C-reactive protein, albumin, lactic dehydrogenase, d-dimer, bronchoalveolar lavage fluid (BALF)-neutrophil percentage, BALF-lymphocyte percentage, hospital-acquired pneumonia associated pathogen infection, pneumothorax, mediastinal emphysema, caspofungin therapy and high dose (≥ 1mg/(kg· d)) glucocorticoids therapy have a risk of death due to PCP patients. Multivariate analysis showed that age (OR = 1.062, 95%CI 1.021–1.104, P = 0.003), hospital-acquired pneumonia associated pathogen infection (OR = 4.170, 95%CI 1.407–12.357, P = 0.010) and high dose glucocorticoid therapy (OR = 7.047, 95%CI 2.482–20.006, P < 0.001) were independent risk factors for in-hospital death in non-HIV-PCP patients. Conclusions Considering the rapid course of the disease in non-HIV-infected immunocompromised patients. Early identification of high-risk PCP patients is critical to reduce morbidity and mortality. Our study found that non-HIV-PCP patients treated with high doses of glucocorticoids, old age, history of chemotherapy and hospital-acquired pneumonia associated pathogen infection had worse outcomes during hospitalization. Pneumocystis Jirovecii Pneumonia Non-Human Immunodeficiency Virus Glucocorticoid Risk factors Figures Figure 1 Figure 2 Background Pneumocystis jirovecii Pneumonia (PCP) often occurs in immunocompromised hosts and is associated with high morbidity and mortality. With the increasing use of immunosuppressants in solid tumors, hematological diseases, organ transplantation, and inflammatory diseases, the population of PCP is gradually transitioning from Human Immunodeficiency Virus (HIV) patients to non-HIV infected patients. Compared with HIV-PCP, non-HIV-PCP patients may present with acute fulminant disease process, with more severe pulmonary inflammation and hypoxemia, and 40% May progress to respiratory failure, with a very high mortality [ 1 , 2 ] . Glucocorticoids are widely used as immunosuppressants in immunocompromised people, which can be divided into the use of glucocorticoids before and after PCP. Glucocorticoids can directly reduce and damage T or B cells [ 3 ] , inhibit the cytotoxicity of NK cells and phagocytosis of macrophages, and inhibit the synthesis of known inflammatory cytokines [ 4 ] . In a retrospective study that included 116 non-HIV-PCP patients, it was found that up to 90% of patients were treated with glucocorticoids within 1 month prior to PCP diagnosis, and the use of glucocorticoids was associated with the development of PCP [ 2 ] . In another study, hormones increased the risk of infection in PCP patients in a dose-dependent manner. Studies have shown that individuals treated with glucocorticoids are susceptible to pneumocystis, but may reduce inflammation caused by infection and reduce the risk of respiratory failure in non-HIV-PCP patients [ 1 ] . However, other studies have shown that the use of glucocorticoids before the onset of PCP in non-HIV-infected patients is not associated with a lower risk of respiratory failure [ 5 ] . Previous studies also found an interesting phenomenon that sudden cessation or gradual reduction of glucocorticoids may aggravate respiratory symptoms and hypoxemia in non-HIV-PCP patients [ 6 , 7 ] . The relationship between withdrawal of glucocorticoids before PCP and prognosis of non-HIV-PCP patients needs further study. In addition, some studies have also shown that glucocorticoid therapy after the occurrence of PCP can prevent early disease deterioration and improve the prognosis of moderate to severe PCP in HIV patients [ 8 ] , while its application in non-HIV-PCP remains controversial [ 9 , 10 ] . As the epidemiology of PCP has changed, people with immunosuppression caused by glucocorticoids and other immunosuppressants are susceptible to PCP, and many clinical cases have shown that this infection often occurs during glucocorticoids withdrawal. Therefore, it is necessary to identify the complex role of glucocorticoids in the pathogenesis and prognosis of non-HIVPCP. The objective of this study was to evaluate the effects of glucocorticoids administration before admission, glucocorticoids withdrawal, and glucocorticoids therapy after PCP on the prognosis of non-HIV-PCP patients. Materials and methods Study design, setting, and study population In this study, PCP patients admitted to Peking University First Hospital from April 2007 to October 2022 were retrospectively collected. Relevant data of patients were collected by consulting electronic medical records, and 200 non-HIV-PCP patients were eventually included (Fig. 1 ). This study was approved by the Ethics Committee of Peking University First Hospital. Data collection and definitions All medical records were retrospectively reviewed using standardized study protocols. Demographic characteristics, underlying diseases or conditions, laboratory results, patient management, and clinical outcomes were evaluated. The adult patients (aged 18 years) who met the following criteria were considered definitively diagnosed with PCP: (1) clinical symptoms or signs relevant to PCP ( fever, cough, or shortness of breath); (2) imaging findings compatible with PCP (ground glass changes in both lungs or diffuse infiltration of lung interstitial shadow); and (3) positive Pneumocystis jirovecii from respiratory samples (BALF, sputum, bronchial flushing fluid, bronchial secretions or lung tissue). Prior glucocorticoids use was defined as a history of glucocorticoids use 1 month prior to admission for PCP, all available information related to dose and duration was recorded, and doses of various types of glucocorticoids were converted to equivalent doses of prednisone. Glucocorticoids-related PCP refers to the patients who developed PCP-related symptoms after glucocorticoids-related withdrawal and were finally diagnosed as PCP by etiology and imaging tests. Hospital-acquired pneumonia-associated pathogen infections are clinically or microbiologically documented infections during hospitalization and 48 hours after discharge. Statistical analysis The non-normal distribution of the continuous variable is expressed by the median (interquartile distance [IQR]), and the normal distribution is expressed by the mean ± standard deviation (SD). Compared the two groups using either the T-test or the Mann-Whitney U test. The categorical variables were expressed as percentages (%), and the comparison between the two groups was performed by Fisher or Chi-square test. P value < 0.05 was considered statistically significant. Covariates with a P-value < 0.05 in the univariate analysis were included in the final model of multivariable logistic regression. All the above data were analyzed using SPSS 23.0. Results Clinical characteristics of study subjects Non-HIV-PCP patients were divided into death group (n = 58) and survival group (n = 142) according to clinical outcomes during hospitalization. Compared with the survival group, the death group had a higher median age (62 vs 51.5, P < 0.001), a shorter hospital stay (14 vs 24, P < 0.001), and a higher rate of combined respiratory failure (98.3% vs 62.7%, P < 0.001). There were no significant differences in gender, body mass index (BMI) and smoking history between the two groups. In terms of underlying diseases, the death group had a higher proportion of autoimmune diseases (46.6% vs 29.6%, P = 0.022), while the survival group had a higher proportion of organ transplants (19.7% vs 5.2%, P = 0.016). Compared with the survival group, patients' drug use before PCP occurred had a higher proportion of glucocorticoids use in the death group (96.6% vs 85.9%, P = 0.029). There were no significant differences in glucocorticoid dose, duration of glucocorticoid use, withdrawal of glucocorticoids, use of immunosuppressants, use of biologics, use of immune checkpoint inhibitors, and preventive use of sulfonamide between the two groups. The proportion of patients with a history of chemotherapy was higher in the survival group (22.5% vs 3.4%, P = 0.001), and there was no significant difference between radiotherapy and radiotherapy combined with chemotherapy (Table 1 ). There were no significant differences in the clinical manifestations of dyspnea, fever, cough, sputum, chest pain and hemoptysis between the two groups. Compared with the survival group, patients in the death group showed platelet count (152 vs 184, P = 0.002), lymphocyte count (0.4 vs 0.6, P = 0.008), total protein (54.2 vs 57.4, P = 0.031), albumin (27.5 vs 29.6, neutrophil count (7.5 vs 6.2, P = 0.04), neutrophil/lymphocyte ratio (NLR) (17.7 vs 9.8, P < 0.001), hypersensitive C-reactive protein (HsCRP) (88.5 vs 54.2, P = 0.012), glutamic oxalacetic transaminase (29 vs 25, P = 0.021), lactate dehydrogenase (LDH) (482.5 vs 386, P < 0.001), d-dimer (1 vs 0.48, P = 0.001), fibrinogen degradation products (6.6 vs 3.9, P < 0.001) and G test index (261.6 vs 141.8, P = 0.004) were higher. Blood gas analysis showed that oxygenation index (OI) (203.2 vs 272.7, P < 0.001), arterial oxygen saturation (SaO2) (89.3 vs 93, P < 0.001), and arterial partial pressure of carbon dioxide (PaCO 2 ) (30.4 vs 32.9, P = 0.008) were lower in the death group than in the survival group, and the difference of pulmonary arterial oxygen pressure (P(A-a)O 2 ) was higher (93.8 vs 59.5, P < 0.001). In terms of blood immune indexes, IgG level (9 vs 6.3, P = 0.034), percentage of B cells (14.9% vs 7.2%, P = 0.009) and CD3 + T cell count (301 vs 514.6, P = 0.002) were higher, CD8 + T cell counts were lower (156.4 vs 262.4, P < 0.001) in the death group, and CD4 + T cell counts were not significantly different between the two groups. BALF lymphocyte subsets showed no statistically significant differences in the percentages of CD3 + T cells, CD4 + T cells, and CD8 + T cells between the two groups. In BALF cell classification, the percentage of macrophages (28% vs 40%, P = 0.034) and lymphocytes (16% vs 34.5%, P < 0.001) were lower in the death group, and the percentage of neutrophils (51% vs 15%, P < 0.001) was higher (Table 2 ). Compared with the survival group, the death group had more common pathogens (82.8% vs 49.3%, P < 0.001), two pathogens (34.5% vs 14.8%, P = 0.002), and three pathogens (16.6% vs 1.4%, P < 0.001) and a higher proportion of pathogens associated with common hospital-acquired pneumonia (43.1% vs 11.3%, P < 0.001), as shown in Table 3 . Among the combined etiology species, Acinetobacter baumannii (15.5% vs 3.5%, P = 0.007), Pseudomonas aeruginosa (15.5% vs 2.8%, P = 0.003), Klebsiella pneumoniae (13.8% vs 2.1%, P = 0.003), Candida candida (12.1% vs 0.7%, P = 0.001) and the rates of Cryptococcal infection (6.9% vs 0.7%, P = 0.041) were higher in the death group. The rates of Cytomegalovirus (CMV) and Aspergillus infection were not statistically different between the two groups, as shown in Fig. 2 . In terms of imaging, the proportions of pneumothorax (17.2% vs 3.5%, P = 0.002) and mediastinal emphysema (10.3% vs 1.4%, P = 0.011) in the death group were significantly higher than those in the survival group. The survival group showed a higher proportion of lobular core nodules (13.4% vs 3.4%, P = 0.038), while there was no statistical difference between the two groups in imaging findings such as distribution near pleura, distribution along vascular bundles, ground glass density shadow, plaque shadow, solid shadow, mesh shadow, thickening interlobular interval, pulmonary air sac, pleural effusion, and lymph node enlargement, as shown in Table 4 . Treatment outcomes Compared with the survival group, the death group were more likely to be treated with second-line agents (36.2% vs 9.2%, P < 0.001) and carpofungin (56.9% vs 31.7%, P = 0.001) and the proportion of high dose (≥ 1mg/ (kg· d)) glucocorticoids treatment was higher (55.6% vs 26.8%, P < 0.001). The proportion of patients treated with low-dose (< 0.5mg/ (kg· d)) glucocorticoids was higher in the survival group (11.1% vs 28.3%, P = 0.012). The proportion of second-line treatment in the death group was higher than that in the survival group (29.3% vs 4.2%, P < 0.001). Rates of ICU admission in the death group (77.6% vs. 28.9%, P < 0.001), use of high-flow oxygen therapy (81% vs. 39.4%, P < 0.001), non-invasive mechanical ventilation (84.5% vs. 20.4%, P < 0.001) and invasive mechanical ventilation were higher than those in the survival group (82.8% vs 7%, P < 0.001), as shown in Table 5 . Prognostic factors of non-HIV-infected patients with PCP Logistic univariate regression analysis was performed for non-HIV-PCP patients. Results showed age, history of chemotherapy, history of glucocorticoid use, autoimmune disease, organ transplantation, respiratory failure, platelet count, NLR, HsCRP, albumin, LDH, d-dimer, BALF-neutrophil percentage, BALF-lymphocyte percentage, and combined with hospital-acquired pneumonia associated pathogen infection, pneumothorax, mediastinal emphysema, treatment with carpofungine and adjuvant high-dose glucocorticoids were statistically significant between the two groups (P < 0.05). The factors with P < 0.05 were incorporated into the logistic model for stepwise regression analysis, and the results showed that age (OR = 1.062, 95% CI 1.021–1.104, P = 0.003), combined with hospital-acquired pathogen infection (OR = 4.170, 95%CI 1.407–12.357, P = 0.010), adjuvant high-dose glucocorticoids therapy (OR = 7.047, 95% CI 2.482–20.006, P < 0.001) were independent risk factors for death in non-HIV-PCP patients, history of chemotherapy (OR = 0.067, 95% CI 0.007–0.670, P = 0.021) was independent protective factor factors for death in non-HIV-PCP patients, as shown in Table 6 . Discussion Non-HIV-PCP patients have a higher mortality rate than HIV-PCP patients, and finding the risk factors that affect the prognosis is the key to reduce the mortality rate. A meta-analysis of risk factors for death in non-HIV-PCP patients conducted by Wang Y et al. showed that age, other pulmonary diseases at diagnosis of PCP, solid tumors, CMV infection, LDH, lymphocyte count, invasive mechanical ventilation during hospitalization, and pneumothorax were non-risk factors for HIV-related PCP death [ 11 ] . Liu CJ et al. conducted a retrospective study on PCP patients in a medical center in northern Taiwan, and the results showed that lymphocytopenia, adjuvant glucocorticoids therapy and pneumothorax were significantly associated with high mortality in non-HIV-PCP patients [ 12 ] . Duan J et al. conducted a multi-factor analysis of 56 non-HIV-PCP patients admitted to ICU, suggesting that neutrophil/lymphocyte percentage and co-infection were independent risk factors for poor prognosis [ 13 ] .This study showed that old age, combination of pathogens associated with hospital-acquired pneumonia, and adjuvant use of high-dose glucocorticoids were independent risk factors for death in non-HIV-PCP patients, and chemotherapy history was a protective factor in non-HIV-PCP