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  • 1
    Online Resource
    Online Resource
    Serum Steroid Hormonal Profiles by Reversed-Phase Liquid Chromatography in Patients with 17-Hydroxylase Deficiency and in an Affected Family
    Oxford University Press (OUP) ; 1992
    In:  Clinical Chemistry Vol. 38, No. 1 ( 1992-01-01), p. 76-82
    Details
    In: Clinical Chemistry, Oxford University Press (OUP), Vol. 38, No. 1 ( 1992-01-01), p. 76-82
    Abstract: We used an optimized isocratic reversed-phase high-performance liquid-chromatographic procedure to separate and measure 12 steroid hormones, and studied the steroid hormone profiles in sera from three patients with 17-hydroxylase deficiency (17-OHD). Two of the patients were sisters, one of whom (II-3), expressing normotension and primary amenorrhea, was diagnosed on the basis of chromatographic data and followed up for seven years. The untreated patients had obvious abnormalities on chromatograms of serum extracts, characterized by markedly increased corticosterone (B) and decreased or undetectable cortisol (F) and cortisone (E). The concentration of 11-deoxycorticosterone was much greater in the patient with classical symptoms than in the normotensive patient. In all three patients, concentrations of aldosterone were within the normal range, but concentrations of progesterone were much lower than in the patients with 21-hydroxylase deficiency. We evaluated the responses to corticotropin and dexamethasone. HPLC evaluation of the serum steroid profiles before and after corticotropin stimulation in the affected family showed that in the parents and one other sibling, concentrations of F before and after stimulation were within the normal ranges. The sums of the ratio of B to F before and the ratio of B to F after corticotropin stimulation (sigma B/F) in the parents and the other sibling were 0.292, 0.496, and 0.614, respectively, all much higher than the normal value (mean +/- SD: 0.164 +/- 0.038). Thus the sigma B/F value may be a hormonal marker of heterozygotes carrying this defect.
    Type of Medium: Online Resource
    ISSN: 0009-9147 , 1530-8561
    URL: Article
    DOI: 10.1093/clinchem/38.1.76
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 1992
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  • 2
    Online Resource
    Online Resource
    Prospective observational cohort study on grading the severity of postoperative complications in global surgery research
    Oxford University Press (OUP) ; 2019
    In:  British Journal of Surgery Vol. 106, No. 2 ( 2019-01-08), p. e73-e80
    Details
    In: British Journal of Surgery, Oxford University Press (OUP), Vol. 106, No. 2 ( 2019-01-08), p. e73-e80
    Abstract: The Clavien–Dindo classification is perhaps the most widely used approach for reporting postoperative complications in clinical trials. This system classifies complication severity by the treatment provided. However, it is unclear whether the Clavien–Dindo system can be used internationally in studies across differing healthcare systems in high- (HICs) and low- and middle-income countries (LMICs). Methods This was a secondary analysis of the International Surgical Outcomes Study (ISOS), a prospective observational cohort study of elective surgery in adults. Data collection occurred over a 7-day period. Severity of complications was graded using Clavien–Dindo and the simpler ISOS grading (mild, moderate or severe, based on guided investigator judgement). Severity grading was compared using the intraclass correlation coefficient (ICC). Data are presented as frequencies and ICC values (with 95 per cent c.i.). The analysis was stratified by income status of the country, comparing HICs with LMICs. Results A total of 44 814 patients were recruited from 474 hospitals in 27 countries (19 HICs and 8 LMICs). Some 7508 patients (16·8 per cent) experienced at least one postoperative complication, equivalent to 11 664 complications in total. Using the ISOS classification, 5504 of 11 664 complications (47·2 per cent) were graded as mild, 4244 (36·4 per cent) as moderate and 1916 (16·4 per cent) as severe. Using Clavien–Dindo, 6781 of 11 664 complications (58·1 per cent) were graded as I or II, 1740 (14·9 per cent) as III, 2408 (20·6 per cent) as IV and 735 (6·3 per cent) as V. Agreement between classification systems was poor overall (ICC 0·41, 95 per cent c.i. 0·20 to 0·55), and in LMICs (ICC 0·23, 0·05 to 0·38) and HICs (ICC 0·46, 0·25 to 0·59). Conclusion Caution is recommended when using a treatment approach to grade complications in global surgery studies, as this may introduce bias unintentionally.
    Type of Medium: Online Resource
    ISSN: 0007-1323 , 1365-2168
    URL: Article
    DOI: 10.1002/bjs.11025
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 2006309-X
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  • 3
    Online Resource
    Online Resource
    Updated incidence rates and risk factors of esophageal cancer in Nan'ao Island, a coastal high-risk area in southern China : Incidence and risk factor of esophageal cancer
    Oxford University Press (OUP) ; 2016
    In:  Diseases of the Esophagus ( 2016-02), p. n/a-n/a
    Details
    In: Diseases of the Esophagus, Oxford University Press (OUP), ( 2016-02), p. n/a-n/a
    Type of Medium: Online Resource
    ISSN: 1120-8694
    URL: Article
    DOI: 10.1111/dote.12468
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2016
    detail.hit.zdb_id: 2004949-3
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  • 4
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    Online Resource
    Development and validation of novel models for the prediction of intravenous corticosteroid resistance in acute severe ulcerative colitis using logistic regression and machine learning
    Oxford University Press (OUP) ; 2022
    In:  Gastroenterology Report Vol. 10 ( 2022-01-25)
    Details
    In: Gastroenterology Report, Oxford University Press (OUP), Vol. 10 ( 2022-01-25)
    Abstract: The early prediction of intravenous corticosteroid (IVCS) resistance in acute severe ulcerative colitis (ASUC) patients remains an unresolved challenge. This study aims to construct and validate a model that accurately predicts IVCS resistance. Methods A retrospective cohort was established, with consecutive inclusion of patients who met the diagnosis criteria of ASUC and received IVCS during index hospitalization in Peking Union Medical College Hospital between March 2012 and January 2020. The primary outcome was IVCS resistance. Classification models, including logistic regression and machine learning-based models, were constructed. External validation was conducted in an independent cohort from Shengjing Hospital of China Medical University. Results A total of 129 patients were included in the derivation cohort. During index hospitalization, 102 (79.1%) patients responded to IVCS and 27 (20.9%) failed; 18 (14.0%) patients underwent colectomy in 3 months; 6 received cyclosporin as rescue therapy, and 2 eventually escalated to colectomy; 5 succeeded with infliximab as rescue therapy. The Ulcerative Colitis Endoscopic Index of Severity (UCEIS) and C-reactive protein (CRP) level at Day 3 are independent predictors of IVCS resistance. The areas under the receiver-operating characteristic curves (AUROCs) of the logistic regression, decision tree, random forest, and extreme-gradient boosting models were 0.873 (95% confidence interval [CI], 0.704–1.000), 0.648 (95% CI, 0.463–0.833), 0.650 (95% CI, 0.441–0.859), and 0.604 (95% CI, 0.416–0.792), respectively. The logistic regression model achieved the highest AUROC value of 0.703 (95% CI, 0.473–0.934) in the external validation. Conclusions In patients with ASUC, UCEIS and CRP levels at Day 3 of IVCS treatment appeared to allow the prompt prediction of likely IVCS resistance. We found no evidence of better performance of machine learning-based models in IVCS resistance prediction in ASUC. A nomogram based on the logistic regression model might aid in the management of ASUC patients.
    Type of Medium: Online Resource
    ISSN: 2052-0034
    URL: Article
    DOI: 10.1093/gastro/goac053
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2710871-5
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