Poor Positive Predictive Value Research Articles

Assessing Treatment Response after Lung SABR: An Evaluation of the Predictive Value of RECIST Criteria

<h3>Purpose/Objective(s)</h3> Response Evaluation Criteria In Solid Tumors (RECIST) – version 1.1 is a commonly used framework to assess treatment response. However, response assessment after lung stereotactic ablative radiotherapy (SABR) can be difficult due to radiation-induced lung changes. The goal of this study was to assess how frequently lung lesions treated with SABR triggered RECIST criteria for recurrence and to correlate RECIST findings with actual treatment outcomes. <h3>Materials/Methods</h3> We reviewed patients who were treated with lung SABR between 2010-2015. Prescribed dose was 54-60 Gy in 3-8 fractions. Both primary lung and metastatic lesions were included. All lesion measurements were based on maximum diameter on CT axial slices. After treatment, progressive disease (PD) by RECIST was based on strict RECIST criteria and defined as: 1) increase of ≥ 20% compared to post-treatment minimum and 2) ≥ 5 mm absolute increase. The final assessment of recurrence was based on subsequent changes in lesions size after PD by RECIST and, when available, PET scan and/or pathology. When assessing subsequent changes in lesion size, stability (≤ 20% change) in size for at least one year or a decrease (> 20%) in size indicated no recurrence, while subsequent growth (> 20%) indicated recurrence. The assessment of lesion response by the treating radiation oncologist (RO) in the clinical record was also recorded when available. <h3>Results</h3> A total of 85 patients, with 88 lesions, met inclusion criteria. 75 of these lesions were lung primaries, the remainder were metastases. Median patient age was 79 years (IQR: 73-85) and mean lesion size was 2.1 ± 0.9 cm. Median follow-up was 52 months (IQR: 33-68). 66% (58/88) of treated lesions met criteria for PD by RECIST. However, on final assessment only 10% (9/88) were found to have recurrence. The positive predictive value (PPV) of RECIST criteria was 0.16. In the subset of patients with primary lung tumors only, 64% (48/75) were classified as PD by RECIST, but only 12% (9/75) were categorized as recurrence on final assessment. PPV was 0.19. The predictive value of RECIST was lower when PD by RECIST was triggered ≤ 12 vs. > 12 months post-treatment (PPV 0.08 vs. PPV 0.21). Median time to PD by RECIST was 19 months (IQR: 12-27) for those with recurrence vs. 15 months (IQR: 8-24) for those without recurrence on final assessment (p=0.13). Assessment by treating RO was only available for 57% (50/88) of cases, but concordance with final study assessment was 0.85, translating to an overall predictive accuracy of 94% (47/50). <h3>Conclusion</h3> Using strict RECIST criteria, two-thirds of patients treated with lung SABR met criteria for PD. However, on further follow-up only a minority of these patients were felt to have recurrence, leading to a poor PPV for RECIST criteria in this setting. Further work is needed to develop validated criteria for designation of recurrence after lung SABR.

Transcranial versus direct electrical stimulation for intraoperative motor-evoked potential monitoring: Prognostic value comparison in asleep brain tumor surgery.

ObjectiveSafe resection of gliomas involving motor pathways in asleep-anesthesia requires the combination of brain mapping, to identify and spare essential motor sites, and continuous monitoring of motor-evoked potentials (MEPs), to detect possible vascular damage to the corticospinal tract (CST). MEP monitoring, according to intraoperative neurophysiology societies, is generally recommended by transcranial electrodes (TES), and no clear indications of direct cortical stimulation (DCS) or the preferential use of one of the two techniques based on the clinical context is available. The main aim of the study was to identify the best technique(s) based on different clinical conditions, evaluating the efficacy and prognostic value of both methodologies.MethodsA retrospective series of patients with tumors involving the motor pathways who underwent surgical resection with the aid of brain mapping and combined MEP monitoring via TES and DCS was evaluated. Irreversible MEP amplitude reduction (>50% compared to baseline) was used as an intraoperative warning and correlated to the postoperative motor outcome. Selectivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were computed for both techniques.ResultsFour hundred sixty-two patients were retrospectively analyzed, and only 1.9% showed a long-term motor impairment. Both TES and DCS obtained high specificity and NPV for the acute and 1-month motor deficit. Sensitivity was rather low for the acute deficit but excellent considering the 1-month follow-up for both techniques. DCS was extremely reliable in predicting a postoperative motor decline (PPV of 100% and 90% for acute and long-term deficit, respectively). Conversely, TES produced a high number of false-positive results, especially for long-term deficits (65, 87.8% of all warnings) therefore obtaining poor PPV values (18% and 12% for acute and 1-month deficits, respectively). TES false-positive results were significantly associated with parietal tumors and lateral patient positioning.ConclusionsData support the use of mapping and combined monitoring via TES and DCS. The sole TES monitoring is reliable in most procedures but not in parietal tumors or those requiring lateral positioning. Although no indications are available in international guidelines, DCS should be recommended, particularly for cases approached by a lateral position.