patients Previous studies have shown that chemotherapy before PCP is a risk factor for PCP in patients with solid tumors and organ transplantation [ 14 , 15 ] . With the establishment of international guidelines (HIV, hematologic malignancies, and transplantation) in recent years, the promotion of prophylactic use of sulfonamides in HIV, hematologic malignancies, and transplantation populations has resulted in a significant reduction in PCP morbidity and mortality in these populations. This study showed that patients with a history of chemotherapy before PCP had a better prognosis. Considering that the release of relevant specialist guidelines in recent years has raised the awareness of clinicians on the preventive use of sulfonamides for this type of disease, and thus made this type of PCP patients less likely to develop into severe diseases. At present, age is the main demographic characteristic related to the prognosis of non-HIV-PCP with clinical evidence. A study from Japan showed that the median age of PCP patients was 62 years old, showing a bimodal distribution, and the median age of children and adults was 5 years old and 63 years old, respectively. The mortality rate of adults was higher than that of children [ 16 ] . An epidemiological study of PCP from Germany showed that nearly half of PCP patients were between 50 and 75 years old, and the median age of patients increased from 62 to 64 years between 2014 and 2019 [ 17 ] . With the decline of physical function and the increase of basic diseases, the general immunity of the elderly is poor and easy to be infected with various respiratory pathogens. In adult HIV and non-HIV-PCP patients, the older the age, the worse the prognosis for PCP [ 18 , 19 ] . Roux A and colleagues confirmed the association between advanced age and PCP death in a large prospective cohort study that collected and analyzed 544 patients with PCP in France and found that the risk of death increased with age in patients older than 50 years [ 20 ] . Ricciardi A et al. performed a retrospective study of 116 non-HIV-PCP patients and found that advanced age was associated with the severity of PCP as well as death [ 21 ] . Compared with the elderly, in the study of PCP in children, Yun KS et al. found that age 60 years old and children < 5 years old should be more active in the assessment of disease, admission to hospital and early intervention treatment to avoid delaying the disease. In terms of pathogen infection, we classified Acinetobacter baumannii , Pseudomonas aeruginosa , Klebsiella pneumoniae and other pathogens detected after admission as hospital-acquired pneumonia-related pathogens, and found that infection with hospital-acquired pneumonia-related pathogens was an independent risk factor for death in HIV-PCP patients. Due to low immune function and lower than normal lymphocyte levels, non-HIV patients are often infected with multiple pathogens in addition to PCP infection. Kim SJ and colleagues found that co-bacterial infection was an independent predictor of death in non-HIV-PCP patients, and co-bacterial infection may be an indirect indicator of the severity of immunosuppression in non-HIV-PCP patients [ 23 ] . Patients with different immunosuppressive states are susceptible to different pathogens. In addition to Pneumocystis , T cell deficiency patients are often associated with bacteria, respiratory viruses and Cryptococcus infections. B-cell deficiency patients are often associated with bacterial infection. Patients with granulocyte defects are often infected with bacteria, Aspergillus, Nocardia , and Mycobacterium [ 24 ] . This also indirectly confirmed the results of this study, which showed that reduced counts of lymphocytes, CD3 + T cells, and CD8 + T cells were associated with death in non-HIV-PCP patients, possibly due to co-infection. Therefore, investigating the presence of respiratory co-infection at the time of PCP diagnosis can better identify patients at risk. Glucocorticoid is a "double-edged sword", for HIV-PCP patients, glucocorticoid has an important therapeutic effect, but for some non-HIV-PCP patients who must use glucocorticoid for a long time, glucocorticoid is an important cause of pneumocystis infection. Limper et al. [ 25 ] studied and analyzed BALF cell components during PCP and found that non-HIV infected patients had more neutrophilic infiltration in the lungs than HIV patients, and the higher burden of inflammatory cells was corresponding to the deterioration of oxygenation. Therefore, they believed that compared with other immunocompromised PCP patients, PCP has a better prognosis in inflammatory diseases treated with chronic glucocorticoids. However, a study conducted by Wieruszewski and colleagues in non-HIV-PCP patients who used glucocorticoids before PCP showed that glucocorticoids use before PCP in non-HIV patients was not associated with a reduced risk of respiratory failure [ 5 ] . Earlier studies also found an interesting phenomenon that the occurrence and development of PCP are related to glucocorticoids reduction [ 26 ] , and sudden cessation or gradual reduction of glucocorticoids may aggravate respiratory symptoms and hypoxemia in non-HIV-PCP patients [ 7 ] . Our study found that pre-withdrawal of glucocorticoids from PCP was a risk factor for non-HIV-PCP in-hospital death, but it was not an independent risk factor, which may be related to the sample size. We will expand the sample size for further study in the future. The use of glucocorticoids in HIV-PCP patients has been well established, and the U.S. Guidelines for the Prevention and Treatment of HIV Opportunistic infections in adults and adolescents recommend that, for patients who are not oxygenated, Moderate to severe PCP patients with PaO 2 < 70 mmHg or P(A-a)O 2 ≥ 35mmHg should be treated with glucocorticoids within 72 hours of anti-PCP treatment [ 27 ] . However, its use in non-HIV-PCP patients is still controversial, and there are currently no accepted guidelines that clearly recommend it [ 9 , 10 ] . Mundo W et al. conducted a single-center retrospective cohort study on PCP patients in the United States, including 28 non-HIV patients, and the results showed that the adjuvant use of glucocorticoids was associated with reduced mortality in non-HIV-PCP patients [ 28 ] . Other studies have shown that glucocorticoid therapy is associated with shorter ventilator use time and shorter ICU stay [ 29 ] ,but other studies have shown that glucocorticoid use is not correlated with clinical outcomes [ 30 , 31 ] . However, the samples of the above studies were small, with less than 100 cases. Therefore, Lemiale V et al. analyzed 139 non-HIV-PCP patients admitted to ICU in a hospital in Paris, France, and compared the prognosis of patients with different doses. The results showed that the use of high-dose glucocorticoids was associated with increased mortality in non-HIV-PCP patients, but not with ICU acquired infections [ 32 ] . Wieruszewski PM and colleagues assessed 30-day mortality in 323 adults with non-HIV-PCP who were divided into early (within 48 hours) glucocorticoids use group and non-early glucocorticoids use group, and showed that early adjuvant glucocorticoids use did not improve clinical outcomes in non-HIV-PCP patients [ 8 ] . Our study shows that adjuvant use of high-dose glucocorticoids is an independent risk factor for non-HIV-PCP death. It is unclear why the effects of adjuvant glucocorticoids therapy on outcomes differ between HIV and non-HIV patients. We speculate that these differences may be due to patients' previous exposure to glucocorticoids prior to the appearance of PCP resulting in a reduced response to the drug, which may be a consideration for future research. Shortcomings of this study: Firstly, this study was a single-center retrospective study. Due to the particularity of the disease, only 200 patients were included in the study in 15 years, and the sample size was not large enough. Secondly, the main underlying diseases of the patients studied were autoimmune diseases, kidney diseases, and organ transplantation, and the research results may not be applicable to patients with other underlying diseases. Thirdly, despite the combination of clinical symptoms, imaging findings, and etiology to diagnose PCP, the possibility of inclusion of pneumocystis colonized patients cannot be eliminated. Conclusions In conclusion, non-HIV-PCP patients treated with high doses of glucocorticoids, old age, and hospital-acquired pneumonia associated pathogen infection had worse outcomes during hospitalization. Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Peking University First Hospital (2021KEYAN111). The need for informed consent was waived by the Ethics Committee of Peking University First Hospital due to the retrospective nature of the study. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding ：This work was supported by Beijing Clinical Key Specialty Project (XKB2022B1002) and National Key R&D Program of China (2020YFC2005401). Authors’ contribution JL: Conceptualization, data collection, formal analysis, interpretation of data, writing of original draft and review, and editing. HCL: Conceptualization, data collection, interpretation of data, writing of original draft and review. XDM: Interpretation of data, writing of original draft and review, and editing. XML: Conceptualization, formal analysis, interpretation of data, writing of original draft and review, and editing. All authors read and approved the final manuscript. 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Corticosteroids as adjunctive therapy for severe Pneumocystis carinii pneumonia in non-human immunodeficiency virus-infected patients: retrospective study of 31 patients[J]. Clin Infect Dis. 1999;29(3):670–2. Moon SM, Kim T, Sung H, et al. Outcomes of moderate-to-severe Pneumocystis pneumonia treated with adjunctive steroid in non-HIV-infected patients[J]. Antimicrob Agents Chemother. 2011;55(10):4613–8. Lemiale V, Debrumetz A, Delannoy A, et al. Adjunctive steroid in HIV-negative patients with severe Pneumocystis pneumonia[J]. Respir Res. 2013;14(1):87. Tables Table 1. Comparison of clinical features between death group and survival group in non-HIV-PCP patients Death group （n=58 ） Survival group(n=142) P-value Age a , years 62（53.8，71） 51.5（37，62.3） ＜0.001 * Gender, n (%) Male Female 35（60.3） 23（39.7） 101（71.1） 41（28.9） 0.138 BMI a （kg/m 2 ） 22.5（20.4，24.2） 22.8（20.2，25.6） 0.494 Smoking history, n (%) 27（46.6） 48（33.8） 0.091 Length of stay a , (day) 14（8.8，29） 24（16，35） ＜0.001 * Underlying disease,n (%) Autoimmune disease Kidney disease Organ transplantation Solid malignant tumor Hematological diseases Skin disease Interstitial lung disease Primary immunodeficiency disease 27（46.6） 17（29.3） 3（5.2） 5（8.6） 2（3.4） 5（8.6） 1（1.7） 0（0） 42（29.6） 35（24.6） 28（19.7） 16（11.3） 17（12.0） 13（9.2） 4（2.8） 1（0.7） 0.022 * 0.495 0.016 * 0.580 0.081 0.905 1.000 1.000 Pre-admission immunosuppressants , n(%) Radiotherapy, n (%) 1（1.7） 3（2.1） 1.000 Chemotherapy, n (%) 2（3.4） 32（22.5） 0.001 * Radiotherapy + chemotherapy, n (%) 4（6.9） 5（3.5） 0.503 Corticosteroids, n (%) 56（96.6） 122（85.9） 0.029 * Corticosteroids duration a (days) 68.5（44.8，102.8） 71.5（47，126.5） 0.567 Daily dosage at presentation a (mg/d) 45（31.3，50） 40（30，55） 0.733 Corticosteroids withdrawal, n (%) 33（56.9） 67（47.2） 0.213 Immunosuppressive therapy, n (%) 36（62.1） 100（70.4） 0.250 Biological agent therapy, n (%) 6（10.3） 21（14.8） 0.404 Immune checkpoint inhibitors, n (%) 1（1.7） 4（2.8） 1.000 Preventive use of sulfonamides, n (%) 2（3.4） 3（2.1） 0.960 Respiratory failure, n (%) 57（98.3） 89（62.7） ＜0.001 * Symptom , n (%) Dyspnea 48（82.8） 103（72.5） 0.127 Fever 48（82.8） 124（87.3） 0.398 Cough 32（55.2） 94（66.2） 0.143 Expectoration 18（31） 52（36.6） 0.452 Chest pain 3（5.2） 6（4.2） 1.000 Hemoptysis 1（1.7） 3（2.1） 1.000 a: median (quartile); b: mean ± standard deviation; * : P < 0.05, indicating statistically significant difference. Table 2. Comparison of laboratory indicators between the death group and the survival group of non-HIV-PCP patients Death group （n=58 ） Survival group(n=142) P-value White blood cell count a (×10^9/L) 8.6（5.5，11.7） 7.7（4.7，10.3） 0.182 Hemoglobin b (g/L) 104.5±25.1 110.2±24 0.135 Platelet count a (×10^9/L) 152（93.8，198.0） 184（127.0，257.3） 0.002 * Neutrophil count a (×10^9/L) 7.5（4.7，10.5） 6.2（3.9，8.9） 0.040 * Lymphocyte count a (×10^9/L) 0.4（0.2，0.9） 0.6（0.4，0.9） 0.008 * NLR a 17.7（6.8，29.8） 9.8（5.6，15.6） ＜0.001 * Procalcitonin (μg/L)，n (%) ＜0.5 ≥0.5 36（61.2） 19（32.8） 98（69） 28（19.7） 0.082 HsCRP a (mg/l) 88.5（55.3，109） 54.2（16.9，95） 0.012 * Erythrocyte sedimentation rate a (mm/h) 46（24，84.5） 58（35，85） 0.193 Alanine aminotransferase a (IU/L) 27（16，59.8） 22.5（15，38.8） 0.076 Aspartate aminotransferase a (IU/L) 29（20，52.8） 25（18，37） 0.021 * Total Protein b (g/L) 54.2±8.4 57.4±9.8 0.031 * Albumin b (g/L) 27.5±6.9 29.6±5.9 0.035 * Serum creatinine a (μmol/L) 103.5（62.6，157.3） 90.5（68，165.0） 0.295 Urea nitrogen a (mmol/L) 11.2（5.9，16.9） 7.7（5.4，14.4） 0.295 LDH a (IU/L) 482.5（359.5，713） 386（296.5，505） ＜0.001 * D-dimer a (mg/L) 1.0（0.35，2.55） 0.48（0.25，0.94） 0.001 * G test a 261.6（171.9，481.8） 141.8（49.6，284.9） 0.004 * Blood gas analysis P/F b (mmHg) 203.2±66.2 272.7±92.8 ＜0.001 * SaO 2 a (%) 89.3（85，93.8） 93（88.6，95.5） ＜0.001 * PaO 2 a (mmHg) 56.8(49.8,65.5) 66.4（56.3，78.1） ＜0.001 * P(A-a)O 2 a 93.8（61.4，145.6） 59.5（43.1，102.3） ＜0.001 * Immune globulin IgG a (g/L) 9.0（5.8，14.2） 6.3（5.0，10.3） 0.034 * IgA a (g/L) 1.5（1.0，2.3） 1.6（1.0，2.5） 0.632 IgM a (g/L) 0.8（0.4，1.6） 0.9（0.5，1.5） 0.492 Peripheral lymphocyte subsets CD3+ T cell count a (/μl) 301（175.0，574.7） 514.6（274.7，940.5） 0.002 * CD4+ T cell count a (/μl) 148.6（60.7，225.6） 183.6（94.6，345.2） 0.079 CD8+ T cell coun a (/μl) 156.4（80.8，280.6） 262.4（141.6，538.1） ＜0.001 * CD4+/CD8+ a 0.9（0.6，1.6） 0.7（0.4，1.3） 0.149 B cell count a (/μl) 55.3（27.4，118.1） 52.6（6.4，119.4） 0.424 NK cell count a (/μl) 57.3（24.3，137.2） 63.7（34.4，144.6） 0.297 BALF CD3+ T cell a (%) 93.2（87.9，97.6） 95.2（92.8，97.7） 0.061 CD4+ T cell a (%) 33.4（23.1，43.2） 31.4（24.0，45.0） 0.920 CD8+ T cell a (%) 54.1（42.7，67.3） 57.5（46.4,67.6） 0.730 CD4 + /CD8 + a 0.6（0.4，1.0） 0.6 (0.4,0.9) 0.931 B cell a (%) 0.2（0，0.7） 0.2（0，1.0） 0.516 NK cell a (%) 4.7（1.1，7.2） 2.3 (0.7,4.9) 0.100 Macrophage a (%) 28（15.3，49.8） 40（23.3，51.8） 0.034 * Neutrophil a (%) 51（25.8，73） 15（7，41.8） ＜0.001 * Lymphocyte a (%) 16（7，26.8） 34.5（15，49） ＜0.001 * Note: a: median (quartile), b: mean ± standard deviation; NLR: Neutrophil/Lymphocyte Ratio; P/F: arterial partial pressure of oxygen/inhaled oxygen concentration; * P < 0.05, indicating a statistically significant difference. Table 3. Comparison of etiological examination between death group and survival group in non-HIV-PCP patients Death group （n=58 ） Survival group （n=142 ） P-value Co-pathogen infection, n (%) One pathogen infection Bacteria Fungus Virus 48（82.8） 