The predictive value of SOFA score, PLR score and SII/ALB in patients with pulmonary fibrosis with novel coronavirus pneumonia
Zhang Qiao, Fu Weiping
Abstract Objective To investigate the SOFA score, PLR score, systemic immune inflammation index and albumin ratio(SII/ALB) predictive value of pulmonary fibrosis in patients with novel coronavirus pneumonia. Methods This study is a single-center, retrospective, observational cohort study, which was collected continuously in 2021111 Until December 2023 , he was diagnosed with the new crown in the First Affiliated Hospital of Kunming Medical UniversityThe clinical data of 101 patients with pneumonia, according to the presence or absence of pulmonary fibrosis on chest HRCT, the new crown pneumonia patients were divided into lungsFibrosis group (n=26) and pneumofibrosis group (n=75). )。 The demographic data, clinical characteristics, disease severity scores, laboratory tests, complications, treatment measures and clinical outcomes of patients were collected, and the risk factors and predictive value of pulmonary fibrosis were analyzed. Results The SII/ALB ratio, PLR score, and SOFA score in the pulmonary fibrosis group were significantly higher than those in the non-pulmonary fibrosis group (P < 0.05); The oxygenation index of the pulmonary fibrosis group was lower than that of the non-pulmonary fibrosis group (P < 0.05). The number of patients with asthma and sepsis in the pulmonary fibrosis group was higher than that in the non-pulmonary fibrosis group (P < 0.05); Risk factors for pulmonary fibrosis in patients with novel coronavirus pneumonia include SII/ALB ratio, PLR score, SOFA score, and PaO2/FiO2. Asthma, sepsis
SII/ALB ratio, PLR score、
SOFA scores are separate and
Three
The AUC of patients with pulmonary fibrosis was 0.659, 0.683 and 0.737, respectively、0.777。
conclusion
SOFA score, PLR score与
Systemic immune inflammation index to albumin ratio(SII/ALB,the radio of system immune-inflammation index to Albumin)
Ratio to COVID-19 with pulmonary fibrosis
patient
Predictive value.
Key words: Systemic immune inflammation index to albumin ratio (SII/ALB); COVID; pulmonary fibrosis; risk factors; Predictive value
【Abstract】Objective explore the predictive value of SOFA score ,PLR score and SII/ALB in patients with post COVID-19 pulmonary fibrosis Methods
Results
Author Affilications:650021 Kunming, Yunnan, China, the Second Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Kunming Medical University
Notification author: Fu Weiping, E-mail: fuweiping2@ 163. com.
Coronavirus disease 2019 (COVID-19) has dealt a severe blow to healthcare systems, economic development, and social cohesion around the world. As of 28 April 2024, more than 775 million confirmed cases and more than 7 million deaths have been reported globally[1], making it the largest global public health crisis of this century. COVID-19 can cause different clinical symptoms and severity. Most patients will have symptoms such as fever, sore throat, and dry cough, and patients with severe COVID-19 will have ARDS-related sequelae of fibrosis and pulmonary impairment, manifesting as restrictive lung disease [2]; During a one-year follow-up of SARS survivors, pulmonary function tests revealed abnormal lung function and poor quality of life after discharge [25]. The long-term survival rate and quality of life caused by pulmonary fibrosis decreased by novel coronavirus pneumonia complicated with pulmonary fibrosis, and the mortality rate of pulmonary fibrosis combined with pulmonary fibrosis was further increased.
It is well known that inflammation is associated with changes in many hematological parameters, but a single indicator in the blood routine is susceptible to the influence of underlying medical history, nutritional conditions, age, and other underlying factors, and has limited predictive and diagnostic value. Therefore, in this study, novel composite inflammatory indicators such as: platelet count X neutrophil count/lymphocyte count ratio (SII) and neutrophil/lymphocyte ratio (NLR) were introduced), platelet/lymphocyte ratio (PLR) and other indicators can help improve the prognosis of severe and critical illness in patients with new coronary pneumoniaAccuracy of the test. SII, a new indicator of systemic inflammation response, integrates host and immunofactors, and has high value in predicting disease deterioration and intensive care unit (ICU) admission 。 Albumin is synthesized by liver parenchymal cells and plays an important physiological role in the human body, and capillary leakage is the main cause of hypoalbuminemia in patients with severe COVID-19 through the hyperpermeability of proteins and the induction of pro-inflammatory procoagulant factor pathways by endothelial cells. [4] However, at present, there are few predictions of SII and SII/ALB ratios for COVID-related pulmonary fibrosis.
