1
|
Li Y, Yin X, Shi B, Li J. Surgical Management of Airway Obstruction following Posterior Pharyngeal Flap. Plast Reconstr Surg 2025; 155:365e-376e. [PMID: 38652864 DOI: 10.1097/prs.0000000000011486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2024]
Abstract
BACKGROUND The posterior pharyngeal flap (PPF) is effective in managing velopharyngeal insufficiency but is associated with airway obstruction risk. This study compared the effectiveness and complications of 2 PPF revision procedures and screened potential prognostic factors to postoperative hypernasality and persistent obstruction. METHODS Patients who received flap division (FD) or port enlargement (PE) for airway obstruction following PPF were reviewed. Ventilation status was assessed using the Nasal Obstruction Symptom Evaluation scale, and velopharyngeal closure was assessed using subjective speech evaluation and nasopharyngoscopy. The effectiveness of ventilation relief and complication rate (hypernasality and persistent obstruction) of the 2 techniques were compared. A comprehensive panel of factors-including age, velopharyngeal mobility, obstruction laterality, body mass index, jaw relationship, and adenoid hypertrophy-was evaluated for correlation with complications. RESULTS A total of 79 patients were enrolled, with 51 undergoing FD and 28 undergoing PE. Both techniques significantly improved ventilation dysfunction and hyponasality. Mild hypernasality occurred in 10 cases in the FD group and 3 in the PE group. Age at surgery was significantly associated with persistent obstruction after PPF revision. The occurrence of persistent obstruction was significantly higher among patients younger than 12 years than those older than 12 years. Obstruction laterality was suggested in significant correlation with hypernasality after PPF revision. Among patients with unilateral port obstruction, the occurrence of hypernasality after FD was significantly higher than after PE. CONCLUSIONS Both flap division and port enlargement are effective revision procedures to relieve airway obstruction after PPF. Patients younger than 12 years are more likely to experience persistent ventilation problems after PPF revision. CLINICAL QUESTION/LEVEL OF EVIDENCE Therapeutic, II.
Collapse
Affiliation(s)
- Yanan Li
- From the State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases
- Departments of Oral and Maxillofacial Surgery
| | - Xing Yin
- From the State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases
- Orthodontics, West China Hospital of Stomatology, Sichuan University
| | - Bing Shi
- From the State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases
- Departments of Oral and Maxillofacial Surgery
| | - Jingtao Li
- From the State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases
- Departments of Oral and Maxillofacial Surgery
| |
Collapse
|
2
|
Yang B, Li J, Feng D, Gong J, Yang Y, Cai X, Huang S, Suen LKP, Gao P, Wa Q, Zhou J. Latent profiles and determinants of postoperative sleep quality in elective surgery patients. Sci Rep 2025; 15:617. [PMID: 39753664 PMCID: PMC11698858 DOI: 10.1038/s41598-024-84896-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Accepted: 12/29/2024] [Indexed: 01/06/2025] Open
Abstract
It is crucial to determine the potential subgroups of sleep disturbances in patients undergoing elective surgery based on the importance of symptom clusters and individual characteristics in order to develop targeted symptom management plans. This study explored the potential categories of postoperative sleep disturbances in patients undergoing elective surgery through latent profile analysis, and explored the influencing factors of each category. A total of 400 eligible elective surgery patients were included in the analysis, and three potential subgroups were identified: mild sleep disturbance group (c1 = 140,35.0%), moderate sleep sleep disturbance group (c2 = 177,44.2%), and severe sleep disturbance group (c3 = 83,20.8%). It was found that the higher the BMI, the greater the probability of patients belonging to the moderate sleep disturbance group (OR = 1.114, P = 0.002) and the severe sleep disturbance group (OR = 1.258, P < 0.001),the longer the duration of anesthesia the greater the likelihood of patients belonging to the severe sleep disturbance group (OR = 1.004,P = 0.011), the greater the pain the greater the probability of patients belonging to the moderate sleep disturbance group (OR = 1.590,P < 0.001) and severe sleep disturbance group (OR = 1.785,P < 0.001), and the higher the anxiety level the greater the probability that patients were in the moderate sleep disturbance group (OR = 1.135,P = 0.007) and severe sleep disturbance group (OR = 1.261,P < 0.001).