20（34.5） 5（8.6） 5（8.6） 10（17.2） 70（49.3） 48（33.8） 11（7.7） 9（6.3） 28（19.7） ＜0.001 * 0.927 Two pathogens infection Bacteria + Fungi Fungus + Virus Bacteria + Virus Three pathogens infection 20（34.5） 9（15.6） 3（5.2） 8（13.8） 8（16.6） 21（14.8） 3（2.1） 7（4.9） 11（7.7） 1（1.4） 0.002 * ＜0.001 * Type of co-pathogen infection, n (%) Common pathogens causing hospital-acquired pneumonia § 25（43.1） 16（11.3） ＜0.001 * CMV 26（44.8） 43（30.3） 0.050 Aspergillus 13（22.4） 17（12） 0.061 Epstein-barr virus 4（6.9） 7（4.9） 0.832 Candida 7（12.1） 1（0.7） 0.001 * Cryptococcus 4（6.9） 1（0.7） 0.041 * Note: § Common pathogens causing hospital acquired pneumonia include Acinetobacter baumannii , Pseudomonas aeruginosa , Klebsiella pneumoniae , Staphylococcus , Stenotrophomonas maltophilia , Enterobacter cloacae , Escherichia coli ; * P < 0.05, indicating a statistically significant difference. Table 4. Comparison of imaging findings between the death group and survival group of non-HIV-PCP patients Death group （n=58 ） Survival group （n=142 ） P-value Proximal pleural distribution, n (%) 10（17.2） 36（25.4） 0.216 Distribution along vascular bundle, n (%) 5（8.6） 8（5.6） 0.644 Ground glass density shadow, n (%) 47（81.0） 127（89.4） 0.109 Spot shadow, n (%) 27（46.6） 59（41.5） 0.517 Solid shading, n (%) 32（55.2） 76（53.5） 0.832 Grid shadow, n (%) 7（12.1） 11（7.7） 0.332 Honeycomb, n (%) 7（12.1） 6（4.2） 0.084 Interlobular thickening, n (%) 36（62.1） 77（54.2） 0.310 Lobular core tubercles, n (%) 2（3.4） 19（13.4） 0.038 * Pulmonary air sac, n (%) 2（3.4） 2（1.4） 0.705 Pneumothorax, n (%) 10（17.2） 5（3.5） 0.002 * Mediastinal emphysema, n (%) 6（10.3） 2（1.4） 0.011 * Pleural effusion, n (%) 15（25.9） 41（28.9） 0.667 Lymph node enlargement, n (%) 1（1.7） 6（4.2） 0.653 * P < 0.05, indicating a statistically significant difference. Table 5. Comparison of treatment between death and survival in non-HIV-PCP patients Death group （n=58 ） Survival group （n=142 ） P-value Therapeutic drugs TMP-SMZ，n（%） 57（98.3） 141（99.3） 0.497 Second-line treatment € ，n（%） 21（36.2） 13（9.2） ＜0.001 * Reasons for second-line treatment, n（%） The effect of sulfonamides treatment was poor Sulfonamides cause adverse reactions Ψ Sulfonamides hypersensitivity 17（29.3） 3（5.2） 1（8.6） 6（4.2） 4（2.8） 3（2.1） ＜0.001 * 0.690 1.000 Carpofungin，n（%） 33（56.9） 45（31.7） 0.001 * Corticosteroids therapy（mg/（kg· d）） ＜0.5，n（%） 6（11.1） 36（28.3） 0.012 * 0.5-1，n（%） 18（33.3） 57（44.9） 0.149 ≥1，n（%） 30（55.6） 34（26.8） ＜0.001 * Mode of oxygen inhalation High flow oxygen therapy, n (%) 47（81） 56（39.4） ＜0.001 * Non-invasive mechanical ventilation, n (%) 49（84.5） 29（20.4） ＜0.001 * Invasive mechanical ventilation, n (%) 48（82.8） 10（7） ＜0.001 * Admission to ICU, n (%) 45（77.6） 41（28.9） ＜0.001 * Length of ICU stay a (days) 11（5.5，18） 14（6，17） 0.738 Note : a: median (quartile); €: Second-line treatment refers to clindamycin, primaquine treatment; Ψ: The adverse reactions caused by sulfonamides refer to thrombocytopenia, hemolytic anemia, kidney injury; * P < 0.05, indicating a statistically significant difference. Table 6. Analysis of factors associated with poor prognosis in non-HIV-PCP patients Univariate analysis Multivariate analysis OR 95% CI P-value OR 95% CI P-value Age 1.053 1.028-1.079 ＜0.001 * 1.062 1.021-1.104 0.003 * BMI 0.965 0.895-1.041 0.362 Smoking history 1.706 0.916-3.178 0.093 Chemotherapy history 0.123 0.028-0.531 0.005 * 0.067 0.007-0.670 0.021 * History of glucocorticoid use 4.590 1.037-20.318 0.045 * Withdrawal of glucocorticoid history 1.478 0.799-2.734 0.214 Autoimmune disease 2.074 1.105-3.891 0.023 * Organ transplantation 0.222 0.065-0.762 0.017 * Combined with CMV infection 1.871 0.997-3.510 0.051 Respiratory failure 33.944 4.566-252.351 0.001 * Platelet count 0.995 0.991-0.998 0.005 * NLR 1.026 1.009-1.044 0.003 * HsCRP 1.006 1.001-1.011 0.025 * Albumin 0.947 0.900-0.997 0.037 * LDH 1.002 1.001-1.003 0.002 * D-dimer 1.235 1.068-1.428 0.004 * G test 1.001 1.000-1.001 0.075 IgG 1.038 0.980-1.099 0.202 BALF-percentage of neutrophils 1.033 1.019-1.047 ＜0.001 * 1.018 1.000-1.037 0.052 BALF-percentage of lymphocytes 0.957 0.937-0.977 ＜0.001 * Pathogens associated with hospital-acquired pneumonia 5.966 2.860-12.445 ＜0.001 * 4.170 1.407-12.357 0.010 * Honeycomb shadow 3.111 0.998-9.698 0.050 Pneumothorax 5.708 1.857-17.543 0.002 * Mediastinal emphysema 8.077 1.580-41.292 0.012 * Carpofungin treatment 2.845 1.518-5.335 0.001 * High dose glucocorticoid therapy (≥1mg/ (kg· d)) 3.419 1.758-6.649 ＜0.001 * 7.047 2.482-20.006 ＜0.001 * Note: * P < 0.05 was statistically significant. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3906065","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":271406842,"identity":"3b88e6df-6198-47a8-9c4b-15db2c333294","order_by":0,"name":"Jun Li","email":"","orcid":"","institution":"Beijing Tsinghua Chang Gung Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Li","suffix":""},{"id":271406843,"identity":"62a0d7c2-eae8-4134-8017-a87039911729","order_by":1,"name":"Xiangdong Mu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIiWNgGAWjYJCCA0DM2ADEDxgYmIGIuYFoLcwGEC2MhLUwQLWwSYC1MBDQojsjx/DAzx21sv3S7deqblRYR/O3A7X8qNjGwD8bu1azG2kJB3vPHDeeOedM2e2cM+m5Mw4zNjD2nLnNIHHnAA4tyQcO8LYdS9xwIyftdm7b4dwGoBZmxrbbDAYSCTi0JDYc/AvVUpz773DufMJakg8c5m2rAWpJP8YMtCJ3A0EtZ54lHJZtO2A8c0YOs3TOsfTcjUAtB4F+4ZG4gUPL8Rzjj2/b6mT7JdIffs6psc6dd/7wwQc/Km7L8c/ArgUKDgMxjwGcewDExaceCOqAmP0BAUWjYBSMglEwUgEAygtu9OUhPNsAAAAASUVORK5CYII=","orcid":"","institution":"Beijing Tsinghua Chang Gung Hospital","correspondingAuthor":true,"prefix":"","firstName":"Xiangdong","middleName":"","lastName":"Mu","suffix":""},{"id":271406844,"identity":"04b0c82a-70d7-4fbb-ae34-5d1f7114cb2f","order_by":2,"name":"Haichao Li","email":"","orcid":"","institution":"Peking University First Hospital","correspondingAuthor":false,"prefix":"","firstName":"Haichao","middleName":"","lastName":"Li","suffix":""},{"id":271406845,"identity":"31adf8ad-d83b-472b-b3a3-2d1211ba5b6c","order_by":3,"name":"Xinmin Liu","email":"","orcid":"","institution":"Peking University First Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xinmin","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-01-28 14:46:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3906065/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3906065/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50818905,"identity":"6eab103f-8ad1-46cf-a5c9-68dc5d701e11","added_by":"auto","created_at":"2024-02-07 20:23:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":68931,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy flow chart\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3906065/v1/866acfc80c771829a511a8d8.png"},{"id":50818906,"identity":"590c7bd6-e5cd-477e-9e2e-c76df2b565c7","added_by":"auto","created_at":"2024-02-07 20:23:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":43643,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEtiological composition of non-HIV-PCP patients in death group and survival group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e Other pathogens included: 1 case of \u003cem\u003ePenicillium flavus\u003c/em\u003e, 1 case of \u003cem\u003eHerpes simplex virus\u003c/em\u003e, 1 case of \u003cem\u003eCoronavirus\u003c/em\u003e, and 3 cases of unidentified pathogen. * P \u0026lt; 0.05, indicating a statistically significant difference.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3906065/v1/66c52e9fbd49b7543908a5d3.png"},{"id":64732960,"identity":"b6ba29cb-9c8b-4f6d-ab7f-9cbcbc66a9d7","added_by":"auto","created_at":"2024-09-18 07:16:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1301974,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3906065/v1/bf352fd2-7f20-4fd4-a32d-52ab4b43ae2d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Evaluation of risk factors and prognostic impact of glucocorticoid therapy among non-HIV patients with Pneumocystis Jirovecii Pneumonia (PCP) Running title：Glucocorticoid therapy among non-HIV patients with PCP","fulltext":[{"header":"Background","content":"\u003cp\u003e \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e Pneumonia (PCP) often occurs in immunocompromised hosts and is associated with high morbidity and mortality. With the increasing use of immunosuppressants in solid tumors, hematological diseases, organ transplantation, and inflammatory diseases, the population of PCP is gradually transitioning from \u003cem\u003eHuman Immunodeficiency Virus\u003c/em\u003e (HIV) patients to non-HIV infected patients. Compared with HIV-PCP, non-HIV-PCP patients may present with acute fulminant disease process, with more severe pulmonary inflammation and hypoxemia, and 40% May progress to respiratory failure, with a very high mortality\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGlucocorticoids are widely used as immunosuppressants in immunocompromised people, which can be divided into the use of glucocorticoids before and after PCP. Glucocorticoids can directly reduce and damage T or B cells\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e, inhibit the cytotoxicity of NK cells and phagocytosis of macrophages, and inhibit the synthesis of known inflammatory cytokines\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. In a retrospective study that included 116 non-HIV-PCP patients, it was found that up to 90% of patients were treated with glucocorticoids within 1 month prior to PCP diagnosis, and the use of glucocorticoids was associated with the development of PCP\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. In another study, hormones increased the risk of infection in PCP patients in a dose-dependent manner. Studies have shown that individuals treated with glucocorticoids are susceptible to pneumocystis, but may reduce inflammation caused by infection and reduce the risk of respiratory failure in non-HIV-PCP patients\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. However, other studies have shown that the use of glucocorticoids before the onset of PCP in non-HIV-infected patients is not associated with a lower risk of respiratory failure\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Previous studies also found an interesting phenomenon that sudden cessation or gradual reduction of glucocorticoids may aggravate respiratory symptoms and hypoxemia in non-HIV-PCP patients\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. The relationship between withdrawal of glucocorticoids before PCP and prognosis of non-HIV-PCP patients needs further study. In addition, some studies have also shown that glucocorticoid therapy after the occurrence of PCP can prevent early disease deterioration and improve the prognosis of moderate to severe PCP in HIV patients\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e, while its application in non-HIV-PCP remains controversial\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs the epidemiology of PCP has changed, people with immunosuppression caused by glucocorticoids and other immunosuppressants are susceptible to PCP, and many clinical cases have shown that this infection often occurs during glucocorticoids withdrawal. Therefore, it is necessary to identify the complex role of glucocorticoids in the pathogenesis and prognosis of non-HIVPCP. The objective of this study was to evaluate the effects of glucocorticoids administration before admission, glucocorticoids withdrawal, and glucocorticoids therapy after PCP on the prognosis of non-HIV-PCP patients.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design, setting, and study population\u003c/h2\u003e \u003cp\u003e\u003cp\u003eIn this study, PCP patients admitted to Peking University First Hospital from April 2007 to October 2022 were retrospectively collected. Relevant data of patients were collected by consulting electronic medical records, and 200 non-HIV-PCP patients were eventually included (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This study was approved by the Ethics Committee of Peking University First Hospital.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData collection and definitions\u003c/h2\u003e \u003cp\u003eAll medical records were retrospectively reviewed using standardized study protocols. Demographic characteristics, underlying diseases or conditions, laboratory results, patient management, and clinical outcomes were evaluated. The adult patients (aged 18 years) who met the following criteria were considered definitively diagnosed with PCP: (1) clinical symptoms or signs relevant to PCP ( fever, cough, or shortness of breath); (2) imaging findings compatible with PCP (ground glass changes in both lungs or diffuse infiltration of lung interstitial shadow); and (3) positive \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e from respiratory samples (BALF, sputum, bronchial flushing fluid, bronchial secretions or lung tissue).\u003c/p\u003e \u003cp\u003ePrior glucocorticoids use was defined as a history of glucocorticoids use 1 month prior to admission for PCP, all available information related to dose and duration was recorded, and doses of various types of glucocorticoids were converted to equivalent doses of prednisone. Glucocorticoids-related PCP refers to the patients who developed PCP-related symptoms after glucocorticoids-related withdrawal and were finally diagnosed as PCP by etiology and imaging tests. Hospital-acquired pneumonia-associated pathogen infections are clinically or microbiologically documented infections during hospitalization and 48 hours after discharge.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe non-normal distribution of the continuous variable is expressed by the median (interquartile distance [IQR]), and the normal distribution is expressed by the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Compared the two groups using either the T-test or the Mann-Whitney U test. The categorical variables were expressed as percentages (%), and the comparison between the two groups was performed by Fisher or Chi-square test. P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Covariates with a P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the univariate analysis were included in the final model of multivariable logistic regression. All the above data were analyzed using SPSS 23.0.