The scientific assumptions of this study are that the SOFA score, PLR score and
SII/ALB has predictive value in pulmonary fibrosis complicated with new coronary pneumonia. Previous studies have shown that the predictive value of new composite inflammatory indicators in other diseases is higher than that of a single index, but whether these indicators have higher predictive value in patients with new crown pneumonia needs to be further investigated. Therefore, this study analyzed the clinical data of 101 inpatients with novel coronavirus pneumonia, and combined conventional laboratory indicators with new composite indicators to explore
The predictive value of SII/ALB in the later stage of pulmonary fibrosis in patients with new coronary pneumonia can help clinicians to intervene early in disease progression.
In order to do so
"Early Identification, Early Diagnosis, Early Intervention",
In order to reduce the risk of severe disease and death, improve the level of diagnosis and treatment, and reduce mortality.
1 Materials and methods
Clinical Research Norms, Ethics and Quality Control
The First Affiliated Hospital of Kunming Medical University collects clinical data in accordance with the norms of clinical research.
Inclusion of study participants
Study location and time This study was conducted in the hospital of the First Affiliated Hospital of Kunming Medical University. This study retrospectively analyzed 101 patients who visited the hospital from January 1, 2021 to December 31, 2023, as study subjects, and collected clinical and laboratory-related data or test results of study subjects based on the hospital clinical data management system.
Inclusion Criteria and Exclusion Criteria Inclusion Criteria: Refer to the "Diagnosis and Treatment Protocol for Novel Coronavirus Infection (Trial Tenth Edition)" [26]1.Have relevant clinical manifestations of novel coronavirus infection. 2. Positive nucleic acid test for new coronavirus; Exclusion Criteria: (1) Age less than 18 years; (2) pregnant or lactating patients; (3) Patients infected with the new crown but without pneumonia; (4) Patients with serious lack of case data; (5) Pulmonary fibrosis (IPF and other interstitial lung diseases) has been diagnosed before this admission.
Study group According to the HRCT results, the patients were divided into two groups, pulmonary fibrosis group and no pulmonary fibrosis group.
Clinical data collection Demographic data, clinical features, disease severity score (SII/ALB), laboratory tests, treatment measures for complications, and clinical outcomes.
Statistical analysis using SPSS 27.0 (SPSS, Chicago, IL, USA) statistical software package for database creation and statistical analysis. According to the distribution of continuous variables in the data, the normality test and the homogeneity test of variance were carried out for the quantitative data, and the quantitative data of normal distribution were compared, the t-test was used for comparison between the two groups, and the non-normally distributed quantitative data was compared, and the nonparametric Mann-Whitney U method was used to compare the differences between the two groups. Categorical data were expressed in the number of cases (percentage), and chi-square test was used for comparison between groups. Binary logistic regression analysis was used to analyze the risk factors of pulmonary fibrosis in patients with COVID-19 pneumonia. P<0.05 indicated that the difference was statistically significant.
Results
Screening of study subjects
From January 1, 2021 to December 31, 2023, 635 cases of new crown pneumonia patients confirmed in the Second Department of Respiratory and Critical Care Medicine and the Department of Infectious Diseases of the First Affiliated Hospital of Kunming Medical University were collected, 216 cases of patients with missing case data were excluded, 217 cases of patients with new crown infection but no manifestations of pneumonia (mild new crown infection) were excluded, 14 cases of patients younger than 18 years old and pregnant or lactating patients were excluded, and 87 cases of pulmonary fibrosis (IPF and other interstitial diseases) were diagnosed before this admission. All 101 patients with COVID-19 pneumonia who met the inclusion criteria were included in the study. Among them, pulmonary fibrosis group (n=26 cases) and no pulmonary fibrosis group (n=75 cases).
2 Pulmonary fibrosis group versus no pulmonary fibrosis group
2.1 Comparison of demographic data with clinical features
A total of 101 patients with COVID-19 were included in this study, including 26 in the pulmonary fibrosis group and 75 in the non-pulmonary fibrosis group. In terms of basic data, the mean age of the pulmonary fibrosis group was greater than that of the non-pulmonary fibrosis group; There were statistically significant differences in bronchial asthma (P<0.05) and PaO2/FiO2 in basic vital signs and symptoms ( P<0.05); There was no statistical difference in the remaining indicators (P>0.05).
