Serial assessment of inflammatory parameters for prediction of septic complications following surgery for colorectal endometriosis

Summary Purpose To assess whether C‑reactive protein (CRP), white blood cell count (WBC) and body temperature changes are suitable parameters for the early detection of septic complications following resection of colorectal deep endometriosis (DE). Methods Retrospective data analysis of CRP, WBC and body temperature courses following colorectal surgery for DE at a tertiary referral center for endometriosis. Results Out of 183 surgeries performed, 10 major surgical complications were observed, including 4 anastomotic leakages (AL 2%) and 2 rectovaginal fistulae (RVF 1%). In the presence of a lower gastrointestinal tract (GIT)-related septic complication or abdominal wall abscess, serum CRP levels were increased starting at postoperative day 2–3. A cut-off value of 10 mg/dl on day 4 for prediction of early septic complications could be verified (area under the curve 0.94, obtained by receiver operating characteristics analysis, sensitivity 88%, specificity 90%, positive predictive value 32%, negative predictive value 99%). Additionally, most patients with early septic complications exhibited increased WBC levels starting mainly from day 3–4; however, increased inflammatory parameters could not be observed in one patient with an RVF. Body temperature did not prove useful for early discrimination between uncomplicated cases and those with early septic complications. Conclusion Relevant elevations of serum CRP and WBC levels were demonstrated in patients with early septic complications following surgery for colorectal DE starting at postoperative day 2–4. The cut-off value of 10 mg/dl for CRP levels may serve as an early predictor for lower GIT-related septic complications but should be used with caution in women with suspected RVF development.

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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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First trimester prediction of maternal glycemic status

Journal of Perinatal Medicine ◽

10.1515/jpm-2014-0149 ◽

2015 ◽

Vol 43 (3) ◽

Cited By ~ 8

Author(s):

Rinat Gabbay-Benziv ◽

Lauren E. Doyle ◽

Miriam Blitzer ◽

Ahmet A. Baschat

Keyword(s):

Risk Score ◽

Predictive Value ◽

Challenge Test ◽

Area Under The Curve ◽

First Trimester ◽

Tolerance Test ◽

Oral Glucose ◽

Operating Characteristics ◽

Maternal Characteristics ◽

Predictive Algorithm

AbstractTo predict gestational diabetes mellitus (GDM) or normoglycemic status using first trimester maternal characteristics.We used data from a prospective cohort study. First trimester maternal characteristics were compared between women with and without GDM. Association of these variables with sugar values at glucose challenge test (GCT) and subsequent GDM was tested to identify key parameters. A predictive algorithm for GDM was developed and receiver operating characteristics (ROC) statistics was used to derive the optimal risk score. We defined normoglycemic state, when GCT and all four sugar values at oral glucose tolerance test, whenever obtained, were normal. Using same statistical approach, we developed an algorithm to predict the normoglycemic state.Maternal age, race, prior GDM, first trimester BMI, and systolic blood pressure (SBP) were all significantly associated with GDM. Age, BMI, and SBP were also associated with GCT values. The logistic regression analysis constructed equation and the calculated risk score yielded sensitivity, specificity, positive predictive value, and negative predictive value of 85%, 62%, 13.8%, and 98.3% for a cut-off value of 0.042, respectively (ROC-AUC – area under the curve 0.819, CI – confidence interval 0.769–0.868). The model constructed for normoglycemia prediction demonstrated lower performance (ROC-AUC 0.707, CI 0.668–0.746).GDM prediction can be achieved during the first trimester encounter by integration of maternal characteristics and basic measurements while normoglycemic status prediction is less effective.

