Lymphocyte count trajectories are associated with the prognosis of sepsis patients

Abstract

Sepsis causes multiorgan dysfunction from immune dysregulation, resulting in high ICU admissions and mortality [1]. Lymphocytes are essential in the immune response during sepsis, with lymphopenia linked to increased vulnerability to secondary infections, higher sepsis severity, and mortality [2]. However, prior studies primarily analyzed lymphocyte counts at fixed time points, overlooking their dynamic nature and association with sepsis prognosis. Furthermore, unlike other complex immune biomarkers such as HLA-DR, lymphocyte count is easily accessible, making it a valuable marker for continuous monitoring of immune status. This study aims to identify heterogeneous lymphocyte count trajectories in sepsis patients by leveraging the group-based trajectory modeling (GBTM) [3], which accommodates unbalanced panels and missing values.

This is a retrospective study based on data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) v3.1 database (certification number: 64590357). We extracted data on 24,792 adult sepsis patients admitted to the ICU, diagnosed using Sepsis-3.0 criteria (suspected infection and a SOFA score increase of ≥ 2). After excluding patients with conditions such as long-term steroid use, transplant status, malignancy, rheumatic disease, or hematologic disease (detailed information provided in Table S1), 12,078 cases were retained. Among these, 3152 sepsis patients who had at least two lymphocyte count measurements within 7 days of ICU admission were included, with a hospital mortality rate of 24.6%.

We applied GBTM to identify lymphocyte count trajectories, selecting a three-class model (Fig. 1), based on the Akaike and Bayesian information criterion, and clinical rationality (Table S2). Trajectory 1, the “Rapid-slow decrease” class, included 525 (16.7%) patients and was characterized by a rapid decrease in lymphocyte counts in the first 3 days, followed by a slower decline. Trajectory 2, the “Stable” class, included 1453 (46.1%) patients with relatively stable lymphocyte counts. Trajectory 3, the “Rapid-slow increase” class, included 1174 (37.2%) patients who showed a rapid increase in lymphocyte counts in the first 3 days, followed by a slower rise at relatively low levels. Baseline characteristics varied significantly across these trajectories (Table 1). Patients in Trajectory 3 had the longest hospital stays, higher APSIII, OASIS, and MELD scores, and a greater prevalence of comorbidities, with the highest 28-day mortality (22.9%). In contrast, patients in Trajectory 1 had the shortest hospital stays but higher SIRS score and the highest 7-day mortality (12%).

Fig. 1

Lymphocyte trajectories over the first 7 days of ICU admission

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Table 1 Baseline characteristics comparison among the three lymphocyte trajectories

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Cox regression analysis and Kaplan–Meier survival curves were used to examine the relationship between lymphocyte trajectories and mortality. Compared to Trajectory 2, Trajectory 3 was associated with increased 28-day mortality (HR 1.61, 95% CI 1.34–1.92, p < 0.001), while Trajectory 1 was linked to higher 7-day mortality (HR 1.58, 95% CI 1.16–2.15, p = 0.004). After adjusting for confounders, Trajectory 3 remained an independent risk factor of both 7-day and 28-day mortality, while Trajectory 1 was no longer significant (Table 2). Survival curves illustrated differences in mortality among trajectories over 28 days (Fig. 2). Consistent with the Cox regression results, Trajectory 1 had the highest mortality within the first 7 days, after which its mortality curve overlapped with that of Trajectory 2, while Trajectory 3 had the highest mortality beyond the 7-day timeframe. Additional subgroup analysis stratified by comorbidities demonstrated no significant interaction between lymphocyte count trajectories and any comorbidities (Figure S1 and Figure S2), indicating that comorbidities did not affect the association between trajectories and patient outcomes.

Table 2 Univariate and multivariate Cox regression analysis of the three lymphocyte trajectories

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Fig. 2

Kaplan–Meier survival curves of the three trajectories

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The distinct lymphocyte trajectories might imply different immune profiles and outcomes in sepsis. Trajectory 1, with initially high lymphocyte counts, was associated with elevated SIRS scores and 7-day mortality, possibly reflecting a pro-inflammatory sepsis phenotype. In contrast, Trajectory 3, with relatively low lymphocyte counts, correlated with higher 28-day mortality, suggesting an immunosuppressive profile. This pattern aligns with prior research indicating that early death in sepsis is driven by intense inflammation, while late death is more commonly associated with immunosuppression [4]. These findings highlight the potential role of tailored therapies for different sepsis subtypes. Specifically, patients with a pro-inflammatory profile (Trajectory 1) may benefit from anti-inflammatory agents like corticosteroids or ulinastatin [5]. For patients with an immunosuppressive profile (Trajectory 3), immune-stimulating therapies such as thymosin α1, which restores lymphocyte counts, or IL-7, which promotes lymphocyte proliferation and prevents apoptosis, might be advantageous [5]. As for patients in the stable profile (Trajectory 2), representing the majority of cases with the lowest mortality, standard, guideline-based supportive care may be sufficient.

In conclusion, three distinct lymphocyte trajectories were identified in sepsis patients using GBTM. Trajectory 3 was a strong predictor of 7-day and 28-day mortality, while Trajectory 1 was associated with early death. These findings might support the development of more personalized management strategies for sepsis. Future prospective studies could focus on investigating the efficacy of targeted immune therapy on different trajectories to better understand potential interactions between immune therapy and sepsis subgroups.

No datasets were generated or analysed during the current study.

ICU:

Intensive care unit

HLA-DR:

Human leukocyte antigen-DR isotype

GBTM:

Group-based trajectory modeling

MIMIC:

Medical information mart for intensive care

SOFA:

Sequential organ failure assessment

APSIII:

Acute physiology score III

OASIS:

Oxford acute severity of illness score

SIRS:

Systemic inflammatory response syndrome

MELD:

Model for end-stage liver disease

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This research was funded by the Natural Science Foundation of Guangdong Province (2024A1515012909) and the Guangzhou Municipal Science and Technology Project (2024A03J0643).

Authors and Affiliations

1. Guangzhou University of Chinese Medicine, Guangzhou, China

   Jiale Yang

2. Department of Intensive Care Unit, General Hospital of Southern Theatre Command of PLA, Guangzhou, China

   Jiale Yang, Binli Ma & Huasheng Tong

3. Guangdong Pharmaceutical University, Guangzhou, China

   Binli Ma

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Contributions

JY contributed to conceptualization, manuscript writing and editing, statistical analysis, and visualization. BM contributed to data collection and statistical analysis. HT contributed to manuscript reviewing and funding acquisition. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Huasheng Tong.

Competing interests

The authors declare no competing interests.

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Not applicable. The MIMIC database is publicly available and has been anonymized. No need for further approval from an ethical committee.

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Yang, J., Ma, B. & Tong, H. Lymphocyte count trajectories are associated with the prognosis of sepsis patients. Crit Care 28, 399 (2024). https://doi.org/10.1186/s13054-024-05186-6

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• Received: 15 November 2024

• Accepted: 22 November 2024

• Published: 02 December 2024

• DOI: https://doi.org/10.1186/s13054-024-05186-6

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