Research Article
Haematologic and Biochemical Parameters to Differentiate Severe Malaria from Uncomplicated Malaria in a Ghanaian Population in Sub-Saharan Africa
Issue:
Volume 11, Issue 1, February 2026
Pages:
1-8
Received:
3 November 2025
Accepted:
18 November 2025
Published:
16 January 2026
DOI:
10.11648/j.ajlm.20261101.11
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Abstract: Malaria is classified as either uncomplicated (UM) or severe (SM), but the mechanism underlying the progression from uncomplicated to severe is still unclear. This study aimed to assess haematologic and biochemical parameters as potential prognostic biomarkers for differentiating SM from UM in a Ghanaian population. A descriptive cross-sectional study was conducted to sample 166 participants, comprising 42 healthy controls, 78 uncomplicated malaria cases, and 46 severe malaria cases. Blood samples were analysed for full blood count, liver function test, renal function test, and serum angiopoietins. Statistical analyses were carried out using GraphPad Prism 9 software. Median and interquartile ranges, Mann-Whitney U test, and Kruskal-Wallis analysis were done to compare groups. The haemoglobin and platelet counts of SM patients were significantly lower than those of the UM group (p < 0.05). However, the White Blood Cell (WBC) counts of severe malaria patients (7.4, IQR: 5.4 - 10.6) were significantly higher than the uncomplicated malaria population (5.7, IQR: 5.0 - 6.5) (p < 0.001). Serum levels of bilirubin (total and direct), alanine transaminase (ALT), aspartate transaminase (AST), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), and total proteins in severe malaria were significantly higher than uncomplicated malaria group (p < 0.001). These findings indicate that haemoglobin, platelet, creatinine, urea, AST, ALT, GGT and bilirubin levels may serve as biomarkers for distinguishing severe from uncomplicated malaria.
Abstract: Malaria is classified as either uncomplicated (UM) or severe (SM), but the mechanism underlying the progression from uncomplicated to severe is still unclear. This study aimed to assess haematologic and biochemical parameters as potential prognostic biomarkers for differentiating SM from UM in a Ghanaian population. A descriptive cross-sectional st...
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Review Article
Triglyceride Glucose Index Is More Robust Surrogate Biomarker for Predicting Type 2 Diabetes Mellitus Than HOMA-IR in Population Attending Aulaqi Specialized Medical Laboratories, Yemen
Issue:
Volume 11, Issue 1, February 2026
Pages:
9-15
Received:
7 December 2025
Accepted:
20 December 2025
Published:
16 January 2026
DOI:
10.11648/j.ajlm.20261101.12
Downloads:
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Abstract: Insulin resistance (IR) is an independent risk factor for type 2 diabetes mellitus (T2DM). Because only triglyceride levels and fasting blood glucose are required to measure the triglyceride-glucose (TyG) index, and the insulin test, which is used in the homeostatic model assessment of insulin resistance (HOMA-IR) calculation, is costly and unavailable in the majority of laboratories in the cities of developing countries. Thus, the goal of our study was compared the predictive power of HOMA-IR and the TyG index for assessing IR, as well as the incidence and prevalence of T2DM. Methods: From January 2025 to July 2025, a cross-sectional study was carried out at Aulaqi Specialized Med. Lab. Several risk factors were evaluated among 215 participants, 110 of whom had T2DM and 105 of whom without diabetes. The following analysis data were collected; high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglycerides (TG), fasting blood glucose (FBG), HBA1c, C-peptide, TyG index and HOMA-IR. The results of the statistical test were considered significant if the P value>0.05. Results: The T2DM participants had higher mean TyG index (4.87 ± 0.32 vs. 4.66 ± 0.31, P<0.001) and HOMA-IR (3.07 ± 1.99 vs. 2.32 ± 1.07, P=0.001) values than non-diabetes. In the receiver operating characteristic (ROC) analysis, the TyG index demonstrated a better performance [area under the curve (AUC) 0.832), with 76.7% sensitivity and 73.8% specificity] in predicting T2DM compared to HOMA-IR (AUC 0.700), which had 67.0% sensitivity and 66.7% specificity (P<0.001). Conclusion: The TyG index correlates with HOMA-IR and outperforms it in terms of T2DM detection and prediction, furthermore, the TyG index regarded as useful and valuable surrogate for estimating IR and for predicting T2DM in individuals who appear to be healthy.
Abstract: Insulin resistance (IR) is an independent risk factor for type 2 diabetes mellitus (T2DM). Because only triglyceride levels and fasting blood glucose are required to measure the triglyceride-glucose (TyG) index, and the insulin test, which is used in the homeostatic model assessment of insulin resistance (HOMA-IR) calculation, is costly and unavail...
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,
Max Efui Annani-Akollor,
Christopher Nkrumah
