OBJECTIVES

Timely access to appropriate levels of care is essential for improving maternal, newborn,
and child health outcomes. To address persistent service delivery fragmentation and strengthen referral systems, the Philippine Department of Health issued Administrative Order 2020-0019 to guide the design of Health Care Provider Networks (HCPNs) under the Universal Health Care Act of 2019. This study assessed the extent to which sixteen municipalities across four provinces in Eastern Visayas comply with the HCPN service delivery guidelines in the context of maternal and newborn care.

The study employed a descriptive cross-sectional mixed-methods design, utilizing structured facility checklists to assess compliance with HCPN standards. Qualitative data were gathered through key informant interviews and focus group discussions with purposively selected stakeholders—decision makers, health personnel, and mothers—to contextualize findings. A three-lever framework for integrated care (policy, operational, and cross- cutting) guided the analysis

The findings revealed significant gaps between the current capacities of study health facilities and the requirements outlined in the HCPN guidelines. Major gaps included (1) weak cooperative governance mechanisms to support network-wide coordination; (2) limited systematic linkages between facilities, including fragmented referral protocols and non-interoperable health information systems; (3) inadequate investments in infrastructure, health human resources, and medical commodities; and (4) absence of performance monitoring systems across HCPNs.

Background: The purpose of our study was to analyze the effects of hospital volume and region on in-hospital and long-term mortality, direct medical costs (DMCs), and length of hospital stay (LOS) in elderly patients following hip fracture, utilizing nationwide claims data. Methods: This retrospective nationwide study sourced its subjects from the Korean National Health Insurance Review and Assessment Service database spanning from January 2011 to December 2018. A generalized estimating equation model with a Poisson distribution and logarithmic link function was used to estimate adjusted odds ratios (aORs) and 95% CIs to assess the association of hospital volume with in-hospital and 1-year mortality, DMCs, and LOS . Results: A total of 172,144 patients were included. Comparing the risk of in-hospital death between high-volume and low-volume hospitals, the risk of in-hospital death was 1.2 times higher at low-volume hospitals (aOR, 1.20; 95% CI, 1.07–1.33; p = 0.002).Additionally, the risk of death at 1 year was 1.05 times higher at low-volume hospitals (aOR, 1.05; 95% CI, 1.01–1.09; p = 0.008) compared to high-volume hospitals. DMCs were 0.84 times lower at low-volume hospitals for in-hospital period (aOR, 0.84; 95% CI, 0.84–0.85; p < 0.001) and 0.87 times lower for 1 year (aOR, 0.87; 95% CI, 0.86–0.88; p < 0.001) compared to high-volume hospitals. In-hospital LOS was 1.21 times longer at low-volume hospitals (aOR, 1.21; 95% CI, 1.20–1.22; p < 0.001) than at high-volume hospitals. In addition, the risk of in-hospital death was 1.22 times higher (aOR, 1.22; 95% CI, 1.12–1.33; p < 0.001) and the risk of 1-year death was 1.07 times higher (aOR, 1.07; 95% CI, 1.04–1.10; p < 0.001) at rural hospitals compared to urban hospitals. Conclusions Clinicians should focus on improving clinical outcomes for hip fracture patients in low-volume and rural hospital settings, with a specific emphasis on reducing mortality rates.

Background: Given the association between nonalcoholic fatty liver disease and metabolic risks, a new term, metabolic dysfunction- associated steatotic liver disease (MASLD) has been proposed. We aimed to explore the association between MASLD and all-cause, cause-specific mortalities. Methods: We included individuals with steatotic liver disease (SLD) from the Korean National Health Insurance Service. Moreover, SLD was defined as a fatty liver index ≥30. Furthermore, MASLD, metabolic alcohol-associated liver disease (MetALD), and alcoholic liver disease (ALD) with metabolic dysfunction (MD) were categorized based on alcohol consumption and MD. We also analyzed all-cause, liver-, cancer-, hepatocellular carcinoma (HCC)- and cardiovascular (CV)-related mortalities. Results: This retrospective nationwide cohort study included 1,298,993 individuals aged 40 to 79 years for a mean follow-up duration of 9.04 years. The prevalence of MASLD, MetALD, and ALD with MD was 33.11%, 3.93%, and 1.00%, respectively. Relative to the “no SLD” group, multivariable analysis identified that MASLD (adjusted hazard ratio [aHR], 1.28; 95% confidence interval [CI], 1.26 to 1.31), MetALD (aHR, 1.38; 95% CI, 1.32 to 1.44), and ALD with MD group (aHR, 1.80; 95% CI, 1.68 to 1.93) have a significantly higher risk of all-cause mortality. Furthermore, MASLD, MetALD, ALD with MD groups showed higher liver-, cancer- and HCC-related mortality than “no SLD” group. While all-cause specific mortalities increase from MASLD to MetALD to ALD with MD, the MetALD group shows a lower risk of CV-related mortality compared to MASLD. However, ALD with MD group still have a higher risk of CV-related mortality compared to MASLD. Conclusion SLD is associated with an increased risk of all-cause, liver-, cancer-, HCC-, and CV-related mortalities.

