Hereditary fibrosing poikiloderma with tendon contractures, myopathy, and pulmonary fibrosis (POIKTMP) is a rare autosomal dominant genetic disorder. It may also involve many other organ systems, leading to complications such as exocrine pancreatic insufficiency, liver dysfunction, lymphedema, and developmental delay. The FAM111B has been determined as the pathogenic gene associated with POIKTMP syndrome, whose protein product plays a critical role in regulating essential cellular processes including DNA repair and replication, cell cycle progression, apoptosis, nuclear transport, and telomere length maintenance. This article has provided a comprehensive review for the genetic basis of POIKTMP syndrome and its correlation with various phenotypes, which may offer insights for basic research and clinical diagnosis of this disease.
Humans ; Pulmonary Fibrosis/genetics* ; Skin Diseases, Genetic/genetics*

Introduction: The growing popularity of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) for weight management has inadvertently perpetuated demand for unregulated experimental peptides procured through gray markets. Retatrutide, a novel triple GLP-1/glucose-dependent insulinotropic polypeptide (GIP)/glucagon receptor agonist undergoing Phase III trials; AOD -9604, an abandoned synthetic human growth hormone fragment; and tesamorelin, a synthetic GHRH analogue, are increasingly self-administered without medical supervision. Their combined metabolic and thromboembolic risks remain unknown and unreported. Case: A 50-year-old Malaysian female with morbid obesity and poorly controlled type 2 diabetes mellitus (hemoglobin A1c 13%) presented with acute dyspnea, chest tightness, syncope, and cardiogenic shock. Three weeks prior, she had self-initiated subcutaneous retatrutide, AOD-9604, and tesamorelin procured through unregulated online platforms, achieving rapid weight loss of 10 kg. Despite markedly reduced oral intake from GLP-1-mediated gastrointestinal side effects, she continued her prescribed high-dose insulin regimen and sodium-glucose cotransporter-2 (SGLT2) inhibitor without dose adjustment. She developed concurrent diabetic ketoacidosis, confirmed biochemically, alongside massive saddle pulmonary embolism with right ventricular strain on echocardiography and computed tomography pulmonary angiography. She was successfully treated with systemic thrombolysis using alteplase, guideline-directed diabetic ketoacidosis management including fixed-rate insulin infusion and fluid resuscitation, and anticoagulation. The SGLT2 inhibitor was withheld throughout admission. She was discharged on rivaroxaban with counseling to cease all unregulated compounds. All three agents were submitted to the National Pharmaceutical Regulatory Authority/Malaysian Adverse Drug Reactions Advisory Committee for adverse drug reaction reporting. Conclusion To our knowledge, this is the first reported case of concurrent massive pulmonary embolism and diabetic ketoacidosis precipitated by unsupervised gray-market retatrutide, AOD-9604, and tesamorelin. Clinicians should enquire about unregistered supplement use, counsel insulin-dependent patients on sick-day rules when appetitesuppressing agents are initiated, and report adverse events to pharmacovigilance authorities.
AOD 9604 ; tesamorelin ; Diabetic Ketoacidosis ; Pulmonary Embolism ; Peptides

BACKGROUND AND OBJECTIVE

Medication errors pose substantial risks in hospitals, particularly concerning patient safety. These errors, occurring throughout the medication use process, are one of the most common causes of morbidity and mortality in clinical practice. In the Philippines, there is a lack of evidence on the prevalence and effects of medication errors, emphasizing the need for further investigation. This study evaluated the prescribing, transcribing, and monitoring errors among inpatients under the Pulmonary Medicine Service of the Department of Medicine in the Philippine General Hospital.

This cross-sectional retrospective records review used the total population purposive sampling technique to examine eligible charts of inpatients with asthma and/or COPD from August 1 to December 31, 2022. The frequency, type, and severity of medication errors were determined. Linear regression and Cox proportional hazards models were used to examine the relationship between patient-related factors and medication errors, and length of hospital stay and mortality.

Fifty (50) out of 226 medical records were processed and analyzed. Included patients were predominantly older male adults. More than two-thirds of the patients were diagnosed with COPD while approximately one-fourth suffered from asthma. All patients were practicing polypharmacy and the vast majority presented with comorbidities. A total of 6,517 medication errors, predominantly prescribing errors (99.1%), were identified. Despite the high prevalence of medication errors, the majority were classified as “error, no harm” (98.8%), while only 1.17% were deemed as “error, harm.” As the frequency of prescribing errors increases in the power of three (rough approximation of e), from 1 to 3 to 9 to 27, etc., the expected hospital stay increases by 2.078 days (pCONCLUSION

All eligible patient charts had at least one medication error, with the majority being prescribing errors. Among the variables, prescribing errors significantly affected the length of stay, while severity of transcribing errors had a marginally significant effect. It is essential to develop comprehensive education and training initiatives and adopt a systematic approach to mitigate medication errors and promote patient safety.

