Paraquat (1,1′-dimethyl-4,4′-bipyridinium dichloride) is a highly effective, fast-acting, and non-selective herbicide widely used in agriculture, especially in developing countries like India where it remains easily accessible in local markets [1]. Despite its agricultural utility, paraquat is notorious for its extreme human toxicity, particularly following oral ingestion. Even a small quantity—such as a teaspoon of concentrated formulation—can lead to rapid multi-organ failure and death, with reported case fatality rates as high as 70% [2,3].The toxicity of paraquat is primarily driven by a vicious cycle of redox cycling within cells, leading to massive production of reactive oxygen species (ROS). This results in oxidative damage to cellular lipids, proteins, and DNA, triggering widespread inflammation and apoptosis [4,5]. The lungs are the primary target organ due to active accumulation via polyamine transporters, leading to progressive alveolitis, pulmonary oedema, and ultimately irreversible fibrosis and acute respiratory distress syndrome (ARDS) [6,7]. Other organs, especially the kidneys and liver, are also severely affected, contributing to multi-organ dysfunction syndrome (MODS) [8].A major challenge in managing acute paraquat poisoning is the lack of a specific antidote. Treatment remains largely supportive and includes measures like decontamination, immunosuppressive therapy (e.g., pulse methylprednisolone and cyclophosphamide), and organ support [9,10]. Despite these interventions, mortality remains distressingly high. Therefore, early and accurate prediction of which patients will develop life-threatening complications like ARDS or MODS is crucial. It can help clinicians in risk stratification, guiding the intensity of therapy, allocating ICU resources efficiently, and providing realistic prognostic information to families. Traditional prognostic methods, such as estimating the ingested dose or using the urine sodium dithionite test, are often unreliable as patients may not recall the exact amount, and qualitative tests lack precision [11]. In recent years, scoring systems like the Sequential Organ Failure Assessment (SOFA) and Acute Kidney Injury Network (AKIN) criteria have been validated in various critical illnesses to quantify organ dysfunction and predict outcomes [12,13]. Similarly, simple and inexpensive haematological indices, particularly the Neutrophil-to-Lymphocyte Ratio (NLR), have emerged as robust markers of systemic inflammation and stress, showing prognostic value in sepsis, cardiovascular diseases, and other toxicological emergencies [14,15]. However, there is limited prospective data from the Indian setting on the combined utility of these easily accessible tools—SOFA, AKIN, and NLR—in predicting the clinical course of acute paraquat poisoning. This study was therefore designed to evaluate whether haematological indices (total leukocyte count, neutrophil count, lymphocyte count, platelet count, NLR) and established organ failure scores (SOFA and AKIN) measured early in the hospital course can serve as reliable predictors for the development of ARDS, need for advanced organ support (mechanical ventilation, haemodialysis), and overall mortality in patients with acute paraquat poisoning.

Study Design and Setting This was a prospective, observational, single-center study conducted in the intensive care unit (ICU) of a tertiary care teaching hospital in South India. The study was approved by the Institutional Ethics Committee (IEC No: IEC/313/2023), and written informed consent was obtained from all participants or their legally authorized representatives. Data were collected over a period of 17 months, from August 2023 to December 2024. Study Participants We included 50 consecutive adult patients admitted to the ICU with a confirmed diagnosis of acute paraquat poisoning. Diagnosis was based on a clear history of ingestion and a positive urine sodium dithionite test. Inclusion Criteria: • All patients aged 18 years or older with acute paraquat poisoning, regardless of sex or route of exposure (though all cases in this cohort were oral ingestions). • Patients whose caregivers provided written informed consent. Exclusion Criteria: • Poisoning with other pesticides or mixed ingestions. • Pre-existing chronic liver disease, chronic kidney disease (CKD), known pulmonary disorders (e.g., COPD, interstitial lung disease), or malignancy. • Patients with incomplete data or