Comparison of Mallampati test in sitting position and in supine position for prediction of difficult tracheal intubation among adult patients who underwent surgery under general anesthesia at Addis Ababa governmental hospitals 2021, comparative cross-sectional study.

BackgroundThe Mallampati test is used to evaluate the airway to predict difficult laryngoscopy and intubation. The sitting position is the standard for this test, but it has limited practical utility due to its low sensitivity and moderate specificity in predicting difficult intubation and laryngoscopy. The supine position, on the other hand, may improve its efficacy.ObjectiveTo assess the Mallampati test in sitting and supine positions on predicting difficult laryngoscopy and intubation among Adult surgical patients undergoing general anesthesia in selected governmental hospitals of Addis Ababa.MethodA cross-sectional study was conducted on 403 adult patients who underwent surgery that required endotracheal intubation. The preoperative Mallampati test in sitting and supine positions was compared to the Cormac and Lehan grade and Intubation Difficulty Scale using the chi-square test. The Statistical Package for Social Sciences (SPSS) software version 26.0 was used to analyze the data. A p-value of less than 0.05 was used to determine statistical significance. As statistical measurements, sensitivity, specificity, positive predictive values, and negative predictive values were calculated.ResultThe incidence of difficult laryngoscopy and intubation is 13.7% and 9.7% respectively. Supine positions show a sensitivity of 78.8%; specificity of 93%; a positive predictive value of 64.1 and a negative predictive value of 96. Whereas sitting shows sensitivity of 75%; specificity of 96.3%; positive predictive value of 76.5 and negative predictive value of 96 concerning difficult laryngoscopy. Related to difficult intubation supine shows a sensitivity of 78.4%; 89.8% specificity; 45.3 positive predictive value and 97.5 negative predictive values, whereas sitting shows 73% sensitivity, 93% specificity, 52.9% positive predictive value and 97% negative predictive value.Conclusionand recommendation: For predicting difficult tracheal intubation and laryngoscopy, sitting has a high specificity and positive predictive value, but supine has high sensitivity and negative predictive value. Despite its poor positive predictive value, supine has a comparable prediction for difficult intubation therefore it can be used as an alternative approach.

Emergent neurovascular imaging in patients with blunt traumatic injuries.

Blunt cerebrovascular injuries (BCVIs) are commonly encountered after blunt trauma. Given the increased risk of stroke incurred after BCVI, it is crucial that they are promptly identified, characterized, and treated appropriately. Current screening practices generally consist of computed tomography angiography (CTA), with escalation to digital subtraction angiography for higher-grade injuries. Although it is quick, cost-effective, and readily available, CTA suffers from poor sensitivity and positive predictive value. A review of the current literature was conducted to examine the current state of emergent imaging for BCVI. After excluding reviews, irrelevant articles, and articles exclusively available in non-English languages, 36 articles were reviewed and included in the analysis. In general, as CTA technology has advanced, so too has detection of BCVI. Magnetic resonance imaging (MRI) with sequences such as vessel wall imaging, double-inversion recovery with black blood imaging, and magnetization prepared rapid acquisition echo have notably improved the utility for MRI in characterizing BCVIs. Finally, transcranial Doppler with emboli detection has proven to be associated with strokes in anterior circulation injuries, further allowing for the identification of high-risk lesions. Overall, imaging for BCVI has benefited from a tremendous amount of innovation, resulting in better detection and characterization of this pathology.

Clinical predictors of pulmonary embolism for inpatients: are computed tomography pulmonary angiograms being requested appropriately?