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Prognostic value of AIMS65 score in cirrhotic patients with variceal bleeding

MedPharmRes ◽

10.32895/ump.mpr.6.1.4 ◽

2021 ◽

Vol 6 (1) ◽

pp. 22-26

Author(s):

Trong Nguyen Dang Huynh

Keyword(s):

Variceal Bleeding ◽

Predictive Value ◽

Prognostic Value ◽

Area Under The Curve ◽

Scoring Systems ◽

Meld Score ◽

Operating Characteristics ◽

Increased Risk ◽

Cirrhotic Patients ◽

Ctp Score

Background: In cirrhotic patients, variceal bleeding remains a major cause of death. After a variceal bleeding episode, mortality and rebleeding rates spike for the first 6 weeks before levelling off. We aimed to evaluate the performance of AIMS65 score in comparison with Child-Turcotte-Pugh (CTP) score and model for end-stage liver disease (MELD) score in predicting 6-week mortality and rebleeding in cirrhotic patients with variceal bleeding. Method: Data were collected prospectively from patients with cirrhosis and variceal bleeding at Gastroenterology and Hepatology Department of Cho Ray hospital from September 2016 to April 2017. The primary endpoint was 6-week mortality and rebleeding. The prognostic value of AIMS65, CTP, and MELD scoring systems for 6-week mortality and rebleeding was compared by receiver operating characteristics curves (ROC) and the area under the curve (AUC). Results: Among 80 patients, 15% rebled and 25% died during 6-week follow-up. AUCROC of AIMS65, CTP, and MELD scores in predicting 6-week rebleeding were 0.68, 0.54, and 0.48, respectively. AUCROC of AIMS65, CTP, and MELD scores in predicting 6-week mortality were 0.80, 0.74, and 0.64, respectively. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of AIMS65 score at the cutoff point of 2 were 95%, 55%, 41.3%, and 97%, respectively. Conclusion: AIMS65 score is a simple yet applicable tool for risk stratification in cirrhotic patients with variceal bleeding. We recommend using AIMS65 score with a cut-off point of 2 to identify patients at increased risk for 6-week mortality after variceal bleeding.

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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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Development of a Bayesian Belief Network Model for Personalized Prognostic Risk Assessment in Colon Carcinomatosis

The American Surgeon ◽

10.1177/000313481107700225 ◽

2011 ◽

Vol 77 (2) ◽

pp. 221-230 ◽

Cited By ~ 10

Author(s):

Alexander Stojadinovic ◽

Aviram Nissan ◽

John Eberhardt ◽

Terence C. Chua ◽

Joerg O.W. Pelz ◽

...

Keyword(s):

Decision Support ◽

Predictive Model ◽

Negative Predictive Value ◽

Predictive Value ◽

Performance Status ◽

Area Under The Curve ◽

Decision Support Tools ◽

Operating Characteristics ◽

Peritoneal Cancer ◽

Support Tools

Multimodality therapy in selected patients with peritoneal carcinomatosis is gaining acceptance. Treatment-directing decision support tools are needed to individualize care and select patients best suited for cytoreductive surgery ± hyperthermic intraperitoneal chemotherapy (CRS ± HIPEC). The purpose of this study is to develop a predictive model that could support surgical decisions in patients with colon carcinomatosis. Fifty-three patients were enrolled in a prospective study collecting 31 clinical-pathological, treatment-related, and outcome data. The population was characterized by disease presentation, performance status, extent of peritoneal cancer (Peritoneal Cancer Index, PCI), primary tumor histology, and nodal staging. These preoperative parameters were analyzed using step-wise machine-learned Bayesian Belief Networks (BBN) to develop a predictive model for overall survival (OS) in patients considered for CRS ± HIPEC. Area-under-the-curve from receiver-operating-characteristics curves of OS predictions was calculated to determine the model's positive and negative predictive value. Model structure defined three predictors of OS: severity of symptoms (performance status), PCI, and ability to undergo CRS ± HIPEC. Patients with PCI < 10, resectable disease, and excellent performance status who underwent CRS ± HIPEC had 89 per cent probability of survival compared with 4 per cent for those with poor performance status, PCI > 20, who were not considered surgical candidates. Cross validation of the BBN model robustly classified OS (area-under-the-curve = 0.71). The model's positive predictive value and negative predictive value are 63.3 per cent and 68.3 per cent, respectively. This exploratory study supports the utility of Bayesian classification for developing decision support tools, which assess case-specific relative risk for a given patient for oncological outcomes based on clinically relevant classifiers of survival. Further prospective studies to validate the BBN model-derived prognostic assessment tool are warranted.