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eClinical characteristics of study subjects\u003c/h2\u003e \u003cp\u003eNon-HIV-PCP patients were divided into death group (n\u0026thinsp;=\u0026thinsp;58) and survival group (n\u0026thinsp;=\u0026thinsp;142) according to clinical outcomes during hospitalization. Compared with the survival group, the death group had a higher median age (62 vs 51.5, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), a shorter hospital stay (14 vs 24, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and a higher rate of combined respiratory failure (98.3% vs 62.7%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). There were no significant differences in gender, body mass index (BMI) and smoking history between the two groups. In terms of underlying diseases, the death group had a higher proportion of autoimmune diseases (46.6% vs 29.6%, P\u0026thinsp;=\u0026thinsp;0.022), while the survival group had a higher proportion of organ transplants (19.7% vs 5.2%, P\u0026thinsp;=\u0026thinsp;0.016). Compared with the survival group, patients' drug use before PCP occurred had a higher proportion of glucocorticoids use in the death group (96.6% vs 85.9%, P\u0026thinsp;=\u0026thinsp;0.029). There were no significant differences in glucocorticoid dose, duration of glucocorticoid use, withdrawal of glucocorticoids, use of immunosuppressants, use of biologics, use of immune checkpoint inhibitors, and preventive use of sulfonamide between the two groups. The proportion of patients with a history of chemotherapy was higher in the survival group (22.5% vs 3.4%, P\u0026thinsp;=\u0026thinsp;0.001), and there was no significant difference between radiotherapy and radiotherapy combined with chemotherapy (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThere were no significant differences in the clinical manifestations of dyspnea, fever, cough, sputum, chest pain and hemoptysis between the two groups. Compared with the survival group, patients in the death group showed platelet count (152 vs 184, P\u0026thinsp;=\u0026thinsp;0.002), lymphocyte count (0.4 vs 0.6, P\u0026thinsp;=\u0026thinsp;0.008), total protein (54.2 vs 57.4, P\u0026thinsp;=\u0026thinsp;0.031), albumin (27.5 vs 29.6, neutrophil count (7.5 vs 6.2, P\u0026thinsp;=\u0026thinsp;0.04), neutrophil/lymphocyte ratio (NLR) (17.7 vs 9.8, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hypersensitive C-reactive protein (HsCRP) (88.5 vs 54.2, P\u0026thinsp;=\u0026thinsp;0.012), glutamic oxalacetic transaminase (29 vs 25, P\u0026thinsp;=\u0026thinsp;0.021), lactate dehydrogenase (LDH) (482.5 vs 386, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), d-dimer (1 vs 0.48, P\u0026thinsp;=\u0026thinsp;0.001), fibrinogen degradation products (6.6 vs 3.9, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and G test index (261.6 vs 141.8, P\u0026thinsp;=\u0026thinsp;0.004) were higher. Blood gas analysis showed that oxygenation index (OI) (203.2 vs 272.7, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), arterial oxygen saturation (SaO2) (89.3 vs 93, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and arterial partial pressure of carbon dioxide (PaCO\u003csub\u003e2\u003c/sub\u003e) (30.4 vs 32.9, P\u0026thinsp;=\u0026thinsp;0.008) were lower in the death group than in the survival group, and the difference of pulmonary arterial oxygen pressure (P(A-a)O\u003csub\u003e2\u003c/sub\u003e) was higher (93.8 vs 59.5, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In terms of blood immune indexes, IgG level (9 vs 6.3, P\u0026thinsp;=\u0026thinsp;0.034), percentage of B cells (14.9% vs 7.2%, P\u0026thinsp;=\u0026thinsp;0.009) and CD3\u0026thinsp;+\u0026thinsp;T cell count (301 vs 514.6, P\u0026thinsp;=\u0026thinsp;0.002) were higher, CD8\u0026thinsp;+\u0026thinsp;T cell counts were lower (156.4 vs 262.4, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in the death group, and CD4\u0026thinsp;+\u0026thinsp;T cell counts were not significantly different between the two groups. BALF lymphocyte subsets showed no statistically significant differences in the percentages of CD3\u0026thinsp;+\u0026thinsp;T cells, CD4\u0026thinsp;+\u0026thinsp;T cells, and CD8\u0026thinsp;+\u0026thinsp;T cells between the two groups. In BALF cell classification, the percentage of macrophages (28% vs 40%, P\u0026thinsp;=\u0026thinsp;0.034) and lymphocytes (16% vs 34.5%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were lower in the death group, and the percentage of neutrophils (51% vs 15%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was higher (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCompared with the survival group, the death group had more common pathogens (82.8% vs 49.3%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), two pathogens (34.5% vs 14.8%, P\u0026thinsp;=\u0026thinsp;0.002), and three pathogens (16.6% vs 1.4%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and a higher proportion of pathogens associated with common hospital-acquired pneumonia (43.1% vs 11.3%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Among the combined etiology species, \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e (15.5% vs 3.5%, P\u0026thinsp;=\u0026thinsp;0.007), \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (15.5% vs 2.8%, P\u0026thinsp;=\u0026thinsp;0.003), \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (13.8% vs 2.1%, P\u0026thinsp;=\u0026thinsp;0.003), \u003cem\u003eCandida candida\u003c/em\u003e (12.1% vs 0.7%, P\u0026thinsp;=\u0026thinsp;0.001) and the rates of \u003cem\u003eCryptococcal\u003c/em\u003e infection (6.9% vs 0.7%, P\u0026thinsp;=\u0026thinsp;0.041) were higher in the death group. The rates of \u003cem\u003eCytomegalovirus\u003c/em\u003e (CMV) and \u003cem\u003eAspergillus\u003c/em\u003e infection were not statistically different between the two groups, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eIn terms of imaging, the proportions of pneumothorax (17.2% vs 3.5%, P\u0026thinsp;=\u0026thinsp;0.002) and mediastinal emphysema (10.3% vs 1.4%, P\u0026thinsp;=\u0026thinsp;0.011) in the death group were significantly higher than those in the survival group. The survival group showed a higher proportion of lobular core nodules (13.4% vs 3.4%, P\u0026thinsp;=\u0026thinsp;0.038), while there was no statistical difference between the two groups in imaging findings such as distribution near pleura, distribution along vascular bundles, ground glass density shadow, plaque shadow, solid shadow, mesh shadow, thickening interlobular interval, pulmonary air sac, pleural effusion, and lymph node enlargement, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTreatment outcomes\u003c/h3\u003e\n \u003cp\u003eCompared with the survival group, the death group were more likely to be treated with second-line agents (36.2% vs 9.2%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and carpofungin (56.9% vs 31.7%, P\u0026thinsp;=\u0026thinsp;0.001) and the proportion of high dose (\u0026ge;\u0026thinsp;1mg/ (kg\u0026middot; d)) glucocorticoids treatment was higher (55.6% vs 26.8%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The proportion of patients treated with low-dose (\u0026lt;\u0026thinsp;0.5mg/ (kg\u0026middot; d)) glucocorticoids was higher in the survival group (11.1% vs 28.3%, P\u0026thinsp;=\u0026thinsp;0.012). The proportion of second-line treatment in the death group was higher than that in the survival group (29.3% vs 4.2%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Rates of ICU admission in the death group (77.6% vs. 28.9%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), use of high-flow oxygen therapy (81% vs. 39.4%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), non-invasive mechanical ventilation (84.5% vs. 20.4%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and invasive mechanical ventilation were higher than those in the survival group (82.8% vs 7%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePrognostic factors of non-HIV-infected patients with PCP\u003c/h2\u003e \u003cp\u003eLogistic univariate regression analysis was performed for non-HIV-PCP patients. Results showed age, history of chemotherapy, history of glucocorticoid use, autoimmune disease, organ transplantation, respiratory failure, platelet count, NLR, HsCRP, albumin, LDH, d-dimer, BALF-neutrophil percentage, BALF-lymphocyte percentage, and combined with hospital-acquired pneumonia associated pathogen infection, pneumothorax, mediastinal emphysema, treatment with carpofungine and adjuvant high-dose glucocorticoids were statistically significant between the two groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eThe factors with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were incorporated into the logistic model for stepwise regression analysis, and the results showed that age (OR\u0026thinsp;=\u0026thinsp;1.062, 95% CI 1.021\u0026ndash;1.104, P\u0026thinsp;=\u0026thinsp;0.003), combined with hospital-acquired pathogen infection (OR\u0026thinsp;=\u0026thinsp;4.170, 95%CI 1.407\u0026ndash;12.357, P\u0026thinsp;=\u0026thinsp;0.010), adjuvant high-dose glucocorticoids therapy (OR\u0026thinsp;=\u0026thinsp;7.047, 95% CI 2.482\u0026ndash;20.006, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were independent risk factors for death in non-HIV-PCP patients, history of chemotherapy (OR\u0026thinsp;=\u0026thinsp;0.067, 95% CI 0.007\u0026ndash;0.670, P\u0026thinsp;=\u0026thinsp;0.021) was independent protective factor factors for death in non-HIV-PCP patients, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eNon-HIV-PCP patients have a higher mortality rate than HIV-PCP patients, and finding the risk factors that affect the prognosis is the key to reduce the mortality rate. A meta-analysis of risk factors for death in non-HIV-PCP patients conducted by Wang Y et al. showed that age, other pulmonary diseases at diagnosis of PCP, solid tumors, CMV infection, LDH, lymphocyte count, invasive mechanical ventilation during hospitalization, and pneumothorax were non-risk factors for HIV-related PCP death\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Liu CJ et al. conducted a retrospective study on PCP patients in a medical center in northern Taiwan, and the results showed that lymphocytopenia, adjuvant glucocorticoids therapy and pneumothorax were significantly associated with high mortality in non-HIV-PCP patients\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Duan J et al. conducted a multi-factor analysis of 56 non-HIV-PCP patients admitted to ICU, suggesting that neutrophil/lymphocyte percentage and co-infection were independent risk factors for poor prognosis\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.This study showed that old age, combination of pathogens associated with hospital-acquired pneumonia, and adjuvant use of high-dose glucocorticoids were independent risk factors for death in non-HIV-PCP patients, and chemotherapy history was a protective factor in non-HIV-PCP patients\u003c/p\u003e\u003cp\u003ePrevious studies have shown that chemotherapy before PCP is a risk factor for PCP in patients with solid tumors and organ transplantation\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. With the establishment of international guidelines (HIV, hematologic malignancies, and transplantation) in recent years, the promotion of prophylactic use of sulfonamides in HIV, hematologic malignancies, and transplantation populations has resulted in a significant reduction in PCP morbidity and mortality in these populations. This study showed that patients with a history of chemotherapy before PCP had a better prognosis. Considering that the release of relevant specialist guidelines in recent years has raised the awareness of clinicians on the preventive use of sulfonamides for this type of disease, and thus made this type of PCP patients less likely to develop into severe diseases.\u003c/p\u003e \u003cp\u003eAt present, age is the main demographic characteristic related to the prognosis of non-HIV-PCP with clinical evidence. A study from Japan showed that the median age of PCP patients was 62 years old, showing a bimodal distribution, and the median age of children and adults was 5 years old and 63 years old, respectively. The mortality rate of adults was higher than that of children\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. An epidemiological study of PCP from Germany showed that nearly half of PCP patients were between 50 and 75 years old, and the median age of patients increased from 62 to 64 years between 2014 and 2019\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. With the decline of physical function and the increase of basic diseases, the general immunity of the elderly is poor and easy to be infected with various respiratory pathogens. In adult HIV and non-HIV-PCP patients, the older the age, the worse the prognosis for PCP\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Roux A and colleagues confirmed the association between advanced age and PCP death in a large prospective cohort study that collected and analyzed 544 patients with PCP in France and found that the risk of death increased with age in patients older than 50 years\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Ricciardi A et al. performed a retrospective study of 116 non-HIV-PCP patients and found that advanced age was associated with the severity of PCP as well as death\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Compared with the elderly, in the study of PCP in children, Yun KS et al. found that age\u0026thinsp;\u0026lt;\u0026thinsp;5 years, low oxygen saturation at admission, and hospital onset were independently associated with PCP mortality\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Therefore, both elderly patients\u0026thinsp;\u0026gt;\u0026thinsp;60 years old and children\u0026thinsp;\u0026lt;\u0026thinsp;5 years old should be more active in the assessment of disease, admission to hospital and early intervention treatment to avoid delaying the disease.\u003c/p\u003e \u003cp\u003eIn terms of pathogen infection, we classified \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e and other pathogens detected after admission as hospital-acquired pneumonia-related pathogens, and found that infection with hospital-acquired pneumonia-related pathogens was an independent risk factor for death in HIV-PCP patients. Due to low immune function and lower than normal lymphocyte levels, non-HIV patients are often infected with multiple pathogens in addition to PCP infection. Kim SJ and colleagues found that co-bacterial infection was an independent predictor of death in non-HIV-PCP patients, and co-bacterial infection may be an indirect indicator of the severity of immunosuppression in non-HIV-PCP patients\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Patients with different immunosuppressive states are susceptible to different pathogens. In addition to \u003cem\u003ePneumocystis\u003c/em\u003e, T cell deficiency patients are often associated with bacteria, respiratory viruses and \u003cem\u003eCryptococcus\u003c/em\u003e infections. B-cell deficiency patients are often associated with bacterial infection. Patients with granulocyte defects are often infected with bacteria, \u003cem\u003eAspergillus, Nocardia\u003c/em\u003e, and \u003cem\u003eMycobacterium\u003c/em\u003e\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. This also indirectly confirmed the results of this study, which showed that reduced counts of lymphocytes, CD3\u0026thinsp;+\u0026thinsp;T cells, and CD8\u0026thinsp;+\u0026thinsp;T cells were associated with death in non-HIV-PCP patients, possibly due to co-infection. Therefore, investigating the presence of respiratory co-infection at the time of PCP diagnosis can better identify patients at risk.