Collapse
Affiliation(s)
- Binxu Yang
- The Second Affiliated Hospital of ZunYi Medical University, Zunyi, Guizhou, China
| | - Jingjing Li
- The Second Affiliated Hospital of ZunYi Medical University, Zunyi, Guizhou, China
| | - Dan Feng
- The Second Affiliated Hospital of ZunYi Medical University, Zunyi, Guizhou, China
| | - Jing Gong
- The Second Affiliated Hospital of ZunYi Medical University, Zunyi, Guizhou, China
| | - Yifei Yang
- The Second Affiliated Hospital of ZunYi Medical University, Zunyi, Guizhou, China
| | - Xusihong Cai
- The Second Affiliated Hospital of ZunYi Medical University, Zunyi, Guizhou, China
| | - Shuwen Huang
- The Second Affiliated Hospital of ZunYi Medical University, Zunyi, Guizhou, China
| | - Lorna Kwai Ping Suen
- School of Nursing, Tung Wah College, Homantin, Hong Kong Special Administrative Region, Hong Kong, China
| | - Puzhong Gao
- The Second Affiliated Hospital of ZunYi Medical University, Zunyi, Guizhou, China
| | - Qingde Wa
- The Second Affiliated Hospital of ZunYi Medical University, Zunyi, Guizhou, China.
| | - Jing Zhou
- The Second Affiliated Hospital of ZunYi Medical University, Zunyi, Guizhou, China.
- Nursing School, Zunyi Medical University, Zunyi, China.
| |
Collapse
|
3
|
Power GM, Sanderson E, Pagoni P, Fraser A, Morris T, Prince C, Frayling TM, Heron J, Richardson TG, Richmond R, Tyrrell J, Warrington N, Davey Smith G, Howe LD, Tilling KM. Methodological approaches, challenges, and opportunities in the application of Mendelian randomisation to lifecourse epidemiology: A systematic literature review. Eur J Epidemiol 2024; 39:501-520. [PMID: 37938447 PMCID: PMC7616129 DOI: 10.1007/s10654-023-01032-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 07/21/2023] [Indexed: 11/09/2023]
Abstract
Diseases diagnosed in adulthood may have antecedents throughout (including prenatal) life. Gaining a better understanding of how exposures at different stages in the lifecourse influence health outcomes is key to elucidating the potential benefits of disease prevention strategies. Mendelian randomisation (MR) is increasingly used to estimate causal effects of exposures across the lifecourse on later life outcomes. This systematic literature review explores MR methods used to perform lifecourse investigations and reviews previous work that has utilised MR to elucidate the effects of factors acting at different stages of the lifecourse. We conducted searches in PubMed, Embase, Medline and MedRXiv databases. Thirteen methodological studies were identified. Four studies focused on the impact of time-varying exposures in the interpretation of "standard" MR techniques, five presented methods for repeat measures of the same exposure, and four described methodological approaches to handling multigenerational exposures. A further 127 studies presented the results of an applied research question. Over half of these estimated effects in a single generation and were largely confined to the exploration of questions regarding body composition. The remaining mostly estimated maternal effects. There is a growing body of research focused on the development and application of MR methods to address lifecourse research questions. The underlying assumptions require careful consideration and the interpretation of results rely on select conditions. Whilst we do not advocate for a particular strategy, we encourage practitioners to make informed decisions on how to approach a research question in this field with a solid understanding of the limitations present and how these may be affected by the research question, modelling approach, instrument selection, and data availability.