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Immunohistochemical panel to differentiate endometrial stromal sarcoma, uterine leiomyosarcoma and leiomyoma: something old and something new

Journal of Clinical Pathology ◽

10.1136/jclinpath-2015-202915 ◽

2015 ◽

Vol 68 (9) ◽

pp. 710-717 ◽

Cited By ~ 20

Author(s):

Helena Hwang ◽

Koji Matsuo ◽

Kara Duncan ◽

Elham Pakzamir ◽

Huyen Q Pham ◽

...

Keyword(s):

Predictive Value ◽

Smooth Muscle Actin ◽

Area Under The Curve ◽

Endometrial Stromal Sarcoma ◽

Low Grade ◽

Uterine Leiomyosarcoma ◽

Operating Characteristics ◽

Uterine Sarcomas ◽

Stromal Sarcoma ◽

Receiver Operating Characteristics Curve

AimsTo evaluate an immunohistochemical panel differentiating endometrial stromal sarcoma (ESS) from uterine leiomyosarcoma (ULMS) and leiomyoma (LM).Methods94 cases (28 ESS, 41 ULMS, 25 LM) were retrieved and arrayed. 10 immunomarkers (estrogen receptor (ER), progesterone receptor (PR), CD10, smooth muscle actin, desmin, h-caldesmon, transgelin, GEM, ASC1, stathmin1) were used. A predictive model was constructed and examined by receiver operating characteristics curve analysis to determine area under the curve (AUC).ResultsThe combination of ER+/PR+/CD10+/GEM−/h-caldesmon−/transgelin− can predict ESS versus ULMS with AUC predictive value of 0.872 (95% CI 0.784 to 0.961, p<0.0001). The combination of ER+/PR+/CD10+/h-caldesmon−/transgelin− can predict low grade (LG) ESS from ‘LG’ ULMS with AUC predictive value of 0.914 (95% CI 0.832 to 0.995, p<0.0001). Finally, ULMS and ESS, including the LGs, were more likely to be stathmin1+ than LM.ConclusionsDue to the different clinical course and management, adding novel antibodies (GEM, transgelin) to the well established immunohistochemistry panel seemed to be useful in distinguishing ESS from ULMS and LG ESS from ‘LG’ ULMS. Finally, stathmin1 expression could be of value in differentiating LM from uterine sarcomas.

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Gastric cancer detection using the serum pepsinogen test method

Tumori Journal ◽

10.1177/03008916211014961 ◽

2021 ◽

pp. 030089162110149

Author(s):

Dragan Trivanovic ◽

Stjepko Plestina ◽

Lorena Honovic ◽

Renata Dobrila-Dintinjana ◽

Jelena Vlasic Tanaskovic ◽

...

Keyword(s):

Gastric Cancer ◽

Early Detection ◽

Predictive Value ◽

Area Under The Curve ◽

Test Method ◽

Operating Characteristics ◽

Roc Curve Analysis ◽

Laboratory Assessment ◽

Pepsinogen I ◽

Sensitivity Specificity

Background: Gastric cancer (GC) is the eighth most common cause of cancer deaths in Croatia and one of the most common causes of cancer deaths worldwide. A reliable diagnostic tool for the early detection of GC is essential. Objective: We previously suggested a pepsinogen test method to reduce the mortality from GC by allowing early detection. Here, we report an updated analysis from a prospective single-center clinical study to evaluate the sensitivity and specificity of the pepsinogen test method and to determine whether this test can be used as a part of routine laboratory assessment of high-risk patients. Methods: We present mature data of the pepsinogen test method in the Croatian population after a median follow-up of 36 months. Statistical analyses were performed using a Mann-Whitney U test, multiple logistic regression, and receiver operating characteristics (ROC) to evaluate the predictive power of the assayed biomarkers. Results: Of the 116 patients, 25 patients had GC and 91 demonstrated a nonmalignant pathology based on tissue biopsy. Cutoff values were pepsinogen I ⩽70 and pepsinogen I/II ratio ⩽3.0. Using ROC curve analysis, the accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were determined to be 87.22%, 78.12%, 90.10%, 71.43%, and 92.86%, respectively, for the diagnosis of GC. The area under the curve was 0.700 (95% confidence interval 0.57–0.83). Conclusion: Pepsinogen tests are valuable for screening a population in need of further diagnosis and could help to avoid unnecessary invasive endoscopic procedures.

