OBJECTIVES

Epidemiology data on prolonged mechanical ventilation (PMV) and PMV patient features in the Philippines is lacking. This retrospective cross-sectional study aimed to determine the prevalence of PMV among intubated patients, describe patient characteristics and outcomes, and identify risk factors associated with PMV.

A retrospective review of records was done on adult intubated patients admitted under the Medical Intensive Care Unit Service from July 2022 to June 2023. Various clinical characteristics and outcomes of PMV and non-PMV patients were collected, compared, and analyzed. PMV was defined as having MV for ≥6 hours per day
for >21 days.

Among 261 intubated ICU patients admitted, 75 (28.7%) required PMV. PMV patients were older (62 vs.
53.5), had higher Charlson Comorbidity Index scores (4 vs. 3), and required vasopressors (81.33% vs. 54.84%)
and blood products (93.33% vs. 51.08%) more often. Nosocomial infections (86.67% vs. 45.70%), ventila- tor-related (30.67% vs. 12.37%) and in-hospital (66.22% vs. 32.97%) complications developed more frequently.
Outcomes such as ICU length of stay (29.5 vs. 7 days) and hospital mortality (61.33% vs. 41.94%) were longer. Vasopressor use (OR 2.25, 95% CI 1.06-4.76), develop- ment of nosocomial infections (OR 6.20, 95% CI 2.64-
14.56), and development of in-hospital-related compli- cations (OR 2.20, 95% CI 1.13-4.30) were independent predictors of PMV.

In this single-center investigation, 28.7% of ICU patients required PMV. Knowledge of patient characteristics and risk factors aid in the development of interventions that improve outcomes and reduce PMV prevalence. Larger studies are recommended to assess nationwide PMV epidemiology and provide data on the need for step-down units for weaning.

OBJECTIVE: To analyze the demographic and clinical characteristics of inpatients with osteoporotic vertebral compression fractures (OVCF) and provide a basis for clinical prevention and treatment. METHODS: A retrospective analysis was performed on the clinical data of 744 inpatients diagnosed with OVCF between January 2017 and December 2021 who met the inclusion criteria. Among them, 146 were male and 598 were female, with age ranging from 50 to 95 years (mean, 69.37 years). The demographic characteristics (gender, age, ethnicity, occupation, regional distribution, urban-rural distribution, and seasonal incidence) and clinical features [causes of injury, history of vertebral fractures, smoking and drinking history in males, comorbidities (hypertension, diabetes, coronary atherosclerotic heart disease, cerebral infarction), body mass index (BMI), blood lipid levels, menopausal age in females, vertebral bone mineral density T-value, number of vertebral fractures, and fracture segment distribution] of OVCF patients were analyzed. Multiple linear regression was used to analyze the independent risk factors of vertebral osteoporosis. RESULTS: The demographic analysis indicated that female patients with OVCF were significantly younger than male patients ( P<0.05). Significant differences were observed in the age distribution of OVCF between males and females ( P<0.05), with the highest proportion of male patients in the 70-79 years group (37.0%) and the highest proportion of female patients in the 60-69 years group (40.0%). From 2017 to 2021, the age of onset for OVCF gradually increased, with a similar trend observed for both genders. The distribution of occupations between genders also showed significant differences ( P<0.05); with the top three occupations for males being farmers (48.6%), retirees (24.7%), and workers (13.7%), while for females, the leading occupations were farmers (51.5%), retirees (19.4%), and service workers (10.0%). Female OVCF patients had higher BMI, vertebral bone mineral density T-value, history of vertebral fractures, hypertension prevalence, and blood lipid levels compared to male patients ( P<0.05). No significant difference between the males and the females was found in ethnicity, seasonal distribution, regional distribution, urban-rural distribution, causes of injury, number of vertebral fractures, or prevalence of comorbidities (except hypertension) ( P>0.05). Among the 744 OVCF patients, a total of 1 309 vertebrae were involved, with 628 thoracic vertebrae (48.0%) and 681 lumbar vertebrae (52.0%). The most common fracture segments were L ₁ (22.5%), T ₁₂ (21.2%), followed by L ₂ (12.2%) and T ₁₁ (10.2%). No significant gender difference was observed in the distribution of fracture segments ( P>0.05). Multiple linear regression analysis indicated that older age, female, and lower BMI were independent risk factors for vertebral osteoporosis ( P<0.05). CONCLUSION The age of onset of OVCF patients is increasing year by year. The number of fractured vertebral bodies, age distribution of morbidity, occupational distribution, BMI, history of vertebral fracture, hypertension, and blood lipid levels are related to gender. The occurrence of OVCF is mainly in the thoracolumbar segment. The female, older age, and lower BMI are independent risk factors of osteoporosis.
Humans ; Male ; Female ; Aged ; Middle Aged ; Retrospective Studies ; Spinal Fractures/etiology* ; Aged, 80 and over ; Osteoporotic Fractures/etiology* ; Fractures, Compression/etiology* ; Risk Factors ; Bone Density ; China/epidemiology* ; Osteoporosis/epidemiology* ; Comorbidity ; Inpatients ; Sex Factors ; Age Factors

