Background: Intensive insulin therapy is efficacious in achieving glycemic targets. However, it is associated with adverse cardiovascular outcomes due to an increased risk of hypoglycemia. Objective: To demonstrate the value of automatic snacking in preventing hypoglycemia among outpatient type 2 diabetic patients. Methods: Charts of 118 type 2 diabetes mellitus (DM) patients with HbA1c >7.0% despite oral antidiabetic agents, insulin therapy or in combination were reviewed. Insulin regimens were given as follows: glargine or determir prebreakfast with lispro/aspart premeals 3x a day (regimen A), or premixed 70/30 prebreakfast and predinner with lispro or aspart premeals 3x a day (regimen B), or a premixed 70/30 NPH and aspart (Novomix) 3x a day (regimen C). HBA1c was taken at baseline and repeated three to six months later. Twenty-four hour calorie supplementation included three main meals and three snacks taken automatically two hours after each meal, even the patient was not hungry. Hypoglycemia monitoring was done accordingly. Results: Of the 118 patients, 46(39%) were males; 72 (61%) were females with mean age of 57 years. The majority (75%) of patients were obese (BMI >25kg/m2) with family history of DM (76%). Mean baseline HbA1c was 9.2 ± 1.96 % (7.9 to 14%). Repeat HbA1c on follow-up within six months was 7.17 ± 1.10%. A significant mean decrease of 2.03 ± 1.66 % with a p value of <0.0001 (0.3 to 5.95%) was observed. A total of 103 (88%) patients reached target HbA1c of 7% or below. Of the 88%, 46% reached target HbA1c after three months while the remaining 54% after six months. Of note, no one had significant hypoglycemia. Conclusion: Automatic snacking prevented significant hypoglycemia among outpatient type 2 DM on intensive insulin therapy while achieving target HbA1c level.

INTRODUCTION: In the management of type 2 diabetes, insulin is often started late, when there is failure to achieve good control on maximum oral agents. Clinical inertia to insulin initiation and intensification is widely prevalent in our local setting resulting in poor control of diabetes. This study looked into a stepwise insulin combinations treatment algorithm used in an Endocrinology referral clinic at the University of Santo Tomas Hospital (USTH). It aimed to demonstrate the clinical course of the patients , determine the degree of HbA1c reduction, and show the associated extent of hypoglycemia and weight gain.

METHODS: This is a retrospective chart review of 104 patients that used the following stepwise treatment: Oral regimen; Regimen A: basal+oral; Regimen B: basal+premeal bolus TID±oral; Regimen C: premixed aspart 70/30 or lispro 75/25 TID or BID with prelunch bolus, ± oral; Regimen D: premixed 70/30 BID+premeal bolus TID ± oral; Regimen E: premixed 70/30 BI +premeal bolus TID+basal ±oral. All received automatic snacking two hours after main meals to prevent hypoglycemia. Patients were educated on proper diet and exercise. Data was analyzed using paired t-test, frequencies and percentages.

RESULTS: Most ended on the intensive insulin regimens D 57(55%), and E 18 (17%). Significant HbA1c reduction was demonstrated as follows: Regimen A (n=8):1.376±0.919 (p=0.000), Regimen B (n=18):2.320±2.177 (p=0.000), Regimen D (n=57):2.197±2.158 (p=0.000), Regimen E (n=18):2.684±1.689 (p =0.000). Overall mean weight gain was 1.070 ± 11.435 kg (p=0.335). Ten, nonsevere hypoglycemia events were reported.

CONCLUSION: The use of this stepwise insulin combinations treatment algorithm exerted significant HbA1c reduction, with minimal events of hypoglycemia, and statistically insignificant weight gain. Hence, this is a feasible tool that may be used as a guide for intensification of insulin treatment.

Human ; Male ; Female ; Aged ; Middle Aged ; Adult ; Insulin Lispro ; Insulin ; Diabetes Mellitus, Type 2 ; Regimen B ; Weight Gain ; Hypoglycemia ; Antineoplastic Combined Chemotherapy Protocols ; Diet ; Algorithms

INTRODUCTION: Postprandial lipemia characterized by a rise in triglyceride-rich lipoproteins after eating, is associated with increased risk of cardiovascular disease. Among diabetic patients, postprandial lipemia is often overlooked once fasting lipid parameters are within target. The aim of the study is to determine the correlation of glycemic control and postprandial hyperglycemia with postprandial lipemia among patients with type 2 diabetes mellitus (DM). The result of the study may have important implications on how dyslipidemia should be completely addressed.

METHODOLOGY: A clinic-based retrospective chart review of 102 patients with recorded fasting and postprandial blood measurements was performed. Subjects included adult patients with type 2 DM whose fasting lipid parameters were controlled with diet and/or medications. Plasma glucose and glycosylated hemoglobin (HbA1C) were independent variables while triglyceride, total cholesterol, low density lipoprotein (LDL) and high density lipoprotein (HDL) were dependent variables. Pearson correlation was used to determine the strength of relationships among the variables mentioned. A p-value

RESULTS: Of the 102 patients, 52.9% and 47.1% were achieving their target HbA1C and twohour postprandial plasma glucose, respectively. The postprandial level of plasma glucose, mean triglyceride, total cholesterol, LDL and HDL were 196.39 mg/dL, 189.06 mg/dL, 177.07 mg/dL, 122.40 mg/dL and 34.83 mg/dL, respectively. HbA1C has strong positive correlation with postprandial lipemia (Pearson's r=0.40) while the two-hour plasma glucose has moderate positive correlation (Pearson's r=0.34) with postprandial lipemia. Both relationships were considered significant (p-value <0.05).