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The Challenge of Using an Antigen Test as a Screening Tool for SARS-CoV-2 Infection in an Emergency Department: Experience of a Tertiary Care Hospital in Southern Italy

BioMed Research International ◽

10.1155/2021/3893733 ◽

2021 ◽

Vol 2021 ◽

pp. 1-7

Author(s):

Daniela Loconsole ◽

Francesca Centrone ◽

Caterina Morcavallo ◽

Silvia Campanella ◽

Anna Sallustio ◽

...

Keyword(s):

Emergency Department ◽

Predictive Value ◽

Demographic Data ◽

Tertiary Care ◽

Previous History ◽

Area Under The Curve ◽

Care Hospital ◽

Antigen Test ◽

Operating Characteristics ◽

Likelihood Ratios

Background. In emergency hospital settings, rapid diagnosis and isolation of SARS-CoV-2 patients are required. The aim of the study was to evaluate the performance of an antigen chemiluminescence enzymatic immunoassay (CLEIA) and compare it with that of Real-time Reverse transcription-Polymerase Chain Reaction (RT-qPCR), the gold standard assay, to assess its suitability as a rapid diagnostic method for managing patients in the emergency department (ED). Methods. Consecutive patients with no previous history of SARS-CoV-2 infection attending the ED of the Policlinico Hospital of Bari between 23rd October and 4th November 2020 were enrolled. Clinical and demographic data were collected for all patients. Nasopharyngeal swabs collected on admission were subjected both to molecular (RT-qPCR) and antigen (CLEIA) tests for SARS-CoV-2. The performance of the CLEIA antigen test was analyzed using R Studio software and Microsoft Excel. Receiver operating characteristics were also performed. Results. A total of 911 patients were enrolled, of whom 469 (51.5%) were male. Of the whole cohort, 23.7% tested positive for SARS-CoV-2 by RT-qPCR and 24.5% by CLEIA. The overall concordance rate was 96.8%. The sensitivity, specificity, positive predictive value, and negative predictive value of the antigen test were 94.9% (95% CI, 91.9–97.0), 97.4% (95% CI, 96.5–98.1), 91.9% (95% CI, 89.0–94.0), and 98.4% (95% CI, 97.4–99.1), respectively. The area under the curve (AUC) was 0.99. The kappa coefficient was 0.91. The overall positive and negative likelihood ratios were 37 (95% CI 23-58) and 0.05 (95% CI, 0.03–0.09), respectively. Conclusions. Data analysis demonstrated that the antigen test showed very good accuracy for discriminating SARS-CoV-2-infected patients from negative participants. The CLEIA is suitable for rapid clinical diagnosis of patients in hospital settings, particularly in EDs with a high prevalence of symptomatic patients and where a rapid turnaround time is critical. Timely and accurate testing for SARS-CoV-2 plays a crucial role in limiting the spread of the virus.