Collapse
Affiliation(s)
- Grace M Power
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
| | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Panagiota Pagoni
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Tim Morris
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK
| | - Claire Prince
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Timothy M Frayling
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Jon Heron
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Tom G Richardson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Rebecca Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Jessica Tyrrell
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Nicole Warrington
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- Frazer Institute, University of Queensland, Woolloongabba, Queensland, Australia
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- NIHR Bristol Biomedical Research Centre Bristol, University Hospitals Bristol and Weston NHS Foundation Trust, University of Bristol, Bristol, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Kate M Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| |
Collapse
|
4
|
Tian H, Tom BDM, Burgess S. A data-adaptive method for investigating effect heterogeneity with high-dimensional covariates in Mendelian randomization. BMC Med Res Methodol 2024; 24:34. [PMID: 38341532 PMCID: PMC10858611 DOI: 10.1186/s12874-024-02153-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/17/2024] [Indexed: 02/12/2024] Open
Abstract
BACKGROUND Mendelian randomization is a popular method for causal inference with observational data that uses genetic variants as instrumental variables. Similarly to a randomized trial, a standard Mendelian randomization analysis estimates the population-averaged effect of an exposure on an outcome. Dividing the population into subgroups can reveal effect heterogeneity to inform who would most benefit from intervention on the exposure. However, as covariates are measured post-"randomization", naive stratification typically induces collider bias in stratum-specific estimates. METHOD We extend a previously proposed stratification method (the "doubly-ranked method") to form strata based on a single covariate, and introduce a data-adaptive random forest method to calculate stratum-specific estimates that are robust to collider bias based on a high-dimensional covariate set. We also propose measures based on the Q statistic to assess heterogeneity between stratum-specific estimates (to understand whether estimates are more variable than expected due to chance alone) and variable importance (to identify the key drivers of effect heterogeneity). RESULT We show that the effect of body mass index (BMI) on lung function is heterogeneous, depending most strongly on hip circumference and weight. While for most individuals, the predicted effect of increasing BMI on lung function is negative, it is positive for some individuals and strongly negative for others. CONCLUSION Our data-adaptive approach allows for the exploration of effect heterogeneity in the relationship between an exposure and an outcome within a Mendelian randomization framework. This can yield valuable insights into disease aetiology and help identify specific groups of individuals who would derive the greatest benefit from targeted interventions on the exposure.
Collapse
Affiliation(s)
- Haodong Tian
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
| | - Brian D M Tom
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| |
Collapse
|
5
|
Sadiqa A, Khalid A, Islam A. Physiological association of the breakpoint with the duration of hyperventilation. Saudi Med J 2023; 44:995-999. [PMID: 37777273 PMCID: PMC10541987 DOI: 10.15537/smj.2023.44.10.20230358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 08/24/2023] [Indexed: 10/02/2023] Open
Abstract
OBJECTIVES To determine the relationship of body mass index (BMI) with breath-holding time (BHT) as well as that of BHT with the duration of hyperventilation (DOH) in young healthy adults. METHODS An observational study was performed at Shalamar Medical and Dental College, Lahore, Pakistan, between May 2021 and June 2022. Healthy first-year Bachelor of Medicine, Bachelor of Surgery students aged 18-22 years, with a normal BMI were included. Spirometric measurements were taken through a spirometer pod connected to a pneumotachometer (model: Power Lab 26T). Body mass index was calculated as the weight (kg) to height (m2) ratio. Pearson correlation, linear regression, and t tests were applied using SPSS. RESULTS A total of 101 subjects participated, comprising of 44 men and 57 women. A weak negative association was found between BMI and BHT in all subjects (r= -0.08, p=0.34), in men (r= -0.24, p=0.11), and in women (r= -0.092, p=0.497). Furthermore, a strong association was observed between BHT and DOH in all subjects (r=0.64, p=0.000), in men (r=0.604, p=0.000), and in women (r=0.518, p=0.000). Moreover, a nonsignificant weak inverse linear regression was found between the BMI and BHT of all subjects (β= -0.087, p=0.38), of men (β= -0.241, p=0.11), and of women (β= -0.092, p=0.49). Lastly, a significantly strong positive regression was observed between the BHT and DOH of all subjects (β=0.637, p=0.000), of men (β=0.604, p=0.000), and of women (β=0.518, p=0.000). CONCLUSION No association was found between BMI and BHT. A strong positive association was observed between BHT and DOH in all healthy young people.
