Ischaemic stroke is one of the leading cause of mortality and morbidity across the globe, resulting from occlusion to blood supply to the brain leading to profound neurological deficits. ¹ Although there have been advances in the initial management and rehabilitation of stroke patients, outcomes still vary. This underlies the importance of having reliable markers for anticipating prognosis that may enable the choice of appropriate therapy and an improvement in patient care. ² The triglyceride-glucose (TyG) index was developed a new indicator which is calculated from fasting triglyceride and glucose levels; it could serve as a surrogate measure for insulin resistance in cardiovascular diseases. ^{3, 4}

Insulin resistance is an essential determinant of atherosclerosis development and cardiovascular events both of which are major risk factors for ischemic stroke. ⁵ For its simplicity, relative inexpensive and its strong association with insulin resistance, TyG index has generated considerable interest making it practical tool in clinical settings. ⁶ Numerous studies have shown that TyG index has excellent predictive performance for cardiovascular diseases such as coronary artery disease and hypertension. However, the extent to which it is linked to the outcomes of ischemic stroke has not been well investigated. ^{7, 8}

Examining the correlation among the TyG index and ischemic stroke outcomes might provide significant knowledge about the processes that determine stroke prognosis and help identify people at a high risk. ⁹ This study examined the TyG index and clinical outcomes in ischemic stroke patients, including death and functional status, in a tertiary care hospital with resource limited settings. Results of the study might have important consequences for clinical practice, potentially resulting in the integration of the TyG index into standard evaluation methods for patients with ischemic stroke. This would facilitate the implementation of more precise treatment measures, thereby enhancing patient outcomes. Moreover, this study has the potential to add to the increasing amount of information that supports the significance of insulin resistance in the development of stroke. This, in turn, might lead to more research being conducted on specific therapies for those at high risk of stroke.

The research divided 200 ischemic stroke patients between two groups. Group A contained 112 patients and group B 88. Both group A and group B included 51.8% and 51.1% males, respectively (p = 0.92). Group B showed higher rates of diabetes (73.9% vs. 31.3%, p < 0.001), hypertension (72.7% vs. 53.6%, p < 0.01), and dyslipidemia (59.1% vs. 44.6%, p = 0.05) than Group A. Table 1 shows that the groups smoked similarly (p = 0.47).

Table 2 shows demographics. The average age of participants in Group A was 65.4 ± 10.2 years, slightly lower than Group B (67.1 ± 11.5 years), but not statistically significant (p = 0.253). Age distribution across categories was similar across groups. Both groups had comparable average BMI (26.4 ± 3.7 vs. 27.1 ± 4.1, p = 0.195). Most patients lived in cities, and there was no difference in education, and career. Socioeconomic status was similar among both groups.

Table 3 reveals no significant differences in duration of the disease (7.2 ± 4.8 years for Group A vs. 6.9 ± 5.1 years for Group B, p = 0.621), and drug consumption. Similar proportions of patients used anti-hypertensives, statins, anti-diabetics, anti-platelets, and anticoagulants, showing similar comorbidity treatment.

Table 4 covers primary and secondary outcomes. Group B had a greater 30-day mortality rate (18.2% vs. 8.0%, p = 0.03) than Group A. A higher median (mRS) score at 3 months (3.5 vs. 2.5, p = 0.02) indicated poorer functional status in Group B. Patients in Group B had longer hospital stay (10.5 ± 3.1days vs. 8.2 ± 2.4days, p = 0.01) and higher rate of major adverse cardiovascular events (MACE) (15% vs. 7%, p = 0.05).

Table 5 shows significant main outcome (30-day mortality) predictors using logistic regression. The adjusted odds ratio (OR) for 30-day mortality, 3-month mRS score, and stroke recurrence within one year was greater in Group B (OR = 2.5, 95% CI: 1.1-5.6, p = 0.03).

Table 6 shows 3-month mRS score distribution. No symptoms or little disability were more common in Group A (mRS 0-1: 30.4% vs. 20.5%, p = 0.12) and substantial disability (mRS 2-3: 50% vs. 36.4%, p = 0.05). The percentage of seriously disabled patients in Group B was substantially larger (mRS 4-5: 34.1% vs. 13.4%, p = 0.002). The groups had comparable death rates (mRS 6) (p = 0.49).

