Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Given that the long head of the biceps femoris (BFlh), semitendinosus (ST), and semimembranosus (SM) have hip adduction moment arm, this study aimed to clarify the influence of hip abduction angle on their shear modulus, measured by using shear wave elastography, to determine an effective stretching position where these muscles are more elongated and demonstrate higher passive tension. Twelve healthy young men participated in the study. The shear modulus of BFlh, ST, and SM at the middle point was measured using shear wave elastography. The shear modulus was measured at hip abduction angles of 0°, 15°, 30°, and 45°, with the hip and knee joint held at 70° and 0° flexion, respectively. The effects of hip abduction angle on the muscle shear modulus were analyzed using a Friedman test, followed by Wilcoxon signed-rank tests with Benjamini-Hochberg procedure for post-hoc analysis. Effect sizes were calculated using r. Significant differences in shear modulus were found between hip abduction angles for all muscles (p < 0.05). Post-hoc analysis showed that the shear modulus of the SM at 45° was significantly higher compared to 0° (p < 0.05, r = 0.62) and 15° (p < 0.05, r = 0.54). For ST, the shear modulus at 45° was significantly higher compared to 0° (p < 0.05, r = 0.58). The shear modulus in BFlh at 15° was higher than 0° (p < 0.05, r = 0.53). Adding to hip abduction in a position of hip flexion and knee extension increases the shear modulus of the medial hamstrings, particularly the SM.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

OBJECTIVES

The aim of the study is to estimate the cost of breast cancer diagnosis, treatment, and management in the Philippines. Specifically, it aims to identify the resource requirements and interventions related to breast cancer diagnosis, treatment, and management, measure resource volumes (number of units), learn to value resource items (unit costs), and determine the total cost of treatment per disease stage.

The study covered nine tertiary hospitals, seven of which were government hospitals and two were private hospitals, with all tertiary hospitals providing breast cancer services and accredited by Philippine Health Insurance Corporation (PHIC or PhilHealth) for the Z-Benefit Package. Interventions and services related to breast cancer included radiographic procedures, laboratory and imaging tests, chemotherapy drugs and medications, medical and surgical supplies, surgical rates (for breast surgery), accommodation, staff time and salary/professional fees, and other procedure fees. The study conducted in 2022, examined cost prices of breast cancer interventions and services from stage 1–3B.

Purposive and convenience sampling were used based on PhilHealth accreditation and willingness of hospitals to participate in the study. The study conducted a focus group discussion with oncologists, radiologists, anesthesiologists, and other health care providers to validate the clinical guideline used and to solicit inputs to the costing design, analysis framework, and tools for data collection. Data collection of financial cost information (charge price) was conducted using a set of costing matrices filled out by the various departments of the hospitals. Costs and median rates were calculated across hospitals on diagnostics and imaging tests, surgery costs of both public and private facilities, medical treatment, and radiotherapy.

Breast MRI, Breast Panel, and Chest CT Scan are the top 3 most expensive diagnostic procedures ranging from PhP 8,102.00 to PhP 9,800.00 per procedure. Surgical procedures for breast cancer at private hospitals and public hospitals showed huge differences in costs. The cost of a cycle of chemotherapy ranges from PhP 596.70 to PhP 3,700.00 per session, while the cost of targeted therapy can cost up to PhP 46,394.21 per session. A year of hormone therapy ranges from PhP 3,276.00 with the use of Tamoxifen, and up to PhP 68,284.00 with Goserelin. Aromatase inhibitors such as Anastrozole and Letrozole cost from PhP 18,000 to PhP 36,000, respectively. Multiple cycles depending on the diagnosis are prescribed per patient and used in combination with other chemotherapy medications or other therapies such as targeted therapy and hormone therapy are usually taken daily up to 5 to 10 years. Conventional radiotherapy can cost up to PhP 88,150.00 covering 28 sessions, CT simulation, and CT planning.

This cost study provides relevant information and better perspective on benefit development for the PHIC, policy development for Department of Health on where and how to focus their support for the patient’s financial preparedness to address medical and f inancial catastrophes.

PhilHealth needs to guide the health care providers of their costing method and to develop their own integrated, interoperable, and comprehensive cost data library.