The liver plays a fundamental role in metabolic homeostasis, integrating systemic fuel utilization with the progression of various metabolic diseases. Hepatic stellate cells (HSCs) are a key nonparenchymal cell type in the liver, which is essential for maintaining hepatic architecture in their quiescent state. However, upon chronic liver injury or metabolic stress, HSCs become activated, leading to excessive extracellular matrix deposition and pro-fibrotic signaling, ultimately positioning them as key players in liver pathology. Emerging evidence highlights the critical roles of metabolic reprogramming and epigenetic regulation in HSCs activation. HSCs activation is driven by both intrinsic fuel metabolism reprogramming and extrinsic metabolic cues from the microenvironment, while the metabolic intermediates actively reshape the epigenetic landscape, reinforcing fibrogenic transcriptional programs. In this review, we summarize recent advances in understanding how metabolic and epigenetic alterations drive HSCs activation, thereby shaping transcriptional programs that sustain fibrosis, and discuss potential therapeutic strategies to target these interconnected pathways in human metabolic diseases.

Background: We aimed to investigate the predictive values of plasma C-peptide levels and the continuous glucose monitoring (CGM)-defined coefficient of variation (CV) in risk prediction for hypoglycemia in Korean people with diabetes with normal and impaired kidney function. Methods: We analyzed data from 1,185 participants diagnosed with type 1 and type 2 diabetes who underwent blinded professional CGM between January 2009 and May 2021 at outpatient clinics. We explored correlations among CGM-defined CV, plasma C-peptide levels, and time below range at <70 and 54 mg/dL across different kidney function categories. Results: In patients with chronic kidney disease (CKD) stages 1–2 (n=934), 89.3% who had a random plasma C-peptide level higher than 600 pmol/L exhibited a CV of ≤36%. Among those in CKD stage 3 (n=161) with a random plasma C-peptide level exceeding 600 pmol/L, 66.7% showed a CV of ≤36%. In stages 4–5 of CKD (n=90), the correlation between random C-peptide levels and CV was not significant (r=–0.05, P=0.640), including cases with a CV greater than 36% despite very high random plasma C-peptide levels. Random plasma C-peptide levels and CGM-assessed CV significantly predicted hypoglycemia in CKD stages 1–2 and 1–5, respectively. Conclusion The established C-peptide criteria in Western populations are applicable to Korean people with diabetes for hypoglycemic risk prediction, unless kidney function is impaired equivalent to CKD stage 3–5. The CGM-defined CV is informative for hypoglycemic risk prediction regardless of kidney function.

Background: Sclerostin, initially recognized for its pivotal role in bone metabolism, has gained attention for its multifaceted impact on overall human health. However, its influence on frailty—a condition that best reflects biological age—has not been thoroughly investigated. Methods: We collected blood samples from 244 older adults who underwent comprehensive geriatric assessments. Sclerostin levels were quantified using an enzyme-linked immunosorbent assay. Frailty was assessed using two validated approaches: the phenotypic model by Fried and the deficit accumulation frailty index (FI) by Rockwood. Results: After controlling for sex, age, and body mass index, we found that serum sclerostin levels were significantly elevated in frail individuals compared to their robust counterparts (P<0.001). There was a positive correlation between serum sclerostin concentrations and the FI (P<0.001). Each standard deviation increase in serum sclerostin was associated with an odds ratio of 1.87 for frailty (P=0.003). Moreover, participants in the highest quartile of sclerostin levels had a significantly higher FI and a 9.91-fold increased odds of frailty compared to those in the lowest quartile (P=0.003 and P=0.039, respectively). Conclusion These findings, which for the first time explore the association between circulating sclerostin levels and frailty, have significant clinical implications, positioning sclerostin as one of potential blood-based biomarkers for frailty that captures the comprehensive physical, mental, and social aspects of the elderly, extending beyond its traditional role in bone metabolism.

Background: Intellectual disability (ID) may be associated with an increased risk of diabetes mellitus (DM). However, evidence from longitudinal studies is scarce, particularly in Asian populations. Methods: This retrospective cohort study used representative linked data from the Korea National Disability Registration System and the National Health Insurance Service database. Adults (≥20 years) who received a national health examination in 2009 (3,385 individuals with ID and 3,463,604 individuals without ID) were included and followed until 2020. ID was identified using legal registration information. Incident DM was defined by prescription records with relevant diagnostic codes. Multivariable-adjusted Cox proportional hazards regression models were used to estimate the adjusted hazard ratio (aHR) and 95% confidence interval (CI) for DM risks in individuals with ID compared to those without ID. Results: Over a mean follow-up of 9.8 years, incident DM occurred in 302 (8.9%) individuals with ID and 299,156 (8.4%) individuals without ID. Having ID was associated with increased DM risk (aHR, 1.38; 95% CI, 1.23 to 1.55). Sensitivity analysis confirmed a higher DM risk in individuals with ID (aHR, 1.39; 95% CI, 1.24 to 1.56) than those with other disabilities (aHR, 1.11; 95% CI, 1.10 to 1.13) or no disability (reference). Stratified analysis showed higher DM risk in non-hypertensive subjects (aHR, 1.63; 95% CI, 1.43 to 1.86) compared to hypertensive subjects (aHR, 1.00; 95% CI, 0.80 to 1.26; P for interaction <0.001). Conclusion Adults with ID have an increased risk of developing DM, highlighting the need for targeted public health strategies to promote DM prevention in this population.

Alzheimer disease (AD) diagnosis is confirmed using a medley of modalities, such as the detection of amyloid-β (Aβ) neuritic plaques and neurofibrillary tangles with positron electron tomography (PET) or the appraisal of irregularities in cognitive function with examinations. Although these methods have been efficient in confirming AD pathology, the rising demand for earlier intervention during pathogenesis has led researchers to explore the diagnostic potential of fluid biomarkers in cerebrospinal fluid (CSF) and plasma. Since CSF sample collection is invasive and limited in quantity, biomarker detection in plasma has become more attractive and modern advancements in technology has permitted more efficient and accurate analysis of plasma biomolecules. In this study, we found that a composite of standard factors, Aβ40 and total tau levels in plasma, divided by the variation factor, plasma Aβ42 level, provide better correlation with amyloid neuroimaging and neuropsychological test results than a level comparison between total tau and Aβ42 in plasma. We collected EDTA-treated blood plasma samples of 53 subjects, of randomly selected 27 AD patients and 26 normal cognition (NC) individuals, who received amyloid-PET scans for plaque quantification, and measured plasma levels of Aβ40, Aβ42, and total tau with digital enzyme-linked immunosorbent assay (ELISA) in a blinded manner. There was difficulty distinguishing AD patients from controls when analyzing biomarkers independently. However, significant differentiation was observed between the two groups when comparing individual ratios of total-tau×Aβ40/Aβ42. Our results indicate that collectively comparing fluctuations of these fluid biomarkers could aid in monitoring AD pathogenesis.

Background/Aims: This study aimed to evaluate the performance of the Model for End-Stage Liver Disease (MELD) 3.0 for predicting mortality and liver-related complications compared with the Child-Pugh classification, albumin-bilirubin (ALBI) grade, the MELD, and the MELD sodium (MELDNa) score. Methods: We evaluated a multicenter retrospective cohort of incorporated patients with cirrhosis between 2013 and 2019. We conducted comparisons of the area under the receiver operating characteristic curve (AUROC) of the MELD3.0 and other models for predicting 3-month mortality. Additionally, we assessed the risk of cirrhosis-related complications according to the MELD3.0 score. Results: A total of 3,314 patients were included. The mean age was 55.9±11.3 years, and 70.2% of the patients were male. Within the initial 3 months, 220 patients (6.6%) died, and the MELD3.0had the best predictive performance among the tested models, with an AUROC of 0.851, outperforming the Child-Pugh classification, ALBI grade, MELD, and MELDNa. A high MELD3.0score was associated with an increased risk of mortality. Compared with that of the group with a MELD3.0 score <10 points, the adjusted hazard ratio of the group with a score of 10–20 pointswas 2.176, and that for the group with a score of ≥20 points was 4.892. Each 1-point increase inthe MELD3.0 score increased the risk of cirrhosis-related complications by 1.033-fold. The risk of hepatorenal syndrome showed the highest increase, with an adjusted hazard ratio of 1.149, followed by hepatic encephalopathy and ascites. Conclusions The MELD3.0 demonstrated robust prognostic performance in predicting mortality in patients with cirrhosis. Moreover, the MELD3.0 score was linked to cirrhosis-related complications, particularly those involving kidney function, such as hepatorenal syndrome and ascites.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.