The heterogeneity of inpatient pulmonary embolism (PE) presentations may lead to computed tomography pulmonary angiograms (CTPA) being over-requested. Current clinical predictors for PE, including Wells criteria and Pulmonary Embolism Rule-out Criteria (PERC), have predominantly focussed on outpatient and emergency department populations. To determine the clinical indicators for ordering inpatient CTPA and the predictors of positive scans for PE. Consecutive inpatient CTPA (performed >24 h after admission) from January 2017 to December 2017 were retrospectively reviewed. Variables including baseline characteristics, vital signs and risk factors for PE were extracted. A total of 312 CTPA was reviewed (average patient age 67 years; 46% male) and 36 CTPA were positive for PE (11.5%). The average time to inpatient CTPA request was 7 days. Clinical indicators associated with positive scans were hypoxia (odds ratio (OR) 2.4; 95% confidence interval (CI) 1.1-5.6), tachypnoea (OR 2.5; 95% CI 1.2-6.0), recent surgery or immobilisation (OR 2.7; 95% CI 1.2-6.4), S1Q3T3 pattern on electrocardiogram (ECG; OR 7.2; 95% CI 1.4-35.7) and right bundle branch block pattern on ECG (OR 4.7; 95% CI 1.6-13.1). Hypotension, fever and malignancy were not significant. Both PERC and Wells criteria had poor positive predictive value (12% and 27% respectively), but the negative predictive value for PERC and Wells was 100% and 95.8% respectively. Inpatient CTPA appear to be over-requested and can potentially be rationalised based on a combination of clinical predictors and Wells criteria and/or PERC rule. Further prospective studies are needed to develop accurate clinical decision tools targeted towards inpatients.

This Month in Pediatric Urology

You have accessJournal of UrologyThis Month in Pediatric Urology1 Oct 2022This Month in Pediatric Urology Julian Wan Julian WanJulian Wan More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002899AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail Diagnostic Code-Based Screening for Identifying Children with Primary Hyperoxaluria Before hypotheses could be generated, observation and data were needed. These conjectures could then be tested and their results collated. The interpretation of these new data restarts the cycle; hypotheses are discarded, revised, and reformulated. New tests are run and so on and so forth. Arthur Conan Doyle’s Sherlock Holmes, the famous fictional detective notable for his deductive acumen, identified a key weakness to this method: it needed reliable observations. In “The Adventure of the Copper Beeches,” he exclaims “Data! Data! Data! … I can’t make bricks without clay.”1 The near ubiquity of the computers, the Internet, and electronic medical records offer the hope that data could be gathered from vast physical and virtual networks. Reports of rare and unusual conditions that would take hundreds of years to collate by any single practitioner or institution could be gathered easily. Common conditions could likewise be accumulated and subjected to new analysis. In a multi-institutional study, Tasian et al (page 898) investigated this idea by evaluating the use of diagnostic clinical codes for primary hyperoxaluria.2 They obtained data from PEDSnet, a clinical research network that gathers electronic medical records comprising millions of children from a consortium of large children’s hospitals. They found, unfortunately, that there are weaknesses in the accuracy of coding and discovered the data not to be as useful as they might hope. The diagnostic codes for primary hyperoxaluria have poor positive predictive value; only those patients who had additional coding were most predictive. This suggests caution and preparations are needed when using large administrative data sets—one cannot simply presume accuracy and validity despite the relative ease of acquisition and transmission.

Diagnostic Code-Based Screening for Identifying Children with Primary Hyperoxaluria.

We evaluated the utility of diagnostic codes to screen for patients with primary hyperoxaluria (PH) and evaluate their positive predictive value (PPV) in identifying children with this rare condition in PEDSnet, a clinical research network of pediatric health systems that shares electronic health records data. We conducted a cross-sectional study of children who received care at 7 PEDSnet institutions from January 2009 through January 2021. We developed and applied screening criteria using diagnostic codes that generated 3 categories of the hypothesized probability of PH. Tier 1 had specific diagnostic codes for PH; tier 2 had codes for hyperoxaluria, oxalate nephropathy, or oxalosis; and tier 3 had a combination of ≥2 codes for disorder of carbohydrate metabolism and ≥1 code for kidney stones. We reviewed the electronic health records of patients with possible PH to confirm PH diagnosis and evaluate the accuracy and timing of diagnostic codes. The PPV of the codes was compared across tiers, time, PH type, and site. We identified 341 patients in the screen; 33 had confirmed PH (9.7%). Tier 1 had the highest proportion of PH; however, the PPV was only 20%. The degree to which an institution accurately represented point of care diagnoses in the data extraction process was predictive of higher PPV. The PPV of diagnostic codes was highest for PH3 (100%) and lowest for PH1 (22.8%). Diagnostic codes for PH have poor PPV. Findings suggest that one should be careful in research using large databases in which source validation is not possible.

