Risk factors for inadequate bowel preparation: a validated predictive score

Abstract Background and study aim Inadequate bowel cleansing negatively affects the efficiency of colonoscopy in routine clinical practice. The aim of this study was to design and validate a predictive model for inadequate bowel cleanliness. Patients and methods The model was built from 667 consecutive outpatients (development cohort) who were prospectively scheduled for colonoscopy between June and September 2014. The validation cohort included 409 outpatients who underwent colonoscopy between October and December 2014. Cleansing was evaluated using the Boston Bowel Preparation Scale (BBPS). Bowel preparation was administered on the same day as the examination. Results In the development cohort, BBPS was adequate in 541 patients (81.1 %). At multivariate analysis, antidepressants (odds ratio [OR] 4.25, 95 % confidence interval [CI] 1.91 – 9.47), co-morbidity (OR 3.35, 95 %CI 2.16 – 5.18), constipation (OR 2.09, 95 %CI 1.29 – 3.40), and abdominal/pelvic surgery (OR 1.60, 95 %CI 1.03 – 2.47) were independent predictors for inadequate cleansing. The model built with these variables showed an area under the curve of 0.72 in the development cohort and 0.70 in the validation cohort. A cutoff of 1.225 predicted inadequate bowel preparation with a sensitivity, specificity, positive predictive value, and negative predictive value of 60.3 % (95 %CI 51.6 – 68.4), 75.4 % (95 %CI 71.6 – 78.9), 36.4 % (95 %CI 30.1 – 43.1), and 89.1 % (95 %CI 85.9 – 91.6) in the development cohort, and 50.0 % (95 %CI 38.1 – 61.9), 80.0 % (95 %CI 75.3 – 84.2), 35.7 % (95 %CI 26.4 – 45.6), and 87.9 % (95 %CI 83.7 – 91.3) in the validation cohort. Conclusion A simple score may assist the clinician in predicting which patients are at high risk of inadequate bowel cleanliness. This may guide changes in bowel preparation strategy accordingly.

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Validation and Application of Predictive Models for Inadequate Bowel Preparation in Colonoscopies in a Tertiary Hospital Population

GE Portuguese Journal of Gastroenterology ◽

10.1159/000520905 ◽

2021 ◽

pp. 1-7

Author(s):

Edgar Afecto ◽

Ana Ponte ◽

Sónia Fernandes ◽

Catarina Gomes ◽

João Paulo Correia ◽

...

Keyword(s):

Abdominal Surgery ◽

Bowel Preparation ◽

Predictive Value ◽

Tricyclic Antidepressants ◽

Quality Criterion ◽

Roc Curves ◽

Tertiary Hospital ◽

Asa Score ◽

Inadequate Bowel Preparation ◽

Sensitivity Specificity

Background: Bowel preparation is a major quality criterion for colonoscopies. Models developed to identify patients with inadequate preparation have not been validated in external cohorts. We aim to validate these models and determine their applicability. Methods: Colonoscopies between April and November 2019 were retrospectively included. Boston Bowel Preparation Scale ≥2 per segment was considered adequate. Insufficient data, incomplete colonoscopies, and total colectomies were excluded. Two models were tested: model 1 (tricyclic antidepressants, opioids, diabetes, constipation, abdominal surgery, previous inadequate preparation, inpatient status, and American Society of Anesthesiology [ASA] score ≥3); model 2 (co-morbidities, tricyclic antidepressants, constipation, and abdominal surgery). Results: We included 514 patients (63% males; age 61.7 ± 15.6 years), 441 with adequate preparation. The main indications were inflammatory bowel disease (26.1%) and endoscopic treatment (24.9%). Previous surgery (36.2%) and ASA score ≥3 (23.7%) were the most common comorbidities. An ASA score ≥3 was the only identified predictor for inadequate preparation in this study (p < 0.001, OR 3.28). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of model 1 were 60.3, 64.2, 21.8, and 90.7%, respectively. Model 2 had a sensitivity, specificity, PPV, and NPV of 57.5, 67.4, 22.6, and 90.5%, respectively. The AUC for the ROC curves was 0.62 for model 1, 0.62 for model 2, and 0.65 for the ASA score. Conclusions: Although both models accurately predict adequate bowel preparation, they are still unreliable in predicting inadequate preparation and, as such, new models, or further optimization of current ones, are needed. Utilizing the ASA score might be an appropriate approximation of the risk for inadequate bowel preparation in tertiary hospital populations.