The study thoroughly compared socio-demographics and clinical parameters, in ischemic stroke patients with different TyG index values. The gender distribution in our study was evenly distributed throughout the groups with the proportion of male patients slightly higher than female, which aligns with prior study examining the correlation between metabolic indicators and stroke outcomes. ¹⁰ However, our analysis revealed notable disparities in the occurrence of diabetes, hypertension, and dyslipidemia among the groups. These findings are consistent with research indicating that these additional health conditions are common among individuals who have had a stroke and can have an impact on the results or consequences. ¹¹ A research by Wang L and colleagues, revealed that diabetes patients with elevated TyG indices have a greater propensity to develop comorbidities such as hypertension and dyslipidemia which aligns with our research. ¹²

The 30-day mortality rate in Group A (8%) considerably decreases than Group B (18%) (p = 0.03). This finding indicates that the intervention, and feature being studied in Group A might also have a beneficial effect in lowering short-term mortality compared to Group B. Several studies have reported findings similar to our research. A study by Mosisa et al. observed a similar mortality rate reduction in patients receiving similar interventions to Group A. ¹³ Similarly, a study by Moraes et al, demonstrated a statistically sizable lower in 30-day mortality with a similar remedy approach. ¹⁴

Conversely, research by Massaud and colleagues and Guo J et al, suggested lower mortality rates in patients with TyG more than 8.8 in comparison to Group B in our research. ^{15, 16} Variations in affected participants demographics, treatment protocols, and other factors could have an effect on mortality consequences different than observed in our research.

The median mRS score at three months was 2.5 in Group A and 3.5 in Group B, with a statistically great distinction (p = 0.02). This suggests higher functional consequences at 3 months among patients in Group A in comparison to Group B. Similar findings were mentioned by means of Chye et al, and De Silva et al., who found better mRS rankings at three months of their intervention groups as compared to controls. ^{17, 18} These studies support our finding that the intervention, and feature in Group A may additionally make contributions positively to functional recovery.

Studies by Altuntas et al. and Ernst et al, specified no huge difference in mRS scores between intervention and control groups, differing from our effects. ^{19, 20} These discrepancies highlight the complexity in accomplishing constant results throughout studies, probably due to variations in research design, patient selection and treatment modalities.

The extended duration of hospitalization for patients in Group B (10.5 ± 3.1 days vs. 8.2 ± 2.4 days, p = 0.01) and the increased occurrence of Major Adverse Cardiovascular Events (MACE) (15% vs. 7%, p = 0.05) emphasize the added healthcare burden linked to elevated TyG indices. Research conducted by Li X et al, supports the claim that metabolic syndrome components, such as high levels of triglycerides and glucose, have a substantial effect on the length of hospital stay and the occurrence of cardiovascular problems in stroke patients. ²¹

The logistic regression analysis indicated that an elevated TyG index is a standalone predictor of unfavourable outcomes. The results show that the TyG index has a significant predictive value, as evidenced by the adjusted odds ratios for 30-day mortality (OR = 2.5, 95%CI: 1.1-5.6, p = 0.03) and mRS score at 3 months (OR = 1.8, 95%CI: 1.2-3.0, p = 0.02). This discovery aligns with a research by Gao et al, which found comparable odds ratios for negative outcomes in patients with high TyG indices. ²²

Group B (TyG index >8.8) had a larger proportion of severe disability (mRS 4-5: 34.1% vs. 13.4%, p = 0.002) after 3 months, indicating that the higher TyG index significantly affected functional recovery. Prior research, such as the study conducted by Liu D and colleagues, has emphasized the connection between higher levels of triglycerides and glucose and unfavorable neurological outcomes, which supports our own findings. ²³

The TyG index may predict outcomes in diabetic ischemic stroke patients, according to one research. ²⁴ Regular triglyceride and glucose monitoring may help identify high-risk individuals who may benefit from more aggressive care to reduce unfavorable outcomes. Lifestyle adjustments and tailored medication may enhance prognosis in this patient group by lowering the TyG index.

This research establishes a significant association among the TyG score and unfavorable outcomes in individuals with ischemic stroke. An elevated TyG index is associated with greater mortality and worse functional status indicating its potential as a helpful prognostic indicator. These results emphasize the significance of targeting insulin resistance in the treatment of ischemic stroke to enhance patient outcomes. Additional investigation is necessary to validate these findings and to create specific therapies aimed at decreasing insulin resistance in this particular group of patients.

The IRB of Khyber Teaching Hospital, Peshawar accepted the research protocol. Approval was granted vide no: 47, dated: 26 ^th July 2022. Research was retrospective, thus informed consent was waived off. The institute granted the permission to share the data publicly.