INTRODUCTION: The 30-day readmission rate for chronic obstructive pulmonary disease (COPD) is a common performance metric but may be confounded by factors unrelated to quality of care. Our aim was to assess how sociodemographic factors, multimorbidity and frailty impact 30-day readmission risk after COPD hospitalisation, and whether risk adjustment alters interpretation of temporal trends. METHOD: This is a retrospective analysis of administra-tive data from October 2017 to June 2023 from Changi General Hospital, Singapore. Multivariable mixed-effects logistic regression models were used to estimate unadjusted and risk-adjusted 30-day readmission odds. Covariates included age, sex, race, Charlson Comorbidity Index (CCI), Hospital Frailty Risk Score (HFRS) and year. Temporal trends in readmission risk were compared across unadjusted and adjusted models. RESULTS: Of the 2774 admissions, 749 (27%) resulted in 30-day readmissions. Higher CCI (CCI≥4 versus [vs] CCI=1: adjusted odds ratio [aOR] 2.00, 95% confidence interval [CI] 1.33-2.99, P=0.003; CCI 2-3 vs CCI=1: aOR 1.50, 95% CI 1.15-1.96, P=0.001) and higher HFRS (≥5 vs <5: aOR 1.29, 95% CI 1.01-1.65, P=0.04) were independently associated with increased readmission risk. While unadjusted analyses showed no significant temporal trends, the risk-adjusted model revealed a 32-35% reduction in readmission odds in 2021-2023 compared to baseline. CONCLUSION Multimorbidity and frailty significantly impact COPD readmissions. Risk adjustment revealed improvements in readmission risk not evident in unadjusted analyses, emphasising the importance of applying risk adjustments to ensure valid performance metrics.
Humans ; Pulmonary Disease, Chronic Obstructive/therapy* ; Patient Readmission/trends* ; Male ; Female ; Retrospective Studies ; Aged ; Singapore/epidemiology* ; Multimorbidity ; Frailty/epidemiology* ; Middle Aged ; Risk Adjustment ; Aged, 80 and over ; Logistic Models ; Risk Factors

The increasing prevalence of aging has led to a rising incidence of comorbidity of sarcopenia and obesity, posing significant burdens on socioeconomic and public health. Current research has systematically explored the pathogenesis of each condition; however, the mechanisms underlying their comorbidity remain unclear. This study reviews the current literature on sarcopenia and obesity in the aging population, focusing on their shared biological mechanisms, which include loss of autophagy, abnormal macrophage function, mitochondrial dysfunction, and reduced sex hormone secretion. It also identifies metabolic mechanisms such as insulin resistance, vitamin D metabolism abnormalities, dysregulation of iron metabolism, decreased levels of nicotinamide adenine dinucleotide, and gut microbiota imbalances. Additionally, this study also explores the important role of genetic factors, such as alleles and microRNAs, in the co-occurrence of sarcopenia and obesity. A better understanding of these mechanisms is vital for developing clinical interventions and preventive strategies.
Humans ; Sarcopenia/physiopathology* ; Obesity/physiopathology* ; Aging/physiology* ; Autophagy/physiology* ; Insulin Resistance ; Comorbidity ; Vitamin D/metabolism* ; Gonadal Steroid Hormones/metabolism* ; Gastrointestinal Microbiome ; Mitochondria ; MicroRNAs

Psychogenic non-epileptic seizures are accompanied by motor,behavioral,sensory,and/or cognitive changes,with the clinical manifestations similar to epileptic seizures.This disease is easy to be misdiagnosed and neglected in clinical work.At present,most intervention measures still depend on the experience of clinicians.This article reviews the comorbidities of psychogenic non-epileptic seizures,including mental and cognitive disorders,somatic syndrome,sleep disorders,and epilepsy.This review aims to strengthen the precision of clinical treatment and management of patients with psychogenic non-epileptic seizures and provide more efficient individualized diagnosis and treatment programs for patients.
Humans ; Seizures/diagnosis* ; Comorbidity ; Epilepsy ; Sleep Wake Disorders ; Mental Disorders ; Psychophysiologic Disorders ; Cognition Disorders

BACKGROUND

Overweight and obesity, as well as the coexistence of multimorbidity, have been recognized as global health challenges. However, less is known about the prevalence of obesity and multimorbidity among older people in the Philippines. This study sought to determine the prevalence of obesity and multimorbidity among community-living older people.