Table 1. Comparison of demographic data and clinical characteristics between the group and those without pulmonary fibrosis
|
(n=26) |
(n=75) |
| P |
| 17(65.38) | 37(49.33) | 1.406 | 0.236 |
| 70+ 10 | 64+ 16 | -2.272 | 0.026 |
BMI | 23.55 (20.30-24.83) | 23.43 (21.13-25.63) | 0.416 | 0.519 |
| ||||
| 11(42.3) | 16(21.3) | 3.332 | 0.068 |
AECOPD(有) | 4(15.3) | 6(8.0) | 0.137 | 0.711 |
| 4(15.3) | 1(1.33) | 5.390 | 0.02 |
| 15(57.6) | 47(62.7) | 0.046 | 0.830 |
| 7(26.9) | 24(32) | 0.056 | 0.813 |
| 2(7.6) | 12(16.0) | 0.529 | 0.467 |
| 13(50) | 40(53.3) | 0.004 | 0.948 |
| 3(11.5) | 3(4.0) | 0.846 | 0.358 |
| 8(30.7) | 18(24) | 0.176 | 0.674 |
| 1(3.8) | 3(4.0) | NA | NA |
| ||||
| 91 + 14 | 89+ 13 | -0.497 | 0.620 |
| 83 +12 | 86±15 | 0.873 | 0.385 |
| 20(20-22) | 20(20-21) | 5.017 | 0.025 |
| 36.5 (36.3-36.8) | 36.5 (36.2-36.8) | 0.023 | 0.879 |
PaO2/FiO2 | 221(174-321) | 346(198-400) | 6.125 | 0.013 |
| ||||
| 20(76.9) | 56(74.7) | NA | NA |
| 22(84.6) | 73(97.3) | 3.544 | 0.06 |
| 22(84.6) | 61(81.3) | 0.006 | 0.937 |
| 13(50) | 44(58.7) | 0.290 | 0.590 |
| 6(23) | 11(14.7) | 0.467 | 0.494 |
| 2(7.6) | 4(5.3) | NA | NA |
| 5(19.2) | 13(17.3) | NA | NA |
| 3(11.5) | 5(6.7) | 0.138 | 0.710 |
Note: P<0.05 was considered statistically significant;
2.2 Compare the new composite inflammatory indicators
The comparison of various new composite inflammatory indexes after admission showed that there were statistically significant differences in SII, SII/ALB, PLR, AFR and SOFA scores (P<0.05), but the rest were not statistically significant.
Table 2Novel composite inflammatory markers
|
(n=26) |
(n=75) |
| P |
SII | 1655.59 (583.08-4690.89) | 800.74(309.30-0859.94) | 5.215 | 0.022 |
SII/ALB | 48.07 (15.79-120.70) | 20.78(8.14-52.60) | 5.322 | 0.021 |
NLR | 8.39(2.40-8.58) | 4.18 (2.11-9.20) | 3.831 | 0.050 |
PLR | 279.94(161.74-474.10) | 189.63 (128.26-254.70) | 7.689 | 0.006 |
LCR | 0.03(0.01-0.08) | 0.04(0.02-0.16) | 2.815 | 0.093 |
AFR | 7.06(5.84-8.86) | 8.33(6.87-10.82) | 4.629 | 0.031 |
CAR | 0.83(0.25-2.01) | 0.52(0.14-1.30) | 1.775 | 0.183 |
| 3(2-5) | 1(1-3) | 13.450 | <0.001 |
| 3(2-4) | 3(2-4) | 2.700 | 0.100 |
| 4(2-5) | 3(2-5) | 1.618 | 0.203 |
2.3 Laboratory indicators
The comparison of inflammatory indexes, cardiovascular system, coagulation fibrinolytic system and etiological indicators showed that there were statistically significant differences in absolute lymphocyte value and BNP (P% 3C0.05)。
