Introduction
Sepsis remains one of the greatest challenges in contemporary critical care, accounting for a substantial proportion of global deaths and intensive care unit admissions, with persistently high mortality despite advances in antimicrobial therapy and organ support. According to the Sepsis3 definition, sepsis is a lifethreatening organ dysfunction arising from a dysregulated host response to infection, underscoring the central role of immune derangement in determining disease severity and outcomes.[1] Early recognition and timely initiation of appropriate therapy during the initial golden hours are critical for survival, as even a 1hour delay in antibiotic administration has been associated with significantly increased mortality.[2]
Clinical scoring systems such as SIRS, MEWS, NEWS, SOFA, and qSOFA have been widely adopted to facilitate early identification and risk stratification, yet they often lack optimal sensitivity or specificity and sometimes require laboratory parameters that are not immediately available, limiting their utility in resourceconstrained settings.[3] The qSOFA, although simple and rapid at the bedside, shows variable prognostic performance and does not directly reflect the underlying inflammatory or immune response. In this context, there is growing interest in biomarkers that can support early diagnosis, risk stratification, and outcome prediction in sepsis. Commonly used markers such as Creactive protein (CRP) and procalcitonin (PCT) are helpful but limited by cost, availability, and turnaround time, particularly in low and middleincome countries where many patients are managed in peripheral or rural centers.[2-4]
Absolute eosinophil count (AEC) has recently emerged as a promising, lowcost biomarker in sepsis. Eosinophils are routinely reported as part of the complete blood count, which is widely available even in basic laboratory setups, so absolute eosinophil count does not entail additional reagent costs or specialized equipment.[5] Eosinopenia, or a reduction in circulating eosinophils, is a common feature of acute infections and systemic inflammatory states, thought to result from cortisolmediated redistribution, bonemarrow suppression, and apoptosis, making it a potential marker of systemic stress and severe infection. Historically recognized as a sign of acute infection, eosinopenia has recently been associated with sepsis and adverse outcomes such as increased mortality, prolonged ICU stay, and higher organ dysfunction, even in populations with high background eosinophilia due to parasitic infestations.[5-6]
In North India, where sepsis burden is high and advanced biomarker testing is often unavailable, an inexpensive and rapidly measurable marker such as absolute eosinophil count could significantly improve early risk stratification and clinical decisionmaking.[7] Existing data suggest that persistently low AEC on ICU admission and over time is linked with worse outcomes, whereas recovery of eosinophil counts may reflect clinical improvement, but populationspecific evidence from North India remains limited. Therefore, the present study compared absolute eosinophil count levels with clinical outcomes in septic patients admitted to the ICU, with specific objectives to estimate AEC at admission, on day 3, and on day 7, and to evaluate its correlation with mortality and duration of hospital/ICU stay, thereby assessing its potential as a simple, costeffective prognostic tool in a resourcelimited setting.
Materials and Methods
Study Design and Setting
This hospital-based prospective study was conducted in the Department of Medicine at Tertiary care Hospital from July 2024 to December 2025 (18 months). Institutional Research and Ethics Committee approval was obtained prior to initiation (SGRD/IEC/2024-372).
Participants
Adult patients (>18 years) admitted to the inpatient or emergency department at SGRDIMSAR with suspected infection and clinical features suggestive of sepsis were screened using the quick Sequential Organ Failure Assessment (qSOFA) score: altered mental status (Glasgow Coma Scale <15), systolic blood pressure ≤100 mmHg, or respiratory rate ≥22 breaths/min. Patients with qSOFA ≥2 were triaged to the intensive care unit (cases); those with lower scores were managed in general wards (non-cases for comparative purposes).
Inclusion and Exclusion Criteria
Cases with sepsis or septic shock diagnosis; age >18 years were included in the study. Whereas tropical infections (leptospirosis, scrub typhus, malaria, kala-azar, enteric fever); hematological malignancies; known acute/chronic inflammatory or autoimmune diseases; long-term steroid therapy; acute myocardial infarction were excluded.
Procedures
Eligible patients (or legally authorized representatives) provided written informed consent in the vernacular language. A structured proforma captured detailed history, physical examination, and laboratory data. Patients were followed until hospital discharge or death. Sepsis management adhered to Sepsis-3 guidelines, including qSOFA screening, fluid resuscitation, microbiological cultures, empirical antibiotics, and lactate monitoring.