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A PREDICTIVE SCORE OF INADEQUATE BOWEL PREPARATION BASED ON A SELF-ADMINISTRED QUESTIONNAIRE

10.1055/s-0038-1637216 ◽

2018 ◽

Author(s):

A Berger ◽

E Cesbron-Métivier ◽

S Bertrais ◽

A Olivier ◽

A Becq ◽

...

Keyword(s):

Bowel Preparation ◽

Predictive Score ◽

Inadequate Bowel Preparation

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Clot imaging characteristics predict first pass effect of aspiration—first approach to thrombectomy

Interventional Neuroradiology ◽

10.1177/15910199211019174 ◽

2021 ◽

pp. 159101992110191

Author(s):

Muhammad Waqas ◽

Weizhe Li ◽

Tatsat R Patel ◽

Felix Chin ◽

Vincent M Tutino ◽

...

Keyword(s):

Internal Carotid ◽

Validation Cohort ◽

Area Under The Curve ◽

Large Vessel Occlusion ◽

Vessel Occlusion ◽

First Pass Effect ◽

Imaging Characteristics ◽

First Pass ◽

Sensitivity Specificity ◽

Youden’S Index

Background The value of clot imaging in patients with emergent large vessel occlusion (ELVO) treated with thrombectomy is unknown. Methods We performed retrospective analysis of clot imaging (clot density, perviousness, length, diameter, distance to the internal carotid artery (ICA) terminus and angle of interaction (AOI) between clot and the aspiration catheter) of consecutive cases of middle cerebral artery (MCA) occlusion and its association with first pass effect (FPE, TICI 2c-3 after a first attempt). Results Patients ( n = 90 total) with FPE had shorter clot length (9.9 ± 4.5 mm vs. 11.7 ± 4.6 mm, P = 0.07), shorter distance from ICA terminus (11.0 ± 7.1 mm vs. 14.7 ± 9.8 mm, P = 0.048), higher perviousness (39.39 ± 29.5 vs 25.43 ± 17.6, P = 0.006) and larger AOI (153.6 ± 17.6 vs 140.3 ± 23.5, P = 0.004) compared to no-FPE patients. In multivariate analysis, distance from ICA terminus to clot ≤13.5 mm (odds ratio (OR) 11.05, 95% confidence interval (CI) 2.65–46.15, P = 0.001), clot length ≤9.9 mm (OR 7.34; 95% CI 1.8–29.96, P = 0.005), perviousness ≥ 19.9 (OR 2.54, 95% CI 0.84–7.6, P = 0.09) and AOI ≥ 137°^ (OR 6.8, 95% CI 1.55–29.8, P = 0.011) were independent predictors of FPE. The optimal cut off derived using Youden’s index was 6.5. The area under the curve of a score predictive of FPE success was 0.816 (0.728–0.904, P < 0.001). In a validation cohort ( n = 30), sensitivity, specificity, positive and negative predictive value of a score of 6–10 were 72.7%, 73.6%, 61.5% and 82.3%. Conclusions Clot imaging predicts the likelihood of achieving FPE in patients with MCA ELVO treated with the aspiration-first approach.

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New screening approach to detecting congenital syphilis in China: a retrospective cohort study

Archives of Disease in Childhood ◽

10.1136/archdischild-2020-320549 ◽

2020 ◽

pp. archdischild-2020-320549

Author(s):

Fang Hu ◽

Shuai-Jun Guo ◽

Jian-Jun Lu ◽

Ning-Xuan Hua ◽

Yan-Yan Song ◽

...

