Abstract
Background
While elevated fibrinogen-to-albumin ratio (FAR) correlates with all-cause mortality in adults, its prognostic value in pediatric intensive care units (PICUs) remains unclear. This study aimed to investigate the association between FAR and in-hospital all-cause mortality in critically ill pediatric patients.
Methods
We conducted a retrospective cohort study analyzing the PIC database from 2010 to 2018. Blood samples for fibrinogen and serum albumin were collected within 24 h of admission. The primary outcome was 28-day all-cause mortality. We utilized multivariable Cox proportional hazards regression, smooth curve fitting, and Kaplan–Meier survival curves, along with subgroup analyses and a two-piecewise linear regression model to assess associations.
Results
A total of 5,087 patients (mean age 1.4 years; 44.7% female) were included. The 28-day mortality rate was 4.7% (240/5,087). FAR was independently associated with mortality risk (HR: 0.83, 95% CI: 0.70–0.98; P = 0.031). Higher FAR tertiles correlated with decreased mortality risk (HR: 0.66, 95% CI: 0.44–1.00; P = 0.005). The FAR-mortality relationship was L-shaped, with a threshold around 0.648. The effect sizes on the left and right sides of the inflection point were 0.076 (95% CI: 0.025–0.234, P < 0.001) and 1.126 (95% CI: 0.669–1.895, P = 0.656), respectively. No significant interactions were observed between FAR and 28-day mortality, except in patients with malignant cancer (P for interaction > 0.05). The results of the sensitivity analysis remained stable.
Conclusions
This study reveals an L-shaped relationship between FAR and 28-day in-hospital all-cause mortality in PICU patients, suggesting that FAR may serve as a prognostic marker for mortality in critically ill children.
Graphical Abstract
Supplementary Information
The online version contains supplementary material available at 10.1186/s12887-025-06011-x.
Keywords: Fibrinogen to albumin ratio, Mortality, Cohort study, Pediatric intensive care unit (PIC) database
Introduction
Critically ill pediatric patients represent a highly vulnerable population with elevated morbidity and mortality rates worldwide. Over 80% of the annual 6.4 million global deaths among children under 14 years of age occur in low and middle-income countries (LMICs), where healthcare resources are limited [1]. Despite a consistent decline in child mortality rates from 1990 to 2019 due to initiatives like the Sustainable Development Goals [2]. pediatric mortality remains a significant global challenge. Importantly, the risk of mortality in this population is often inadequately quantified [3]. Therefore, reliable biomarkers that can predict poor prognosis in pediatric patients are urgently needed to facilitate risk stratification, guide clinical decision-making, and optimize resource allocation.
Fibrinogen, a liver-produced protein, serves as a key indicator of the procoagulant state and plays a multifaceted role in inflammatory responses [4]. Previous studies have demonstrated that plasma fibrinogen levels, which act as both an inflammatory biomarker and a core component of the coagulation pathway, are associated with the severity of coronary artery disease and may predict cardiovascular events in the general population [5, 6]. On the other hand, albumin, the most abundant plasma protein, is a negative acute-phase reactant synthesized in the liver. Serum albumin concentrations are closely linked to inflammatory and hemostatic processes [7]. Lower levels of serum albumin have been inversely associated with cardiovascular mortality and are correlated with increased mortality in various individuals [8].Additionally, albumin plays a critical role in assessing nutritional status and systemic inflammation [9, 10]. While fibrinogen and albumin are individually important markers of systemic inflammation and hemorheological alterations, relying on a single indicator may be insufficient for predicting poor prognosis. The combination of elevated fibrinogen and decreased albumin levels is a common feature in inflammatory diseases.
Previous studies have established scoring systems, such as the Pediatric Risk of Mortality (PRISM) and the Pediatric Index of Mortality (PIM), to identify mortality risk [11, 12]; however, these scores require the collection of numerous complex clinical and laboratory variables, limiting their feasibility, particularly in resource-constrained settings. The fibrinogen-to-albumin ratio (FAR) represents a novel approach: it is a simple biomarker derived from two routinely measured parameters (fibrinogen and albumin), yet it potentially reflects integrated information about inflammation, coagulation status, and nutritional state – key pathophysiological pathways in critical illness [13]. Emerging evidence has highlighted the fibrinogen-to-albumin ratio (FAR) as a novel inflammatory biomarker with promising prognostic value across multiple adult diseases, including malignancies, cardiovascular disorders, cerebrovascular diseases, and COVID-19 [14–19]. Nevertheless, pediatric evidence remains limited to single-center sepsis cohorts and neonatal outcomes [20, 21]. the prognostic value of the FAR concerning all-cause mortality in pediatric patients remains scarce. To fill this knowledge gap, our retrospective cohort study aimed to investigate the association between FAR and in-hospital all-cause mortality in critically ill pediatric patients.
Methods
Data sources
This retrospective cohort study analyzed data sourced from the PIC (version 1.1) database, a comprehensive and de-identified clinical dataset encompassing routine hospital care records from the Children’s Hospital, Zhejiang University School of Medicine. The dataset comprises clinical information from 12,341 pediatric patients, aged 0 to 18 years, across 13,941 hospitalizations in various Pediatric Intensive Care Units (PICUs) within a single center during the period from 2010 to 2018. Ethical approval for the study was granted by the Institutional Review Board/Ethical Committee of the Children’s Hospital, Zhejiang University School of Medicine (Hangzhou, China; 2019_IRB_052). In accordance with the Declaration of Helsinki, informed consent was not required due to the deidentification of personal information using random codes for the protection of patient privacy. Data extraction was performed using Structured Query Language (SQL) via Postgres SQL software (version 13.9) and Navicat Premium software (version 16.3). The study methodology adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [22]. Further details regarding the PIC database are available on the official website (http://pic.nbscn.org/).
