Introduction: Cushing’s disease (CD) in adolescents may present with subtle clinical features, resulting in a significant diagnostic challenge. We report a case of a young lady whose CD initially masqueraded as Type 2 diabetes (T2D), highlighting the difficulties in differentiating early hypercortisolism from T2D. Case: A 12-year-old female was incidentally diagnosed with diabetes during routine medical screening. Examination revealed an overweight female without the classical features of Cushing’s syndrome. Due to the presence of acanthosis nigricans, a diagnosis of T2D was initially made. Her diabetes remained well-controlled with a single oral glucose-lowering drug. The diagnostic challenge became apparent over time. She experienced delayed menarche at the age of 17, and a diagnosis of Cushing’s syndrome was suspected when she subsequently developed hypertension and reduced bone mineral density. Biochemical evaluation was consistent with adrenocorticotropic hormone (ACTH)- dependent hypercortisolism, evidenced by the failure of serum cortisol suppression on low dose and overnight dexamethasone suppression tests. Her 24-hour urinary cortisol was elevated twofold, and plasma ACTH was elevated (17.8 pmol/L). MRI demonstrated a right-sided pituitary microadenoma (0.3 × 0.5 × 0.3 cm), and inferior petrosal sinus sampling confirmed the diagnosis of CD. She underwent endoscopic transsphenoidal surgery 7 years later, which was complicated by panhypopituitarism and cranial diabetes insipidus. Postoperatively, CD was cured, with the resolution of her metabolic comorbidities. Conclusion Despite the increasing prevalence of T2D in adolescents, clinicians must recognize the diagnostic challenge of CD in this age group. Atypical manifestations in a presumed T2D patient should prompt consideration of Cushing’s syndrome.
Adolescent ; Humans ; Diabetes Mellitus, Type 2

Objectives: This study aimed to describe and compare health-related quality of life (QoL) as measured by the World Health Organization Quality of Life–BREF (WHOQoL-BREF) and the EuroQol-5 Dimensions (EQ-5D) among the Malaysian population, examining differences by sociodemographic characteristics including age, income, sex, ethnicity, educational level, and occupation. Methods: This cross-sectional study used data from 19,402 individuals collected as part of a health and demographic surveillance system survey conducted in the Segamat district of Malaysia in 2018–2019. Descriptive statistics and measures of central tendency were produced.Differences in QoL among demographic sub-groups were examined using the t-test and analysisof variance, while the correlations between the WHOQoL-BREF and EQ-5D were evaluated usingPearson correlation coefficients. Results: Based on complete case analysis (n = 19,129), the average scores for the 4 WHOQoLBREF domains were 28.2 (physical), 24.1 (psychological), 12.0 (social relationships), and 30.4 (environment). The percentages of participants not in full health for each EQ-5D dimension were 12.8% (mobility), 3.1% (self-care), 6.9% (usual activities), 20.9% (pain/discomfort), and 6.8% (anxiety/depression). Correlations between the 4 WHOQoL-BREF domains and the 5 EQ-5D dimensions were relatively weak, ranging from –0.06 (social relationships with self-care and pain/discomfort; p < 0.001) to –0.42 (physical with mobility; p < 0.001). Conclusion Although health-related QoL as measured by the WHOQoL-BREF and the EQ-5D are correlated, these 2 measures should not be considered interchangeable. The choice betweenthem should be guided by the specific research questions and the intended use of the data.

Objectives: This study aimed to describe and compare health-related quality of life (QoL) as measured by the World Health Organization Quality of Life–BREF (WHOQoL-BREF) and the EuroQol-5 Dimensions (EQ-5D) among the Malaysian population, examining differences by sociodemographic characteristics including age, income, sex, ethnicity, educational level, and occupation. Methods: This cross-sectional study used data from 19,402 individuals collected as part of a health and demographic surveillance system survey conducted in the Segamat district of Malaysia in 2018–2019. Descriptive statistics and measures of central tendency were produced.Differences in QoL among demographic sub-groups were examined using the t-test and analysisof variance, while the correlations between the WHOQoL-BREF and EQ-5D were evaluated usingPearson correlation coefficients. Results: Based on complete case analysis (n = 19,129), the average scores for the 4 WHOQoLBREF domains were 28.2 (physical), 24.1 (psychological), 12.0 (social relationships), and 30.4 (environment). The percentages of participants not in full health for each EQ-5D dimension were 12.8% (mobility), 3.1% (self-care), 6.9% (usual activities), 20.9% (pain/discomfort), and 6.8% (anxiety/depression). Correlations between the 4 WHOQoL-BREF domains and the 5 EQ-5D dimensions were relatively weak, ranging from –0.06 (social relationships with self-care and pain/discomfort; p < 0.001) to –0.42 (physical with mobility; p < 0.001). Conclusion Although health-related QoL as measured by the WHOQoL-BREF and the EQ-5D are correlated, these 2 measures should not be considered interchangeable. The choice betweenthem should be guided by the specific research questions and the intended use of the data.