Table 3.Comparison of laboratory indicators/examinations between the two groups
|
(n=26) |
(n=75) |
| P | n |
| |||||
| 7.63(4.38-11.05) | 5.46(4.12-9.03) | 2.009 | 0.156 | |
NEUT(109·L-1) | 5.39(3.43-9.76) | 4.11(2.44-7.33) | 2.110 | 0.146 | |
NEUT% | 0.82(0.64-0.90) | 0.73(0.59-0.85) | 3.563 | 0.059 | |
LYM(109·L-1) | 0.70(0.40-1.36) | 1.00(0.68-1.37) | 3.924 | 0.048 | |
PLT(109·L-1) | 214 (162-328) | 179 (144-255) | 2.802 | 0.094 | |
| |||||
ALB(g/L) | 35.36±5.26 | 37.15±5.07 | 1.537 | 0.127 | |
HGB(g/L) | 129.00 (123.75-142.50) | 137.00 (120.00-150.00) | 0.193 | 0.661 | |
| 64.85(60.20-68.73) | 67.40(63.20-71.00) | 2.611 | 0.106 | |
| 1.20(1.00-1.40) | 1.30(1.10,1.50) | 1.441 | 0.230 | |
| 6.27(4.11-8.83) | 5.24(4.00-6.54) | 1.075 | 0.300 | |
| 74.84 (59.04-96.40) | 74.25(61.90-93.9) | 0.068 | 0.795 | |
AST(IU/L) | 22.29(17.13-27.38) | 24.07(18.30-36.30) | 0.697 | 0.404 | |
ALT(IU/L) | 23.90(16.09-39.53) | 23.10(14.65-44.09) | 0.122 | 0.727 | |
| 9.8(7.23-13.90) | 9.90(7.20-12.70) | 0.038 | 0.846 | |
LDH(U/L) | 238.50(179.25-341.25) | 213.00(189.25-271.25) | 0.403 | 0.525 | 58 |
ALP(U/L) | 77.9(53.93-98.43) | 74.5(59.9-88.3) | 0.027 | 0.870 | |
| 6.10(4.30-7.13) | 6.50(5.50-7.80) | 1.935 | 0.164 | |
GGT(IU/L) | 46.00(29.25-96.50) | 40.00(25.00-75.00) | 1.287 | 0.257 | |
| |||||
IL-6 | 2.50(1.11-15.18) | 3.24(1.63-14.38) | 0.743 | 0.389 | 86 |
CRP(μmol·L-1) | 27.50(10.25-61.45) | 18.10(5.30-48.50) | 1.693 | 0.193 | |
PCT(ng/mL) | 0(0-0.06) | 0(0-0.14) | 0.196 | 0.658 | |
| |||||
BNP(ng/L) | 67.01(28.40-115.39) | 20.00(10.00-85.44) | 4.735 | 0.03 | |
| 26.88 (12.92-45.00) | 23.73(12.00-41.32) | 0.367 | 0.545 | |
| 0.016 (0.011-0.020) | 0.011(0.006-0.024) | 2.740 | 0.098 | |
| |||||
FIB(g/L) | 5.05+ 1.15 | 4.45+1.32 | -1.762 | 0.081 | |
D-Di(mg/L) | 0.73(0.42-1.13) | 0.49(0.30-1.16) | 3.015 | 0.083 | |
PT(s) | 12.8(12.3-13.6) | 12.7(12.2-13.3) | 1.809 | 0.179 | |
APTT(s) | 37.00(32.85-40.85) | 35.70(33.70-39.30) | 0.179 | 0.672 | |
| |||||
| 3(13.64) | 17(30.36) | 2.316 | 0.128 | 78 |
PCR | 31.13 + 4.19 | 28.80 + 5.51 | -1.688 | 0.096 |
2.4 Comparison of complications and treatment measures
The comparison of serious complications in hospital admission showed that there was a statistically significant difference in sepsis (P<0.01). The comparison of treatment measures showed that there were statistically significant differences in length of hospital stay and hormone use (P<0.05), but there was no statistical difference.