Study population
The study focused on pediatric patients aged ≥ 28 days and < 18 years admitted to various Pediatric Intensive Care Units (PICUs). For patients with multiple hospitalizations, only data from the first admission data were retained. Patients missing clinical measurements of blood fibrinogen and serum albumin within the first 24 h of admission were excluded. Additionally, individuals who stayed in the ICU of less than 24 h were excluded.
Study variables and outcome
Exposure variable
The FAR was selected as the primary study variable. Blood fibrinogen concentration (g/L) and serum albumin (g/L) were measured within the first 24 h of admission to minimize the influence of subsequent therapeutic interventions. If multiple results for these parameters were available during this period, the first recorded values were used.
Variable
Based on previous literature [23, 24] and our clinical practice, the following potential confounding factors were included in the analysis: Demographics (age, sex, race), ICU category, (CICU: cardiac intensive care unit; GICU: general intensive care unit; PICU: pediatric intensive care unit; SICU: surgical intensive care unit). Vital Signs (Temperature, Respiratory Rate Heart Rate, Systolic Blood Pressure, Diastolic Blood Pressure, Oxygen saturation), Comorbidities (Sepsis, Pneumonia, Encephalitis, Heart disease, Liver disease, Kidney disease, Malignant cancer). Laboratory Indicators (White blood cells, Neutrophils, Lymphocyte Count, Hemoglobin, Red blood cell distribution width, Platelet, Alanine Aminotransferase (ALT), Aspartate Aminotransferase (AST), Albumin, Bilirubin Total, Lactate Dehydrogenase (LD) Glucose, Urea, Creatinine, Potassium, Sodium, Chloride, C-reactive protein, Procalcitonin, Fibrinogen, Lactate, D dimer, Ferritin, Humanil6, ICU length of stay (LOS), Hospital length of stay (LOS), 28-day all-cause mortality (Death within 28 days of PICU admission), Hospital mortality (Death during the hospital stay, regardless of length of stay), ICU mortality (Death during the ICU stay, regardless of length of stay). Vital signs were recorded at ICU admission, while laboratory data were obtained from the first values within 24 h of admission.
Outcomes
The primary endpoint of this study was the 28-day in-hospital mortality following PICU admission due to any cause.
Statistical analysis
Study participants were categorized into tertiles based on FAR values for descriptive analyses. Categorical variables are expressed as frequencies and percentages, whereas continuous variables were presented as means with standard deviations (SDs) for normally distributed data or medians with interquartile ranges (IQRs) for skewed distributions. Group differences were assessed using independent t-tests, one-way analysis of variance (ANOVA), chi-squared tests, or Fisher’s exact tests as appropriate.
Multivariate Cox regression analysis was conducted by incorporating variables with a significance level of P < 0.05 in the univariate model. Three models were constructed to assess the independent association between FAR and 28-day in-hospital mortality: Model I: Adjusted for age, sex, and ethnicity. Model II: Additionally adjusted for ICU unit, sepsis, pneumonia, encephalitis, heart diseases, liver diseases, kidney diseases and malignant cancer. Model III: Further adjusted for temperature, respiratory rate, oxygen saturation, white blood cells, lymphocyte, hemoglobin, platelet count, alanine aminotransferase, aspartate aminotransferase, bilirubin total, cholesterol total, triglycerides, glucose, potassium, chloride, urea, creatinine, lactate, C-reactive protein, procalcitonin, D dimer, Ferritin, humanil6.
In addition, restricted cubic spline (RCS) regression was performed with 4 knots at the 5th, 35th, 65th, and 95th percentiles of FAR to assess linearity and examine the dose–response curve between FAR and all-cause mortality after adjusting variables in Model III. A two-piecewise logistic regression model with smoothing was used to identify the association threshold between FAR and 28-day mortality, with inflection points determined via likelihood-ratio tests and bootstrap resampling. Kaplan–Meier survival curves were generated to compare survival probabilities across FAR tertiles.
Furthermore, stratified and interaction analyses were applied according to age (< 1, 1 ≤ age<3, or ≥ 3 years), sex (male or female), Pneumonia (yes or no), Encephalitis (yes or no), Heart diseases (yes or no), Malignant cancer (yes or no), White blood cells (< 10^9/L or ≥ 10^9/L), Hemoglobin (< 90 g/L or ≥ 90 g/L), Glucose (< 7 or ≥ 7mmol/L), and Lactate (< 2 or ≥ 2mmol/L). Each stratification adjusted for confounders in Model III, excluding the stratification factor itself.
To avoid bias, variables with > 30% missing values were excluded. For continuous variables with < 5% missing data, missing values were imputed using mean or median values. To assess the robustness of the findings, Sensitivity analyses included patients < 28 days old (n = 727) (Supplementary Table 2) and excluded patients with ICU stays < 48 h (n = 91) (Supplementary Table 3).
