Pub Date : 2024-05-17DOI: 10.1097/MD.0000000000038197
Qudsia Umaira Khan, Muneeb Ur Rehman, Mohammad Ali Arshad Abbasi, Rubina Rafique Shiekh, Munazza Nazir, S. Raja, Amna Akbar, Sabahat Tasneem, S. K. Jadoon, S. Alvi
Background: The association between allergies and cancer is contradictory, whereas some forms of cancer have inverse associations with allergies. Allergic rhinitis (AR) is the most prevalent form of allergy, and lung cancer is one of the most prevalent forms of cancer with the highest mortality rate. Recent studies have reported a positive association between asthma and lung cancer; however, this association is inconclusive. Furthermore, AR is positively associated with asthma; therefore, our research question was to explore whether there is any correlation between AR and lung cancer epidemiologically. Methods: After a rigorous search of PubMed, Google Scholar, and ScienceDirect, 7 eligible articles were included in this systematic review and meta-analysis, including 4724 cases and 9059 controls, 5 from the USA, and one each from Canada and Germany. Results: Pooled analysis (OR, 0.55; 95% CI: 0.45–0.68; P value < .00001) showed a strong inverse relationship between AR and lung cancer. Conclusion: The current meta-analysis suggests an inverse relationship between AR and lung cancer; however, new epidemiological studies are required to observe the current scenario more comprehensively.
{"title":"Correlation between allergic rhinitis or hay fever and lung cancer: A systematic review and meta-analysis","authors":"Qudsia Umaira Khan, Muneeb Ur Rehman, Mohammad Ali Arshad Abbasi, Rubina Rafique Shiekh, Munazza Nazir, S. Raja, Amna Akbar, Sabahat Tasneem, S. K. Jadoon, S. Alvi","doi":"10.1097/MD.0000000000038197","DOIUrl":"https://doi.org/10.1097/MD.0000000000038197","url":null,"abstract":"Background: The association between allergies and cancer is contradictory, whereas some forms of cancer have inverse associations with allergies. Allergic rhinitis (AR) is the most prevalent form of allergy, and lung cancer is one of the most prevalent forms of cancer with the highest mortality rate. Recent studies have reported a positive association between asthma and lung cancer; however, this association is inconclusive. Furthermore, AR is positively associated with asthma; therefore, our research question was to explore whether there is any correlation between AR and lung cancer epidemiologically. Methods: After a rigorous search of PubMed, Google Scholar, and ScienceDirect, 7 eligible articles were included in this systematic review and meta-analysis, including 4724 cases and 9059 controls, 5 from the USA, and one each from Canada and Germany. Results: Pooled analysis (OR, 0.55; 95% CI: 0.45–0.68; P value < .00001) showed a strong inverse relationship between AR and lung cancer. Conclusion: The current meta-analysis suggests an inverse relationship between AR and lung cancer; however, new epidemiological studies are required to observe the current scenario more comprehensively.","PeriodicalId":508590,"journal":{"name":"Medicine","volume":"12 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140962944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Identifying prognostic factors in elderly patients with severe coronavirus disease 2019 (COVID-19) is crucial for clinical management. Recent evidence suggests malnutrition and renal dysfunction are associated with poor outcome. This study aimed to develop a prognostic model incorporating prognostic nutritional index (PNI), estimated glomerular filtration rate (eGFR), and other parameters to predict mortality risk. This retrospective analysis included 155 elderly patients with severe COVID-19. Clinical data and outcomes were collected. Logistic regression analyzed independent mortality predictors. A joint predictor “L” incorporating PNI, eGFR, D-dimer, and lactate dehydrogenase (LDH) was developed and internally validated using bootstrapping. Decreased PNI (OR = 1.103, 95% CI: 0.78–1.169), decreased eGFR (OR = 0.964, 95% CI: 0.937–0.992), elevated D-dimer (OR = 1.001, 95% CI: 1.000–1.004), and LDH (OR = 1.005, 95% CI: 1.001–1.008) were independent mortality risk factors (all P < .05). The joint predictor “L” showed good discrimination (area under the curve [AUC] = 0.863) and calibration. The bootstrapped area under the curve was 0.858, confirming model stability. A combination of PNI, eGFR, D-dimer, and LDH provides useful prognostic information to identify elderly patients with severe COVID-19 at highest mortality risk for early intervention. Further external validation is warranted.
{"title":"The prognostic value of prognostic nutritional index and renal function indicators for mortality prediction in severe COVID-19 elderly patients: A retrospective study","authors":"Angyang Cao, Wenjun Luo, Long Wang, Jianhua Wang, Yanling Zhou, Changshun Huang, Binbin Zhu","doi":"10.1097/MD.0000000000038213","DOIUrl":"https://doi.org/10.1097/MD.0000000000038213","url":null,"abstract":"Identifying prognostic factors in elderly patients with severe coronavirus disease 2019 (COVID-19) is crucial for clinical management. Recent evidence suggests malnutrition and renal dysfunction are associated with poor outcome. This study aimed to develop a prognostic model incorporating prognostic nutritional index (PNI), estimated glomerular filtration rate (eGFR), and other parameters to predict mortality risk. This retrospective analysis included 155 elderly patients with severe COVID-19. Clinical data and outcomes were collected. Logistic regression analyzed independent mortality predictors. A joint predictor “L” incorporating PNI, eGFR, D-dimer, and lactate dehydrogenase (LDH) was developed and internally validated using bootstrapping. Decreased PNI (OR = 1.103, 95% CI: 0.78–1.169), decreased eGFR (OR = 0.964, 95% CI: 0.937–0.992), elevated D-dimer (OR = 1.001, 95% CI: 1.000–1.004), and LDH (OR = 1.005, 95% CI: 1.001–1.008) were independent mortality risk factors (all P < .05). The joint predictor “L” showed good discrimination (area under the curve [AUC] = 0.863) and calibration. The bootstrapped area under the curve was 0.858, confirming model stability. A combination of PNI, eGFR, D-dimer, and LDH provides useful prognostic information to identify elderly patients with severe COVID-19 at highest mortality risk for early intervention. Further external validation is warranted.","PeriodicalId":508590,"journal":{"name":"Medicine","volume":"51 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140965578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.1016/j.mpmed.2023.12.002
S. Nayee, Martyn Ormond, Jeremy D. Sanderson, Michael P. Escudier
{"title":"Disorders of the mouth","authors":"S. Nayee, Martyn Ormond, Jeremy D. Sanderson, Michael P. Escudier","doi":"10.1016/j.mpmed.2023.12.002","DOIUrl":"https://doi.org/10.1016/j.mpmed.2023.12.002","url":null,"abstract":"","PeriodicalId":508590,"journal":{"name":"Medicine","volume":"188 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139827398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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