INTRODUCTION

It is anticipated that Chronic Obstructive Pulmonary Disease (COPD) has greater risk in acquiring COVID-19 infection and poorer outcome. However, current worldwide data are conflicting.

This study primarily aims to compare the outcomes of COVID-19 patients with COPD and those without COPD in terms of length of hospital stay (LOS), recovery or mortality, treatment received, and predictors of mortality.

This is a retrospective cohort chart review of 1,017 admitted adult COVID-19 patients from July to December 2020. Age, gender, smoking status, current control and medications for COPD, COVID-19 severity, symptoms, treatment, and outcomes of the two study groups were compared.

Prevalence rate of COPD was 3.8%. COVID-19 patients with COPD were older (median age of 69 vs 54, pCONCLUSION

COPD increases the risk for severe COVID-19 and lengthens LOS.

Real-time acquisition of pulmonary ventilation and perfusion information through thoracic electrical impedance tomography (EIT) holds significant clinical value. This study proposes a novel method based on the rime (RIME) algorithm-optimized variational mode decomposition (VMD) to separate lung ventilation and perfusion signals directly from raw voltage data prior to EIT image reconstruction, enabling independent imaging of both parameters. To validate this approach, EIT data were collected from 16 healthy volunteers under normal breathing and inspiratory breath-holding conditions. The RIME algorithm was employed to optimize VMD parameters by minimizing envelope entropy as the fitness function. The optimized VMD was then applied to separate raw data across all measurement channels in EIT, with spectral analysis identifying relevant components to reconstruct ventilation and perfusion signals. Results demonstrated that the structural similarity index (SSIM) between perfusion images derived from normal breathing and breath-holding states averaged approximately 84% across all 16 subjects, significantly outperforming traditional frequency-domain filtering methods in perfusion imaging accuracy. This method offers a promising technical advancement for real-time monitoring of pulmonary ventilation and perfusion, holding significant value for advancing the clinical application of EIT in the diagnosis and treatment of respiratory diseases.
Humans ; Electric Impedance ; Algorithms ; Tomography/methods* ; Pulmonary Ventilation/physiology* ; Lung/diagnostic imaging* ; Image Processing, Computer-Assisted/methods* ; Adult

Electrical impedance tomography (EIT) is a new non-invasive functional imaging technology, which has the advantages of non-invasion, non-radiation, low cost, fast response, portability and visualization. In recent years, more and more studies have shown that EIT has great potential in the detection of lung diseases and has been applied to early diagnosis and treatment of some diseases. This paper introduced the basic principle of EIT, discussed the research and clinical application of EIT in the detection of acute respiratory distress syndrome, chronic obstructive pulmonary disease, pneumothorax and pulmonary embolism, and focused on the summary and introduction of indicators and functional images of EIT related to the detection of lung diseases. This review will help medical workers understand and use EIT, and promote the further development of EIT in lung diseases as well as other fields.
Humans ; Electric Impedance ; Tomography/methods* ; Lung Diseases/diagnosis* ; Pulmonary Disease, Chronic Obstructive/diagnosis* ; Pulmonary Embolism/diagnosis* ; Respiratory Distress Syndrome/diagnosis*

Lung cancer is the leading cause of cancer-related deaths worldwide. Radiation pneumonitis is a major complication in lung cancer radiotherapy. Four-dimensional computed tomography (4DCT) imaging provides dynamic ventilation information, which is valuable for lung function assessment and radiation pneumonitis prevention. Many methods have been developed to calculate lung ventilation from 4DCT, but a systematic comparison is lacking. Prediction of radiation pneumonitis using 4DCT-based ventilation is still in an early stage, and no comprehensive review exists. This paper presented the first systematic comparison of functional lung ventilation algorithms based on 4DCT over the past 15 years, highlighting their clinical value and limitations. It then reviewed multimodal approaches combining 4DCT ventilation imaging, dose metrics, and clinical data for radiation pneumonitis prediction. Finally, it summarized current research and future directions of 4DCT in lung cancer radiotherapy, offering insights for clinical practice and further studies.
Humans ; Lung Neoplasms/diagnostic imaging* ; Four-Dimensional Computed Tomography/methods* ; Radiation Pneumonitis/etiology* ; Algorithms ; Lung/radiation effects* ; Pulmonary Ventilation