Blood Sample Collection and Analysis
Venous blood (2 mL) was collected in EDTA vials at admission (Day 1), Day 3, and Day 7. Samples were analyzed in the SGRDIMSAR Department of Pathology. Peripheral smears were prepared, stained with Leishman (1 min) then Giemsa (20 min), and examined at 40× magnification. Eosinophils were enumerated per 100 white blood cells for percentage; absolute eosinophil count (AEC) was calculated as:
Routine hematology (total and differential leukocyte counts) used automated analyzers.
Statistical Analysis
Data were managed and analysed in Microsoft Excel. Continuous variables were summarized as mean ± SD; categorical as frequencies/percentages. Group comparisons used Student's t-test (continuous) or χ²/Fisher's exact test (categorical). Statistical significance was set at p<0.05 (two-sided).
Results
In a cohort of 120 ICU patients presented in Table 1 (61.7% male, 38.3% female; age distribution: 4.2% 18–30, 5.8% 31–40, 15.8% 41–50, 27.5% 51–60, 29.2% 61–70, 17.5% >70), prevalent comorbidities were diabetes mellitus (48.3%), hypertension (37.5%), chronic kidney disease (10%), hypothyroidism (3.3%), cerebrovascular accident and COPD (2.5% each), and others (25.8%); 93.3% presented with qSOFA score 2 and 6.7% with score 3. ICU stays averaged 7.2 ± 3.8 days (median 7, range 1–29; 14.2% 1–3 days, 36.7% 4–7, 30% 8–10, 19.1% >10), while hospital stays averaged 9.1 ± 4.2 days (median 8, range 1–21; 17.5% 1–5, 43.3% 6–10, 25.8% 11–15, 13.4% >15). Outcomes included 72.5% survival and 27.5% mortality; Day 7 PaO₂/FiO₂ ratios indicated good oxygenation in most (>400: 75.8%; 300–400: 10.8%; 200–300: 1.7%; 100–200: 6.7%; <100: 5%).
| Variable | Category / Finding | N | % |
| Age group (years) | 18–30 | 5 | 4.2 |
| 31–40 | 7 | 5.8 | |
| 41–50 | 19 | 15.8 | |
| 51–60 | 33 | 27.5 | |
| 61–70 | 35 | 29.2 | |
| >70 | 21 | 17.5 | |
| Total | 120 | 100.0 | |
| Gender | Male | 74 | 61.7 |
| Female | 46 | 38.3 | |
| Total | 120 | 100.0 | |
| Comorbidity | Diabetes mellitus | 58 | 48.3 |
| Hypertension | 45 | 37.5 | |
| Chronic kidney disease | 12 | 10.0 | |
| Cerebrovascular accident | 3 | 2.5 | |
| COPD | 3 | 2.5 | |
| Hypothyroidism | 4 | 3.3 | |
| Others | 31 | 25.8 | |
| qSOFA at admission | Score = 2 | 112 | 93.3 |
| Score = 3 | 8 | 6.7 | |
| Total | 120 | 100.0 | |
| ICU stay (days) | 1–3 | 17 | 14.2 |
| 4–7 | 44 | 36.7 | |
| 8–10 | 36 | 30.0 | |
| >10 | 23 | 19.1 | |
| Mean ± SD | 7.2 ± 3.8 days | ||
| Hospital stay (days) | 1–5 | 21 | 17.5 |
| 6–10 | 52 | 43.3 | |
| 11–15 | 31 | 25.8 | |
| >15 | 16 | 13.4 | |
| Mean ± SD | 9.1 ± 4.2 days | ||
| Outcome | Survived | 87 | 72.5 |
| Expired | 33 | 27.5 | |
| PaO₂/FiO₂ ratio-Day 7 | <100 | 6 | 5.0 |
| 100–200 | 8 | 6.7 | |
| 200–300 | 2 | 1.7 | |
| 300–400 | 13 | 10.8 | |
| >400 | 91 | 75.8 |
The table 2 strikingly reveals the prognostic power of Absolute Eosinophil Count (AEC) in 120 critically ill patients tracked over ICU days 0 (n=120), 3 (n=101), and 7 (n=79), where AEC distributions shifted from a mean of 204.6 ± 118.4 cells/mm³ (most in 150–300 range) to 254.8 ± 186.2 by day 7 (rising >300 cases to 27.8%). Even more compelling, survivors consistently outshone fatalities with higher mean AEC—day 0: 218.4 ± 112.6 vs 168.2 ± 124.8 (p=0.006); day 3: 242.8 ± 138.4 vs 128.6 ± 108.2 (p=0.00004); day 7: 276.4 ± 182.5 vs 108.4 ± 94.6 (p=0.0012)—and far greater proportions exceeding 150 cells/mm³ (day 0: 67.8% vs 39.4%; day 3: 77.8% vs 30%; day 7: 83.3% vs 28.6%), underscoring AEC as a dynamic, statistically robust marker of favorable outcomes.