A cross-sectional analysis of older persons aged 60 years and above was conducted from the Focused Intervention for Frail Older Adults Research and Development Program (FITforFrail). Height and weight were measured, and body mass index (BMI) was classified as follows: underweight,

The prevalence of obesity was 15.4%, which was significantly more common among women (p < 0.013) and nonsmokers (p < 0.006). Multimorbidity, including overweight and obesity, was reported by 77.9% of older persons, and among those with overweight and obesity, multimorbidity was present in 76.5%. A higher number of chronic diseases were reported by older persons who were overweight and obese (p < 0.006). Significantly more overweight and obese older women reported having multimorbidity (p < 0.049) compared to older men. Hypertension, hyperlipidemia, musculoskeletal disorders, and hyperuricemia were the most commonly reported chronic diseases among older persons with overweight and obesity.

The results of this study highlight the importance of overweight and obesity as determinants of multimorbidity. Future research should explore gender differences in risk factors and multimorbidity patterns.

The growing population of senior citizens in the Philippines faces increased vulnerability to co-existence of two or more chronic diseases, highlighting the complex interplay of health, socioeconomic, and healthcare access challenges in this age group. This case report presents a 71-year-old Filipino female from Barangay Bunuanan, Catbalogan City, Samar, diagnosed with hypertension, gout, and diabetes mellitus. The patient experiences difficulties common to elderly individuals in the Philippines, including financial limitations and managing multiple chronic illnesses. Laboratory tests revealed elevated blood uric acid, borderline high lipid profile, and an HbA1c level indicative of poor glycemic control. The case highlights the complexity of multimorbidity in the elderly and the impact of socioeconomic factors on disease management.

This study was to survey the relationship between semen values and demographics, comorbidities, and recreational substance use in a large cohort of adult men at the University of Chicago Medical Center Department of Urology (Chicago, IL, USA). We performed an analysis from January 2013 to December 2023 of semen samples obtained from adult patients at our institution and collected their demographics, comorbid medical conditions, and recreational substance use information. Patients were divided into categories of normozoospermia, oligozoospermia, and azoospermia on the basis of the 5 th version of the World Health Organization (WHO) guidelines. Data were analyzed by univariate linear and logistic regression models, after which statistically significant variables were placed into multivariable models. Azoospermia and oligozoospermia were both associated with Caucasian or Black, Indigenous, and People of Color (BIPOC) race (both P < 0.001), increasing age ( P = 0.005 and P < 0.001, respectively), anemia ( P < 0.001 and P = 0.02, respectively), lifetime tobacco use (both P < 0.001), lifetime alcohol use ( P = 0.02 and P < 0.001, respectively), and lifetime use of at least two recreational substances ( P < 0.001 and P = 0.003, respectively) in multivariable models. Oligospermia was additionally associated with benign prostatic hyperplasia (BPH; P = 0.003) in multivariable models. This study suggests that at-risk populations may benefit from additional early screening and workup for infertility.
Humans ; Male ; Adult ; Longitudinal Studies ; Middle Aged ; Semen Analysis ; Life Style ; Oligospermia/epidemiology* ; Azoospermia/epidemiology* ; Comorbidity ; Midwestern United States/epidemiology* ; Young Adult