Keyword(s):

Predictive Value ◽

Congenital Syphilis ◽

Area Under The Curve ◽

Diagnostic Tools ◽

Operating Characteristics ◽

Loss To Follow Up ◽

Sensitivity Specificity ◽

Mother To Child ◽

Rule Out

BackgroundDiagnosis of congenital syphilis (CS) is not straightforward and can be challenging. This study aimed to evaluate the validity of an algorithm using timing of maternal antisyphilis treatment and titres of non-treponemal antibody as predictors of CS.MethodsConfirmed CS cases and those where CS was excluded were obtained from the Guangzhou Prevention of Mother-to-Child Transmission of syphilis programme between 2011 and 2019. We calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using receiver operating characteristics (ROC) in two situations: (1) receiving antisyphilis treatment or no-treatment during pregnancy and (2) initiating treatment before 28 gestational weeks (GWs), initiating after 28 GWs or receiving no treatment for syphilis seropositive women.ResultsAmong 1558 syphilis-exposed children, 39 had confirmed CS. Area under the curve, sensitivity and specificity of maternal non-treponemal titres before treatment and treatment during pregnancy were 0.80, 76.9%, 78.7% and 0.79, 69.2%, 88.7%, respectively, for children with CS. For the algorithm, ROC results showed that PPV and NPV for predicting CS were 37.3% and 96.4% (non-treponemal titres cut-off value 1:8 and no antisyphilis treatment), 9.4% and 100% (non-treponemal titres cut-off value 1:16 and treatment after 28 GWs), 4.2% and 99.5% (non-treponemal titres cut-off value 1:32 and treatment before 28 GWs), respectively.ConclusionsAn algorithm using maternal non-treponemal titres and timing of treatment during pregnancy could be an effective strategy to diagnose or rule out CS, especially when the rate of loss to follow-up is high or there are no straightforward diagnostic tools.

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Value and Diagnostic Efficacy of Fetal Morphology Assessment Using Ultrasound in A Poor-Resource Setting

Diagnostics ◽

10.3390/diagnostics9030109 ◽

2019 ◽

Vol 9 (3) ◽

pp. 109 ◽

Cited By ~ 1

Author(s):

Ukweh ◽

Ugbem ◽

Okeke ◽

Ekpo

Keyword(s):

Predictive Value ◽

Performance Metrics ◽

Area Under The Curve ◽

Youden Index ◽

Likelihood Ratios ◽

Diagnostic Efficacy ◽

Predictive Values ◽

Resource Setting ◽

Post Test ◽

Sensitivity Specificity

Background: Ultrasound is operator-dependent, and its value and efficacy in fetal morphology assessment in a low-resource setting is poorly understood. We assessed the value and efficacy of fetal morphology ultrasound assessment in a Nigerian setting. Materials and Methods: We surveyed fetal morphology ultrasound performed across five facilities and followed-up each fetus to ascertain the outcome. Fetuses were surveyed in the second trimester (18th–22nd weeks) using the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) guideline. Clinical and surgical reports were used as references to assess the diagnostic efficacy of ultrasound in livebirths, and autopsy reports to confirm anomalies in terminated pregnancies, spontaneous abortions, intrauterine fetal deaths, and still births. We calculated sensitivity, specificity, positive and negative predictive values, Area under the curve (AUC), Youden index, likelihood ratios, and post-test probabilities. Results: In total, 6520 fetuses of women aged 15–46 years (mean = 31.7 years) were surveyed. The overall sensitivity, specificity, and AUC were 77.1 (95% CI: 68–84.6), 99.5 (95% CI: 99.3–99.7), and 88.3 (95% CI: 83.7–92.2), respectively. Other performance metrics were: positive predictive value, 72.4 (95% CI: 64.7–79.0), negative predictive value, 99.6 (95% CI: 99.5–99.7), and Youden index (77.1%). Abnormality prevalence was 1.67% (95% CI: 1.37–2.01), and the positive and negative likelihood ratios were 254 (95% CI: 107.7–221.4) and 0.23 (95% CI: 0.16–0.33), respectively. The post-test probability for positive test was 72% (95% CI: 65–79). Conclusion: Fetal morphology assessment is valuable in a poor economics setting, however, the variation in the diagnostic efficacy across facilities and the limitations associated with the detection of circulatory system anomalies need to be addressed.