Given that the determination of the sample size was exclusively reliant on the provided data, no a priori statistical power estimates were conducted. All the analyses were performed with the statistical software packages R (http://www.R-project.org, The R Foundation) and Free Statistics software versions 1.92. A two-tailed test was performed and p < 0.05 was declared statistically significant.
Results
Population and baseline characteristics
Initially, a total of 13,941 pediatric patients aged 0–18 years were incorporated into the PIC database. Within this cohort, the incidence rates of complications were as follows: sepsis at 1.4% (69/5087), pneumonia at 8.2% (419/5087), encephalitis at 3.3% (170/5087), heart disease at 33.5% (1705/5087), liver disease at 2.4% (120/5087), kidney disease at 1.2% (63/5087), and malignancy at 9.3% (472/5087), among others. Based on the exclusion criteria, 1,610 patients were omitted due to technical errors, multiple admissions, or ICU stays of less than 24 h. Furthermore, an additional 7,244 patients were excluded due to age constraints (less than 28 days) or missing data on fibrinogen or serum albumin. Consequently, the final analysis included 5,087 pediatric patients aged 28 days to 18 years. The comprehensive inclusion and exclusion process is illustrated in Fig. 1.
Fig. 1.
Flow chart of this cohort study population
The baseline demographic and clinical characteristics of the study population, stratified by FAR tertiles, are summarized in Table 1. The median age of participants was 1.4 years (IQR: 0.4–4.3 years), and 44.7% (n = 2,274) were female. The median FAR was 0.06 (IQR 0.03–0.10), 28-day all-cause mortality and PICU all-cause mortality were 4.7% (n = 240) and 5.7% (n = 292), respectively. The median ICU length of stay was 2.9 days (IQR: 1.0–6.9 days), while the median hospital stay was 13.1 days (IQR: 8.0–20.8 days). Patients with elevated FAR exhibited significantly decreased mortality rates at 28 days, along with a notable extension in hospital stay. Stratification based on FAR values resulted in three groups (T1 < 0.04, 0.04 ≤ T2<0.07, T3 ≥ 0.07). Patients in the highest FAR tertile (T3 ≥ 0.07) were predominantly older and female, exhibiting significantly higher levels of systolic and diastolic blood pressure, white blood cell count, urea, creatinine, C-reactive protein, procalcitonin, fibrinogen, D-dimer, and human IL-6 compared to those in the lowest FAR tertile (T1 < 0.04) (all P < 0.05). Conversely, patients in T3 had lower respiratory rate, heart rate, hemoglobin, lymphocyte count, red blood cell distribution width, alanine aminotransferase, aspartate aminotransferase, serum albumin, total bilirubin, potassium, and ferritin levels (all P < 0.05). Additionally, the high FAR group showed a significantly higher prevalence of sepsis, encephalitis, heart disease, kidney disease, and malignant cancer, while pneumonia and liver disease were less prevalent in this group.
Table 1.
Baseline characteristics of the study participants sorted by tertiles of the FAR levels
| fibrinogen to albumin ratio (FAR) | |||||
|---|---|---|---|---|---|
| Variables | Total | T1(<0.04) | T2(0.04–0.07) | T3(>0.07) | P-value |
| Participants | 5087 | 1571 | 1658 | 1858 | |
| Age, (Years) | 1.4 (0.4, 4.3) | 0.7 (0.3, 2.1) | 1.3 (0.4, 4.1) | 2.5 (0.9, 6.0) | < 0.001 |
