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Diagnostic accuracy of ESPEN Diagnostic Criteria for malnutrition in selected clinical populations

The effect of a dermoscopy training programme on diagnostic accuracy and management decisions regarding pigmented skin lesions: a comparison between dermal therapists and general practitioners

Abstract Background Dermoscopy is known to increase the diagnostic accuracy of pigmented skin lesions (PSLs) when used by trained professionals. The effect of dermoscopy training on the diagnostic ability of dermal therapists (DTs) has not been studied so far. Objectives This study aimed to investigate whether DTs, in comparison with general practitioners (GPs), benefited from a training programme including dermoscopy, in both their ability to differentiate between different forms of PSL and to assign the correct therapeutic strategy. Methods In total, 24 DTs and 96 GPs attended a training programme on PSLs. Diagnostic skills as well as therapeutic strategy were assessed, prior to the training (pretest) and after the training (post-test) using clinical images alone, as well as after the addition of dermatoscopic images (integrated post-test). Bayesian hypothesis testing was used to determine statistical significance of differences between pretest, post-test and integrated post-test scores. Results Both the DTs and the GPs demonstrated benefit from the training: at the integrated post-test, the median proportion of correctly diagnosed PSLs was 73% (range 30–90) for GPs and 63% (range 27–80) for DTs. A statistically significant difference between pretest results and integrated test results was seen, with a Bayes factor>100. At 12 percentage points higher, the GPs outperformed DTs in the accuracy of detecting PSLs. Conclusions The study shows that a training programme focusing on PSLs while including dermoscopy positively impacts detection of PSLs by DTs and GPs. This training programme could form an integral part of the training of DTs in screening procedures, although additional research is needed

Diagnostic accuracy of the PG-SGA short form and NRS 2002 in internal medicine ward

Rationale: The PG-SGA is a validated instrument to assess malnutrition and its risk factors. Its patient component, i.e. the PG-SGA Short Form (SF), can be used as screening instrument. In this multicenter study, we aimed to assess diagnostic accuracy of the PG-SGA SF and NRS 2002, in patients at the Internal Medicine ward.Methods: In 192 patients (76.0±13.5 years; 53% female) in 9 Portuguese internal medicine wards, malnutrition risk was assessed by PG-SGA SF and NRS 2002. PG-SGA SF ≤8 was defined as low/medium malnutrition risk and NRS 2002 ≤2 as low risk. PG-SGA SF ≥9 and NRS 2002 ≥3 were defined as high malnutrition risk. Nutritional status was assessed by the full PG-SGA (reference method). Malnutrition was defined as PG-SGA Stage B (moderate/suspected malnutrition) or Stage C (severely malnourished). Diagnostic accuracy was tested by sensitivity, specificity, positive and negative predictive value, and receiver operating curve. Agreement between PG-SGA and NRS-2002 was tested by McNemar’s test and Cohen’s kappa (κ).Results: Forty-six % and 53% were categorized as at risk of malnutrition by PG-SGA SF and NRS 2002, respectively. In total, 55% were malnourished. Sensitivity, specificity, positive and negative predictive value of PG-SGA SF and NRS 2002 were 0.84, 1.00, 1.00, 0.83 and 0.74, 0.74, 0.77 and 0.70, respectively. Area under curve of PG-SGA SF and NRS 2002 was 0.987 and 0.778 respectively. McNemar’s test showed no significant disagreement (p=0.86) between PG-SGA SF and NRS 2002. Cohen’s kappa showed weak agreement (κ=0.492; p<0.001) (Table 1).Conclusion: Our findings indicate that in patients at the internal medicine ward, PG-SGA SF shows better diagnostic accuracy than NRS 2002, i.e. better sensitivity and specificity.

A Bayesian Network Analysis of the Diagnostic Process and Its Accuracy to Determine How Clinicians Estimate Cardiac Function in Critically Ill Patients