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Identification of the most specific markers to differentiate primary pulmonary carcinoma from metastatic gastrointestinal carcinoma to the lung

Diagnostic Pathology ◽

10.1186/s13000-021-01184-2 ◽

2022 ◽

Vol 17 (1) ◽

Author(s):

Bachar Alabdullah ◽

Amir Hadji-Ashrafy

Keyword(s):

Gastrointestinal Tract ◽

Predictive Value ◽

Regression Models ◽

Area Under The Curve ◽

Roc Curves ◽

Multivariate Models ◽

Gastrointestinal Carcinoma ◽

Lung Tumours ◽

Napsin A ◽

Sensitivity Specificity

Abstract Background A number of biomarkers have the potential of differentiating between primary lung tumours and secondary lung tumours from the gastrointestinal tract, however, a standardised panel for that purpose does not exist yet. We aimed to identify the smallest panel that is most sensitive and specific at differentiating between primary lung tumours and secondary lung tumours from the gastrointestinal tract. Methods A total of 170 samples were collected, including 140 primary and 30 non-primary lung tumours and staining for CK7, Napsin-A, TTF1, CK20, CDX2, and SATB2 was performed via tissue microarray. The data was then analysed using univariate regression models and a combination of multivariate regression models and Receiver Operating Characteristic (ROC) curves. Results Univariate regression models confirmed the 6 biomarkers’ ability to independently predict the primary outcome (p < 0.001). Multivariate models of 2-biomarker combinations identified 11 combinations with statistically significant odds ratios (ORs) (p < 0.05), of which TTF1/CDX2 had the highest area under the curve (AUC) (0.983, 0.960–1.000 95% CI). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 75.7, 100, 100, and 37.5% respectively. Multivariate models of 3-biomarker combinations identified 4 combinations with statistically significant ORs (p < 0.05), of which CK7/CK20/SATB2 had the highest AUC (0.965, 0.930–1.000 95% CI). The sensitivity, specificity, PPV, and NPV were 85.1, 100, 100, and 41.7% respectively. Multivariate models of 4-biomarker combinations did not identify any combinations with statistically significant ORs (p < 0.05). Conclusions The analysis identified the combination of CK7/CK20/SATB2 to be the smallest panel with the highest sensitivity (85.1%) and specificity (100%) for predicting tumour origin with an ROC AUC of 0.965 (p < 0.001; SE: 0.018, 0.930–1.000 95% CI).

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The role of red cell distribution width in the differential diagnosis of iron deficiency anemia and non-transfusion dependent thalassemia patients

Hematology Reports ◽

10.4081/hr.2018.7605 ◽

2018 ◽

Vol 10 (3) ◽

Cited By ~ 3

Author(s):

Pokpong Piriyakhuntorn ◽

Adisak Tantiworawit ◽

Thanawat Rattanathammethee ◽

Chatree Chai-Adisaksopha ◽

Ekarat Rattarittamrong ◽

...

