scholarly journals OC05.01: Predicting ovarian malignancy if simple rules are not applicable

2009 ◽  
Vol 34 (S1) ◽  
pp. 7-7
Author(s):  
D. Timmerman ◽  
L. Ameye ◽  
D. Fischerova ◽  
E. Epstein ◽  
G. B. Melis ◽  
...  
Keyword(s):  
Ovarian Malignancy ◽  
Simple Rules

scholarly journals OC04.03: Quantifying the risk of ovarian malignancy prior to surgery based on the IOTA simple rules

2015 ◽  
Vol 46 ◽  
pp. 7-8
Author(s):  
B. Van Calster ◽  
D. Timmerman ◽  
A.C. Testa ◽  
L. Savelli ◽  
D. Fischerová ◽  
...  
Keyword(s):  
Ovarian Malignancy ◽  
Simple Rules

scholarly journals International Ovarian Tumor Analysis (IOTA) Scoring System to Predict Ovarian Malignancy Preoperatively

2016 ◽  
Author(s):  
Yuri Feharsal ◽  
Andi D Putra
Keyword(s):  
Predictive Value ◽  
Ovarian Tumor ◽  
Diagnostic Performance ◽  
Ca 125 ◽  
Ovarian Malignancy ◽  
Scoring Method ◽  
Simple Rules ◽  
Histopathology Result ◽  
Risk Of Malignancy ◽  
Sensitivity Specificity

Objective: To compare diagnostic performance of International Ovarian Tumor Analysis (IOTA) scoring method with Risk of Malignancy Index-4 (RMI-4) and Sassone Morphology Index to predict ovarian malignancy preoperatively. Method: Retrospective study with 119 subject who underwent surgical removal of ovarian tumor and performed histopathological examination at Dr. Cipto Mangunkusumo Hospital on January to December 2013. Demographic status, ultrasound scans, CA-125 level and histopathological result were collected to calculate the score of each method. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy were calculated by comparing each score with histopathology result. Comparison of diagnostic performance was analyzed by ROC curve. Result: There were 51.26% subjects with benign tumor and 48.74% subjects with malignant tumor. Result was analyzed with sensitivity test (IOTA simple-rules, IOTA subgroup, RMI-4 and Sassone): 98%, 88%, 86% and 79%; specificity: 74%, 67%, 61% and 89%; positive predictive value: 78%, 72%, 68% and 87%; negative predictive value: 98%, 85%, 82% and 81%; and accuracy: 86%, 77%, 73% and 84%. AUC value for IOTA simple-rules, IOTA subgroup, RMI-4 and Sassone were: 0.86, 0.78, 0.73 and 0.84. Comparison of these results were significant with p = 0.000. Conclusion: IOTA simple-rules had better sensitivity, negative predictive value and accuracy than IOTA subgroup, RMI-4 and Sassone morphology index to predict ovarian malignancy preoperatively. [Indones J Obstet Gynecol 2016; 1: 42-46] Keywords: iota, ovarian neoplasm, risk of malignancy, scoring

Imagine Law Without Simple Rules

1995 ◽  
Vol 40 (2) ◽  
pp. 143-144
Author(s):  
Arthur C. Graesser
Keyword(s):  
Simple Rules

Complex Networks from Simple Rules

2013 ◽  
Vol 22 (2) ◽  
pp. 151-174 ◽  
Author(s):  
Richard Southwell ◽  
Jianwei Huang ◽  
Chris Cannings ◽  
◽  
Keyword(s):  
Complex Networks ◽  
Simple Rules

How to Evaluate Clinically Relevant Literature: Five Simple Rules for the Practicing Clinician in Stroke Neurorehabilitation

2020 ◽  
Author(s):  
Jonathan Sanching Tsay ◽  
Carolee Winstein
Keyword(s):  
Clinical Decision Making ◽  
Relevant Literature ◽  
Clinical Decision ◽  
Balance Sheets ◽  
Neural Connections ◽  
Recovery Processes ◽  
Immediate Recovery ◽  
Simple Rules ◽  
Busy Clinician ◽  
New Generation

Neurorehabilitation relies on core principles of neuroplasticity to activate and engage latent neural connections, promote detour circuits, and reverse impairments. Clinical interventions incorporating these principles have been shown to promote recovery while demoting compensation. However, many clinicians struggle to find evidence for these principles in our growing but nascent body of literature. Regulatory bodies and organizational balance sheets further discourage evidence-based, methodical, time-intensive, and efficacious interventions because practical needs often outweigh and dominate clinical decision making. Modern neurorehabilitation practices that result from these pressures favor strategies that encourage compensation over those that promote recovery. With a focus on helping the busy clinician evaluate the rapidly growing literature, we put forth five simple rules that direct clinicians toward intervention studies that value more enduring but slower biological recovery processes over the more alluring practical and immediate “recovery” mantra. Filtering emerging literature through this critical lens has the potential to change practice and lead to more durable long-term outcomes. This perspective is meant to serve a new generation of mechanistically minded clinicians, students, and trainees poised to not only advance our field but to also erect policy changes that promote recovery-based care of stroke survivors.

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