|
(n=26) |
(n=75) |
| P |
| ||||
ARDS(有) | 2(7.6) | 5(6.7) | NA | NA |
MODS(有) | 1(3.8) | 2(2.7) | NA | NA |
| 1(3.8) | 1(1.3) | NA | NA |
| 1(3.8) | 5(6.7) | 0.002 | 0.966 |
CRRT(有) | 1(3.8) | 1(1.3) | NA | NA |
Sepsis(有) | 22(84.6) | 34(45.3) | 10.522 | 0.001 |
| ||||
| 11(8,13) | 6(7-11) | 4.931 | 0.026 |
| 21(80.7) | 57(76.0) | 0.052 | 0.819 |
| 4(15.3) | 2(2.7) | 3.544 | 0.06 |
| 23(88.4) | 47(62.7) | 4.576 | 0.032 |
| 21(80.7) | 65(86.7) | 0.167 | 0.683 |
| 19(73) | 46(61.3) | 0.705 | 0.401 |
Table 4.Complications and treatments
2.5 Comparison of clinical outcomes
The comparison of clinical outcomes after admission showed that there were no significant differences in case fatality rate, incidence of ICU transfer, use of non-invasive ventilator, and duration of ventilator use.
Table 5.Comparison of clinical outcomes
|
(n=26) |
(n=75) |
| P |
| 1(3.8) | 6(8.0) | 0.073 | 0.787 |
| 3(11.5) | 0 | NA>0.999 | |
| 0(0,0) | 0(0,0) | 8.828 | 0.003 |
| 9(34.6) | 13(17.3) | 3.351 | 0.067 |
| 0(0,24) | 0(0,10) | 2.552 | 0.110 |
2.6 Multivariate binary logistic regression analysis
In this study, multi-element binary logistic regression analysis was used to explore the risk factors associated with pulmonary fibrosis after COVID-19. Whether fibrosis occurred was the dependent variable (assignment: pulmonary fibrosis group = 1, no pulmonary fibrosis group = 0), age (years), bronchial asthma, respiratory rate (times/min), PaO2/FiO2, absolute lymphocyte value, BNP, length of hospital stay, SII, sepsis, hormone use, SII/ALB, PLR score, AFR score, SOFA score, and AFR score were independent variables. Regression analysis showed that high age was negatively correlated with the occurrence of pulmonary fibrosis, with underlying respiratory diseases, bronchial asthma, rapid respiratory rate, and low PaO2/FiO2, high BNP, increased length of hospital stay, high SII score, sepsis, no-ball use, hormone use, high SII/ALB score, high PLR score, high SOFA score, and AFR score were positively correlated with the occurrence of pulmonary fibrosis.
High SII/ALB score, bronchial asthma, low PaO2/FiO2, sepsis, high PLR score, and high SOFA score were independent risk factors for the development of pulmonary fibrosis after COVID-19.
2.7 Predicting the ROC curve of COVID-related pulmonary fibrosis
High SII/ALB score, bronchial asthma, low PaO2/FiO2, sepsis, high PLR score, and high SOFA score are independent risk factors for the development of pulmonary fibrosis after new coronary pneumonia. The area under the ROC curve was used to evaluate the predictive performance. High SII/ALB score, PLR score, bronchial asthma, bulb-free use, hormone use, sepsis, and SOFA score have predictive value for pulmonary fibrosis in patients with new coronary pneumonia.
Table 7.ROC curves for independent risk factors
| AUC | SE | P | 95%CI |
SII/ALB | 0.659 | 0.064 | 0.023 | 0.525-0.775 |
| 0.737 | 0.054 | 0.000 | 0.630-0.844 |
| 0.683 | 0.065 | 0.006 | 0.556-0.811 |
| 0.683 | 0.065 | 0.006 | 0.556-0.811 |
| 0.761 | 0.055 | 0.000 | 0.653-0.869 |
| 0.777 | 0.051 | 0.000 | 0.678-0.877 |
SII/ALB ratio, PLR score, Sofa score, ROC curve
Discussion
This study showed that SOFA score, PLR score and systemic immune inflammation index to albumin ratio (SII/ALB) had good predictive value for pulmonary fibrosis in patients with novel coronavirus pneumonia. High SOFA score, high PLR score, and high SII/ALB can be considered to have a high probability of pulmonary fibrosis in patients with new coronary pneumonia, in order to help clinicians intervene early in disease progression, reduce the risk of severe disease and death, improve the level of diagnosis and treatment, and reduce mortality.
