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Chan LE, Casiraghi E, Reese J, Harmon QE, Schaper K, Hegde H, Valentini G, Schmitt C, Motsinger-Reif A, Hall JE, Mungall CJ, Robinson PN, Haendel MA. Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests. Int J Med Inform 2024; 187:105461. [PMID: 38643701 PMCID: PMC11188727 DOI: 10.1016/j.ijmedinf.2024.105461] [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: 09/11/2023] [Revised: 04/09/2024] [Accepted: 04/16/2024] [Indexed: 04/23/2024]
Abstract
OBJECTIVE Female reproductive disorders (FRDs) are common health conditions that may present with significant symptoms. Diet and environment are potential areas for FRD interventions. We utilized a knowledge graph (KG) method to predict factors associated with common FRDs (for example, endometriosis, ovarian cyst, and uterine fibroids). MATERIALS AND METHODS We harmonized survey data from the Personalized Environment and Genes Study (PEGS) on internal and external environmental exposures and health conditions with biomedical ontology content. We merged the harmonized data and ontologies with supplemental nutrient and agricultural chemical data to create a KG. We analyzed the KG by embedding edges and applying a random forest for edge prediction to identify variables potentially associated with FRDs. We also conducted logistic regression analysis for comparison. RESULTS Across 9765 PEGS respondents, the KG analysis resulted in 8535 significant or suggestive predicted links between FRDs and chemicals, phenotypes, and diseases. Amongst these links, 32 were exact matches when compared with the logistic regression results, including comorbidities, medications, foods, and occupational exposures. DISCUSSION Mechanistic underpinnings of predicted links documented in the literature may support some of our findings. Our KG methods are useful for predicting possible associations in large, survey-based datasets with added information on directionality and magnitude of effect from logistic regression. These results should not be construed as causal but can support hypothesis generation. CONCLUSION This investigation enabled the generation of hypotheses on a variety of potential links between FRDs and exposures. Future investigations should prospectively evaluate the variables hypothesized to impact FRDs.
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Affiliation(s)
- Lauren E Chan
- Oregon State University, College of Public Health and Human Sciences, Corvallis, OR, USA.
| | - Elena Casiraghi
- AnacletoLab, Dipartimento di Informatica, Università degli Studi di Milano, Italy; Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA; European Laboratory for Learning and Intelligent Systems, ELLIS
| | - Justin Reese
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Quaker E Harmon
- National Institute of Environmental Health Sciences, Epidemiology Branch, Durham, NC, USA
| | - Kevin Schaper
- University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Harshad Hegde
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Giorgio Valentini
- AnacletoLab, Dipartimento di Informatica, Università degli Studi di Milano, Italy; European Laboratory for Learning and Intelligent Systems, ELLIS
| | - Charles Schmitt
- National Institute of Environmental Health Sciences, Office of Data Science, Durham, NC, USA
| | - Alison Motsinger-Reif
- National Institute of Environmental Health Sciences, Biostatistics & Computational Biology Branch, Durham, NC, USA
| | - Janet E Hall
- National Institute of Environmental Health Sciences, Clinical Research Branch, Durham, NC, USA
| | - Christopher J Mungall
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Peter N Robinson
- European Laboratory for Learning and Intelligent Systems, ELLIS; The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT, USA
| | - Melissa A Haendel
- University of North Carolina, Dept. of Genetics, Chapel Hill, NC, USA
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Chan LE, Casiraghi E, Putman T, Reese J, Harmon QE, Schaper K, Hedge H, Valentini G, Schmitt C, Motsinger-Reif A, Hall JE, Mungall CJ, Robinson PN, Haendel MA. Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.14.23292679. [PMID: 37502882 PMCID: PMC10371183 DOI: 10.1101/2023.07.14.23292679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Objective Female reproductive disorders (FRDs) are common health conditions that may present with significant symptoms. Diet and environment are potential areas for FRD interventions. We utilized a knowledge graph (KG) method to predict factors associated with common FRDs (e.g., endometriosis, ovarian cyst, and uterine fibroids). Materials and Methods We harmonized survey data from the Personalized Environment and Genes Study on internal and external environmental exposures and health conditions with biomedical ontology content. We merged the harmonized data and ontologies with supplemental nutrient and agricultural chemical data to create a KG. We analyzed the KG by embedding edges and applying a random forest for edge prediction to identify variables potentially associated with FRDs. We also conducted logistic regression analysis for comparison. Results Across 9765 PEGS respondents, the KG analysis resulted in 8535 significant predicted links between FRDs and chemicals, phenotypes, and diseases. Amongst these links, 32 were exact matches when compared with the logistic regression results, including comorbidities, medications, foods, and occupational exposures. Discussion Mechanistic underpinnings of predicted links documented in the literature may support some of our findings. Our KG methods are useful for predicting possible associations in large, survey-based datasets with added information on directionality and magnitude of effect from logistic regression. These results should not be construed as causal, but can support hypothesis generation. Conclusion This investigation enabled the generation of hypotheses on a variety of potential links between FRDs and exposures. Future investigations should prospectively evaluate the variables hypothesized to impact FRDs.
