scholarly journals Externe Validierung einer Single-Item Skala zur Erfassung der Motivation zum Rauchstopp

2021 ◽  
Vol 67 (4) ◽  
pp. 171-180
Author(s):  
Yekaterina Pashutina ◽  
Sabrina Kastaun ◽  
Elena Ratschen ◽  
Lion Shahab ◽  
Daniel Kotz
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Odds Ratio ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Single Item ◽  
Logistische Regression ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Zusammenfassung. Zielsetzung: Die Motivation to Stop Scale (MTSS) ist eine englischsprachige Single-Item Skala zur Vorhersage von Rauchstoppversuchen. Ziel dieser Arbeit war die externe Validierung der deutschsprachigen Version der MTSS (Motivation zum Rauchstopp Skala, MRS) an einer Stichprobe von aktuell Tabakrauchenden in Deutschland. Methodik: Datenbasis war die Deutsche Befragung zum Rauchverhalten (DEBRA), eine deutschlandweite, persönlich-mündliche Haushaltsbefragung von Personen ab 14 Jahren mit telefonischer Nachbefragung nach 6 Monaten. Analysiert wurden Daten aus den ersten 18 Wellen (Juni 2016–Mai 2019) von 767 aktuell Tabakrauchenden. Die MRS (Stufe 1–7 = keine bis höchste Motivation) wurde bei der Erstbefragung eingesetzt. Bei der Nachbefragung wurde die Anzahl der Rauchstoppversuche seit Erstbefragung erfasst. Logistische Regression wurde durchgeführt und die diskriminative Genauigkeit der MRS mittels Area Under the Receiver Operating Characteristic Curve (ROC-AUC) berechnet. Ergebnisse: Bei Erstbefragung waren 61,1 % ( n = 469; 95 % Konfidenzintervall (KI) = 57.7–64.6) der 767 Rauchenden nicht zum Rauchstopp motiviert (MRS-Stufe 1–2). Insgesamt unternahmen 185 der 767 Rauchenden (24,1 %; 95 % KI = 21.1–27.1) zwischen der Erst- und Nachbefragung mindestens einen Rauchstoppversuch. Mit steigender Motivationsstufe auf der MRS nahm die Wahrscheinlichkeit für einen Rauchstoppversuch zu: Odds Ratio = 1.37, 95 % KI = 1.25–1.51, bei einer diskriminativen Genauigkeit von ROC-AUC = 0.64. Schlussfolgerung: Die MRS ist ein kurzes und valides Messinstrument zur Erfassung der Rauchstoppmotivation im deutschen Sprachraum.

A validated novel preoperative index to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology: A cohort study

2019 ◽  
Vol 30 (7-8) ◽  
pp. 221-228
Author(s):  
Shahab Hajibandeh ◽  
Shahin Hajibandeh ◽  
Nicholas Hobbs ◽  
Jigar Shah ◽  
Matthew Harris ◽  
...  
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Validation Cohort ◽  
Characteristic Curve ◽  
Curve Analysis ◽  
Emergency Laparotomy ◽  
Contamination Index ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Aims To investigate whether an intraperitoneal contamination index (ICI) derived from combined preoperative levels of C-reactive protein, lactate, neutrophils, lymphocytes and albumin could predict the extent of intraperitoneal contamination in patients with acute abdominal pathology. Methods Patients aged over 18 who underwent emergency laparotomy for acute abdominal pathology between January 2014 and October 2018 were randomly divided into primary and validation cohorts. The proposed intraperitoneal contamination index was calculated for each patient in each cohort. Receiver operating characteristic curve analysis was performed to determine discrimination of the index and cut-off values of preoperative intraperitoneal contamination index that could predict the extent of intraperitoneal contamination. Results Overall, 468 patients were included in this study; 234 in the primary cohort and 234 in the validation cohort. The analyses identified intraperitoneal contamination index of 24.77 and 24.32 as cut-off values for purulent contamination in the primary cohort (area under the curve (AUC): 0.73, P < 0.0001; sensitivity: 84%, specificity: 60%) and validation cohort (AUC: 0.83, P < 0.0001; sensitivity: 91%, specificity: 69%), respectively. Receiver operating characteristic curve analysis also identified intraperitoneal contamination index of 33.70 and 33.41 as cut-off values for feculent contamination in the primary cohort (AUC: 0.78, P < 0.0001; sensitivity: 87%, specificity: 64%) and validation cohort (AUC: 0.79, P < 0.0001; sensitivity: 86%, specificity: 73%), respectively. Conclusions As a predictive measure which is derived purely from biomarkers, intraperitoneal contamination index may be accurate enough to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology and to facilitate decision-making together with clinical and radiological findings.

A conditional approach for the receiver operating characteristic curve construction to evaluate diagnostic test performance in a family-matched case–control design

2021 ◽  
pp. 096228022199595
Author(s):  
Yalda Zarnegarnia ◽  
Shari Messinger
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Case Control ◽  
Paired Data ◽  
Characteristic Curves ◽  
Receiver Operating Characteristic Curves ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Receiver operating characteristic curves are widely used in medical research to illustrate biomarker performance in binary classification, particularly with respect to disease or health status. Study designs that include related subjects, such as siblings, usually have common environmental or genetic factors giving rise to correlated biomarker data. The design could be used to improve detection of biomarkers informative of increased risk, allowing initiation of treatment to stop or slow disease progression. Available methods for receiver operating characteristic construction do not take advantage of correlation inherent in this design to improve biomarker performance. This paper will briefly review some developed methods for receiver operating characteristic curve estimation in settings with correlated data from case–control designs and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using conditional receiver operating characteristic curves will be demonstrated. The proposed approach will use information about correlation among biomarker values, producing conditional receiver operating characteristic curves that evaluate the ability of a biomarker to discriminate between affected and unaffected subjects in a familial paired design.

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