SII was first studied in 2014 as a new indicator of the level of systemic inflammatory response, and it was confirmed that SII can be used as a reliable predictor of sepsis prognosis [3].。 There is also a growing body of research on the predictive role of SIIs in COVID-19 patients. Since the beginning of the year, it has been found that the SII value of COVID-19 patients is higher than that of healthy people, which is statistically different, and it is further proposed that SII can preliminarily distinguish between positive and negative groups of novel coronavirus, which has potential value for the diagnosis of the disease [5]. In many oncology and infectious diseases, systemic indices correlate with clinical outcomes. A small number of studies have shown that mortality from COVID-19 is commensurate with severity [6][7]. In the mata analysis of 39 articles by Mangoni et al. [8], it was found that high SII was associated with COVID-19is associated with mortality from COVID-19. In a multicenter COVID-19 study conducted by Hamad et al. [9], the SII (>1346) was found to be the most specific ( (95.6%) of inflammatory markers, which had a higher value in predicting exacerbation and intensive care unit (ICU) admission. Albumin is a serum protein, and its plasma levels may vary depending on inflammation and nutritional status. Hypoproteinemia has been found to be associated with the prognosis of severe disease [10]. Critically ill patients with COVID-19 may present with hypoalbuminemia, which is characterized by increased vascular permeability and deterioration of liver and kidney function. Studies have found that morbidity and mortality from COVID-19 are associated with reduced albumin levels [11].。 In these studies, patients who developed ARDS, required intensive care, and died had higher SIIs. Pulmonary complications are prevalent during and after Sars-Cov-2 infection. Common complications include pulmonary fibrosis, respiratory failure, pulmonary embolism, secondary bacterial pneumonia, etc. The damage to the lung epithelium is due to the direct action of the virus or the action of the immune system in a small space, and this damage and influence leads to pulmonary fibrosis, making it difficult for a person to breathe. In addition, immune cells are recruited, releasing TNF-α, IL-1b, IFN-γ, and granulosacyte-phagocyte colony-stimulating factor[12][13].。 Due to the recruitment of immune cells at the site of injury, these cells also secrete proteolytic enzymes such as matrix metalloproteinase (MMP) to degrade the extracellular matrix and produce the release of cytokines, TGF-β, and chemoattractant protein (MCP)1, which in turn induces the detachment of fibroblasts, collagen, and cell matrix components, and aggravates pulmonary fibrosis[14-17]。 In this study, systemic inflammatory indices were collected, and several indicators were superior to NLR in predicting prognosis, including systemic immune inflammatory index (SII), prognostic nutritional index (PNI), and C-reactive protein (CRP) to albumin ratio (CAR) [22]. However, there are few literature reports on the predictive value of SII and SII/ALB in patients with pulmonary fibrosis. In this study, the systemic immune inflammatory index and albumin were combined to provide a certain predictive value for the occurrence of pulmonary fibrosis and poor prognosis in patients with novel coronavirus pneumonia based on the level of inflammation and nutritional status of the body.
In this study, age, underlying bronchial asthma disease, respiratory rate, PaO2/FiO2, absolute lymphocyte value, BNP, length of hospital stay, length of ICU stay, SII, sepsis, There were statistically significant levels of hormone use, SII/ALB, PLR score, AFR score, and Sofa score (P<0.05). There have been reports that the severity of COVID-19 varies by age, with older adults at higher risk and severity of morbidity, as well as a higher likelihood of sequelae and death compared to children and young adults. However, it is important to note that the impact of COVID-19 on children remains a topic of debate and ongoing research [18-20]. Lymphopenia is an immunological indicator of viral infection and is associated with the severity and mortality of COVID-19 [21]. Age and oxygenation index are independently associated with COVID-19 mortality [23]. Pulmonary fibrosis has been found to account for a significant proportion of patients with COVID-19, with persistent pulmonary fibrosis being found in patients with older age, high BMI, severe/critical illness, fever, long viral clearance, underlying medical conditions, and long hospital stays [24]. This is consistent with the results of this study. Bronchial asthma, low PaO2/FiO2, sepsis, hormone use, high SII/ALB score, high PLR score, and high Sofa score are independent risk factors for the development of pulmonary fibrosis after COVID-19.
In this study, some new composite inflammatory indicators were introduced, which were more reliable than single indicators, not easily disturbed by body factors, and had high credibility and practicability. This study is a single-center retrospective study with a small sample size and possible errors, and large-sample, multi-center, and prospective data are still needed to further verify the prediction efficacy.
Conclusions
SOFA score, PLR score and SII/ALB have good predictive value in patients with pulmonary fibrosis.
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Diagnosis and Treatment Protocol for Novel Coronavirus Infection (Trial 10th Edition)