| AEC (cells/mm³) | Day 0 (n=120) | Day 3 (n=101) | Day 7 (n=79) | ||
| <50 | 8 | 5 | 4 | ||
| 50–100 | 18 | 12 | 8 | ||
| 100–150 | 22 | 20 | 14 | ||
| 150–200 | 28 | 24 | 15 | ||
| 200–300 | 26 | 22 | 16 | ||
| >300 | 18 | 18 | 22 | ||
| Total | 120 | 101 | 79 | ||
| Mean ± SD | 204.6 ± 118.4 | 218.5 ± 142.7 | 254.8 ± 186.2 | ||
| AEC and outcome (n=120/ 101/79) | |||||
| Time Point | Group | (Survived/ Expired) n | Mean AEC (cells/mm³) | Proportion with AEC >150 | pvalue (survived vs expired) |
| Day 0 | Survived | 87 | 218.4 ± 112.6 | 67.8% (59/87) | 0.006 |
| Expired | 33 | 168.2 ± 124.8 | 39.4% (13/33) | ||
| Day 3 | Survived | 81 | 242.8 ± 138.4 | 77.8% (63/81) | 0.00004 |
| Expired | 20 | 128.6 ± 108.2 | 30.0% (6/20) | ||
| Day 7 | Survived | 72 | 276.4 ± 182.5 | 83.3% (60/72) | 0.0012 |
| Expired | 7 | 108.4 ± 94.6 | 28.6% (2/7) |
(*Proportion with AEC ≤150 is complementary; “Trend” line: Survivors show rising AEC; nonsurvivors show decreasing AEC.)
The 3 table demonstrates Absolute Eosinophil Count (AEC) as a vital prognostic tool across ICU days 0, 3, and 7 in critically ill patients, where Sequential Organ Failure Assessment (SOFA) scores improved from a mean 8.01±3.23 to 4.81±5.85, mirroring AEC's strengthening inverse correlations: moderate-to-strong negative with SOFA (r=-0.42 to -0.64, all p<0.001), moderate with ICU stay (r=-0.186 to -0.428, p≤0.001 from day 3), weak-to-moderate with hospital stay (r=-0.142 to -0.386, significant by day 3), and moderate-to-strong with C-reactive protein (r=-0.521 to -0.621, all p<0.001). ROC analysis further cements AEC's predictive prowess for mortality (n=120), boasting rising AUCs from 0.672 (95% CI 0.562–0.782; optimal ≤152 cells/mm³, 60.6% sensitivity/67.8% specificity; p=0.006) on day 0, to 0.784 (≤148; 66.7%/74.7%; p<0.001) on day 3, and a robust 0.846 (≤142; 75.8%/83.9%; p=0.0012) by day 7-highlighting its escalating accuracy in forecasting survival.