| Sex, n (%) | 0.016 | ||||
| Female | 2274 (44.7) | 656 (41.8) | 755 (45.5) | 863 (46.4) | |
| Male | 2813 (55.3) | 915 (58.2) | 903 (54.5) | 995 (53.6) | |
| Ethnicity, (%) | 0.777 | ||||
| Others | 41 (0.8) | 11 (0.7) | 13 (0.8) | 17 (0.9) | |
| Han | 5046 (99.2) | 1560 (99.3) | 1645 (99.2) | 1841 (99.1) | |
| ICU unit, n (%) | < 0.001 | ||||
| GICU | 471 (9.3) | 210 (13.4) | 105 (6.3) | 156 (8.4) | |
| PICU | 1171 (23.0) | 444 (28.3) | 314 (18.9) | 413 (22.2) | |
| CICU | 1823 (35.8) | 412 (26.3) | 651 (39.3) | 760 (40.9) | |
| SICU | 1622 (31.9) | 505 (32.1) | 588 (35.5) | 529 (28.5) | |
| Temperature, (℃) | 36.8 ± 0.9 | 36.8 ± 0.8 | 36.8 ± 1.1 | 36.9 ± 0.8 | < 0.001 |
| Respiratory rate, (bpm) | 29.5 ± 10.3 | 31.1 ± 8.7 | 28.9 ± 7.5 | 28.8 ± 13.2 | < 0.001 |
| Heartrate, (bpm) | 128.6 ± 26.2 | 131.5 ± 26.8 | 127.0 ± 26.4 | 127.8 ± 25.3 | < 0.001 |
| Systolic blood pressure (mmHg) | 103.6 ± 29.1 | 100.0 ± 15.4 | 104.4 ± 36.4 | 105.6 ± 29.2 | < 0.001 |
| Diastolic blood pressure (mmHg) | 60.7 ± 14.8 | 58.2 ± 17.3 | 60.3 ± 13.7 | 63.0 ± 13.3 | < 0.001 |
| Oxygen saturation, (%) | 98.5 ± 3.1 | 98.3 ± 3.0 | 98.6 ± 2.9 | 98.4 ± 3.3 | 0.143 |
| Sepsis, n (%) | 69 (1.4) | 24 (1.5) | 10 (0.6) | 35 (1.9) | 0.004 |
| Pneumonia, n (%) | 419 (8.2) | 183 (11.6) | 116 (7) | 120 (6.5) | < 0.001 |
| Encephalitis, n (%) | 170 (3.3) | 47 (3) | 48 (2.9) | 75 (4) | 0.111 |
| Heart. disease, n (%) | 1705 (33.5) | 398 (25.3) | 593 (35.8) | 714 (38.4) | < 0.001 |
| Liver. disease, n (%) | 120 (2.4) | 63 (4) | 41 (2.5) | 16 (0.9) | < 0.001 |
| Kidney. disease, n (%) | 62 (1.2) | 7 (0.4) | 20 (1.2) | 35 (1.9) | < 0.001 |
| Malignant cancer, n (%) | 472 (9.3) | 120 (7.6) | 123 (7.4) | 229 (12.3) | < 0.001 |
| White blood cells, (10^9/L) | 9.2 (6.3, 13.4) | 8.4 (5.7, 12.2) | 8.8 (6.2, 12.5) | 10.6 (7.2, 14.9) | < 0.001 |
| Neutrophils, (10^9/L) | 6.0 (3.5, 9.7) | 4.8 (2.7, 7.9) | 5.7 (3.5, 9.2) | 7.5 (4.6, 11.4) | < 0.001 |
| Lymphocyte, (10^9/L) | 2.2 (1.4, 3.2) | 2.4 (1.5, 3.7) | 2.2 (1.5, 3.1) | 2.0 (1.3, 2.9) | < 0.001 |
| Hemoglobin, (g/L) | 105.5 ± 20.5 | 104.6 ± 21.9 | 107.5 ± 19.7 | 104.5 ± 19.9 | < 0.001 |
| Platelet, (10^9/L) | 247.0 (160.0, 349.0) | 243.5 (144.0, 352.0) | 252.0 (165.0, 350.0) | 243.0 (165.0, 346.0) | 0.077 |
| Red blood cell distribution width, (%) | 14.3 ± 2.3 | 14.6 ± 2.5 | 14.2 ± 2.1 | 14.2 ± 2.3 | < 0.001 |
| Alanine aminotransferase, (U/L) | 20.0 (13.0, 34.0) | 24.0 (15.0, 42.0) | 20.0 (13.0, 33.0) | 18.0 (12.0, 31.0) | < 0.001 |
| Aspartate aminotransferase, (U/L) | 52.0 (31.0, 94.0) | 56.0 (35.0, 109.0) | 50.0 (30.0, 94.0) | 51.0 (30.0, 83.0) | < 0.001 |
| Albumin, (g/L) | 37.3 ± 5.8 | 38.3 ± 5.8 | 38.2 ± 5.1 | 35.8 ± 6.1 | < 0.001 |
| Bilirubin total, (µmol/L) | 10.7 (6.6, 18.1) | 11.6 (6.9, 23.0) | 10.9 (6.7, 18.6) | 9.8 (6.2, 15.0) | < 0.001 |
| Cholesterol total, (mmol/L) | 3.0 ± 1.2 | 3.0 ± 1.4 | 3.1 ± 1.1 | 3.0 ± 1.2 | 0.638 |
| triglycerides, (mg/dl) | 0.8 (0.5, 1.1) | 0.8 (0.6, 1.2) | 0.7 (0.5, 1.0) | 0.7 (0.5, 1.1) | < 0.001 |
| Creatinine, (µmol/L) | 3.3 (2.3, 4.4) | 3.1 (2.1, 4.6) | 3.2 (2.3, 4.1) | 3.5 (2.5, 4.5) | < 0.001 |
| Urea, (mmol/L) | 39.0 (32.0, 48.0) | 39.0 (31.0, 48.0) | 39.0 (32.0, 46.0) | 40.0 (33.0, 49.0) | < 0.001 |
| Glucose, (mmol/L) | 8.4 ± 3.8 | 8.3 ± 4.3 | 8.5 ± 3.8 | 8.3 ± 3.3 | 0.392 |
| Sodium, (mmol/L) | 137.9 ± 5.1 | 137.7 ± 5.0 | 138.1 ± 4.9 | 137.8 ± 5.3 | 0.099 |