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Procalcitonin to Detect Bacterial Infections in Critically Ill Pediatric Patients

Clinical Pediatrics ◽

10.1177/0009922817715937 ◽

2017 ◽

Vol 56 (9) ◽

pp. 821-827 ◽

Cited By ~ 3

Author(s):

David M. Jacobs ◽

Maya Holsen ◽

Shirley Chen ◽

Nicholas M. Fusco ◽

Amanda B. Hassinger

Keyword(s):

Predictive Value ◽

Bacterial Infections ◽

Pediatric Patients ◽

Area Under The Curve ◽

Pediatric Intensive Care ◽

Antibiotic Consumption ◽

Operating Characteristics ◽

Diagnostic Ability ◽

Discriminatory Ability ◽

Serious Bacterial Infections

The diagnostic power of procalcitonin (PCT) in the pediatric intensive care unit (PICU) is uncertain. This study aimed to determine the diagnostic ability of PCT to detect serious bacterial infections (SBI) in a heterogeneous PICU population. This was a retrospective cohort study of patients on whom a PCT level was obtained within 48 hours of admission to a PICU from 2013 to 2015. Discriminatory ability of PCT to predict SBI was examined by test and receiver operating characteristics (AUC [area under the curve]-ROC). Seventy-five patients were included and 28 (37%) had an SBI (median PCT = 6.48 ng/mL) compared with 47 (63%) in the noninfection group (median PCT = 0.23 ng/mL, P < .0001). PCT was able to adequately predict SBI (AUC-ROC = 0.83, 95% CI 0.74-0.93; P < .0001), and a PCT ≥1.28 ng/mL was the optimal threshold to detect SBI with a positive predictive value of 76.7% and negative predictive value of 88.9%. PCT adequately predicted SBI in a heterogeneous PICU population and may be useful for minimizing antibiotic consumption.

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Drain output volume after pancreaticoduodenectomy is a useful warning sign for postoperative complications

BMC Surgery ◽

10.1186/s12893-021-01285-1 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Taro Fukui ◽

Hiroshi Noda ◽

Fumiaki Watanabe ◽

Takaharu Kato ◽

Yuhei Endo ◽

...

Keyword(s):

Predictive Value ◽

Roc Analysis ◽

Independent Predictor ◽

Area Under The Curve ◽

Warning Sign ◽

Operating Characteristics ◽

Protein Loss ◽

Chyle Leak ◽

Major Complications ◽

Output Volume

Abstract Introduction The drain output volume (DOV) after pancreaticoduodenectomy (PD) is an easily assessable indicator in clinical settings. We explored the utility of the DOV as a possible warning sign of complications after PD. Methods A total of 404 patients undergoing PD were considered for inclusion. The predictability of the DOV for overall morbidity, major complications, intraabdominal infection (IAI), clinically relevant (CR) postoperative pancreatic fistula (POPF), CR delayed gastric emptying (DGE), CR chyle leak (CL), and CR post-pancreatectomy hemorrhaging (PPH) was evaluated. Results One hundred (24.8%) patients developed major complications, and 131 (32.4%) developed IAI. Regarding CR post-pancreatectomy complications, 75 (18.6%) patients developed CR-POPF, 23 (5.7%) developed CR-DGE, 20 (5.0%) developed CR-CL, and 28 (6.9%) developed CR-PPH. The median DOV on postoperative day (POD) 1 and POD 3 was 266 and 234.5 ml, respectively. A low DOV on POD 1 was an independent predictor of CR-POPF, and a high DOV on POD 3 was an independent predictor of CR-CL. A receiver operating characteristics (ROC) analysis revealed that the DOV on POD 1 had a negative predictive value (area under the curve [AUC] 0.655, sensitivity 65.0%, specificity 65.3%, 95% confidence interval [CI]: 0.587–0.724), with a calculated optimal cut-off value of 227 ml. An ROC analysis also revealed that the DOV on POD 3 had a positive predictive value (AUC 0.753, sensitivity 70.1%, specificity 75.0%, 95% CI: 0.651–0.856), with a calculated optimal cut-off value of 332 ml. Conclusion A low DOV on POD 1 might be a postoperative warning sign for CR-POPF, similar to high drain amylase (DA) on POD 1, high DA on POD 3, and high CRP on POD 3. When the DOV on POD 1 after PD was low, surgeons should evaluate the reasons of a low DOV. A high DOV on POD 3 was a postoperative warning sign CR-CL, and might require an appropriate management of protein loss.

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