2.1 Study design
We retrospectively included patients with sepsis admitted in the ICU of Dongyang Hospital for the first time. The exclusion criteria were age < 18 years, ICU stay < 72 h, and > 20% missing data. The study followed the reporting guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology (Table S1).
2.2 Data collection
Data were collected using the medical record data mining software provided by Le9 Health (Shanghai, China). The following information were collected: (1) basic clinical and demographic characteristics such as age, sex, acute physiology, and chronic health evaluation (APACHE) score, sequential organ failure assessment (SOFA) score, and comorbidities such as hypertension, diabetes, and chronic obstructive pulmonary disease (COPD); (2) biochemical indicators such as procalcitonin level, complete blood cell count, blood gas concentration, liver function, kidney function, and coagulation function; and (3) daily CRP values for 5 days after ICU admission.
The primary study outcome was in-hospital mortality rate, and the secondary outcomes were duration of mechanical ventilation, duration of ICU stay, and total length of hospital stay.
2.3 Definition of sepsis
According to Sepsis 3.0, sepsis was defined as organ dysfunction triggered by an infection that endangers the patient’s life and causes a rapid increase in SOFA score > = 2 points)3.
2.4 Data processing
Variables with > 20% missing values were deleted. The missing values of variables with loss rates < 20% were replaced using multiple imputations. Outliers were detected using interquartile range (IQR) and handled as missing values.
2.5 Statistical analysis
All statistical analyses were performed using R (software version 4.1.3). Descriptive statistics were performed using the CBCgrps package in R15. Normally and non-normally distributed measurement data are expressed as mean ± standard deviation and median (IQR), respectively. Among-group comparisons of continuous and categorical variables were performed using analysis of variance and chi-square tests, respectively. Statistical significance was set at p < 0.05.
LGMM is used to classify the CRP trajectories and is based on the Extended Mixed Models Using Latent Classes and Latent Processes (lcmm) of the R package (version 2.0.0)12,16. A crucial factor in creating LGMM is determining the number of latent classes. To select the optimal number of latent classes, we built models with two to six classes. Indicators reflecting the goodness of fit of LGMM include log likelihood, entropy, and information criteria. The lower the Akaike information criterion (AIC), Bayesian information criterion (BIC), and sample-adjusted BIC (SABIC), the better the model fit17. The entropy value (range: 0–1) indicates the accuracy of a model in classifying individuals into the corresponding classes. Generally, an entropy value > 0.80 is considered indicative of high classification accuracy, with a higher entropy value indicating a better goodness-of-fit of the model18. Additionally, to ensure the stability of the model, we controlled the sample size of each class to be > 1% of the total study population. Furthermore, the goodness-of-fit of the model was ensured by verifying that the average posterior probability of all classification members was ≥ 70%. Finally, we considered the clinical interpretability of the model.
Logistic regression analysis was used to explore the association between CRP trajectories and the in-hospital mortality risk. Three models were used to calculate the crude and adjusted odds ratios (ORs), with trajectory 1 as the reference. Model 1 was unadjusted; model 2 was adjusted for age and sex; and model 3 was adjusted for age, sex, and other confounders. The adjusted ORs were reported with 95% CIs and p values. The models comprised variables with a p value < 0.10 in univariate analysis and clinically important variables. Multicollinearity was tested using the variance inflation factor (VIF), with VIF ≥ 5 indicating multicollinearity. The Kaplan–Meier method was used to calculate the 30-day in-hospital survival rate.
2.6 Ethics approval
This study was conducted in accordance with the tenets of the Declaration of Helsinki. This study was approved by the Ethics Committee of Dongyang People’s Hospital (DRY-2023-YX-103). This study followed all related local guidelines and regulations, including human genetics-related regulations. The requirement for informed consent was waived by the Ethical Committee of Dongyang People’s Hospital due to the retrospective nature of this study, and the study involved no human tissue collection and storage process. The data were analyzed anonymously by removing patients’ personal information.