A Clinical Predictive Model for the Early Diagnosis of Adnexal Torsion in Children

Abstract Background: Lower Gastro-Intestinal Bleeding (LGIB) is a common presentation of surgical admissions, imposing a significant burden on healthcare costs and resources. There is a paucity of standardised clinical predictive tools available for the initial assessment and risk stratification of patients with LGIB. We propose a simple clinical scoring model to prognosticate patients at risk of severe LGIB and an algorithm to guide management of such patients.Methods: A retrospective cohort study was conducted, identifying consecutive patients admitted to our institution for LGIB over a 1-year period. Baseline demographics, clinical parameters at initial presentation and treatment interventions were recorded. Severe LGIB was the primary outcome measure. Multivariate logistic regression was performed to identify factors predictive of severe LGIB. A clinical management algorithm was developed to discriminate between patients requiring admission, and to guide endoscopic, angiographic and/or surgical intervention.Results: 226/649 (34.8%) patients had severe LGIB. Six variables were entered into a clinical predictive model for risk stratification of LGIB: Tachycardia (HR>100), hypotension (SBP<90mmHg), anemia (Hb<9g/dL), metabolic acidosis, use of antiplatelet/anticoagulants, and active per-rectal bleeding. The optimum cut-off score of >1 had a sensitivity of 91.9%, specificity of 39.8%, and Positive and Negative Predictive Values of 45% and 90.2% respectively for predicting severe LGIB. The Area Under Curve (AUC) was 0.77.BConclusion: Early diagnosis and management of severe LGIB remains a challenge for the acute care surgeon. The predictive model described comprises objective clinical parameters routinely obtained at initial triage to guide risk stratification, disposition and inpatient management of patients.

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A clinical predictive model of renal injury in children with congenital solitary functioning kidney

Pediatric Nephrology ◽

10.1007/s00467-018-4111-3 ◽

2018 ◽

Vol 34 (3) ◽

pp. 465-474 ◽

Cited By ~ 6

Author(s):

Isabel V. Poggiali ◽

Ana Cristina Simões e Silva ◽

Mariana A. Vasconcelos ◽

Cristiane S. Dias ◽

Izabella R. Gomes ◽

...

Keyword(s):

Predictive Model ◽

Renal Injury ◽

Solitary Functioning Kidney ◽

Clinical Predictive Model ◽

Functioning Kidney

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Abstract PS1-29: Predicting axillary pathologic response to neoadjuvant chemotherapy for node-positive breast cancer: Clinical predictive model by using MRI and ultrasound

10.1158/1538-7445.sabcs20-ps1-29 ◽

2021 ◽

Author(s):

Akiko Matsumoto ◽

Miki Yamada ◽

Daisuke Tsukahara ◽

Yasuko Umemoto ◽

Hiromitsu Jinno

Keyword(s):

Breast Cancer ◽

Neoadjuvant Chemotherapy ◽

Predictive Model ◽

Pathologic Response ◽

Node Positive ◽

Clinical Predictive Model ◽

Response To Neoadjuvant Chemotherapy ◽

Positive Breast Cancer

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944-P: Gestational Diabetes and Abnormal Glucose Metabolism One Year Postpartum: Clinical Predictive Model vs. 4-12 Week Postpartum Glucose Tolerance Test

Diabetes ◽

10.2337/db21-944-p ◽

2021 ◽

Vol 70 (Supplement 1) ◽

pp. 944-P

Author(s):

ERIKA WERNER ◽

ANA LUCIA ESPINOSA DICE ◽

ANGELA BENGTSON

Keyword(s):

Glucose Metabolism ◽

Gestational Diabetes ◽

Glucose Tolerance ◽

Predictive Model ◽

Glucose Tolerance Test ◽

Tolerance Test ◽

Abnormal Glucose Metabolism ◽

One Year ◽

Clinical Predictive Model

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Clinical predictive model for brain metastasis at presentation in patients with non-small-cell lung cancer (NSCLC).