\u003c/p\u003e \u003cp\u003eGlucocorticoid is a \"double-edged sword\", for HIV-PCP patients, glucocorticoid has an important therapeutic effect, but for some non-HIV-PCP patients who must use glucocorticoid for a long time, glucocorticoid is an important cause of pneumocystis infection. Limper et al.\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003estudied and analyzed BALF cell components during PCP and found that non-HIV infected patients had more neutrophilic infiltration in the lungs than HIV patients, and the higher burden of inflammatory cells was corresponding to the deterioration of oxygenation. Therefore, they believed that compared with other immunocompromised PCP patients, PCP has a better prognosis in inflammatory diseases treated with chronic glucocorticoids. However, a study conducted by Wieruszewski and colleagues in non-HIV-PCP patients who used glucocorticoids before PCP showed that glucocorticoids use before PCP in non-HIV patients was not associated with a reduced risk of respiratory failure\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Earlier studies also found an interesting phenomenon that the occurrence and development of PCP are related to glucocorticoids reduction\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e, and sudden cessation or gradual reduction of glucocorticoids may aggravate respiratory symptoms and hypoxemia in non-HIV-PCP patients\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Our study found that pre-withdrawal of glucocorticoids from PCP was a risk factor for non-HIV-PCP in-hospital death, but it was not an independent risk factor, which may be related to the sample size. We will expand the sample size for further study in the future.\u003c/p\u003e\u003cp\u003eThe use of glucocorticoids in HIV-PCP patients has been well established, and the U.S. Guidelines for the Prevention and Treatment of HIV Opportunistic infections in adults and adolescents recommend that, for patients who are not oxygenated, Moderate to severe PCP patients with PaO\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;70 mmHg or P(A-a)O\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;\u0026ge;\u0026thinsp;35mmHg should be treated with glucocorticoids within 72 hours of anti-PCP treatment\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. However, its use in non-HIV-PCP patients is still controversial, and there are currently no accepted guidelines that clearly recommend it\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Mundo W et al. conducted a single-center retrospective cohort study on PCP patients in the United States, including 28 non-HIV patients, and the results showed that the adjuvant use of glucocorticoids was associated with reduced mortality in non-HIV-PCP patients\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Other studies have shown that glucocorticoid therapy is associated with shorter ventilator use time and shorter ICU stay\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e,but other studies have shown that glucocorticoid use is not correlated with clinical outcomes\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. However, the samples of the above studies were small, with less than 100 cases. Therefore, Lemiale V et al. analyzed 139 non-HIV-PCP patients admitted to ICU in a hospital in Paris, France, and compared the prognosis of patients with different doses. The results showed that the use of high-dose glucocorticoids was associated with increased mortality in non-HIV-PCP patients, but not with ICU acquired infections\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Wieruszewski PM and colleagues assessed 30-day mortality in 323 adults with non-HIV-PCP who were divided into early (within 48 hours) glucocorticoids use group and non-early glucocorticoids use group, and showed that early adjuvant glucocorticoids use did not improve clinical outcomes in non-HIV-PCP patients\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Our study shows that adjuvant use of high-dose glucocorticoids is an independent risk factor for non-HIV-PCP death. It is unclear why the effects of adjuvant glucocorticoids therapy on outcomes differ between HIV and non-HIV patients. We speculate that these differences may be due to patients' previous exposure to glucocorticoids prior to the appearance of PCP resulting in a reduced response to the drug, which may be a consideration for future research.\u003c/p\u003e\u003cp\u003eShortcomings of this study: Firstly, this study was a single-center retrospective study. Due to the particularity of the disease, only 200 patients were included in the study in 15 years, and the sample size was not large enough. Secondly, the main underlying diseases of the patients studied were autoimmune diseases, kidney diseases, and organ transplantation, and the research results may not be applicable to patients with other underlying diseases. Thirdly, despite the combination of clinical symptoms, imaging findings, and etiology to diagnose PCP, the possibility of inclusion of pneumocystis colonized patients cannot be eliminated.\u003c/p\u003e"},{"header":"Conclusions","content":" \u003cp\u003eIn conclusion, non-HIV-PCP patients treated with high doses of glucocorticoids, old age, and hospital-acquired pneumonia associated pathogen infection had worse outcomes during hospitalization.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Peking University First Hospital (2021KEYAN111). The need for informed consent was waived by the Ethics Committee of Peking University First Hospital due to the retrospective nature of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e：This work was supported by Beijing Clinical Key Specialty Project (XKB2022B1002) and National Key R\u0026amp;D Program of China (2020YFC2005401).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJL:\u0026nbsp;Conceptualization, data collection, formal analysis, interpretation of data, writing of original draft and review, and editing.\u0026nbsp;HCL: Conceptualization, data collection, interpretation of data, writing of original draft and review.\u0026nbsp;XDM: Interpretation of data, writing of original draft and review, and editing.\u0026nbsp;XML: Conceptualization, formal analysis, interpretation of data, writing of original draft and review, and editing.\u0026nbsp;All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFestic E, Gajic O, Limper AH, et al. Acute respiratory failure due to pneumocystis pneumonia in patients without human immunodeficiency virus infection: outcome and associated features[J]. Chest. 2005;128(2):573\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYale SH, Limper AH. Pneumocystis carinii pneumonia in patients without acquired immunodeficiency syndrome: associated illness and prior corticosteroid therapy[J]. Mayo Clin Proc. 1996;71(1):5\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchaffner A. Therapeutic concentrations of glucocorticoids suppress the antimicrobial activity of human macrophages without impairing their responsiveness to gamma interferon[J]. J Clin Invest. 1985;76(5):1755\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoumpas DT, Chrousos GP, Wilder RL, et al. Glucocorticoid therapy for immune-mediated diseases: basic and clinical correlates[J]. Ann Intern Med. 1993;119(12):1198\u0026ndash;208.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWieruszewski PM, Barreto EF, Barreto JN, et al. Preadmission Corticosteroid Therapy and the Risk of Respiratory Failure in Adults Without HIV Presenting With Pneumocystis Pneumonia[J]. J Intensive Care Med. 2020;35(12):1465\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSepkowitz KA. Pneumocystis carinii pneumonia in patients without AIDS[J]. Clin Infect Dis. 1993;17(Suppl 2):416\u0026ndash;S422.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSlivka A, Wen PY, Shea WM, et al. Pneumocystis carinii pneumonia during steroid taper in patients with primary brain tumors[J]. Am J Med. 1993;94(2):216\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWieruszewski PM, Barreto JN, Frazee E, et al. Early Corticosteroids for Pneumocystis Pneumonia in Adults Without HIV Are Not Associated With Better Outcome[J]. Chest. 2018;154(3):636\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaschmeyer G, Helweg-Larsen J, Pagano L, et al. ECIL guidelines for treatment of Pneumocystis jirovecii pneumonia in non-HIV-infected haematology patients[J]. J Antimicrob Chemother. 2016;71(9):2405\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInjean P, Eells SJ, Wu H, et al. A Systematic Review and Meta-Analysis of the Data Behind Current Recommendations for Corticosteroids in Non-HIV-Related PCP: Knowing When You Are on Shaky Foundations[J]. Transpl Direct. 2017;3(3):e137.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, Zhou X, Saimi M, et al. Risk Factors of Mortality From Pneumocystis Pneumonia in Non-HIV Patients: A Meta-Analysis[J]. Front Public Health. 2021;9:680108.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu CJ, Lee TF, Ruan SY, et al. Clinical characteristics, treatment outcomes, and prognostic factors of Pneumocystis pneumonia in non-HIV-infected patients[J]. Infect Drug Resist. 2019;12:1457\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuan J, Gao J, Liu Q, et al. Characteristics and Prognostic Factors of Non-HIV Immunocompromised Patients With Pneumocystis Pneumonia Diagnosed by Metagenomics Next-Generation Sequencing[J]. Front Med (Lausanne). 2022;9:812698.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCilloniz C, Dominedo C, Alvarez-Martinez MJ, et al. Pneumocystis pneumonia in the twenty-first century: HIV-infected versus HIV-uninfected patients[J]. Expert Rev Anti Infect Ther. 2019;17(10):787\u0026ndash;801.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFishman JA, Gans H. Pneumocystis jiroveci in solid organ transplantation: Guidelines from the American Society of Transplantation Infectious Diseases Community of Practice[J]. Clin Transpl. 2019;33(9):e13587.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShoji K, Michihata N, Miyairi I, et al. Recent epidemiology of Pneumocystis pneumonia in Japan[J]. J Infect Chemother. 2020;26(12):1260\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKolbrink B, Scheikholeslami-Sabzewari J, Borzikowsky C, et al. Evolving epidemiology of pneumocystis pneumonia: Findings from a longitudinal population-based study and a retrospective multi-center study in Germany[J]. Lancet Reg Health Eur. 2022;18:100400.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi MC, Lee NY, Lee CC, et al. Pneumocystis jiroveci pneumonia in immunocompromised patients: delayed diagnosis and poor outcomes in non-HIV-infected individuals[J]. J Microbiol Immunol Infect. 2014;47(1):42\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFei MW, Kim EJ, Sant CA, et al. Predicting mortality from HIV-associated Pneumocystis pneumonia at illness presentation: an observational cohort study[J]. Thorax. 2009;64(12):1070\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoux A, Canet E, Valade S, et al. Pneumocystis jirovecii pneumonia in patients with or without AIDS, France[J]. Emerg Infect Dis. 2014;20(9):1490\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRicciardi A, Gentilotti E, Coppola L, et al. Infectious disease ward admission positively influences P. jiroveci pneumonia (PjP) outcome: A retrospective analysis of 116 HIV-positive and HIV-negative immunocompromised patients[J]. PLoS ONE. 2017;12(5):e176881.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYun KS, Anh B, Choi SH et al. Clinical Characteristics and Prognosis of the Modified Probable Pneumocystis jirovecii Pneumonia in Korean Children, 2001\u0026ndash;2021[J]. Children (Basel), 2022, 9(10).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim SJ, Lee J, Cho YJ, et al. Prognostic factors of Pneumocystis jirovecii pneumonia in patients without HIV infection[J]. J Infect. 2014;69(1):88\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzoulay E, Russell L, Van de Louw A, et al. Diagnosis of severe respiratory infections in immunocompromised patients[J]. Intensive Care Med. 2020;46(2):298\u0026ndash;314.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLimper AH, Offord KP, Smith TF, et al. Pneumocystis carinii pneumonia. Differences in lung parasite number and inflammation in patients with and without AIDS[J]. Am Rev Respir Dis. 1989;140(5):1204\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRIFKIND D, STARZL T E, MARCHIORO T L, et al. TRANSPLANTATION PNEUMONIA[J] JAMA. 1964;189:808\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuidelines for the Prevention. and Treatment of Opportunistic Infections in Adults and Adolescents with HIV[EB/OL]. (2023-01-18)\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://clinicalinfo.hiv.gov\u003c/span\u003e\u003cspan address=\"https://clinicalinfo.hiv.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMundo W, Morales-Shnaider L, Tewahade S, et al. Lower Mortality Associated With Adjuvant Corticosteroid Therapy in Non-HIV-Infected Patients With Pneumocystis jirovecii Pneumonia: A Single-Institution Retrospective US Cohort Study[J]. Open Forum Infect Dis. 2020;7(9):a354.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePareja JG, Garland R, Koziel H. Use of adjunctive corticosteroids in severe adult non-HIV Pneumocystis carinii pneumonia[J]. Chest. 1998;113(5):1215\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDelclaux C, Zahar JR, Amraoui G, et al. Corticosteroids as adjunctive therapy for severe Pneumocystis carinii pneumonia in non-human immunodeficiency virus-infected patients: retrospective study of 31 patients[J]. Clin Infect Dis. 1999;29(3):670\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoon SM, Kim T, Sung H, et al. Outcomes of moderate-to-severe Pneumocystis pneumonia treated with adjunctive steroid in non-HIV-infected patients[J]. Antimicrob Agents Chemother. 2011;55(10):4613\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLemiale V, Debrumetz A, Delannoy A, et al. Adjunctive steroid in HIV-negative patients with severe Pneumocystis pneumonia[J]. Respir Res. 2013;14(1):87.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Comparison of clinical features between death group and survival group in non-HIV-PCP patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"637\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeath\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003egroup\u003c/strong\u003e\u003cstrong\u003e（n=58\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvival group(n=142)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge \u003csup\u003ea\u003c/sup\u003e, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e62（53.8，71）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e51.5（37，62.