| Parameter/Time Point | Day 0 | Day 3 | Day 7 | ||
| SOFA score (mean± SD) | 8.01±3.23 | 5.78±4.14 | 4.81±5.85 | ||
| AEC vs SOFA | r=−0.42; p<0.001 (moderate negative) | r=−0.58; p<0.001 (moderate negative) | r=−0.64; p<0.001 (strong negative) | ||
| AEC vs ICU stay (days) | r=−0.186; p=0.042 (weak negative) | r=−0.312; p=0.001 (weak negative) | r=−0.428; p<0.001 (moderate negative) | ||
| AEC vs hospital stay (days) | r=−0.142; p=0.122 (NS) | r=−0.268; p=0.003 (weak negative) | r=−0.386; p<0.001 (weak–moderate negative) | ||
| AEC vs CRP | r=−0.521; p<0.001 (moderate negative) | r=−0.571; p<0.001 (moderate negative) | r=−0.621; p<0.001 (strong negative) | ||
| ROC analysis of AEC for predicting mortality (n=120) | |||||
| Time Point | AUC (95% CI) | Optimal cutoff (cells/mm³) | Sensitivity (%) | Specificity (%) | pvalue |
| Day 0 | 0.672 (0.562–0.782) | ≤152 | 60.6 | 67.8 | 0.006 |
| Day 3 | 0.784 (0.672–0.896) | ≤148 | 66.7 | 74.7 | <0.001 |
| Day 7 | 0.846 (0.712–0.980) | ≤142 | 75.8 | 83.9 | 0.0012 |
The table 4 represent key microbiological and biomarker insights in 120 ICU patients, revealing sparse culture positivity (overall <3% total, with urine leading at 11.7%, followed by other sites like wound/sputum/CSF at 5.8% and blood at just 1.7%), alongside strikingly elevated CRP levels dominated by severe inflammation (65.8% in 100–500 mg/dL, 27.5% 10–100, 4.2% 3–10, and 2.5% >500). It also spotlights dynamic trends: overall SOFA scores improved from day 0 to 7, while AEC patterns diverged sharply by outcome—rising progressively in survivors but declining in non-survivors—reinforcing eosinophils as a telling marker of recovery versus deterioration in this high-risk cohort.
| Variable | Category / Finding | n | % |
| Culture type – positive | Blood culture | 2 | 1.7 |
| Urine culture | 14 | 11.7 | |
| Other cultures (wound, sputum, CSF, etc.) | 7 | 5.8 | |
| Total culturepositive | <3 | 0 | 0.0 |
| CRP level (mg/dl) | 3–10 | 5 | 4.2 |
| 10–100 | 33 | 27.5 | |
| 100–500 | 79 | 65.8 | |
| >500 | 3 | 2.5 | |
| SOFA score trend | SOFA Day 0 → Day 7 (overall improvement) | – | – |
| AEC trend by group | Survivors: increasing AEC over time | – | – |
| Nonsurvivors: decreasing AEC over time | – | – |
Discussion
This prospective observational study in 120 septic ICU patients demonstrates that absolute eosinophil count (AEC) is a simple, inexpensive, and powerful prognostic biomarker that tracks disease severity, organ dysfunction, and survival. The cohort was predominantly elderly (mean age 59.9 years, peak 61–70 years) and malepredominant (61.7%), with high comorbidity burden diabetes in 48.3%, hypertension in 37.5%, and chronic kidney disease in 10.0% consistent with sepsis epidemiology in older, chronically ill populations. At admission, qSOFA was 2 in 93.3% of patients, SOFA averaged 8.01±3.23 (moderatetosevere organ dysfunction), and inflammatory markers such as CRP and procalcitonin were markedly elevated, confirming a hyperinflammatory state (Table 1). Against this backdrop, serial AEC measurements revealed a consistent inverse relationship with SOFA across days 0, 3, and 7, with correlation strengthening from moderate (r = −0.42) to strong (r = −0.64) over time, aligning with reports by Sharma et al.[8] and Shravani et al.[9] who also observed that lower eosinophil counts correspond to worse organ dysfunction and that AEC can be integrated into routine sepsis monitoring in resourcelimited settings.