those who left against medical advice within 24 hours of admission. Variables and Data Collection For each participant, data were collected using a structured proforma at three time points: at admission (0 hours), at 24 hours, and at 48 hours. Data included: • Demographic details: Age, sex. • Exposure details: Amount and type of paraquat consumed, time of ingestion, time of arrival to hospital. • Clinical parameters: Glasgow Coma Scale (GCS), mean arterial pressure (MAP). • Laboratory investigations: • Complete blood count (CBC): Total leukocyte count, neutrophil count, lymphocyte count, platelet count, hemoglobin. • Neutrophil-to-lymphocyte ratio (NLR), calculated as absolute neutrophil count divided by absolute lymphocyte count. • Renal function tests: Serum urea, serum creatinine. • Liver function tests: Serum bilirubin. • Inflammatory marker: C-reactive protein (CRP). • Arterial blood gas (ABG) analysis: pH, partial pressure of arterial oxygen (PaO₂), partial pressure of arterial carbon dioxide (PaCO₂), bicarbonate (HCO₃⁻), and PaO₂/FiO₂ ratio. Scoring systems: • Sequential Organ Failure Assessment (SOFA) score, calculated using respiratory (PaO₂/FiO₂), coagulation (platelets), liver (bilirubin), cardiovascular (MAP/vasopressors), neurological (GCS), and renal (creatinine/urine output) parameters. • Acute Kidney Injury Network (AKIN) staging, based on serum creatinine rise and urine output criteria. Treatment and outcomes: • Use of pulse immunosuppressive therapy (methylprednisolone, cyclophosphamide), need for mechanical ventilation, need for hemodialysis, development of complications (ARDS, AKI, MODS), duration of hospital stays, and outcome (survival or death). Statistical Methods Data were entered into Microsoft Excel and analysed using IBM SPSS Statistics for Windows, Version 25.0. Descriptive statistics were presented as mean ± standard deviation for continuous variables and as frequency and percentage for categorical variables. Comparisons between groups (e.g., ARDS vs. non-ARDS, survivors vs. non-survivors) were performed using the independent samples t-test for normally distributed continuous variables and the chi-square test or Fisher’s exact test for categorical variables. Repeated measures were analysed using ANOVA where applicable. Correlation between the amount of paraquat ingested and the SOFA score was assessed using Pearson’s correlation coefficient. A p-value of less than 0.05 was considered statistically significant. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Patient confidentiality was strictly maintained. The study protocol, including the consent form in English and local languages (Telugu and Hindi), was reviewed and approved by the institutional ethics committee prior to initiation.

A total of 50 patients with acute paraquat poisoning were included in this prospective observational study. The demographic and clinical characteristics of the study population are summarized (Table 1).Serial hematological and biochemical investigations were performed at admission, 24 hours, and 48 hours(Table 2).The Sequential Organ Failure Assessment (SOFA) and Acute Kidney Injury Network (AKIN) scores were calculated serially. Higher scores correlated strongly with poor outcomes(Table 3&4).The most common complication was acute respiratory distress syndrome (ARDS), followed by acute kidney injury (AKI) and multi-organ dysfunction syndrome (MODS)(Table 5).Patients who developed ARDS had significantly worse laboratory parameters and organ failure scores compared to those who did not(Table 6). A significant positive correlation was found between the amount of paraquat ingested and the SOFA score at admission (r = 0.68, p < 0.001) and at 24 hours (r = 0.72, p < 0.001). Patients ingesting >50 mL had substantially higher SOFA scores and mortality.The overall mortality rate in this cohort was 96% (48 out of 50 patients). The two survivors had ingested less than 20 mL and presented early (<6 hours) with low initial SOFA scores (≤4). Table 1: Demographic and Exposure Characteristics of the Study Population (n=50) Characteristic Category Number (n) Percentage (%) Age Group <20 years 11 22.0 20–50 years 34 68.0 >50 years 5 10.0 Sex Male 27 54.0 Female 23 46.0 Amount Ingested <20 mL 6 12.0 20–50 mL 31 62.0 51–150 mL 7 14.0 >150 mL 6 12.0 Time to Hospital Presentation <6 hours 4 8.0 6–24 hours 38 76.0 >24 hours 8 16.0 Table 2: Trends in Haematological and Biochemical Parameters Over Time