| Potassium, (mmol/L) | 3.7 ± 0.7 | 3.8 ± 0.7 | 3.7 ± 0.8 | 3.6 ± 0.7 | < 0.001 |
| Chloride, (mmol/L) | 108.3 ± 5.6 | 108.0 ± 5.8 | 108.5 ± 5.4 | 108.4 ± 5.7 | 0.021 |
| Calcium total, (mmol/L) | 2.3 ± 0.2 | 2.3 ± 0.2 | 2.3 ± 0.2 | 2.2 ± 0.2 | < 0.001 |
| C-reactive protein, (mg/dl) | 20.0 (5.0, 51.9) | 7.0 (4.0, 30.0) | 15.0 (4.0, 44.0) | 38.4 (10.3, 71.0) | < 0.001 |
| Procalcitonin, (ng/ml) | 0.4 (0.1, 1.9) | 0.4 (0.1, 1.9) | 0.4 (0.1, 1.4) | 0.6 (0.2, 2.2) | < 0.001 |
| Fibrinogen, (g/L) | 2.3 ± 1.1 | 1.3 ± 0.4 | 2.1 ± 0.3 | 3.3 ± 0.9 | < 0.001 |
| Lactate, (mmol/L) | 1.8 (1.3, 2.7) | 1.9 (1.3, 3.0) | 1.7 (1.3, 2.5) | 1.8 (1.3, 2.6) | < 0.001 |
| Humanil6, (ng/L) | 28.5 (8.9, 93.6) | 23.7 (6.3, 79.8) | 22.1 (6.6, 67.9) | 43.9 (14.7, 155.0) | < 0.001 |
| Ferritin, (ug/L) | 51.0 (32.0, 96.5) | 66.2 (31.6, 137.8) | 47.3 (31.4, 89.8) | 48.7 (32.8, 80.9) | < 0.001 |
| D-dimer, (ug/L) | 1.3 (0.9, 2.1) | 1.3 (0.8, 2.3) | 1.2 (0.8, 1.9) | 1.5 (1.0, 2.2) | < 0.001 |
| FAR, | 0.06 ± 0.04 | 0.03 ± 0.01 | 0.05 ± 0.00 | 0.10 ± 0.04 | < 0.001 |
| ICU LOS, (day) | 2.9 (1.0, 6.9) | 3.9 (1.1, 9.0) | 2.0 (1.0, 5.9) | 2.8 (1.0, 6.1) | < 0.001 |
| Hospital LOS, (day) | 13.1 (8.0, 20.8) | 13.9 (7.2, 22.0) | 13.0 (7.7, 20.1) | 13.0 (8.9, 20.0) | 0.138 |
| 28 day Mortality, n (%) | 240 (4.7) | 126 (8) | 45 (2.7) | 69 (3.7) | < 0.001 |
| In-ICU mortality, n (%) | 292 (5.7) | 151 (9.6) | 58 (3.5) | 83 (4.5) | < 0.001 |
| In-hospital mortality, n (%) | 293 (5.8) | 151 (9.6) | 59 (3.6) | 83 (4.5) | < 0.001 |
Association between FAR and 28 day in-hospital mortality
A multivariate Cox regression analysis was conducted to assess the relationship between the fibrinogen-to-albumin ratio (FAR) and 28-day in-hospital mortality. Correlation analysis indicated that both albumin and fibrinogen levels were independently associated with mortality (albumin: HR 0.96, 95% CI 0.94–0.98, P < 0.001; fibrinogen: HR 0.68, 95% CI 0.59–0.79, P < 0.001). Notably, the FAR ratio exhibited a more robust association with mortality (HR 0, 95% CI 0-0.11, P = 0.003), implying that the combined effect of these biomarkers offers enhanced prognostic value. In the unadjusted model, FAR was log-transformed (Lg2), revealing a significant association with reduced mortality risk (HR 0.63; 95% CI 0.54–0.73; P < 0.001). Covariates with P < 0.1 from Table S1, along with clinically significant risk factors, were incorporated into the adjusted multivariate models.
Table 2 displays the adjusted analyses utilizing Cox proportional hazards models. The multivariate regression models demonstrated that a one-unit increase in log-transformed FAR was associated with a 17% reduction in 28-day in-hospital all-cause mortality among critically ill patients (HR 0.83; 95% CI 0.7–0.98, P = 0.031) after adjusting for all covariates in Model III, including: age, sex, ethnicity, ICU unit, sepsis, pneumonia, encephalitis, heart diseases, liver diseases, kidney diseases, malignant cancer, temperature, respiratory rate, oxygen saturation, white blood cells, lymphocyte, hemoglobin, platelet count, alanine aminotransferase, aspartate aminotransferase, bilirubin total, cholesterol total, triglycerides, glucose, potassium, chloride, urea, creatinine, lactate, C-reactive protein, procalcitonin, D dimer, Ferritin and humanil6.
Table 2.