Proximal risk for suicide in correctional settings: A call for priority research.

Suicide is the leading cause of death among jail detainees and the third leading cause of death among state prison inmates. These populations have been recognized as a high-risk group deserving special clinical attention. The literature on deaths by suicide in correctional settings has identified numerous risk factors for eventual death, but few of these risk factors are specific to the last days of life to aid clinicians in estimating near-term risk of serious self-injury or death. The poor understanding of near-term risk is particularly important in jail settings where many suicide deaths occur within 24 hr of entry. Although screening instruments for suicide risk factors are commonly used with jail/prison populations, few have been validated in those settings and all have poor positive predictive value. We call for a focused research effort to improve the identification of those at risk of near-term suicide and to produce tools for clinicians that will reduce the burden of suicide among jail and prison inmates. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A cohort study on use of the spot urine calcium-creatinine ratio for prediction of antepartum preeclampsia among high-risk pregnant women in Delta State, Nigeria

Background/Aim: Preeclampsia is a multisystemic disorder, which significantly contributes to maternal and fetal morbidity and mortality, especially in developing countries where it accounts for about one-third of maternal mortality cases. Predicting its occurrence will reveal a sizeable population of pregnant women who will undoubtedly benefit from prevention. The ideal screening marker for the disease is still being investigated. The urine calcium-creatinine ratio (CCR) is an inexpensive, simple, and easily assayed biomarker. This study determined the accuracy of the spot urinary calcium-creatinine ratio in predicting the occurrence of preeclampsia.&#x0D; Methods: This was a prospective cohort study conducted in Delta State, which involved four healthcare facilities in Nigeria. A total of 138 pregnant women between 8 and 18 weeks gestation were recruited. Urine samples were obtained at 18 weeks to assay their CCR, and patients were followed up weekly for blood pressure measurement and dipstick urinalysis until delivery.&#x0D; Results: The mean spot urine CCR in this study was 0.225 (0.101). It was significantly lower in women who developed preeclampsia compared to normotensive women (P &lt; 0.001). Multiple logistics regression analysis showed that the association between urine CCR and occurrence of preeclampsia was statistically significant. At a receiver operating characteristic cutoff of ≤ 0.1065, CCR had a sensitivity of 75%, specificity of 91.3%, positive predictive value (PPV) of 35.3%, and negative predictive value (NPV) of 98.3%. The low PPV of 35.3% can be explained by the low prevalence of preeclampsia (5.78%) in the study population.&#x0D; Conclusion: In conclusion, the poor PPV of the urine CCR was due to the low prevalence of preeclampsia in the study. However, in considering all women at risk, urine CCR may be a good prognostic marker when the illness prevalence is substantial.

Performance of HIV rapid testing algorithm in Nigeria: Findings from a household-based Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS).

The Nigeria AIDS Indicator and Impact Survey (NAIIS), a cross-sectional household survey, was conducted in 2018 with primary objectives to estimate HIV prevalence, HIV-1 incidence, and status of UNAIDS 90-90-90 cascade. We conducted retrospective analysis of the performance of HIV rapid tests and the national HIV testing algorithm used in Nigeria. The national algorithm included Determine HIV-1/2 as test 1 (T1), Unigold HIV-1/2 as test 2 (T2), and StatPak HIV-1/2 as the tie-breaker test (T3). Individuals reactive with T1 and either T2 or T3 were considered HIV-positive. HIV-positive specimens from the algorithm were further confirmed for the survey using supplemental test Geenius HIV-1/2. If Geenius did not confirm HIV-positive status, HIV-1 Western blot was performed. We calculated the concordance between tests and positive predictive value (PPV) of the algorithm on unweighted data. Of 204,930 participants (ages ≥18 months) 5,103 (2.5%) were reactive on T1. Serial testing of T1 reactive specimens with T2 or if needed by tiebreaker T3 identified 2958 (1.44%) persons as HIV-positive. Supplemental testing confirmed 2,800 (95%) as HIV-positive (HIV-1 = 2,767 [98.8%]; HIV-2 = 5 [0.2%]; dual infections = 22 [0.8%]). Concordance between T1 and T2 was 56.6% while PPV of the national algorithm was 94.5%. Our results show high discordant rates and poor PPV of the national algorithm with a false-positive rate of about 5.5% in the NAIIS survey. Considering our findings have major implications for HIV diagnosis in routine HIV testing services, additional evaluation of testing algorithm is warranted in Nigeria.