CONCLUSION: A significant correlation of glycemic control and postprandial hyperglycemia with postprandial lipemia was observed. Our data suggest that despite achievement of optimal fasting lipid parameters, poor control of diabetes is positively correlated with abnormal elevation of postprandial triglyceride. Addressing both postprandial hyperglycemia and lipemia may improve cardiovascular outcome.

Human ; Male ; Female ; Aged ; Middle Aged ; Adult ; Hemoglobin A, Glycosylated ; Diabetes Mellitus, Type 2 ; Lipoprotein Triglyceride ; Lipoproteins ; Hyperlipidemias ; Dyslipidemias ; Hyperglycemia ; Cholesterol ; Cardiovascular Diseases

OBJECTIVE: To establish data determining the etiology of hypopituitarism in the University of Santo Tomas Hospital (USTH) and to describe the clinical and biochemical profile of these patients.
METHODOLOGY: A retrospective descriptive study in a tertiary hospital (USTH) involving patients diagnosed by clinical evaluation and biochemical tests to have hypopituitarism, admitted or seen at the outpatient department from January 2001 to December 2009 and whose charts were available for review. The clinical profile, manifestations and biochemical profile were defined and causes of hypopituitarism identified. Descriptive statistics were applied using percentages and frequency distribution.
RESULTS: In the nine-year period (2001-2009), a total of 191 patients were recorded to have hypopituitarism but only 143 (75%) have adequate data available for review. Sixty one (43%) were males and 82 (51%) were females with mean age was 45±6 years. Hypopituitarism was found to be most prevalent in the fourth to fifth decade of life and clinical manifestations were noted with mean duration of 20±4 months. The most predominant documented pituitary hormone deficiency was gonadotrophic hormone (60%) manifesting prominently as decreased libido (82%). The most common target end organ hormone deficiency was secondary adrenal insufficiency (90%) and most prevalent etiology of hypopituitarism was pituitary tumors (40%). Sheehan's syndrome (8%) and tuberculosis (3%) were also noted as a cause of hypopituitarism.
CONCLUSION: This study shows that the leading clinical manifestation and documented hormone deficiency of hypopituitarism is hypogonadism. Pituitary adenoma is the most common cause of hypopituitarism along with its treatment. Other causes not commonly seen in other countries but proved to be more prevalent here include Sheehan's syndrome and tuberculosis infection.

Human ; Male ; Female ; Middle Aged ; Adult ; Adenoma ; Adrenal Insufficiency ; Hypogonadism ; Hypopituitarism ; Libido ; Outpatients ; Pituitary Hormones ; Pituitary Neoplasms ; Prevalence ; Retrospective Studies ; Tertiary Care Centers ; Tuberculosis

Communicable Diseases

Cholecystitis ;

BACKGROUND: Osteoporosis in men is markedly underdiagnosed and undertreated despite higher morbidity and mortality associated with fractures. This study aimed to characterize adult Filipino men with osteopenia, osteoporosis and prevalent fractures. METHODS: A cross-sectional study of 184 Filipino men ≥50 years screened for bone mineral density was performed. Age, weight, body mass index (BMI), Osteoporosis Self-Assessment Tool for Asians (OSTA) score, smoking status, family history of fracture, diabetes mellitus, physical inactivity, and T-score were considered. RESULTS: Of the 184 patients, 40.2% and 29.9% have osteopenia and osteoporosis. Sixteen (21.6%) and 18 (32.1%) osteopenic and osteoporotic men have fragility hip, spine, or forearm fractures. Men aged 50 to 69 years have the same risk of osteoporosis and fractures as those ≥70 years. While hip fractures are higher in osteoporotic men, vertebral fractures are increased in both osteopenic and osteoporotic men. Mere osteopenia predicts the presence of prevalent fractures. A high risk OSTA score can predict fracture. A BMI <21 kg/m2 (P<0.05) and current smoking are associated with osteoporosis. CONCLUSION: A significant fraction of Filipino men with osteopenia and osteoporosis have prevalent fractures. Our data suggest that fractures occur in men <70 years even before osteoporosis sets in. Low BMI, high OSTA score, and smoking are significant risk factors of osteoporosis.
Adult* ; Asian Continental Ancestry Group ; Body Weight ; Bone Density* ; Bone Diseases, Metabolic ; Cross-Sectional Studies ; Diabetes Mellitus ; Forearm ; Hip ; Hip Fractures ; Humans ; Male ; Mortality ; Multiple Endocrine Neoplasia Type 1 ; Osteoporosis* ; Risk Factors ; Self-Assessment ; Smoke ; Smoking ; Spine ; Tertiary Care Centers*