Association FAR and the 28-day in-hospital all-cause mortality
| Unadjusted | Model I | Model II | Model III | |||||
|---|---|---|---|---|---|---|---|---|
| Variable | HR (95%CI) | P value | HR (95%CI) | P value | HR (95%CI) | P value | HR (95%CI) | P value |
| FAR Lg2 | 0.63 (0.54 ~ 0.73) | < 0.001 | 0.6 (0.51 ~ 0.7) | < 0.001 | 0.73 (0.62 ~ 0.85) | < 0.001 | 0.83 (0.7 ~ 0.98) | 0.031 |
| FAR, Quartiles | ||||||||
| Group1(Q1<0.03) | 1(Ref) | 1(Ref) | 1(Ref) | 1(Ref) | ||||
| Group2(0.03 ≤ Q2<0.05) | 0.55 (0.38 ~ 0.79) | 0.001 | 0.54 (0.37 ~ 0.78) | 0.001 | 0.68 (0.47 ~ 1) | 0.047 | 0.7 (0.46 ~ 1.05) | 0.085 |
| Group3(0.05 ≤ Q3<0.06) | 0.34 (0.22 ~ 0.51) | < 0.001 | 0.33 (0.21 ~ 0.5) | < 0.001 | 0.5 (0.32 ~ 0.77) | 0.002 | 0.6 (0.38 ~ 0.94) | 0.025 |
| Group4(0.06 ≤ Q4<0.08) | 0.27 (0.18 ~ 0.39) | < 0.001 | 0.26 (0.17 ~ 0.38) | < 0.001 | 0.44 (0.29 ~ 0.66) | < 0.001 | 0.63 (0.41 ~ 0.96) | 0.031 |
| Group5(Q5 ≥ 0.08) | 0.37 (0.26 ~ 0.53) | < 0.001 | 0.33 (0.23 ~ 0.47) | < 0.001 | 0.46 (0.32 ~ 0.67) | < 0.001 | 0.66 (0.44 ~ 1) | 0.005 |
| P for trend | < 0.001 | < 0.001 | < 0.001 | 0.014 | ||||
Model I: adjusted by age +sex +ethnicity;
Model II: adjusted by Model I +ICU unit +sepsis +pneumonia +encephalitis +heart disease +liver disease + kidney disease +malignant cancer;
Model III: adjusted by Model II +temperature +respiratory rate +oxygen saturation +white blood cells +hemoglobin + lymphocyte +platelet + alanine aminotransferase+ aspartate aminotransferase+ bilirubin total +cholesterol total +triglycerides +glucose +potassium + chloride +urea +bun +creatinine + lactate+ C-reactive protein +procalcitonin +D dimer +Ferritin +hum
FAR fibrinogen to albumin ratio, Q quartiles, O odds ratio, CI confidence interval, Ref reference
For further sensitivity analysis, FAR was categorized into quartiles, with Q1 (< 0.03) serving as the reference group. The adjusted Hazard ratios (HR 95% CI) for FAR and 28 day in-hospital all-cause mortality in Q2 (0.03 ~ 0.05), Q3 (0.05 ~ 0.06), Q4 (0.06 ~ 0.08) and Q5 (≥ 0.08) and were 0.7 (95% CI: 0.46 ~ 1.05, P = 0.085), 0.6 (95% CI: 0.38 ~ 0.94, P = 0.025), 0.63 (95% CI: 0.41 ~ 0.96, P = 0.031)and 0.66 (95% CI: 0.44 ~ 1, P = 0.005) in the adjusted Model III (P for trend <0.014), respectively. Patients in higher FAR quartiles had significantly lower in-hospital mortality compared to those in the lowest quartiles (Q1<0.03).
Restricted cubic spline analysis
Restricted cubic spline (RCS) regression revealed a nonlinear, L-shaped association between FAR and 28-day all-cause mortality (P for nonlinearity = 0.003) after adjusting for confounding variables (Fig. 2). In the threshold analysis, the HR of 28-day all-cause mortality was 0.076 (95% CI: 0.025–0.234, P < 0.001) in participants with FAR < 0.648. This means that the risk of 28-day in-hospital mortality is reduced by 24% with every Lg- unit increase in FAR. However, There was no association between FAR and in-hospital mortality when the FAR was ≥ 0.648 (Table 3) (HR: 1.126, 95% CI: 0.669–1.876, P = 0.656).
Fig. 2.
Restricted cubic spline plot for FAR and 28-day in-hospital all-cause mortality. The restricted cubic spline depicting the hazard ratio of fibrinogen to albumin ratio associated with all-cause mortality among pediatric patients. The x-axis represents the fibrinogen-to-albumin ratio, while the y-axis depicts the hazard ratio of all-cause mortality. Pink and blue areas represent the 95% confidence intervals for the hazard ratio of all-cause mortality associated with the FAR. The model was adjusted for age, gender, ethnicity, ICU unit, sepsis, pneumonia, encephalitis, heart disease, liver disease, kidney disease, malignant cancer, temperature, respiratory, oxygen saturation, white blood cells, hemoglobin, lymphocyte, platelet, alanine aminotransferase, aminotransferase, bilirubin total, cholesterol total, triglycerides, potassium, chloride, creatinine, bun, c-reactive protein, procalcitonin, lactate. Solid and dashed lines represent the predicted value and 95% confidence intervals. Only 99.5% of the data is shown
Table 3.
Threshold effect analysis for the relationship between FAR and 28-day in-hospital all-cause mortality
| FAR | HR | 95%CI | P-value |
|---|---|---|---|
| Turning point (%) | 0.648 | 0.591–0.705 | |
| FAR<0.648 | 0.076 | 0.025–0.234 | < 0.001 |
| FAR ≥ 0.648 | 1.126 | 0.669–1.895 | 0.656 |
| Likelihood Ratio test | 0.001 |
They were adjusted for age, gender, ethnicity, ICU unit, sepsis, pneumonia, encephalitis, heart disease, liver disease, kidney disease, malignant cancer, temperature, respiratory, oxygen saturation, white blood cells, hemoglobin, lymphocyte, platelet, alanine aminotransferase, aminotransferase, bilirubin total, cholesterol total, triglycerides, potassium, chloride, creatinine, bun, c-reactive protein, procalcitonin, lactate, humanil6, D-dimer, ferritin
FAR fibrinogen to albumin ratio, OR odds ratio, CI confidence interval, Ref reference
Kaplan–Meier survival analysis
To evaluate cumulative survival period at different FAR groups, Kaplan–Meier survival curves were generated based on FAR tertiles. The curves demonstrated significantly higher 28-day survival rates among patients with higher FAR levels compared to those with lower FAR levels (P < 0.0001; Fig. 3).
Fig. 3.