Abstract 5921: Machine learning based detection of pancreatic tumors using the Dxcover® cancer platform

Abstract Pancreatic cancer is the 7th most deadly cancer worldwide with over 460,000 victims per year. In the current diagnostic pathway, carbohydrate antigen (CA) 19-9 serum test is the first method used for detection of pancreatic cancer; although, with poor positive predictive values reported, it cannot provide certain information about the presence of a pancreatic tumor or other surrounding tumors in symptomatic patients. Attenuated total reflection - Fourier transform infrared spectroscopy (ATR-FTIR) has demonstrated exceptional potential in human blood serum analysis for cancer diagnostics and its implementation in the clinical environment could represent a significant step forward in the early detection of pancreatic cancer. This proof-of-concept study was focused on the discrimination between both cancer versus healthy control samples, and cancer versus symptomatic control samples from patients with comorbidities and/or confounding diseases. The study aimed to investigate the use of the Dxcover® cancer platform as a novel approach for pancreatic cancer detection. Various machine learning algorithms were applied to discriminate between cancer (n=100) and healthy control samples (n=100), achieving results amounting to a sensitivity of 91.0 ± 5.6%, specificity of 87.6 ± 5.8%, and accuracy of 89.3 ± 3.8% with partial least squares-discriminant analysis (PLS-DA). Moreover, an area under the curve (AUC) equal to 0.9536 was obtained through receiving operating characteristic (ROC) analysis. The same algorithms were also applied to discriminate between cancer (n=35) and symptomatic control samples (n=35) achieving a balanced sensitivity and specificity over 75% with an AUC of 0.8436. Both discriminations underwent bootstrapping validation and were proven statistically significant. Herein, we present these results and demonstrate that ATR-FTIR spectroscopic analysis of serum is a cost-effective, minimally invasive, highly sensitive and specific test for detection of pancreatic cancer. Citation Format: Alexandra Sala, James M. Cameron, Cerys A. Jenkins, Hugh Barr, Loren Christie, Justin J. Conn, Thomas (Jeff) R. Evans, Dean A. Harris, David S. Palmer, Christopher Rinaldi, Ashton G. Theakstone, Matthew J. Baker. Machine learning based detection of pancreatic tumors using the Dxcover® cancer platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5921.

A digital assay for programmed death-ligand 1 (22C3) quantification combined with immune cell recognition algorithms in non-small cell lung cancer

PD-L1 (22C3) checkpoint inhibitor therapy represents a mainstay of modern cancer immunotherapy for non-small cell lung cancer (NSCLC). In vitro diagnostic (IVD) PD-L1 antibody staining is widely used to predict clinical intervention efficacy. However, pathologist interpretation of this assay is cumbersome and variable, resulting in poor positive predictive value concerning patient therapy response. To address this, we developed a digital assay (DA) termed Tissue Insight (TI) 22C3 NSCLC, for the quantification of PD-L1 in NSCLC tissues, including digital recognition of macrophages and lymphocytes. We completed clinical validation of this digital image analysis solution in 66 NSCLC patient samples, followed by concordance studies (comparison of PD-L1 manual and digital scores) in an additional 99 patient samples. We then combined this DA with three distinct immune cell recognition algorithms for detecting tissue macrophages, alveolar macrophages, and lymphocytes to aid in sample interpretation. Our PD-L1 (22C3) DA was successfully validated and had a scoring agreement (digital to manual) higher than the inter-pathologist scoring. Furthermore, the number of algorithm-identified immune cells showed significant correlation when compared with those identified by immunohistochemistry in serial sections stained by double immunofluorescence. Here, we demonstrated that TI 22C3 NSCLC DA yields comparable results to pathologist interpretation while eliminating the intra- and inter-pathologist variability associated with manual scoring while providing characterization of the immune microenvironment, which can aid in clinical treatment decisions.