Keyword(s):

Diagnostic Accuracy ◽

Predictive Value ◽

Area Under The Curve ◽

Microcytic Anemia ◽

Deficiency Anemia ◽

Operating Characteristics ◽

Training Set ◽

Distribution Width ◽

Validation Set ◽

Sensitivity Specificity

This study aims to find the cut-off value and diagnostic accuracy of the use of RDW as initial investigation in enabling the differentiation between IDA and NTDT patients. Patients with microcytic anemia were enrolled in the training set and used to plot a receiving operating characteristics (ROC) curve to obtain the cut-off value of RDW. A second set of patients were included in the validation set and used to analyze the diagnostic accuracy. We recruited 94 IDA and 64 NTDT patients into the training set. The area under the curve of the ROC in the training set was 0.803. The best cut-off value of RDW in the diagnosis of NTDT was 21.0% with a sensitivity and specificity of 81.3% and 55.3% respectively. In the validation set, there were 34 IDA and 58 NTDT patients using the cut-off value of >21.0% to validate. The sensitivity, specificity, positive predictive value and negative predictive value were 84.5%, 70.6%, 83.1% and 72.7% respectively. We can therefore conclude that RDW >21.0% is useful in differentiating between IDA and NTDT patients with high diagnostic accuracy

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694. Prediction Tool for Infective Endocarditis in Beta-hemolytic Streptococcal Bacteremia

Open Forum Infectious Diseases ◽

10.1093/ofid/ofab466.891 ◽

2021 ◽

Vol 8 (Supplement_1) ◽

pp. S448-S449

Author(s):

Ryo Hasegawa ◽

Takahiro Matsuo ◽

Osamu Takahashi ◽

Nobuyoshi Mori

Keyword(s):

Infective Endocarditis ◽

Predictive Value ◽

Area Under The Curve ◽

Tertiary Hospital ◽

Predictive Score ◽

Characteristic Analysis ◽

Group B Streptococci ◽

Reactive Protein ◽

Multivariable Analyses ◽

Group B

Abstract Background Although beta-hemolytic streptococci (BHS) is a rare causative pathogen of infective endocarditis (IE), IE is a serious condition and it is important to predict IE in BHS bacteremia (BHS-IE). The purpose of this study was to develop a predictive score for BHS-IE. Methods We conducted a retrospective study comparing the clinical features of BHS-IE and BHS-non infective endocarditis (BHS-nIE) in adult patients with BHS bacteremia at a 520-bed tertiary hospital in Tokyo, Japan from 2004 to 2020. IE was diagnosed according to modified Duke's criteria, and both “Definite” and “Possible” were included. Univariate and multivariable analyses were conducted using logistic regression. Results Among 250 patients with BHS bacteremia, 47 (19%) were diagnosed with BHS-IE. The median (IQR) patient age was 71 (59, 84) years and 121 (68%) were male. The proportions of A, B, C/G groups were 14%, 38.4%, and 47.6%, respectively. Five predictors, either independently associated with BHS-IE or clinically relevant, were used to develop the prediction score: C-reactive protein ≥ 10 mg/dl (2 points); Group B Streptococci (1 point); Auscultation of heart murmur (1 point); Platelet count < 150 /µl (1 point); and Hypotension (systolic blood pressure < 90 mmHg or on vasopressor) (1 point). In a receiver operating characteristic analysis, the area under the curve was 0.74 (95% confidence interval [CI]: 0.66 - 0.82). The cut-point was 2. A score ≥2 had a sensitivity of 87% (95%CI: 0.743 - 0.952), a specificity of 37% (95%CI: 0.308 - 0.445), a positive predictive value of 24%, and a negative predictive value of 93%, respectively. Conclusion We developed the score to help clinicians rule out IE in BHS bacteremia. Further research is warranted for validation. Disclosures All Authors: No reported disclosures

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Development of a delirium predictive model for adult trauma patients in an emergency and critical care center: a retrospective study

Trauma Surgery & Acute Care Open ◽

10.1136/tsaco-2021-000827 ◽

2021 ◽

Vol 6 (1) ◽

pp. e000827

Author(s):

Ayaka Matsuoka ◽

Toru Miike ◽

Mariko Miyazaki ◽

Taku Goto ◽

Akira Sasaki ◽

...