Kaplan–Meier curve of 28-day all-cause mortality for patients. The curved line and shaded areas depict the estimated values and their corresponding 95% confidence intervals. Only patients with a hospital length of stay ≤ 28 days are displayed
Subgroup analyses
Subgroup and interaction analyses were conducted to explore potential modifiers of the association between FAR and 28-day all-cause mortality, adjusting for Model III covariates. Subgroup stratification included variables such as age, sex, pneumonia, encephalitis, heart disease, malignant cancer, white blood cell count, hemoglobin, glucose, and lactate. There was an interaction between malignant cancer and FAR on 28-day mortality (P for interaction < 0.001). However, no significant interactions were identified in other subgroups (P for interaction > 0.05). Detailed results are presented in Fig. 4.
Fig. 4.
Forest plot for the relationship between LAR and 28-day all-cause mortality. Dots indicate hazard ratios (HRs), with horizontal lines indicating 95%CIs. Adjustment factors included age, gender, ethnicity, ICU unit, sepsis, pneumonia, encephalitis, heart disease, liver disease, kidney disease, malignant cancer, temperature, respiratory, oxygen saturation, white blood cells, hemoglobin, lymphocyte, platelet, alanine aminotransferase, aminotransferase, bilirubin total, cholesterol total, triglycerides, potassium, chloride, creatinine, bun, c-reactive protein, procalcitonin, lactate
Sensitivity analysis
Sensitivity analyses confirmed the robustness of the study findings. When participants aged < 28 days (n = 727) were included, the association between FAR and in-hospital mortality remained significant (HR: 0.78; 95% CI: 0.67–0.9; P < 0.001; Supplementary Table S2). Similarly, after excluding patients with ICU stays < 48 h (n = 91), the association persisted in the remaining cohort (n = 4,996) (HR: 0.83; 95% CI: 0.69–0.99; P = 0.041; Supplementary Table S3). The results of the sensitivity analysis remained stable.
Discussion
In this 8-year retrospective cohort study of critically ill pediatric patients in China, elevated fibrinogen-to-albumin ratio (FAR) was independently associated with a 17% reduction in 28-day in-hospital all-cause mortality after multivariable adjustment. Although albumin and fibrinogen levels individually correlated with mortality, FAR more effectively captured their combined prognostic influence, demonstrating superior predictive utility. Furthermore, we observed a nonlinear, L-shaped dose-response relationship between FAR and mortality (P for nonlinearity < 0.05), with mortality risk plateauing beyond a FAR threshold of 0.648. This suggests diminishing protective effects above this inflection point. Our findings support FAR as a promising prognostic biomarker for mortality risk stratification in critically ill pediatric populations. The identified threshold (FAR ≈ 0.648) warrants investigation into whether modulating fibrinogen or albumin pathways influences outcomes, though causal inferences cannot be drawn from this observational design.
The growing evidence demonstrated that FAR has shown promising results in predicting adult prognosis for various adult diseases. For instance, Wang et al. reported elevated FAR correlating with increased stroke recurrence risk and poorer functional outcomes [14]. while Xu et al. identified an association between high FAR levels and in-hospital mortality among ICU patients with heart failure [25]. To date, Several cardiovascular studies further demonstrate elevated FAR independently correlating with increased all-cause mortality [17, 26]. Although prior research typically excluded cancer patients, our study specifically included pediatric cancer cases, carefully adjusting for this variable. Crucially, our findings remained consistent, revealing a significant L-shaped relationship between FAR and mortality with a turning point at approximately 0.648. Differences in study populations, disease progression, and treatment strategies between adults and children may partially account for observed variations. Critically ill pediatric patients frequently exhibit distinct comorbidities—such as pneumonia, encephalitis, sepsis, and malignancies—with differing disease durations and complications compared to adults. Furthermore, limitations in prior studies, including the neglect of admission organ function status, highlight the novelty of our approach, which incorporated diverse laboratory indicators for a more comprehensive assessment of critically ill children. These findings have significant implications for current mortality risk mitigation strategies.
Evidence for FAR’s prognostic value in pediatric populations is emerging. Zu et al. identified elevated FAR as a potential indicator of disease severity in pediatric respiratory syncytial virus infections [20]. Similarly, Dong et al. demonstrated that increased FAR independently correlated with the presence and severity of neonatal sepsis [21]. Our study, however, presents key distinctions: Broader Scope: It features a larger sample size, longer temporal span (8 years), and wider age range (29 days to 18 years). Primary Endpoint: We specifically investigated the association between FAR and all-cause mortality across diverse critical illnesses. Comprehensive Adjustment: Recognizing potential confounding, we rigorously adjusted for multiple variables—including age, gender, race, vital signs, comorbidities, and laboratory indicators—to clarify the FAR-mortality relationship. Our analysis revealed an L-shaped association between FAR and in-hospital all-cause mortality risk. Sensitivity analyses incorporating neonates confirmed the robustness of these findings.