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35（60.3）\u003c/p\u003e\n \u003cp\u003e23（39.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e101（71.1）\u003c/p\u003e\n \u003cp\u003e41（28.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI \u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e（kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e22.5（20.4，24.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e22.8（20.2，25.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.494\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking history, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e27（46.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e48（33.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength of stay \u003csup\u003ea\u003c/sup\u003e, (day)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e14（8.8，29）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e24（16，35）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnderlying disease,n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Autoimmune disease\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Kidney disease\u003c/p\u003e\n \u003cp\u003eOrgan transplantation\u003c/p\u003e\n \u003cp\u003eSolid malignant tumor\u003c/p\u003e\n \u003cp\u003eHematological diseases\u003c/p\u003e\n \u003cp\u003eSkin disease\u003c/p\u003e\n \u003cp\u003eInterstitial lung disease\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Primary immunodeficiency disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27（46.6）\u003c/p\u003e\n \u003cp\u003e17（29.3）\u003c/p\u003e\n \u003cp\u003e3（5.2）\u003c/p\u003e\n \u003cp\u003e5（8.6）\u003c/p\u003e\n \u003cp\u003e2（3.4）\u003c/p\u003e\n \u003cp\u003e5（8.6）\u003c/p\u003e\n \u003cp\u003e1（1.7）\u003c/p\u003e\n \u003cp\u003e0（0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e42（29.6）\u003c/p\u003e\n \u003cp\u003e35（24.6）\u003c/p\u003e\n \u003cp\u003e28（19.7）\u003c/p\u003e\n \u003cp\u003e16（11.3）\u003c/p\u003e\n \u003cp\u003e17（12.0）\u003c/p\u003e\n \u003cp\u003e13（9.2）\u003c/p\u003e\n \u003cp\u003e4（2.8）\u003c/p\u003e\n \u003cp\u003e1（0.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.022\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.495\u003c/p\u003e\n \u003cp\u003e0.016\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.580\u003c/p\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003cp\u003e0.905\u003c/p\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-admission immunosuppressants\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eRadiotherapy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e1（1.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e3（2.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eChemotherapy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e2（3.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e32（22.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eRadiotherapy + chemotherapy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e4（6.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e5（3.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.503\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eCorticosteroids, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e56（96.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e122（85.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.029\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eCorticosteroids duration \u003csup\u003ea\u003c/sup\u003e (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e68.5（44.8，102.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e71.5（47，126.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.567\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eDaily dosage at presentation \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e45（31.3，50）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e40（30，55）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.733\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eCorticosteroids withdrawal, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e33（56.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e67（47.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eImmunosuppressive therapy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e36（62.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e100（70.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eBiological agent therapy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e6（10.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e21（14.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eImmune checkpoint inhibitors, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e1（1.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e4（2.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003ePreventive use of sulfonamides, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e2（3.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e3（2.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.960\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRespiratory failure, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e57（98.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e89（62.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptom\u003c/strong\u003e, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eDyspnea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e48（82.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e103（72.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eFever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e48（82.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e124（87.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eCough\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e32（55.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e94（66.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eExpectoration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e18（31）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e52（36.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eChest pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e3（5.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e6（4.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.05494505494506%\" valign=\"top\"\u003e\n \u003cp\u003eHemoptysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.50706436420722%\" valign=\"top\"\u003e\n \u003cp\u003e1（1.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.937205651491364%\" valign=\"top\"\u003e\n \u003cp\u003e3（2.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.500784929356358%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea: median (quartile); b: mean \u0026plusmn; standard deviation; * : P \u0026lt; 0.05, indicating statistically significant difference.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Comparison of laboratory indicators between the death group and the survival group of non-HIV-PCP patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"638\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeath\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003egroup\u003c/strong\u003e\u003cstrong\u003e（n=58\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvival group(n=142)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eWhite blood cell count \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(\u0026times;10^9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e8.6（5.5，11.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e7.7（4.7，10.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eHemoglobin \u003csup\u003eb\u0026nbsp;\u003c/sup\u003e(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e104.5\u0026plusmn;25.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e110.2\u0026plusmn;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.135\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003ePlatelet count \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(\u0026times;10^9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e152（93.8，198.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e184（127.0，257.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eNeutrophil count \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(\u0026times;10^9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e7.5（4.7，10.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e6.2（3.9，8.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.040\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eLymphocyte count \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(\u0026times;10^9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e0.4（0.2，0.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e0.6（0.4，0.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.008\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eNLR \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e17.7（6.8，29.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e9.8（5.6，15.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eProcalcitonin (\u0026mu;g/L)，n (%)\u003c/p\u003e\n \u003cp\u003e＜0.5\u003c/p\u003e\n \u003cp\u003e\u0026ge;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e36（61.2）\u003c/p\u003e\n \u003cp\u003e19（32.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e98（69）\u003c/p\u003e\n \u003cp\u003e28（19.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eHsCRP\u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(mg/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e88.5（55.3，109）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e54.2（16.9，95）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.012\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eErythrocyte sedimentation rate \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(mm/h)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e46（24，84.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e58（35，85）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.193\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eAlanine aminotransferase \u003csup\u003ea\u003c/sup\u003e (IU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e27（16，59.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e22.5（15，38.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eAspartate aminotransferase \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(IU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e29（20，52.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e25（18，37）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.021\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eTotal Protein \u003csup\u003eb\u003c/sup\u003e(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e54.2\u0026plusmn;8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e57.4\u0026plusmn;9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.031\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eAlbumin \u003csup\u003eb\u003c/sup\u003e(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e27.5\u0026plusmn;6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e29.6\u0026plusmn;5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.035\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eSerum creatinine \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(\u0026mu;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e103.5（62.6，157.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e90.5（68，165.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eUrea nitrogen \u003csup\u003ea\u003c/sup\u003e (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e11.2（5.9，16.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e7.7（5.4，14.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eLDH \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(IU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e482.5（359.5，713）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e386（296.5，505）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eD-dimer \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e1.0（0.35，2.55）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e0.48（0.25，0.94）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eG test\u003c/strong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e261.6（171.9，481.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e141.8（49.6，284.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBlood gas analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eP/F\u003csup\u003eb\u0026nbsp;\u003c/sup\u003e(mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e203.2\u0026plusmn;66.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e272.7\u0026plusmn;92.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eSaO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e89.3（85，93.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e93（88.6，95.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003ePaO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e56.8(49.8,65.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e66.4（56.3，78.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eP(A-a)O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e93.8（61.4，145.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e59.5（43.1，102.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eImmune globulin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eIgG\u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e9.0（5.8，14.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e6.3（5.0，10.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.034\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eIgA\u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e1.5（1.0，2.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e1.6（1.0，2.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eIgM\u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e0.8（0.4，1.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e0.9（0.5，1.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.492\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeripheral lymphocyte subsets\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; CD3+ T cell count \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(/\u0026mu;l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e301（175.0，574.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e514.6（274.7，940.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; CD4+ T cell count \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(/\u0026mu;l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e148.6（60.7，225.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e183.6（94.6，345.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; CD8+ T cell coun \u003csup\u003ea\u003c/sup\u003e(/\u0026mu;l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e156.4（80.8，280.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e262.4（141.6，538.