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Affiliation(s)
- Lauren E Chan
- Oregon State University, College of Public Health and Human Sciences, Corvallis, OR, USA
| | - Elena Casiraghi
- AnacletoLab, Dipartimento di Informatica, Università degli Studi di Milano, Italy
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Tim Putman
- University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Justin Reese
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Quaker E Harmon
- National Institute of Environmental Health Sciences, Epidemiology Branch, Durham, NC, USA
| | - Kevin Schaper
- University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Harshad Hedge
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Giorgio Valentini
- AnacletoLab, Dipartimento di Informatica, Università degli Studi di Milano, Italy
| | - Charles Schmitt
- National Institute of Environmental Health Sciences, Office of Data Science, Durham, NC, USA
| | - Alison Motsinger-Reif
- National Institute of Environmental Health Sciences, Biostatistics & Computational Biology Branch, Durham, NC, USA
| | - Janet E Hall
- National Institute of Environmental Health Sciences, Clinical Research Branch, Durham, NC, USA
| | - Christopher J Mungall
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Peter N Robinson
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT, USA
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Comparison of Laparoscopy and Laparotomy Results for Benign Ovarian Tumors. JOURNAL OF CONTEMPORARY MEDICINE 2022. [DOI: 10.16899/jcm.1123262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Abstract
Objectives: To present the data generated at our hospital by comparing the operative characteristics and surgical results of patients who applied to the clinic and emergency room due to ovarian cyst and underwent laparoscopy or laparotomy.
Materials and Methods: In this retrospective study, patients who underwent cystectomy, oophorectomy, and hysterectomy salpingo-oophorectomy due to ovarian cysts were compared in two groups, comprising laparoscopy and laparotomy. Evaluated retrospectively in this study were 443 patients operated on due to benign ovarian cyst diagnosis. Data in the patient files were analyzed in terms of age, cyst size, postoperative hemoglobin, postoperative white blood cell count, operating time, hospital stay, and surgical site infection.
Results: Postoperative surgical site infection was significantly higher in the laparotomy group. The risk of surgical site infection was RR= 4. 5 (1.74–11.67) times higher in those who underwent laparotomy when compared to laparoscopy. The duration of hospital stay was lower in the laparoscopy group for all operation types (oophorectomy, cystectomy, and hysterectomy salpingo-oophorectomy). The cyst sizes of the patients who underwent hysterectomy salpingo-oophorectomy were significantly more significant in the laparotomy group. The duration of hospital stay in the patients who underwent hysterectomy salpingo-oophorectomy was significantly longer when compared to the laparoscopy group, while no significant difference was found in the oophorectomy and cystectomy patients. The need for blood transfusion was significantly lower in the laparoscopy group for all operation types.
Conclusions: It was concluded that the duration of hospital stay, surgical site infection, need for blood transfusion, and operating time was less in patients who underwent laparoscopy. Laparoscopic surgery methods can be safely recommended for rapid and effective treatment of benign ovarian cysts with cystectomy, oophorectomy, and laparoscopic hysterectomy about hospital stay and complications.
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Donga S, Pandya M, Dei LP, Thakar A. Efficacy of Virechana, Triphaladi decoction with processed Guggulu in the management of ovarian cyst - A pilot study. Ayu 2020; 41:166-172. [PMID: 35370374 PMCID: PMC8966757 DOI: 10.4103/ayu.ayu_254_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 01/15/2020] [Accepted: 02/12/2021] [Indexed: 11/06/2022] Open
Abstract
Background: Ovarian cyst is an emerging problem among the women of reproductive age group. Most of the ovarian cyst (80%–85%) are benign, and two-thirds of these occur in women between 20 and 44 years of age. They may be identified in asymptomatic women during routine pelvic examination or may produce symptoms. Management of the ovarian cyst through surgery is available to meet urgent need of the patient, but to establish a satisfactory conservatory medical treatment is the need of the hour. According to Ayurveda, ovarian cysts can be managed on the line of Kaphaja Granthi (nodular/glandular swellings by Kapha Dosha) and Vidradhi (abscess). Aim: The aim of this study was to evaluate the clinical efficacy of Virechana (therapeutic purgation), Triphaladi Kashaya (decoction) with processed Guggulu (Commiphora mukul Engl.) in the management of ovarian cyst. Materials and methods: 16 patients were included in this clinical study and among them, 15 patients completed the treatment and one patient was dropped out from the trial. Patients were given Virechana followed by Triphaladi Kashaya (50 ml) with processed Guggulu (1 g) orally twice a day before meal for 60 days. The patients were followed up till 1 month. The assessment was carried out on subjective parameters such as lower abdominal pain, backache, and dysmenorrhea as well as objective parameters such as ovarian cyst size and volume by four-dimensional gray scale and color doppler sonography. Cancer antigen 125 was also assessed before and after treatment. Results were statistically analyzed using Wilcoxon signed-rank test and Student's t-test by sigma statistical tool (version 3.5, Systat Software Inc., United States). Results: Significant results were observed in subjective parameters such as lower abdominal pain (93.11%), backache (81.81) and dysmenorrhea (90.90%) as well as objective parameters such as reduction in size of the cyst (60%) and complete resolution of the cyst (26.66%). Conclusion: Triphaladi Kashaya with processed Guggulu is more effective in hemorrhagic cyst and simple cyst rather than other cyst, due to Shothahara properties which may have effectively curtailed the progress of ovarian cyst.
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