Objectives: This study aimed to describe and compare health-related quality of life (QoL) as measured by the World Health Organization Quality of Life–BREF (WHOQoL-BREF) and the EuroQol-5 Dimensions (EQ-5D) among the Malaysian population, examining differences by sociodemographic characteristics including age, income, sex, ethnicity, educational level, and occupation. Methods: This cross-sectional study used data from 19,402 individuals collected as part of a health and demographic surveillance system survey conducted in the Segamat district of Malaysia in 2018–2019. Descriptive statistics and measures of central tendency were produced.Differences in QoL among demographic sub-groups were examined using the t-test and analysisof variance, while the correlations between the WHOQoL-BREF and EQ-5D were evaluated usingPearson correlation coefficients. Results: Based on complete case analysis (n = 19,129), the average scores for the 4 WHOQoLBREF domains were 28.2 (physical), 24.1 (psychological), 12.0 (social relationships), and 30.4 (environment). The percentages of participants not in full health for each EQ-5D dimension were 12.8% (mobility), 3.1% (self-care), 6.9% (usual activities), 20.9% (pain/discomfort), and 6.8% (anxiety/depression). Correlations between the 4 WHOQoL-BREF domains and the 5 EQ-5D dimensions were relatively weak, ranging from –0.06 (social relationships with self-care and pain/discomfort; p < 0.001) to –0.42 (physical with mobility; p < 0.001). Conclusion Although health-related QoL as measured by the WHOQoL-BREF and the EQ-5D are correlated, these 2 measures should not be considered interchangeable. The choice betweenthem should be guided by the specific research questions and the intended use of the data.

Objectives: This study aimed to describe and compare health-related quality of life (QoL) as measured by the World Health Organization Quality of Life–BREF (WHOQoL-BREF) and the EuroQol-5 Dimensions (EQ-5D) among the Malaysian population, examining differences by sociodemographic characteristics including age, income, sex, ethnicity, educational level, and occupation. Methods: This cross-sectional study used data from 19,402 individuals collected as part of a health and demographic surveillance system survey conducted in the Segamat district of Malaysia in 2018–2019. Descriptive statistics and measures of central tendency were produced.Differences in QoL among demographic sub-groups were examined using the t-test and analysisof variance, while the correlations between the WHOQoL-BREF and EQ-5D were evaluated usingPearson correlation coefficients. Results: Based on complete case analysis (n = 19,129), the average scores for the 4 WHOQoLBREF domains were 28.2 (physical), 24.1 (psychological), 12.0 (social relationships), and 30.4 (environment). The percentages of participants not in full health for each EQ-5D dimension were 12.8% (mobility), 3.1% (self-care), 6.9% (usual activities), 20.9% (pain/discomfort), and 6.8% (anxiety/depression). Correlations between the 4 WHOQoL-BREF domains and the 5 EQ-5D dimensions were relatively weak, ranging from –0.06 (social relationships with self-care and pain/discomfort; p < 0.001) to –0.42 (physical with mobility; p < 0.001). Conclusion Although health-related QoL as measured by the WHOQoL-BREF and the EQ-5D are correlated, these 2 measures should not be considered interchangeable. The choice betweenthem should be guided by the specific research questions and the intended use of the data.

Objectives: This study aimed to describe and compare health-related quality of life (QoL) as measured by the World Health Organization Quality of Life–BREF (WHOQoL-BREF) and the EuroQol-5 Dimensions (EQ-5D) among the Malaysian population, examining differences by sociodemographic characteristics including age, income, sex, ethnicity, educational level, and occupation. Methods: This cross-sectional study used data from 19,402 individuals collected as part of a health and demographic surveillance system survey conducted in the Segamat district of Malaysia in 2018–2019. Descriptive statistics and measures of central tendency were produced.Differences in QoL among demographic sub-groups were examined using the t-test and analysisof variance, while the correlations between the WHOQoL-BREF and EQ-5D were evaluated usingPearson correlation coefficients. Results: Based on complete case analysis (n = 19,129), the average scores for the 4 WHOQoLBREF domains were 28.2 (physical), 24.1 (psychological), 12.0 (social relationships), and 30.4 (environment). The percentages of participants not in full health for each EQ-5D dimension were 12.8% (mobility), 3.1% (self-care), 6.9% (usual activities), 20.9% (pain/discomfort), and 6.8% (anxiety/depression). Correlations between the 4 WHOQoL-BREF domains and the 5 EQ-5D dimensions were relatively weak, ranging from –0.06 (social relationships with self-care and pain/discomfort; p < 0.001) to –0.42 (physical with mobility; p < 0.001). Conclusion Although health-related QoL as measured by the WHOQoL-BREF and the EQ-5D are correlated, these 2 measures should not be considered interchangeable. The choice betweenthem should be guided by the specific research questions and the intended use of the data.