BACKGROUND: Hemodynamic assessment of critically ill patients is a challenging endeavor, and advanced monitoring techniques are often required to guide treatment choices. Given the technical complexity and occasional unavailability of these techniques, estimation of cardiac function based on clinical examination is valuable for critical care physicians to diagnose circulatory shock. Yet, the lack of knowledge on how to best conduct and teach the clinical examination to estimate cardiac function has reduced its accuracy to almost that of "flipping a coin."OBJECTIVE: The aim of this study was to investigate the decision-making process underlying estimates of cardiac function of patients acutely admitted to the intensive care unit (ICU) based on current standardized clinical examination using Bayesian methods.METHODS: Patient data were collected as part of the Simple Intensive Care Studies-I (SICS-I) prospective cohort study. All adult patients consecutively admitted to the ICU with an expected stay longer than 24 hours were included, for whom clinical examination was conducted and cardiac function was estimated. Using these data, first, the probabilistic dependencies between the examiners' estimates and the set of clinically measured variables upon which these rely were analyzed using a Bayesian network. Second, the accuracy of cardiac function estimates was assessed by comparison to the cardiac index values measured by critical care ultrasonography.RESULTS: A total of 1075 patients were included, of which 783 patients had validated cardiac index measurements. A Bayesian network analysis identified two clinical variables upon which cardiac function estimate is conditionally dependent, namely, noradrenaline administration and presence of delayed capillary refill time or mottling. When the patient received noradrenaline, the probability of cardiac function being estimated as reasonable or good P(ER,G) was lower, irrespective of whether the patient was mechanically ventilated (P[ER,G|ventilation, noradrenaline]=0.63, P[ER,G|ventilation, no noradrenaline]=0.91, P[ER,G|no ventilation, noradrenaline]=0.67, P[ER,G|no ventilation, no noradrenaline]=0.93). The same trend was found for capillary refill time or mottling. Sensitivity of estimating a low cardiac index was 26% and 39% and specificity was 83% and 74% for students and physicians, respectively. Positive and negative likelihood ratios were 1.53 (95% CI 1.19-1.97) and 0.87 (95% CI 0.80-0.95), respectively, overall.CONCLUSIONS: The conditional dependencies between clinical variables and the cardiac function estimates resulted in a network consistent with known physiological relations. Conditional probability queries allow for multiple clinical scenarios to be recreated, which provide insight into the possible thought process underlying the examiners' cardiac function estimates. This information can help develop interactive digital training tools for students and physicians and contribute toward the goal of further improving the diagnostic accuracy of clinical examination in ICU patients.TRIAL REGISTRATION: ClinicalTrials.gov NCT02912624; https://clinicaltrials.gov/ct2/show/NCT02912624.

The diagnostic accuracy of clinical examination for estimating cardiac index in critically ill patients

PURPOSE: Clinical examination is often the first step to diagnose shock and estimate cardiac index. In the Simple Intensive Care Studies-I, we assessed the association and diagnostic performance of clinical signs for estimation of cardiac index in critically ill patients.METHODS: In this prospective, single-centre cohort study, we included all acutely ill patients admitted to the ICU and expected to stay > 24 h. We conducted a protocolised clinical examination of 19 clinical signs followed by critical care ultrasonography for cardiac index measurement. Clinical signs were associated with cardiac index and a low cardiac index (< 2.2 L min-1 m2) in multivariable analyses. Diagnostic test accuracies were also assessed.RESULTS: We included 1075 patients, of whom 783 (73%) had a validated cardiac index measurement. In multivariable regression, respiratory rate, heart rate and rhythm, systolic and diastolic blood pressure, central-to-peripheral temperature difference, and capillary refill time were statistically independently associated with cardiac index, with an overall R2 of 0.30 (98.5% CI 0.25-0.35). A low cardiac index was observed in 280 (36%) patients. Sensitivities and positive and negative predictive values were below 90% for all signs. Specificities above 90% were observed only for 110/280 patients, who had atrial fibrillation, systolic blood pressures < 90 mmHg, altered consciousness, capillary refill times > 4.5 s, or skin mottling over the knee.CONCLUSIONS: Seven out of 19 clinical examination findings were independently associated with cardiac index. For estimation of cardiac index, clinical examination was found to be insufficient in multivariable analyses and in diagnostic accuracy tests. Additional measurements such as critical care ultrasonography remain necessary.

Do knowledge, knowledge sources and reasoning skills affect the accuracy of nursing diagnoses?

BACKGROUND: This paper reports a study about the effect of knowledge sources, such as handbooks, an assessment format and a predefined record structure for diagnostic documentation, as well as the influence of knowledge, disposition toward critical thinking and reasoning skills, on the accuracy of nursing diagnoses.Knowledge sources can support nurses in deriving diagnoses. A nurse's disposition toward critical thinking and reasoning skills is also thought to influence the accuracy of his or her nursing diagnoses.METHOD: A randomised factorial design was used in 2008-2009 to determine the effect of knowledge sources. We used the following instruments to assess the influence of ready knowledge, disposition, and reasoning skills on the accuracy of diagnoses: (1) a knowledge inventory, (2) the California Critical Thinking Disposition Inventory, and (3) the Health Science Reasoning Test. Nurses (n = 249) were randomly assigned to one of four factorial groups, and were instructed to derive diagnoses based on an assessment interview with a simulated patient/actor.RESULTS: The use of a predefined record structure resulted in a significantly higher accuracy of nursing diagnoses. A regression analysis reveals that almost half of the variance in the accuracy of diagnoses is explained by the use of a predefined record structure, a nurse's age and the reasoning skills of `deduction' and `analysis'.CONCLUSIONS: Improving nurses' dispositions toward critical thinking and reasoning skills, and the use of a predefined record structure, improves accuracy of nursing diagnoses.