It recommends that the government allocate budget and cover for screening and assessment for earlier stage diagnosis of patients and lower health expenditure costs on cancer treatment.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

OBJECTIVES

The aim of the study is to estimate the cost of breast cancer diagnosis, treatment, and management in the Philippines. Specifically, it aims to identify the resource requirements and interventions related to breast cancer diagnosis, treatment, and management, measure resource volumes (number of units), learn to value resource items (unit costs), and determine the total cost of treatment per disease stage.

The study covered nine tertiary hospitals, seven of which were government hospitals and two were private hospitals, with all tertiary hospitals providing breast cancer services and accredited by Philippine Health Insurance Corporation (PHIC or PhilHealth) for the Z-Benefit Package. Interventions and services related to breast cancer included radiographic procedures, laboratory and imaging tests, chemotherapy drugs and medications, medical and surgical supplies, surgical rates (for breast surgery), accommodation, staff time and salary/professional fees, and other procedure fees. The study conducted in 2022, examined cost prices of breast cancer interventions and services from stage 1–3B.

Purposive and convenience sampling were used based on PhilHealth accreditation and willingness of hospitals to participate in the study. The study conducted a focus group discussion with oncologists, radiologists, anesthesiologists, and other health care providers to validate the clinical guideline used and to solicit inputs to the costing design, analysis framework, and tools for data collection. Data collection of financial cost information (charge price) was conducted using a set of costing matrices filled out by the various departments of the hospitals. Costs and median rates were calculated across hospitals on diagnostics and imaging tests, surgery costs of both public and private facilities, medical treatment, and radiotherapy.

Breast MRI, Breast Panel, and Chest CT Scan are the top 3 most expensive diagnostic procedures ranging from PhP 8,102.00 to PhP 9,800.00 per procedure. Surgical procedures for breast cancer at private hospitals and public hospitals showed huge differences in costs. The cost of a cycle of chemotherapy ranges from PhP 596.70 to PhP 3,700.00 per session, while the cost of targeted therapy can cost up to PhP 46,394.21 per session. A year of hormone therapy ranges from PhP 3,276.00 with the use of Tamoxifen, and up to PhP 68,284.00 with Goserelin. Aromatase inhibitors such as Anastrozole and Letrozole cost from PhP 18,000 to PhP 36,000, respectively. Multiple cycles depending on the diagnosis are prescribed per patient and used in combination with other chemotherapy medications or other therapies such as targeted therapy and hormone therapy are usually taken daily up to 5 to 10 years. Conventional radiotherapy can cost up to PhP 88,150.00 covering 28 sessions, CT simulation, and CT planning.

This cost study provides relevant information and better perspective on benefit development for the PHIC, policy development for Department of Health on where and how to focus their support for the patient’s financial preparedness to address medical and f inancial catastrophes.

PhilHealth needs to guide the health care providers of their costing method and to develop their own integrated, interoperable, and comprehensive cost data library.

It recommends that the government allocate budget and cover for screening and assessment for earlier stage diagnosis of patients and lower health expenditure costs on cancer treatment.

The Newcastle disease virus (NDV) outbreak was first reported in Java Island, Indonesia, in 1926, which was then reported further in Newcastle-upon-Tyne, England. Nevertheless, the NDV is still endemic in Indonesia, with outbreaks occurring in free-range and commercial chicken farms. The dynamic evolution of the NDV has led to the further development of vaccines and diagnostic tools for more effective control of this virus. This paper discusses the history of the NDV occurrence, vaccines, the development of diagnostic tools, and the epidemiological condition of the NDV in Indonesia. Indonesia, which has the largest poultry population in the world after China, has challenges in preventing and controlling this virus that causes economic losses to the farmers and has an impact on the welfare of the poultry farming community in Indonesia.

The identification code of a drug is defined as “a code for identifying tablets, etc.” and is described in the “Composition/Properties” section of the package insert. We investigated whether the Pharmaceuticals and Medical Devices Agency (PMDA) website, which allows users to search package insert information, can be used for drug identification using identification codes in 2019 before the new package insert guidelines were implemented, and in 2022, during the revision period. Approximately 30% of the investigated high-risk drugs were unidentifiable in both years. The most common reason was that images were used to register identification codes on the PMDA website, and character strings were not searchable. We then conducted a questionnaire survey of pharmaceutical companies, and only approximately half of the respondents opined that it would be preferable if the registration format for identification codes was established within the pharmaceutical industry. However, hospital pharmacists urged for more simplified identification of drugs on the PMDA website.