Parameter At Admission (Mean ± SD) At 24 Hours (Mean ± SD) At 48 Hours (Mean ± SD) p-value Total Leukocyte Count (cells/µL) 11842 ± 5640 17473 ± 28566 11898 ± 6063 0.002* Neutrophil Count (cells/µL) 4759 ± 940 4907 ± 1265 4683 ± 1024 0.051 Lymphocyte Count (cells/µL) 1390 ± 523 1386 ± 581 1582 ± 719 0.074 NLR 3.96 ± 1.67 4.18 ± 1.87 3.79 ± 2.05 0.041* Platelet Count (×10³/µL) 111.8 ± 38.3 102.8 ± 51.2 112.7 ± 50.8 0.058 Hemoglobin (g/dL) 9.16 ± 0.67 9.00 ± 0.51 8.42 ± 2.10 <0.001* Serum Urea (mg/dL) 81.6 ± 41.0 93.5 ± 40.9 86.4 ± 51.2 0.003* Serum Creatinine (mg/dL) 3.21 ± 2.19 4.22 ± 2.60 4.05 ± 2.97 <0.001* Serum Bilirubin (mg/dL) 3.49 ± 2.46 4.25 ± 2.71 3.79 ± 2.92 <0.001* CRP (mg/dL) 5.97 ± 2.42 7.57 ± 2.96 7.32 ± 3.38 <0.001* Table 3: Distribution of SOFA Scores Over Time and Association with Mortality SOFA Score Category At Admission (n=50) At 24 Hours (n=45) At 48 Hours (n=32) Low (0–6) 16 (32.0%) 14 (31.1%) 13 (40.6%) Moderate (7–12) 30 (60.0%) 2 (4.4%) 9 (28.1%) High (13–24) 4 (8.0%) 29 (64.4%) 10 (31.3%) Table 4: Requirement of Organ Support in Relation to SOFA Score Intervention SOFA Score (Mean ± SD) p-value Mechanical Ventilation (Yes) At Admission: 11.38 ± 1.60 0.009* Mechanical Ventilation (No) At Admission: 7.69 ± 3.73 Hemodialysis (Yes) At 48 Hours: 12.30 ± 1.57 0.003* Hemodialysis (No) At 48 Hours: 7.36 ± 4.72 Table 5: Spectrum of Complications and Mortality Timeline (n=48 Non-survivors) Complication / Outcome Number Percentage (%) ARDS 19 39.5 Acute Kidney Injury (AKI) 13 27.0 MODS 12 25.0 Metabolic Acidosis 4 8.3 Time to Death <24 hours 5 10.4 48 hours 13 27.0 3–7 days 14 29.1 8–14 days 10 20.8 >15 days 6 12.5 Table 6: Comparison of Key Parameters at 48 Hours: ARDS vs. Non-ARDS Patients Parameter Non-ARDS (n=13) Mean ± SD ARDS (n=19) Mean ± SD p-value SOFA Score 3.10 ± 0.50 17.20 ± 5.60 <0.001 AKIN Stage 1.30 ± 0.26 2.90 ± 0.34 <0.001 Leukocyte Count (cells/µL) 6534 ± 3678 16000 ± 3901 <0.001 NLR 1.74 ± 0.29 5.35 ± 1.24 <0.001 Platelet Count (×10³/µL) 161.7 ± 14.4 75.2 ± 32.8 <0.001 PaO₂/FiO₂ Ratio 398.2 ± 21.5 142.6 ± 45.3 <0.001

This prospective observational study of 50 patients with acute paraquat poisoning reinforces the grim reality of this toxicological emergency, demonstrating an overall mortality rate of 96%. The findings highlight the critical prognostic utility of early, simple, and readily available tools—the SOFA score, AKIN staging, and Neutrophil-to-Lymphocyte Ratio (NLR)—in predicting the development of life-threatening complications like ARDS and death.Our cohort predominantly consisted of young adults (20–50 years, 68%), aligning with the economically active population most exposed to agricultural chemicals, a pattern consistently reported in Indian studies [16, 17]. However, contrary to many occupational exposure studies that report a male predominance, our study noted a nearly equal sex distribution (54% male, 46% female). This shift may reflect an increasing trend of paraquat ingestion for suicidal intent among young females in rural settings, a serious public health concern highlighted in sociological studies from agrarian regions in India [17]. The majority (62%) ingested 20–50 mL of paraquat, a volume consistently associated with moderate to severe poisoning and high mortality, as documented in prior toxicokinetic studies [3, 8].Our results demonstrate that systemic inflammation plays a central role in paraquat toxicity. We observed significant leukocytosis and a peak in the Neutrophil-to-Lymphocyte Ratio (NLR) at 24 hours post-admission. Patients who progressed to ARDS had a significantly higher mean NLR (5.35 ± 1.24) at 48 hours compared to non-ARDS patients (1.74 ± 0.29). This aligns with the findings of Zahorec [14] and more recent studies in critical care, which identify NLR as a robust, cost-effective marker of systemic inflammatory response and oxidative stress [14, 15]. The elevated NLR in fatal cases underscores the imbalance between the pro-inflammatory neutrophilic response and the regulatory lymphocytic activity, mirroring the cytokine storm and immune dysregulation described in paraquat’s pathogenesis [4, 5]. Thrombocytopenia emerged as another significant hematological predictor, with ARDS patients showing markedly lower platelet counts. This likely reflects platelet consumption due to widespread endothelial injury and microthrombi formation, a phenomenon noted in other studies of paraquat-induced lung injury [18]. The Sequential Organ Failure Assessment (SOFA) score proved to be a powerful dynamic predictor in our study. A rapid progression to high SOFA scores (≥13) within 24 hours was a hallmark of patients who subsequently required mechanical ventilation, hemodialysis, or succumbed to the illness. Our findings are strongly supported by the work of Weng et al. [12], who first validated the SOFA score as a mortality predictor in paraquat intoxication, demonstrating its superiority over traditional parameters like ingested dose estimation. Similarly, the Acute Kidney Injury Network (AKIN) criteria effectively staged renal dysfunction, with progression to AKIN Stage 3 by 48 hours being a poor prognostic sign. This correlation between early renal injury and overall mortality has been well-established, as impaired renal clearance leads to prolonged systemic exposure to paraquat, creating a vicious cycle of toxicity [8, 13]. The significant correlation we found between the volume ingested and the SOFA score further strengthens the argument for using objective scoring systems over often-unreliable patient history for risk stratification. Consistent with global literature, ARDS was the most common fatal complication in our cohort, affecting 38% of patients and contributing significantly to mortality that peaked between 3–7 days [6, 7]. The pathophysiological link between paraquat’s redox cycling in pneumocytes and the ensuing fibroproliferative phase of ARDS is well-documented [4, 5]. Our data adds clinical correlation: ARDS patients had profoundly worse oxygenation (PaO₂/FiO₂ ratio of 142.6 ± 45.3) and higher markers of inflammation and organ failure. These findings are congruent with studies from Indian ICUs, such as those by Agarwal et al. [7], which also reported refractory hypoxemia as the primary cause of death. Furthermore, anatomical studies on tissue damage, such as those conducted by Shaik Hussain Saheb et al. from India on the histopathological changes in paraquat-induced lung injury, detail the alveolar epithelial necrosis, hyaline membrane formation, and early fibroblastic proliferation that underpin this clinical presentation [19]. This histological evidence provides a structural basis for the severe gas exchange impairment and poor compliance observed in our ARDS patients.The mortality rate in our study (96%) is at the higher end of the spectrum reported in literature, which varies from 60% to over 90% depending on the ingested dose and treatment protocols [3, 9]. This likely reflects a selection bias towards more severe cases presenting to a tertiary care referral centre. While our findings on the prognostic value of SOFA and NLR are consistent with studies from East Asia [12, 15], data from the Indian subcontinent remain limited. Our study reinforces these findings in a distinct socio-agricultural context. The efficacy of immunosuppressive pulse therapy (methylprednisolone and cyclophosphamide) remains debatable. Although it was administered per protocol, the overwhelming mortality suggests that once a critical threshold of oxidative and inflammatory injury is crossed, therapeutic interventions may be futile, emphasizing the paramount importance of prevention and very early intervention [9, 10]. Limitations of our study include its single-centre design and relatively small sample size, which may limit generalizability. The lack of quantitative serum paraquat levels, a constraint in many resource-limited settings, was mitigated using the urine dithionite test and clinical scoring. Future multicenter studies with larger cohorts and serial biomarker measurements (e.g., KL-6, surfactant protein-D) could further refine prognostic models.

In conclusion, this study affirms that acute paraquat poisoning continues to carry a devastatingly high mortality in our setting. The SOFA score, AKIN staging, and NLR are simple, inexpensive, and effective early warning tools that can reliably identify patients at highest risk of developing ARDS and dying. Their use at admission and within the first 24 hours can facilitate timely triage, guide the intensity of monitoring and treatment, and improve communication with families regarding prognosis. Ultimately, given the limited efficacy of advanced treatments, the most effective strategy remains primary prevention through stringent regulation of paraquat availability, public education, and promoting safer agricultural practices.

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