OBJECTIVES: To create a mixed valvular heart disease (MVHD)-related age-adjusted comorbidity index (MVACI) model for predicting mortality risk of patients with MVHD. METHODS: A total of 4080 patients with moderate or severe MVHD in the China-VHD study were included. The primary endpoint was 2-year all-cause mortality. A MVACI model prediction model was constructed based on the mortality risk factors identified by univariate and multivariate Cox regression analysis. Restricted cubic splines were used to assess the relationship between MVACI scores and 2-year all-cause mortality. The optimal threshold, determined by the maximum Youden index from receiver operator characteristic (ROC) curve analysis, was used to stratify patients. Kaplan-Meier method was used to calculate 2-year all-cause mortality and compared using the Log-rank test. Univariate and multivariate Cox proportional hazards models were employed to calculate hazard ratios (HR) and 95% confidence intervals (CI), evaluating the association between MVACI scores and mortality. Paired ROC curves were used to compare the discriminative ability of MVACI scores with the European System for Cardiac Operative Risk Evaluation Ⅱ(EuroSCORE Ⅱ) or the age-adjusted Charlson comorbidity index (ACCI) in predicting 2-year clinical outcomes, while calibration curves assessed the calibration of these models. Internal validation was performed using the Bootstrap method. Subgroup analyses were conducted based on etiology, treatment strategies, and disease severity. RESULTS: Multivariate analysis identified the following variables independently associated with 2-year all-cause mortality in patients: pulmonary hypertension, myocardiopathy, heart failure, low body weight (body mass index <18.5 kg/m²), anaemia, hypoalbuminemia, renal insufficiency, cancer, New York Heart Association (NYHA) class and age. The score was independently associated with the risk of all-cause mortality, and exhibited good discrimination (AUC=0.777, 95%CI: 0.755-0.799) and calibration (Brier score 0.062), with significantly better predictive performance than EuroSCORE Ⅱ or ACCI (both adjusted P<0.01). The internal validation showed that the MVACI model's predicted probability of 2-year all-cause mortality was generally consistent with the actual probability. The AUCs for predicting all-cause mortality risk were all above 0.750, and those for predicting adverse events were all above 0.630. The prognostic value of the score remained consistent in patients regardless of their etiology, therapeutic option, and disease severity. CONCLUSIONS The MVACI was constructed in this study based on age and comorbidities, and can be used for mortality risk prediction and risk stratification of MVHD patients. It is a simple algorithmic index and easy to use.
Humans ; Prognosis ; Comorbidity ; Heart Valve Diseases/epidemiology* ; Female ; Male ; Middle Aged ; Aged ; Proportional Hazards Models ; Risk Factors ; China/epidemiology* ; Age Factors ; Risk Assessment ; Adult ; ROC Curve

OBJECTIVES: To analyze the multimorbidity patterns and core diseases among hospitalized patients in different age groups and to explore the impacts of multimorbidity patterns on hospitalization costs. METHODS: Electronic medical records of adult inpatients (aged ≥18 years) from Ningbo Medical Center Lihuili Hospital between January 1, 2018, and June 30, 2023 were collected. The multimorbidity status involving 53 specific diseases was analyzed across different age groups. Association rule mining was used to identify common multimorbidity patterns. Complex network analysis was used to identify core diseases within the multimorbidity networks. Generalized estimating equations (GEE) were used to analyze the impact of different multimorbidity patterns on hospitalization costs. RESULTS: The prevalence of multimorbidity among the 359 402 adult inpatients was 38.51%, with higher rates observed in males (43.60%) and elderly patients (58.29%). Association rule mining identified 15 common multimorbidity patterns, which exhibited differences across age groups. The most prevalent multimorbidity pattern overall was "diabetes→hypertension" (support=7.04%, confidence=62.17%, lift=2.17). In the young adult group, the most prevalent pattern was "dyslipidemia→chronic liver disease" (support=1.19%, confidence=53.17%, lift=6.04). In the middle-aged group, it was "diabetes→hypertension" (support=4.84%, confidence=50.28%, lift=2.15). In the elderly group, it was "coronary heart disease, diabetes→hypertension" (support=2.38%, confidence=77.43%, lift=1.63). Complex network analysis revealed that the core diseases within multimorbidity networks differed across age groups. The core disease identified in the young adult group was chronic liver disease (degree centrality=50, betweenness centrality=0.055, closeness centrality=0.963). Core diseases in the middle-aged group included hypertension, chronic liver disease, and diabetes (all with degree centrality=52, betweenness centrality=0.022, closeness centrality=1.000). Core diseases in the elderly group comprised hypertension, diabetes, malignant tumors, chronic liver disease, thyroid disease, anemia, and arrhythmia (all with degree centrality=52, betweenness centrality=0.009, closeness centrality=1.000). Generalized estimating equations analysis indicated that, most multimorbidity patterns were significantly associated with increased hospitalization costs. However, the magnitude of cost increase varied across different multimorbidity patterns. Specifically, hospitalization costs for patients with patterns such as "heart failure→hypertension", "stroke→hypertension", "malignant tumor, diabetes→hypertension", "stroke, diabetes→hypertension", and "diabetes, heart failure→hypertension" were more than double those of patients without any target diseases. CONCLUSIONS Multimorbidity patterns and core diseases among hospitalized patients differ significantly across age groups, and different patterns exert varying impacts on hospitalization costs. These findings underscore the necessity for age-stratified and multimorbidity pattern specific management strategies.
Humans ; Multimorbidity ; Male ; Hospitalization/economics* ; Female ; Aged ; Middle Aged ; Adult ; Age Factors ; Young Adult ; Adolescent ; Diabetes Mellitus/epidemiology* ; Electronic Health Records ; Aged, 80 and over ; Hospital Costs ; China/epidemiology* ; Hypertension/economics* ; Liver Diseases/epidemiology*