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; CD4+/CD8+\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e0.9（0.6，1.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e0.7（0.4，1.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; B cell count \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(/\u0026mu;l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e55.3（27.4，118.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e52.6（6.4，119.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; NK cell count\u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(/\u0026mu;l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e57.3（24.3，137.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e63.7（34.4，144.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBALF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; CD3+ T cell \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e93.2（87.9，97.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e95.2（92.8，97.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; CD4+ T cell \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e33.4（23.1，43.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e31.4（24.0，45.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; CD8+ T cell \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e54.1（42.7，67.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e57.5（46.4,67.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.730\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; CD4\u003csup\u003e+\u003c/sup\u003e/CD8\u003csup\u003e+ a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e0.6（0.4，1.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e0.6 (0.4,0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.931\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; B cell \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e0.2（0，0.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e0.2（0，1.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.516\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; NK cell \u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e4.7（1.1，7.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e2.3 (0.7,4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eMacrophage \u003csup\u003ea\u003c/sup\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e28（15.3，49.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e40（23.3，51.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e0.034\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eNeutrophil \u003csup\u003ea\u003c/sup\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e51（25.8，73）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e15（7，41.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.4012539184953%\" valign=\"top\"\u003e\n \u003cp\u003eLymphocyte\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.82445141065831%\" valign=\"top\"\u003e\n \u003cp\u003e16（7，26.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.391849529780565%\" valign=\"top\"\u003e\n \u003cp\u003e34.5（15，49）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.382445141065832%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: a: median (quartile), b: mean \u0026plusmn; standard deviation; NLR: Neutrophil/Lymphocyte Ratio; P/F: arterial partial pressure of oxygen/inhaled oxygen concentration; \u003csup\u003e*\u003c/sup\u003e P \u0026lt; 0.05, indicating a statistically significant difference.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Comparison of etiological examination between death group and survival group in non-HIV-PCP patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"585\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.57534246575342%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.835616438356166%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeath group\u003c/strong\u003e\u003cstrong\u003e（n=58\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.205479452054796%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvival group\u003c/strong\u003e\u003cstrong\u003e（n=142\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.383561643835616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.57534246575342%\" valign=\"top\"\u003e\n \u003cp\u003eCo-pathogen infection, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; One pathogen infection\u003c/p\u003e\n \u003cp\u003eBacteria\u003c/p\u003e\n \u003cp\u003eFungus\u003c/p\u003e\n \u003cp\u003eVirus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.835616438356166%\" valign=\"top\"\u003e\n \u003cp\u003e48（82.8）\u003c/p\u003e\n \u003cp\u003e20（34.5）\u003c/p\u003e\n \u003cp\u003e5（8.6）\u003c/p\u003e\n \u003cp\u003e5（8.6）\u003c/p\u003e\n \u003cp\u003e10（17.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.205479452054796%\" valign=\"top\"\u003e\n \u003cp\u003e70（49.3）\u003c/p\u003e\n \u003cp\u003e48（33.8）\u003c/p\u003e\n \u003cp\u003e11（7.7）\u003c/p\u003e\n \u003cp\u003e9（6.3）\u003c/p\u003e\n \u003cp\u003e28（19.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.383561643835616%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.927\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.57534246575342%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Two pathogens infection\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eBacteria + Fungi\u003c/p\u003e\n \u003cp\u003eFungus + Virus\u003c/p\u003e\n \u003cp\u003eBacteria + Virus\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Three pathogens infection\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.835616438356166%\" valign=\"top\"\u003e\n \u003cp\u003e20（34.5）\u003c/p\u003e\n \u003cp\u003e9（15.6）\u003c/p\u003e\n \u003cp\u003e3（5.2）\u003c/p\u003e\n \u003cp\u003e8（13.8）\u003c/p\u003e\n \u003cp\u003e8（16.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.205479452054796%\" valign=\"top\"\u003e\n \u003cp\u003e21（14.8）\u003c/p\u003e\n \u003cp\u003e3（2.1）\u003c/p\u003e\n \u003cp\u003e7（4.9）\u003c/p\u003e\n \u003cp\u003e11（7.7）\u003c/p\u003e\n \u003cp\u003e1（1.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.383561643835616%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.57534246575342%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of co-pathogen infection, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.835616438356166%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.205479452054796%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.383561643835616%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.57534246575342%\" valign=\"top\"\u003e\n \u003cp\u003eCommon pathogens causing hospital-acquired pneumonia\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.835616438356166%\" valign=\"top\"\u003e\n \u003cp\u003e25（43.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.205479452054796%\" valign=\"top\"\u003e\n \u003cp\u003e16（11.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.383561643835616%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.57534246575342%\" valign=\"top\"\u003e\n \u003cp\u003eCMV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.835616438356166%\" valign=\"top\"\u003e\n \u003cp\u003e26（44.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.205479452054796%\" valign=\"top\"\u003e\n \u003cp\u003e43（30.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.383561643835616%\" valign=\"top\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.57534246575342%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAspergillus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.835616438356166%\" valign=\"top\"\u003e\n \u003cp\u003e13（22.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.205479452054796%\" valign=\"top\"\u003e\n \u003cp\u003e17（12）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.383561643835616%\" valign=\"top\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.57534246575342%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eEpstein-barr virus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.835616438356166%\" valign=\"top\"\u003e\n \u003cp\u003e4（6.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.205479452054796%\" valign=\"top\"\u003e\n \u003cp\u003e7（4.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.383561643835616%\" valign=\"top\"\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.57534246575342%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eCandida\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.835616438356166%\" valign=\"top\"\u003e\n \u003cp\u003e7（12.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.205479452054796%\" valign=\"top\"\u003e\n \u003cp\u003e1（0.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.383561643835616%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"46.57534246575342%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eCryptococcus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.835616438356166%\" valign=\"top\"\u003e\n \u003cp\u003e4（6.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.205479452054796%\" valign=\"top\"\u003e\n \u003cp\u003e1（0.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.383561643835616%\" valign=\"top\"\u003e\n \u003cp\u003e0.041\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e \u003csup\u003e\u0026sect;\u0026nbsp;\u003c/sup\u003eCommon pathogens causing hospital acquired pneumonia include \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, \u003cem\u003eStaphylococcus\u003c/em\u003e, \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e, \u003cem\u003eEnterobacter cloacae\u003c/em\u003e, \u003cem\u003eEscherichia coli\u003c/em\u003e;\u003csup\u003e*\u003c/sup\u003e P \u0026lt; 0.05, indicating a statistically significant difference.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Comparison of imaging findings between the death group and survival group of non-HIV-PCP patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"572\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeath group\u003c/strong\u003e\u003cstrong\u003e（n=58\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvival group\u003c/strong\u003e\u003cstrong\u003e（n=142\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003eProximal pleural distribution, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e10（17.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e36（25.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003eDistribution along vascular bundle, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e5（8.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e8（5.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003eGround glass density shadow, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e47（81.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e127（89.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003eSpot shadow, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e27（46.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e59（41.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003eSolid shading, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e32（55.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e76（53.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003eGrid shadow, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e7（12.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e11（7.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003eHoneycomb, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e7（12.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e6（4.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003eInterlobular thickening, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e36（62.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e77（54.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.310\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003eLobular core tubercles, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e2（3.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e19（13.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.038\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003ePulmonary air sac, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e2（3.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e2（1.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.705\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003ePneumothorax, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e10（17.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e5（3.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003eMediastinal emphysema, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e6（10.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e2（1.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.011\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003ePleural effusion, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e15（25.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e41（28.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.13309982486865%\" valign=\"top\"\u003e\n \u003cp\u003eLymph node enlargement, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.513134851138354%\" valign=\"top\"\u003e\n \u003cp\u003e1（1.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.665499124343256%\" valign=\"top\"\u003e\n \u003cp\u003e6（4.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.68826619964974%\" valign=\"top\"\u003e\n \u003cp\u003e0.653\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* P \u0026lt; 0.05, indicating a statistically significant difference.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Comparison of treatment between death and survival in non-HIV-PCP patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"664\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeath group\u003c/strong\u003e\u003cstrong\u003e（n=58\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvival group\u003c/strong\u003e\u003cstrong\u003e（n=142\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTherapeutic drugs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003eTMP-SMZ，n（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e57（98.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e141（99.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e0.497\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003eSecond-line treatment \u003csup\u003e\u0026euro;\u003c/sup\u003e，n（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e21（36.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e13（9.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003eReasons for second-line treatment, n（%）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;The effect of sulfonamides treatment was poor\u003c/p\u003e\n \u003cp\u003eSulfonamides cause adverse reactions\u003csup\u003e\u0026Psi;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Sulfonamides hypersensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17（29.3）\u003c/p\u003e\n \u003cp\u003e3（5.2）\u003c/p\u003e\n \u003cp\u003e1（8.