Laparoscopic Salvage of Percutaneous Endoscopic Gastrostomy Tract Dehiscence Following Blind Reinsertion: A Case Report Percutaneous endoscopic gastrostomy (PEG) is a commonly performed and generally safe method for long-term enteral nutrition. Nevertheless, accidental dislodgement is a well-recognised complication, and premature or unguided reinsertion may result in severe morbidity. We described a 60-year-old man with a history of cerebrovascular accident who developed peritonitis following blind reinsertion of a dislodged PEG tube. Diagnostic laparoscopy revealed partial tract dehiscence and intraperitoneal contamination, necessitating laparoscopic refashioning and peritoneal lavage. His postoperative course was complicated by recurrent dislodgement and stomal stenosis, successfully managed with endoscopic reinsertion under direct visualisation. Blind reinsertion of PEG tubes carries significant risk even in apparently mature tracts. Laparoscopy provides both diagnostic confirmation and therapeutic control in cases of tract dehiscence or peritonitis. Image-guided or endoscopic techniques should be prioritised to minimise recurrence and ensure safe re-establishment of enteral access. Early recognition and image-guided management are essential to prevent peritonitis and preserve long-term enteral access. Laparoscopy remains the preferred modality for both diagnosis and salvage in complex PEG-related complications.

The increasing number of homeless children is concerning. This study aimed to assess the dietary intake, diet quality, and nutritional status of homeless children in Klang Valley, as well as the relationship between diet quality and nutritional status. Methods: Approximately 120 homeless children aged 7 to 12 years from four locations in Klang Valley were enrolled. Their dietary intake and nutritional status were assessed using a two-day 24-hour dietary recall and body mass index-for-age, respectively. The Healthy Eating Index (HEI) was used to examine diet quality. Results: Prevalence of normal weight respondents was 58.3% (mean±SD: -0.79±1.80), with 25.0% classified as moderately and severely thin. Mean energy intake was significantly lower than recommended nutrient intakes (RNI) (p<0.050), while protein intake was higher (p<0.050). Calcium and zinc intakes were also significantly lower (p<0.001). Boys aged 7-9 years had significantly higher iron intake (median=11.6, IQR=8.7 mg, p=0.003), whereas girls aged 10-12 years had significantly lower intakes of iron (mean±SD=11.4±5.1, 11.1±4.7) and vitamin A (median=416.6, IQR=450.4 µgRE, p<0.001 for both). Mean HEI score was 51.30±6.78, indicating a need for diet quality improvement. No significant association between diet quality and nutritional status was observed (p=0.380). Conclusion: This study provided insights into dietary intake, diet quality, and nutritional status of homeless children. Further research is vital to shape evidence-based nutrition interventions.

CORRIGENDUM TO “CARING FOR PEOPLE LIVING WITH DEMENTIA AND THEIR INFORMAL CAREGIVERS: CURRENT PERSPECTIVES IN MALAYSIA” In our article titled “Caring for people living with dementia and their informal caregivers: Current perspectives in Malaysia” published in this journal (Malaysian Family Physician (2024;19:69)),1 we would like to bring to the readers’ attention to certain discrepancies that have come to light.
Dementia ; Caregivers

Prediabetes is a condition in which blood glucose level is above the normal but below the diagnostic value of diabetes mellitus. Hyperglycaemia can upregulate markers of chronic inflammation and contribute to the overproduction of reactive oxygen species (ROS), which ultimately causes increased oxidative stress. This leads to beta-cell dysfunction and insulin resistance, which are involved in the pathogenesis of prediabetes status. Proper treatment of hyperglycaemia, inhibition of ROS overproduction, and suppression of inflammation are crucial for delaying the onset of diabetes. Therefore, it is essential to determine and understand the mechanisms involved in prediabetes. This review discusses the relationship between oxidative stress and prediabetes, along with the inflammation’s role in prediabetes. Additionally, the effects of some biomarkers of oxidative stress in prediabetes, inflammatory markers, and their influence on chronic inflammation are also briefly reviewed. Finally, the role of antioxidant and anti-inflammatory markers are discussed.