Keyword(s):

Risk Factors ◽

Scoring System ◽

Validation Cohort ◽

Care Center ◽

Univariate Analysis ◽

Area Under The Curve ◽

Predictive Score ◽

Calibration Plot ◽

Trauma Patients ◽

Time Of Admission

BackgroundDelirium has been shown to prolong the length of intensive care unit stay, hospitalization, and duration of ventilatory control, in addition to increasing the use of sedatives and increasing the medical costs. Although there have been a number of reports referring to risk factors for the development of delirium, no model has been developed to predict delirium in trauma patients at the time of admission. This study aimed to create a scoring system that predicts delirium in trauma patients.MethodsIn this single-center, retrospective, observational study, trauma patients aged 18 years and older requiring hospitalization more than 48 hours were included and divided into the development and validation cohorts. Univariate analysis was performed in the development cohort to identify factors significantly associated with prediction of delirium. The final scoring system for predicting delirium was developed using multivariate analysis and internal validation was performed.ResultsOf the 308 patients in the development cohort, 91 developed delirium. Clinical Frailty Score, fibrin/fibrinogen degradation products, low body mass index, lactate level, and Glasgow Coma Scale score were independently associated with the development of delirium. We developed a scoring system using these factors and calculated the delirium predictive score, which had an area under the curve of 0.85. In the validation cohort, 46 of 206 patients developed delirium. The area under the curve for the validation cohort was 0.86, and the calibration plot analysis revealed the scoring system was well calibrated in the validation cohort.DiscussionThis scoring system for predicting delirium in trauma patients consists of only five risk factors. Delirium prediction at the time of admission may be useful in clinical practice.Level of evidencePrognostic and epidemiological, level III.

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Validation of the Indonesian Version of Modified Checklist for Autism in Toddlers: a diagnostic study

Paediatrica Indonesiana ◽

10.14238/pi60.3.2020.159-65 ◽

2020 ◽

Vol 60 (3) ◽

pp. 159-65

Author(s):

Hendra Salim ◽

Soetjiningsih Soetjiningsih ◽

I Gusti Ayu Trisna Windiani ◽

I Gede Raka Widiana ◽

PITIKA ASPR

Keyword(s):

Predictive Value ◽

Characteristic Curve ◽

Area Under The Curve ◽

Negative Likelihood Ratio ◽

Autism Spectrum ◽

Diagnostic Study ◽

Diagnostic Validity ◽

Dsm Iv ◽

Pediatric Outpatients ◽

Sensitivity Specificity

Background Autism is a developmental disorder for which early detection in toddlers is recommended because of its increased prevalence. The Modified Checklist for Autism in Toddlers (M-CHAT) is an easy-to-interprete tool that can be filled out by parents. It has been translated into the Indonesian language but needs to be validated. Objective To evaluate the diagnostic validity of the Indonesian version of M-CHAT in detection of autism spectrum disorder in Indonesia. Methods A diagnostic study was conducted at Sanglah Hospital, Denpasar, Bali, from March 2011 to August 2013. Pediatric outpatients aged 18 to 48 months were included. The Indonesian version of the M-CHAT tool was filled by parents. Autism assessment was done according to the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV-TR). The assessment results were analyzed with the MedCalc program software, in several steps: (i) reliability of M-CHAT; (ii) description, distribution, and proportion to determine the characteristics of the subjects of research; and (iii) validity of M-CHAT compared to the gold standard DSM-IV-TR by a receiver operating characteristic curve and several area under the curve cut-off points, in order to assess the sensitivity, specificity, positive predictive value, negative predictive value, and positive and negative likelihood ratio, accompanied by the 95% confidence interval of each value. Results The Indonesian version of M-CHAT in toddlers had 82.35% sensitivity and 89.68% specificity, using the cut-off point of more than 6 failed questions. Conclusion The Indonesian version M-CHAT translated by Soetjiningsih has optimal diagnostic validity for detection of autism in toddlers.

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