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6（4.2）\u003c/p\u003e\n \u003cp\u003e4（2.8）\u003c/p\u003e\n \u003cp\u003e3（2.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.690\u003c/p\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003eCarpofungin，n（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e33（56.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e45（31.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003eCorticosteroids therapy（mg/（kg\u0026middot; d））\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.5，n（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e6（11.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e36（28.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e0.012\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003e0.5-1，n（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e18（33.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e57（44.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;1，n（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e30（55.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e34（26.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMode of oxygen inhalation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003eHigh flow oxygen therapy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e47（81）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e56（39.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003eNon-invasive mechanical ventilation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e49（84.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e29（20.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003eInvasive mechanical ventilation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e48（82.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e10（7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003eAdmission to ICU, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e45（77.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e41（28.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.84939759036145%\" valign=\"top\"\u003e\n \u003cp\u003eLength of ICU stay \u003csup\u003ea\u003c/sup\u003e (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.716867469879517%\" valign=\"top\"\u003e\n \u003cp\u003e11（5.5，18）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e14（6，17）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.36144578313253%\" valign=\"top\"\u003e\n \u003cp\u003e0.738\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e: a: median (quartile); \u0026euro;: Second-line treatment refers to clindamycin, primaquine treatment; \u0026Psi;: The adverse reactions caused by sulfonamides refer to thrombocytopenia, hemolytic anemia, kidney injury; \u003csup\u003e*\u0026nbsp;\u003c/sup\u003eP \u0026lt; 0.05, indicating a statistically significant difference.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eAnalysis of factors associated with poor prognosis in non-HIV-PCP patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"702\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.6011396011396%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.042735042735046%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.267175572519085%\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.755725190839694%\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.03053435114504%\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.595419847328245%\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.083969465648856%\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.267175572519085%\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e1.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e1.028-1.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e＜0.001\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\" valign=\"top\"\u003e\n \u003cp\u003e1.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\" valign=\"top\"\u003e\n \u003cp\u003e1.021-1.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e0.965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e0.895-1.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\"\u003e\n \u003cp\u003eSmoking history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e1.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e0.916-3.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\"\u003e\n \u003cp\u003eChemotherapy history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e0.028-0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.005\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e0.007-0.670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e0.021\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\"\u003e\n \u003cp\u003eHistory of glucocorticoid use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e4.590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e1.037-20.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.045\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\"\u003e\n \u003cp\u003eWithdrawal of glucocorticoid history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e1.478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e0.799-2.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\"\u003e\n \u003cp\u003eAutoimmune disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e2.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e1.105-3.891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.023\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\"\u003e\n \u003cp\u003eOrgan transplantation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e0.222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e0.065-0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.017\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\"\u003e\n \u003cp\u003eCombined with CMV infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e1.871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e0.997-3.510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\"\u003e\n \u003cp\u003eRespiratory failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e33.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e4.566-252.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.001\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003ePlatelet count\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e0.995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\" valign=\"top\"\u003e\n \u003cp\u003e0.991-0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e1.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\" valign=\"top\"\u003e\n \u003cp\u003e1.009-1.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eHsCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e1.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e1.001-1.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.025\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eAlbumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e0.947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e0.900-0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.037\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eLDH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e1.001-1.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.002\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eD-dimer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e1.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e1.068-1.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.004\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eG test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e1.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\"\u003e\n \u003cp\u003e1.000-1.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eIgG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e1.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\" valign=\"top\"\u003e\n \u003cp\u003e0.980-1.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\" valign=\"top\"\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eBALF-percentage of neutrophils\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e1.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\" valign=\"top\"\u003e\n \u003cp\u003e1.019-1.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\" valign=\"top\"\u003e\n \u003cp\u003e1.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\" valign=\"top\"\u003e\n \u003cp\u003e1.000-1.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eBALF-percentage of lymphocytes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e0.957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\" valign=\"top\"\u003e\n \u003cp\u003e0.937-0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003ePathogens associated with hospital-acquired pneumonia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e5.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\" valign=\"top\"\u003e\n \u003cp\u003e2.860-12.445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\" valign=\"top\"\u003e\n \u003cp\u003e4.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\" valign=\"top\"\u003e\n \u003cp\u003e1.407-12.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e0.010\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eHoneycomb shadow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e3.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\" valign=\"top\"\u003e\n \u003cp\u003e0.998-9.698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\" valign=\"top\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003ePneumothorax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e5.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\" valign=\"top\"\u003e\n \u003cp\u003e1.857-17.543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eMediastinal emphysema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e8.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\" valign=\"top\"\u003e\n \u003cp\u003e1.580-41.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\" valign=\"top\"\u003e\n \u003cp\u003e0.012\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eCarpofungin treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e2.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\" valign=\"top\"\u003e\n \u003cp\u003e1.518-5.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.356125356125357%\" valign=\"top\"\u003e\n \u003cp\u003eHigh dose glucocorticoid therapy (\u0026ge;1mg/ (kg\u0026middot; d))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e3.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.23931623931624%\" valign=\"top\"\u003e\n \u003cp\u003e1.758-6.649\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.965811965811966%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.401709401709402%\" valign=\"top\"\u003e\n \u003cp\u003e7.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.245014245014245%\" valign=\"top\"\u003e\n \u003cp\u003e2.482-20.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.396011396011396%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: \u003cstrong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e P \u0026lt; 0.05 was statistically significant.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pneumocystis Jirovecii Pneumonia, Non-Human Immunodeficiency Virus, Glucocorticoid, Risk factors","lastPublishedDoi":"10.21203/rs.3.rs-3906065/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3906065/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGlucocorticoids have been shown to be very effective in the treatment of \u003cem\u003eHuman Immunodeficiency Virus\u003c/em\u003e (HIV) associated \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e Pneumonia (PCP). However, risk factors and the impact on prognosis in non-HIV-PCP patients remain unclear. Our study aimed to early identification risk factors and prognostic impact of glucocorticoids therapy in non-HIV-PCP patients to decrease patients\u0026rsquo; mortality.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective study was conducted on adult (\u0026ge;\u0026thinsp;18 years old) patients diagnosed with non-HIV-PCP in Peking University First Hospital from April 2007 to October 2022. A total of 269 patients with non-HIV-PCP were hospitalized during the period, and 200 patients were eventually included. Demographic data and related clinical data were collected. Univariate and multivariate logistic regression were used to analyze the relationship between variables and poor prognosis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 200 non-HIV-PCP patients were included. 29% (58/200) patients died during admission. Univariate analysis showed that age, history of chemotherapy, history of glucocorticoid, autoimmune disease, organ transplantation, respiratory failure, platelet count, neutrophil/lymphocyte ratio, highly sensitive C-reactive protein, albumin, lactic dehydrogenase, d-dimer, bronchoalveolar lavage fluid (BALF)-neutrophil percentage, BALF-lymphocyte percentage, hospital-acquired pneumonia associated pathogen infection, pneumothorax, mediastinal emphysema, caspofungin therapy and high dose (\u0026ge;\u0026thinsp;1mg/(kg\u0026middot; d)) glucocorticoids therapy have a risk of death due to PCP patients. Multivariate analysis showed that age (OR\u0026thinsp;=\u0026thinsp;1.062, 95%CI 1.021\u0026ndash;1.104, P\u0026thinsp;=\u0026thinsp;0.003), hospital-acquired pneumonia associated pathogen infection (OR\u0026thinsp;=\u0026thinsp;4.170, 95%CI 1.407\u0026ndash;12.357, P\u0026thinsp;=\u0026thinsp;0.010) and high dose glucocorticoid therapy (OR\u0026thinsp;=\u0026thinsp;7.047, 95%CI 2.482\u0026ndash;20.006, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were independent risk factors for in-hospital death in non-HIV-PCP patients.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eConsidering the rapid course of the disease in non-HIV-infected immunocompromised patients. Early identification of high-risk PCP patients is critical to reduce morbidity and mortality. Our study found that non-HIV-PCP patients treated with high doses of glucocorticoids, old age, history of chemotherapy and hospital-acquired pneumonia associated pathogen infection had worse outcomes during hospitalization.\u003c/p\u003e","manuscriptTitle":"The Evaluation of risk factors and prognostic impact of glucocorticoid therapy among non-HIV patients with Pneumocystis Jirovecii Pneumonia (PCP) Running title：Glucocorticoid therapy among non-HIV patients with PCP","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-07 20:23:42","doi":"10.21203/rs.3.rs-3906065/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6e3a8404-9f77-4318-a991-35b61e177b1f","owner":[],"postedDate":"February 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-18T07:08:21+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-07 20:23:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3906065","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3906065","identity":"rs-3906065","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}