An interventional quasi-experimental study to evaluate the impact of a rapid screening strategy in improving control of nosocomial extended-spectrum beta-lactamase-producing Enterobacterales and carbapenemase-producing organisms in critically ill patients

IntroductionRapid molecular tests could accelerate the control of extended-spectrum beta-lactamase-producing Enterobacterales (ESBL-PE) and carbapenemase-producing organisms (CPO) in intensive care units (ICUs).Objective and methodsThis interventional 12-month cohort study compared a loop-mediated isothermal amplification (LAMP) assay performed directly on rectal swabs with culturing methods (control period, 6 months), during routine ICU screening. Contact precautions (CP) were implemented for CPO or non-E. coli ESBL-producing Enterobacterales (nEcESBL-PE) carriers. Using survival analysis, we compared the time intervals from admission to discontinuation of unnecessary preemptive CP among patients at-risk and the time intervals from screening to implementation of CP among newly identified carriers. We also compared diagnostic performances, and nEcESBL-PE/CPO acquisition rates. This study is registered, ISRCTN 23588440.ResultsWe included 1043 patients. During the intervention and control phases, 92/147 (62.6%) and 47/86 (54.7%) of patients at-risk screened at admission were candidates for early discontinuation of preemptive CP. The LAMP assay had a positive predictive value (PPV) of 44.0% and a negative predictive value (NPV) of 99.9% for CPO, and 55.6% PPV and 98.2% NPV for nEcESBL-PE. Due to result notification and interpretation challenges, the median time from admission to discontinuation of preemptive CP increased during the interventional period from 80.5 (95% CI 71.5–132.1) to 88.3 (95% CI 57.7–103.7) hours (p = 0.47). Due to the poor PPV, we had to stop using the LAMP assay to implement CP. No difference was observed regarding the incidence of nEcESBL-PE and CPO acquisition.ConclusionA rapid screening strategy with LAMP assays performed directly on rectal swabs had no benefit for infection control in a low-endemicity setting.

Machine learning based detection of pancreatic tumors using the Dxcover cancer platform.

e16275 Background: Pancreatic cancer is the 7th most deadly cancer worldwide with over 460,000 victims per year. In the current diagnostic pathway, carbohydrate antigen (CA) 19-9 serum test is the blood assessment used for detection of pancreatic cancer; although, with poor positive predictive values reported, it is not specific for pancreatic tumors as its levels can be raised in symptomatic patients with other benign comorbidities and/or because of other tumors in the surrounding area. Attenuated total reflection–Fourier transform infrared spectroscopy (ATR-FTIR) has demonstrated exceptional potential in human blood serum analysis for cancer diagnostics and its implementation in the clinical environment could represent a significant step forward in the early detection of pancreatic cancer. This proof-of-concept study aimed to investigate the use of the Dxcover cancer liquid biopsy as a novel approach for pancreatic cancer detection. Methods: The study was focused on the discrimination between both cancer (n = 100) versus healthy control samples (n = 100), and cancer (n = 35) versus symptomatic non-malignant control samples (n = 35) from patients with comorbidities and/or confounding diseases. Various machine learning algorithms were applied to discriminate between the classes: random forest (RF), partial least squares-discriminant analysis (PLS-DA) and support vector machine (SVM). Receiver operating characteristic (ROC) analysis was also employed to evaluate the classes’ degree of diagnostic separability. Permutation tests were performed for each classification in order to ensure their statistical significance. Results: Cancer (n = 100) and healthy control samples (n = 100) were distinguished with excellent results, achieving results up to a sensitivity of 91.0 %, specificity of 87.6 %, and accuracy of 89.3 % with PLS-DA. Moreover, an area under the curve (AUC) equal to 0.954 was obtained through ROC analysis. When discriminating between cancer (n = 35) and symptomatic control samples (n = 35), accuracy values were recorded in the range between 70.6 and 77.3 % with ROC analysis showing a balanced sensitivity and specificity over 75 % with an AUC of 0.844. Both discriminations were proven statistically significant. Conclusions: Pancreatic cancer detection in early stages would be key in improving prognosis and survival rates of patients, through targeted earlier surgery and treatments. The Dxcover cancer liquid biopsy could represent a powerful tool in the clinical environment as an easy-to-use, minimally invasive and reliable spectroscopic blood test for detection of pancreatic cancer.

Combination of C-Reactive Protein and Procalcitonin in Distinguishing Fungal from Bacterial Infections Early in Immunocompromised Children.