AEC at admission averaged 204.6±118.4 cells/mm³, with eosinopenia (<50 cells/mm³ Table 2) in 6.7%; patients with AEC ≤150 cells/mm³ had significantly higher mortality (60.6%) than those with AEC >150 cells/mm³, and ROC analysis showed moderate predictive accuracy (AUC 0.672, optimal cutoff ≤152 cells/mm³). This pattern deepened with serial monitoring: by Day 3 (n=101), AEC rose to 218.5±142.7, and the AUC improved to 0.784 (cutoff ≤148 cells/mm³), while by Day 7 (n=79) mean AEC climbed to 254.8±186.2, with survivors increasingly clustered above 150–300 cells/mm³ and AUC reaching 0.846 (cutoff ≤142 cells/mm³ Table 3), closely mirroring findings from Merino et al.[10]; Sharma et al.[8] report that persistently low or declining AEC predicts higher mortality and requirement for organ support. Survivors displayed a clear upward AEC trajectory from Day 0 to Day 7, whereas nonsurvivors showed a progressive decline, echoing systematic reviews that describe eosinophil recovery in survivors and persistent eosinopenia in the deceased as a hallmark dynamic across sepsis, severe infection, and even COVID19.[11]
AEC also correlated significantly with ICU and hospital stay, with a weak negative correlation on Day 0 (r = −0.186, Table 3) that evolved into a moderate negative correlation by Day 7 (r = −0.428), while correlations with hospital stay became significant only on Days 3 and 7; this temporal strengthening supports the view that serial AEC trends better reflect clinical stability and readiness for stepdown care than baseline values alone. Similar to Waseem et al.[12] observation that low eosinophil counts predict longer hospitalization, the present data suggest that AEC can guide resource utilization decisions in the ICU. Microbiological culture positivity was low overall (highest in urine: 11.7%, blood: 1.7%, Table 4), consistent with the influence of preadmission antibiotics and sampling limitations, yet the clinical and laboratory profile still fulfilled Sepsis3 criteria; this aligns with Sisto et al.[13]; Kübler-Kiełb et al.[14] showed that eosinopenia retains high specificity for organ dysfunction even in culturenegative sepsis, reinforcing AEC’s role as a practical diagnostic adjunct alongside CRP and procalcitonin, as noted by Tian et al.[15] who emphasized that while eosinopenia may be less sensitive than classic biomarkers, it is highly specific and best used in combination.
Finally, the progressive improvement in PaO₂/FiO₂ from Day 0 to Day 7, with the proportion of patients above 400 rising from 17.5% to 75.8%, further corroborates the parallel between AEC recovery and systemic clinical improvement. Taken together, these findings supported by data from Sharma et al.[8]; Merino et al.[10]; Magrini et al.[16] and recent metaanalyses confirm that AEC is not only a costeffective surrogate for immune status and organ dysfunction but also a robust, timedependent predictor of mortality, ICU and hospital length of stay, and need for organ support, making it a valuable adjunct to routine sepsis management in general ICU practice.
Limitations
However, the findings of this study should be interpreted in light of certain limitations. Being a single-center study with a relatively limited sample size, the generalizability of the results may be restricted. Additionally, variations in underlying comorbidities, source of infection, antimicrobial therapy, and concurrent medications such as corticosteroids could have influenced eosinophil counts and clinical outcomes. The study also did not evaluate long-term follow-up outcomes or compare AEC with newer sepsis biomarkers such as procalcitonin or interleukin-based markers.
Conclusion
This study highlights the potential role of Absolute Eosinophil Count (AEC) as a simple, inexpensive, and readily available prognostic biomarker in patients with sepsis. Serial monitoring of AEC demonstrated a significant association with disease severity and clinical outcomes, with persistent eosinopenia correlating with higher SOFA scores, progressive organ dysfunction, and increased mortality. In contrast, recovery of eosinophil counts during the course of treatment was associated with clinical improvement and favorable outcomes. The observed correlation between AEC trends and established inflammatory markers such as C-reactive protein further supports its utility as an adjunctive bedside marker for monitoring septic patients in intensive care settings.
Future recommendations
Future multicentric studies with larger patient populations are warranted to validate the prognostic accuracy of serial AEC monitoring across diverse clinical settings. Further research comparing AEC with established and emerging biomarkers may help define its precise role in sepsis prognostication and treatment monitoring. Integration of AEC into standardized sepsis assessment protocols may provide a cost-effective approach for early risk stratification and optimization of critical care resources, particularly in resource-limited healthcare systems.
Declarations
Ethical Approval
The study was approved by the Institutional Ethics Committee of Sri Guru Ram Das Institute of Medical Sciences and Research, Amritsar (SGRD/IEC/2024-372).
Informed Consent
Written informed consent was obtained from all participants prior to enrolment.
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare no conflict of interest.
Data Availability
The datasets generated and analysed during the current study are available from the corresponding author upon reasonable request.
Author Contributions
All authors contributed equally to the conception and design of the study, data acquisition, analysis and interpretation of data, drafting and critical revision of the manuscript, and final approval of the version to be published. All authors have read and approved the final manuscript and agree to be accountable for all aspects of the work.Top of Form
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