Our findings suggest that the L-shaped association observed may be driven by underlying inflammatory and nutritional mechanisms. Fibrinogen is a key glycoprotein synthesized in the liver, whose levels rise during chronic inflammation, contributing to increased blood viscosity, altered coagulation, and endothelial dysfunction [27]. For example, Wang et al. found that fibrinogen was associated with neuroinflammation and impacted long-term outcomes in adult patients [14]. Previous investigations have established that fibrinogen can enhance the expression of pro-inflammatory cytokines, such as interleukin-1 and tumor necrosis factor-α. This cascade of events promotes vascular inflammation and endothelial dysfunction, ultimately lead to poor prognosis [28]。albumin is a negative acute-phase reactant produced in the liver, whose serum concentration is associated with inflammatory and hemostatic processes. Fundamental research has demonstrated that physiological concentrations of serum albumin can inhibit the expression of vascular cell adhesion molecule-1, enhance the clearance of oxygen-free radicals, and ultimately mitigate the inflammatory response. These findings suggest that albumin possesses protective anti-inflammatory properties [29]. Finally, based on previous studies, we speculate that extremely low FAR values likely indicate severe inflammation and malnutrition, while higher FAR levels within the compensatory range might reflect protective mechanisms. Beyond the threshold, however, the pro-inflammatory effects of fibrinogen may outweigh the protective effects of albumin, leading to worsened prognosis. These findings underscore the importance of maintaining an appropriate FAR balance in critically ill pediatric patients. Further basic research on these two molecular mechanisms will help to identify therapeutic targets and improve the prognosis of critically ill children.
Clinically, this study underscores several key implications. The primary advantage of FAR lies in its simplicity and accessibility, requiring minimal routine data, whereas complex scores like PRISM/PIM encompass a broader spectrum of physiological derangements. Monitoring FAR could facilitate early identification of high-risk pediatric patients. Furthermore, therapeutic strategies aimed at modulating fibrinogen and albumin pathways may improve outcomes; however, the current absence of pharmacological agents specifically targeting fibrinogen reduction presents a significant challenge, necessitating research into novel targeted therapies. Routine screening for serum albumin—acknowledging its protective role—should also be prioritized. Ultimately, a deeper understanding of the interplay between inflammatory status and nutritional reserve is essential for optimizing care and improving prognosis in critically ill children.
Despite FAR’s promising implications as a biomarker, this study has several limitations. First, its retrospective design introduces potential selection bias and precludes causal inference. Whilst multivariate regression, stratification, and sensitivity analyses were employed to enhance robustness, prospective studies would provide stronger evidence. Second, dynamic changes in FAR following treatment initiation were not assessed; these temporal variations could influence mortality risk. Future research should incorporate longitudinal FAR measurements to better elucidate its predictive significance. Third, as a single-center study involving 5,087 critically ill pediatric patients from China, the generalizability of our findings to other populations, healthcare systems, and resource settings may be limited. Although the PIC database provides valuable pediatric ICU insights—complementing the primarily adult-focused MIMIC-III database—external validation in diverse, multi-center cohorts, including those from high-resource settings, remains essential to confirm FAR’s broad prognostic applicability in pediatric critical care. Four, Despite PRISM and PIM-3 are clinically established, their implementation requires multiple parameters (PIM-3 employs 10). Constraints within the PIC database precluded direct extraction of these scores; nevertheless, we maximally adjusted for clinically related indicators to ensure study robustness. Five, the lack of acid-base data (e.g., pH, bicarbonate) limits our ability to explore the potential mediating role of acid-base disturbances in the association between FAR and mortality. Consequently, multi-center randomized controlled trials are warranted to validate FAR’s role in predicting mortality across heterogeneous pediatric cohorts.
Conclusion
In conclusion, our study demonstrates a significant L-shaped relationship between FAR and 28-day in-hospital all-cause mortality, suggesting its potential utility as a prognostic marker for mortality in critically ill pediatric patients.
Supplementary Information
Acknowledgements
We would like to express our gratitude to the PIC database provided by the Children’s Hospital, Zhejiang University School of Medicine.
Abbreviations
- FAR
Fibrinogen to albumin ratio
- T
Tertile; Others* ethnic groups include the Hui ethnic, baiyue ethnic, miao ethnic, tujia ethnic, yi ethnic, other ethnic
- CICU
Cardiac intensive care unit
- GICU
General intensive care unit
- PICU
Pediatric intensive care unit
- SICU
Surgical intensive care unit
- ICU Los
The length of stay for the patient for the given ICU stay
Authors’ contributions
W H. Responsible for selecting topics, designing, Writing-original draft and prepared figures. J L. contributed to conception, review and edit articles.R J, X Y. contributed to conception and design of the study, and analysis and interpretation of data.X Z, R C. contributed to conception and design of the study, and drafting the article.All authors have read and approved the final manuscript.
Funding
This research was supported by the Medical Science Research Project of Hebei Province (20251533) and Liangduo Jiang Famous Traditional Chinese Medicine Inheritance Studio.
Data availability
More information regarding the data is available on the PIC website (http://pic.nbscn.org/).
Declarations
Ethics approval and consent to participate
The present study was approved by the Institutional Review Board/Ethical Committee of the Children’s Hospital, Zhejiang University School of Medicine (Hangzhou, China 2019_IRB_052). All study procedures were in accordance with the ethical standards of the Declaration of Helsinki. Given the retrospective nature of the study and the utilization of anonymized patient data, the requirement for obtaining individual patient consent was waived. The Cangzhou Central Hospital institutional review board determined the study to be exempt because it used publicly available deidentified data, and informed consent was waived.
Consent for publication
The submitted manuscript has been read and approved by all authors.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Weichao He and Jie Liu are contributed equally to this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
More information regarding the data is available on the PIC website (http://pic.nbscn.org/).