Collapse
Affiliation(s)
- Ayesha Sadiqa
- From the Physiology Department (Sadiqa), CMH Lahore Medical College and Institute of Dentistry,; and from thePhysiology Department (Khalid, Abdullah)), Shalamar Medical and Dental College, Lahore, Pakistan.
| | - Ambreen Khalid
- From the Physiology Department (Sadiqa), CMH Lahore Medical College and Institute of Dentistry,; and from thePhysiology Department (Khalid, Abdullah)), Shalamar Medical and Dental College, Lahore, Pakistan.
| | - Abdullah Islam
- From the Physiology Department (Sadiqa), CMH Lahore Medical College and Institute of Dentistry,; and from thePhysiology Department (Khalid, Abdullah)), Shalamar Medical and Dental College, Lahore, Pakistan.
| |
Collapse
|
6
|
Agustí A, Melén E, DeMeo DL, Breyer-Kohansal R, Faner R. Pathogenesis of chronic obstructive pulmonary disease: understanding the contributions of gene-environment interactions across the lifespan. THE LANCET. RESPIRATORY MEDICINE 2022; 10:512-524. [PMID: 35427533 PMCID: PMC11428195 DOI: 10.1016/s2213-2600(21)00555-5] [Citation(s) in RCA: 153] [Impact Index Per Article: 51.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 11/08/2021] [Accepted: 12/06/2021] [Indexed: 12/31/2022]
Abstract
The traditional view of chronic obstructive pulmonary disease (COPD) as a self-inflicted disease caused by tobacco smoking in genetically susceptible individuals has been challenged by recent research findings. COPD can instead be understood as the potential end result of the accumulation of gene-environment interactions encountered by an individual over the life course. Integration of a time axis in pathogenic models of COPD is necessary because the biological responses to and clinical consequences of different exposures might vary according to both the age of an individual at which a given gene-environment interaction occurs and the cumulative history of previous gene-environment interactions. Future research should aim to understand the effects of dynamic interactions between genes (G) and the environment (E) by integrating information from basic omics (eg, genomics, epigenomics, proteomics) and clinical omics (eg, phenomics, physiomics, radiomics) with exposures (the exposome) over time (T)-an approach that we refer to as GETomics. In the context of this approach, we argue that COPD should be viewed not as a single disease, but as a clinical syndrome characterised by a recognisable pattern of chronic symptoms and structural or functional impairments due to gene-environment interactions across the lifespan that influence normal lung development and ageing.
Collapse
Affiliation(s)
- Alvar Agustí
- Càtedra Salut Respiratòria, Universitat Barcelona, Barcelona, Spain; Respiratory Institute, Hospital Clinic, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Barcelona, Spain
| | - Erik Melén
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden; Sachs' Children and Youth Hospital, Södersjukhuset, Stockholm, Sweden
| | - Dawn L DeMeo
- Channing Division of Network Medicine, and Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Robab Breyer-Kohansal
- Ludwig Boltzmann Institute for Lung Health, Vienna, Austria; Department of Respiratory and Critical Care Medicine, Clinic Penzing, Vienna, Austria
| | - Rosa Faner
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Barcelona, Spain.
| |
Collapse
|
7
|
Probst-Hensch N, Bochud M, Chiolero A, Crivelli L, Dratva J, Flahault A, Frey D, Kuenzli N, Puhan M, Suggs LS, Wirth C. Swiss Cohort & Biobank - The White Paper. Public Health Rev 2022; 43:1605660. [PMID: 36619237 PMCID: PMC9817110 DOI: 10.3389/phrs.2022.1605660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- Nicole Probst-Hensch
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland
- University of Basel, Basel, Switzerland
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- *Correspondence: Nicole Probst-Hensch,
| | - Murielle Bochud
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Department of Epidemiology and Health Systems (DESS), University Center for General Medicine and Public Health (Unisanté), Lausanne, Switzerland
| | - Arnaud Chiolero
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
| | - Luca Crivelli
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Department of Business Economics, Health and Social Care, University of Applied Sciences and Arts of Southern Switzerland, Manno, Switzerland
- Institute of Public Health Università della Svizzera Italiana, Lugano, Switzerland
| | - Julia Dratva
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Institute of Public Health, Department of Health Sciences, ZHAW Zürich University of Applied Sciences, Winterthur, Switzerland
| | - Antoine Flahault
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Daniel Frey
- Swiss Society for Public Health, Bern, Switzerland
| | - Nino Kuenzli
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland
- University of Basel, Basel, Switzerland
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
| | - Milo Puhan
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, Zurich, Switzerland
| | - L. Suzanne Suggs
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Institute of Public Health Università della Svizzera Italiana, Lugano, Switzerland
| | - Corina Wirth
- Swiss Society for Public Health, Bern, Switzerland
| |
Collapse
|