Invasive fungal infection (IFI) is life-threatening in children with cancer and hematology disorders, especially when diagnosis and treatment are delayed. Conventional β-D-glucan and galactomannan tests have poor positive predictive values in the diagnosis of IFI in children with cancer. This study aims to access the diagnostic performance of C-reactive protein (CRP) and procalcitonin (PCT) in differentiating IFI from bacterial bloodstream infections in children with malignant and hematology disorders. CRP and PCT levels were measured in samples taken from patients between 12 and 24 h after fever onset, of which 24 and 102 were in the IFI and bacterial groups, respectively. We found that the CRP levels were much higher in the IFI group than the bacterial group (100.57 versus 40.04 mg/L, median, p < 0.001), while the PCT levels remained significantly lower (0.45 versus 1.29 μg/L, median, p = 0.007). Both CRP and PCT showed significant diagnostic utilities with an area under the curve (AUC) of 0.780 (95% CI, 0.664–0.896, p < 0.001) and 0.731 (95% CI, 0.634–0.828, p < 0.001) when using the cut-off values of 94.93 mg/L and 2.00 μg/L, respectively. However, the combined biomarker of CRP and PCT yielded a better diagnostic performance with an AUC of 0.934 (95% confidential interval (CI), 0.881–0.987, p < 0.001), which was significantly higher than that of CRP or PCT (both p < 0.001), with a sensitivity of 87.5% and a specificity of 87.3%. Our study demonstrates high levels of CRP combined with low PCT could differentiate IFI from bacterial bloodstream infections in immunocompromised children.

Noninvasive Ventilation and Exogenous Surfactant in Times of Ever Decreasing Gestational Age: How Do We Make the Most of These Tools?

Noninvasive Ventilation and Exogenous Surfactant in Times of Ever Decreasing Gestational Age: How Do We Make the Most of These Tools?

Performance of Xpert® MTB/RIF and Xpert® Ultra for the diagnosis of tuberculous meningitis in children.

OBJECTIVE: To assess Xpert® MTB/RIF (Xpert) and Xpert® MTB/RIF Ultra (Ultra) performance in diagnosing pediatric tuberculous meningitis (TBM).METHODS: We conducted a study among children with suspected meningoencephalitis in Pune, India. Clinical, radiological, laboratory, and treatment data were analyzed to classify disease as definite, probable, possible or no TBM, using microbiologic or composite reference standards. We tested cerebrospinal fluid (CSF) either using Xpert or Ultra and estimated test performance characteristics.RESULTS: Of 341 participants, 149 (43.7%) were tested using Ultra and 192 (56.3%) with Xpert. Ultra had higher sensitivity (50% vs. 18%), lower specificity (91% vs. 99%), poor positive predictive value (PPV) (13% vs. 75%), and higher negative predictive value (NPV) (99% vs. 93%) than Xpert using the composite reference standard, with similar results by the microbiologic reference standard. Of 10 participants with trace positivity on Ultra, none met clinical TBM definitions.CONCLUSION: This is the first study to report on diagnostic performance of Ultra in pediatric TBM, which showed higher sensitivity and NPV than Xpert. For children presenting with nonspecific clinical features, Ultra is a promising diagnostic test. Further studies are required to define its optimal clinical use, including interpretation of trace positive results.

The LAS and Novel Models Poorly Predict Post-Transplant Survival

<h3>Purpose</h3> The Lung Allocation Score (LAS) was designed to allocate donor lungs based on estimates of waitlist mortality and post-transplant survival and has increased the number of lung transplants performed and reduced waitlist mortality. As a component of net "transplant benefit", our aim was to compare the ability of the LAS and 3 novel methods to predict 1-year post-transplant death or retransplant. We also evaluated methods to improve the predictive validity of these models. <h3>Methods</h3> Utilizing the Organ Procurement and Transportation Network database (2005-2017), we compared prediction of post-transplant survival of the LAS, a model described by Chan, <i>et al.</i>, a logistic regression model utilizing <i>a priori</i> expert selection of pre-transplant recipient covariates, and two machine learning models, Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forests, using all available covariates. We compared the area under the receiver-operator characteristic curve (AUC), positive predictive value (PPV), and negative predictive value (NPV) between the models. We evaluated the calibration of each model by comparing average predicted probability of outcomes in each decile to observed outcome percentages. We repeated the analysis evaluating 3-year post-transplant mortality, fitting separate models to disease category, and including donor covariates. <h3>Results</h3> All models demonstrated low AUC (0.55-0.63), poor PPV (<0.23), but relatively high NPV (0.87-0.9). The Random Forests and <i>a priori</i> expert models had higher AUC (both 0.63) than the LAS (0.55), LASSO (0.61), and Chan, <i>et al.</i> (0.59) models. Evaluating calibration of the LAS found that 1-year post-transplant estimates from the LAS consistently overestimated the risk of post-transplant mortality, with greater differences in higher LAS deciles. The LASSO, Random Forests, and <i>a priori</i> expert models showed no improvement in AUC when each were fit to individual disease groups or evaluated with the addition of donor covariates and had lower AUC when evaluated for 3-year outcomes. <h3>Conclusion</h3> The LAS can overestimate a patient's risk of post-transplant death and thus underestimate transplant benefit in the sickest candidates. Novel models based on pre-transplant recipient covariates fail to improve prediction. There should be wariness in the short-term post-transplant survival predictions from the LAS.