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.e19158 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. e19158-e19158

Author(s):

Carlos Rodrigo Acevedo-Gadea ◽

Kathryn Trinkaus ◽

Ramaswamy Govindan ◽

Daniel Morgensztern

Keyword(s):

Lung Cancer ◽

Brain Metastases ◽

Predictive Model ◽

Initial Therapy ◽

Limited Data ◽

Clinical Model ◽

Molecular Determinants ◽

Clinical Predictive Model ◽

Nsclc Patients ◽

Brain Radiation

e19158 Background: There is limited data on the prevalence of brain metastases at presentation in NSCLC. Between 1988 and 1997, the Surveillance, Epidemiology, and End Results (SEER) database recorded the use of brain radiation in patients with lung cancer. We developed a predictive clinical model for brain metastases (BM) at presentation based on the use of brain radiation (BRT), which may be used as a surrogate since it is not indicated in NSCLC patients without BM. Methods: Patients with NSCLC diagnosed between 1988-1997, aged 21 or older were subdivided according to radiation data into none or indicated (given, refused or unknown if administrated). Since the database records only initial therapy, patients with indication for radiotherapy were assumed to have had early brain metastases. Frequencies and odds Ratio (OR) were calculated for each demographic factor and the most significant were included in the predictive model. Results: Among the 131,456 patients evaluated, 10,963 (8.4%) had BRT indicated. The most significant predictors in multivariate analysis were age > 60 (HR 0.5; 95% CI 0.46-0.54), non-squamous histology (HR 0.53; 95% CI 0.48-0.59), size > 5 cm (HR 1.27; 95% CI 1.16-1.39), grades III-IV (HR 2.04; 95% CI 1.82-2.27) and N2-3 involvement (HR 2.55; 95% CI 2.34-2.78). The 40,963 patients with known status of all 5 factors were used in the predictive model. The frequency of BM for patients with zero, 1, 2, 3, 4 and 5 factors were 0.7%, 1.8%, 4.7%, 8.9%, 13.7% and 20.2% respectively. Conclusions: Despite the limitations of this study, including indication for BRT as a surrogate for BM, older data and possible bias in the use of brain imaging according to demographic factors, our findings showed that the risk of BM at presentation may be stratified with the use of 5 clinical factors. These results may be used as a baseline for studies on clinical and molecular determinants of BM.

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Adnexal Torsion in Pediatric Age: Does Bolli’s Score Work? Report of Two Cases

Case Reports in Obstetrics and Gynecology ◽

10.1155/2019/9701874 ◽

2019 ◽

Vol 2019 ◽

pp. 1-4

Author(s):

L. Giambanco ◽

V. Iannone ◽

M. Borriello ◽

G. Scibilia ◽

G. Sozzi ◽

...

Keyword(s):

Abdominal Pain ◽

Early Diagnosis ◽

Pediatric Patients ◽

Clinical Presentation ◽

Reproductive Organs ◽

Pediatric Age ◽

Adnexal Torsion ◽

Radiological Criteria ◽

Exploratory Laparoscopy ◽

Diagnostic Variables

Adnexal torsion is a surgical emergency requiring early diagnosis in order to avoid demolitive surgery. Adnexal torsion’s diagnosis could be very difficult in pediatric patients because children cannot explain symptoms accurately. Furthermore reproductive organs lie high in abdomen, causing unclear examinations findings. For reducing diagnostic mistakes or delay clinical and hematological criteria could be useful. No radiological criteria (CT or MRI) should be taken in count because of the costs and the required time. By combining clinical presentation in patients with OT three useful diagnostic variables have been identified: age, duration of pain, vomiting. Presence of vomiting, short duration of abdominal pain and high CRP levels have great predictive value for the diagnosis of adnexal torsion. In those patients an exploratory laparoscopy should be performed without any doubt and/or delay. These data may aid physicians in the evaluation of abdominal pain in premenarchal girls.

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