Mechanical ventilation (MV) is currently widely used in the treatment of respiratory failure and anesthesia surgery, and is a commonly used respiratory support method for critically ill patients; however, improper usage of MV can lead to ventilator-induced lung injury (VILI), which poses a significant threat to patient life. Alveolar epithelial cell (AEC) has the functions of mechanosensation and mechanotransduction. Physiological mechanical stretching is beneficial for maintaining the lineage homeostasis and normal physiological functions of AEC cells, while excessive mechanical stretching can cause damage to AEC cells. Damage to AEC cells is an important aspect in the occurrence and development of VILI. Understanding the effects of mechanical stretching on AEC cells is crucial for developing safe and effective MV strategies, preventing the occurrence of VILI, and improving the clinical prognosis of VILI patients. From the perspective of cell mechanics, this paper aims to briefly elucidate the mechanical properties of AEC cells, mechanosensation and mechanotransduction of mechanical stretching in AEC cells, and the injury and repair of AEC cells under mechanical stretch stimulation, and potential mechanisms with the goal of helping clinical doctors better understand the pathophysiological mechanism of VILI caused by MV, improve their understanding of VILI, provide safer and more effective strategies for the use of clinical MV, and provide theoretical basis for the prevention and treatment of VILI.
Humans ; Mechanotransduction, Cellular ; Ventilator-Induced Lung Injury ; Stress, Mechanical ; Alveolar Epithelial Cells ; Respiration, Artificial/adverse effects* ; Epithelial Cells ; Pulmonary Alveoli/cytology* ; Animals

OBJECTIVE: To explore the risk factors affecting the prognosis of patients with sepsis complicated with acute pulmonary embolism, and to construct and validate a nomogram predictive model for in-hospital mortality risk. METHODS: Based on the American Medical Information Mart for Intensive Care (MIMIC-III, MIMIC-IV) databases, the data were collected on patients with sepsis complicated with acute pulmonary embolism from 2001 to 2019, including baseline characteristics, and vital signs, disease scores, laboratory tests within 24 hours of admission to the intensive care unit (ICU), and interventions. In-hospital mortality was the outcome event. The total samples were divided into training and testing sets in a 7:3 ratio by random sampling. Univariate Cox regression analysis was used to verify the impact of all variables on the risk of in-hospital mortality, thereby screen potential influencing factors. Subsequently, a stepwise bi-directional regression method was applied to select factors one by one, leading to the construction of a nomogram prediction model. Collinearity testing was used to demonstrate the absence of strong multicollinearity among the influencing factors in the nomogram prediction model. The discrimination of the nomogram model, sequential organ failure assessment (SOFA), and simplified pulmonary embolism severity index (sPESI) was evaluated using C-index in the test set. Receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of various models for in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism. RESULTS: A total of 562 patients with sepsis complicated with acute pulmonary embolism were included, including 393 in the training set and 169 in the testing set. Univariate Cox regression analysis showed that 30 factors associated with in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism. Through stepwise bi-directional regression, 12 variables were ultimately selected, including gender, presence of malignant tumors, body temperature, red cell distribution width (RDW), blood urea nitrogen (BUN), serum potassium, prothrombin time (PT), 24-hour urine output, mechanical ventilation, vasoactive drugs, warfarin use, and sepsis-induced coagulopathy (SIC). Collinearity testing indicated no strong multicollinearity among the influencing factors [all variance inflation factor (VIF) > 10]. A nomogram model was constructed using the 12 variables mentioned above. The nomogram model predicted the C-index and its 95% confidence interval (95%CI) of in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism better than SOFA score and sPESI [0.771 (0.725-0.816) vs. 0.579 (0.519-0.639), 0.608 (0.554-0.663)]. The ROC curve showed that the area under the curve (AUC) and its 95%CI of the nomogram model were higher than those of the SOFA score and sPESI [0.811 (0.766-0.857) vs. 0.630 (0.568-0.691), 0.623 (0.566-0.680)]. These findings were consistently replicated in the internal validation of the testing set. In both the training and testing sets, Delong's test showed that the AUC of the nomogram model was significantly higher than the SOFA score and sPESI (both P < 0.05). CONCLUSION The nomogram model demonstrated good predictive effectiveness for the risk of in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism, enabling clinicians to predict mortality risk in advance and take timely interventions to reduce mortality.
Humans ; Pulmonary Embolism/mortality* ; Hospital Mortality ; Nomograms ; Sepsis/complications* ; Prognosis ; Risk Factors ; Intensive Care Units ; Male ; Female ; Middle Aged ; Aged

PANoptosis is a newly defined type of programmed cell death (PCD), which is triggered by a variety of stimuli and covers three known forms of PCD: apoptosis, pyroptosis and necroptosis. In physiological state, cell death plays an important protective role against pathogen invasion, but its over-activation may aggravate inflammatory response and cause tissue damage. Studies have shown that the occurrence and progression of acute lung injury/acute respiratory distress syndrome (ALI/ARDS), asthma, chronic obstructive pulmonary disease (COPD) and other lung diseases are closely related to PANoptosis. The purpose of this review is to deeply explore the molecular mechanism of PANoptosis and its regulatory factors in lung diseases, in order to discover potential therapeutic targets and provide new targets and innovative ideas for clinical treatment for lung diseases.
Humans ; Lung Diseases ; Apoptosis ; Pyroptosis ; Pulmonary Disease, Chronic Obstructive ; Necroptosis ; Acute Lung Injury