Bony Apprehension Test for Identifying Bone Loss in Patients With Traumatic Anterior Shoulder Instability: A Validation Study

Background: The presence of bone loss has important implications for the surgical treatment of patients with recurrent shoulder instability. The bony apprehension test (BAT) is a physical examination maneuver that was designed to improve specificity from the anterior apprehension test (AAT) in detecting critical bone loss. Purpose: The purpose of this study was to compare the BAT with the AAT and relocation test based on their abilities to predict critical bone loss. Several well–described criteria were utilized to capture critical (≥25%) and subcritical (≥13.5%) glenoid defects, as well as Hill-Sachs defects (≥19%). The ability of the BAT to predict bipolar bone loss was also assessed, as indicated by engaging Hill-Sachs defects and off–track lesions. Study Design: Cohort study (diagnosis); Level of evidence, 1. Methods: The study cohort included patients ≥18 years of age who were scheduled to undergo arthroscopic stabilization for traumatic anterior shoulder instability. Notable exclusion criteria included multidirectional shoulder instability, connective tissue disorders, and workers’ compensation or litigation cases. Patients underwent physical examination immediately before surgery by the treating surgeon (ie, before the induction of anesthesia). Critical glenoid and humeral bone defects were measured on preoperative computed tomography scans. Hill-Sachs engagement and on- or off–track determination of bone loss were assessed arthroscopically and via computed tomography, respectively. Results: A total of 52 patients were included in the study. In cases of subcritical glenoid bone loss (≥13.5%) and critical Hill-Sachs defects (≥19%), the BAT had good and fair specificity (82% and 72%, respectively) but poor sensitivity (40% and 39%). The BAT also had poor sensitivity (0%), specificity (67%), and positive predictive value (0%) for higher percentages of glenoid bone loss (≥25%). When engaging Hill-Sachs lesions were assessed, the BAT had excellent specificity (94%) and positive predictive value (94%) but poor sensitivity (43%) and negative predictive value (44%). Furthermore, the BAT performed poorly at predicting off–track humeral lesions. The AAT demonstrated 100% sensitivity and 0% specificity in detecting all measures of bone loss. Conclusion: The BAT performed poorly at identifying subcritical and critical bone loss and was not found to have any clinical value. Future work is needed to identify a physical examination test that could complement advanced imaging for preoperative assessment of critical bone loss.

A Rapid RT-LAMP Assay for SARS-CoV-2 with Colorimetric Detection Assisted by a Mobile Application.

Loop-mediated amplification has been promoted for SARS-CoV-2 screening, however, antigen tests are preferred in low-income countries and remote zones. Poor training in molecular biology, plus the need for RNA purification or reading instruments to overcome issues of sensitivity in colorimetric detection, are some of the reasons limiting the use of this technique. In this study, nasopharyngeal swabs, aspirates and saliva were amplified in an in-house LAMP assay and subject to colorimetric detection, achieved by the naked eye and by image analysis with a mobile application. Accuracy of detection by the naked eye ranged from 61–74% but improved to 75–86% when using the application. Sensitivity of the digital approach was 81% and specificity 83%, with poor positive predictive value, and acceptable negative predictive value. Additionally to the reported effect of some transport media’s pH, the presence of mucus and warming up of reagents while setting up the reaction critically affected performance. Accuracy per type of sample was 55, 70 and 80%, for swabs, aspirates and saliva, respectively, suggesting potential to improve the test in saliva. This assay, carried out in a closed tube, reduces contamination, has few pipetting steps and requires minimal equipment. Strategies to improve performance and implications of the use this sort of colorimetric LAMP for massive testing are discussed.