A prediction rule for severe adverse events in all inpatients with community-acquired pneumonia: a multicenter observational study

Background Prediction of inpatients with community-acquired pneumonia (CAP) at high risk for severe adverse events (SAEs) requiring higher-intensity treatment is critical. However, evidence regarding prediction rules applicable to all patients with CAP including those with healthcare-associated pneumonia (HCAP) is limited. The objective of this study is to develop and validate a new prediction system for SAEs in inpatients with CAP. Methods Logistic regression analysis was performed in 1334 inpatients of a prospective multicenter study to develop a multivariate model predicting SAEs (death, requirement of mechanical ventilation, and vasopressor support within 30 days after diagnosis). The developed ALL-COP-SCORE rule based on the multivariate model was validated in 643 inpatients in another prospective multicenter study. Results The ALL-COP SCORE rule included albumin (< 2 g/dL, 2 points; 2–3 g/dL, 1 point), white blood cell (< 4000 cells/μL, 3 points), chronic lung disease (1 point), confusion (2 points), PaO2/FIO2 ratio (< 200 mmHg, 3 points; 200–300 mmHg, 1 point), potassium (≥ 5.0 mEq/L, 2 points), arterial pH (< 7.35, 2 points), systolic blood pressure (< 90 mmHg, 2 points), PaCO2 (> 45 mmHg, 2 points), HCO3− (< 20 mmol/L, 1 point), respiratory rate (≥ 30 breaths/min, 1 point), pleural effusion (1 point), and extent of chest radiographical infiltration in unilateral lung (> 2/3, 2 points; 1/2–2/3, 1 point). Patients with 4–5, 6–7, and ≥ 8 points had 17%, 35%, and 52% increase in the probability of SAEs, respectively, whereas the probability of SAEs was 3% in patients with ≤ 3 points. The ALL-COP SCORE rule exhibited a higher area under the receiver operating characteristic curve (0.85) compared with the other predictive models, and an ALL-COP SCORE threshold of ≥ 4 points exhibited 92% sensitivity and 60% specificity. Conclusions ALL-COP SCORE rule can be useful to predict SAEs and aid in decision-making on treatment intensity for all inpatients with CAP including those with HCAP. Higher-intensity treatment should be considered in patients with CAP and an ALL-COP SCORE threshold of ≥ 4 points. Trial registration This study was registered with the University Medical Information Network in Japan, registration numbers UMIN000003306 and UMIN000009837.

Prevalence of Persistent Olfactory Disorders in Patients With COVID-19: A Psychophysical Case-Control Study With 1-Year Follow-up

The purpose of this multicenter case-control study was to evaluate a group of patients at least 1 year after coronavirus disease 2019 (COVID-19) with Sniffin’ Sticks tests and to compare the results with a control population to quantify the potential bias introduced by the underlying prevalence of olfactory dysfunction (OD) in the general population. The study included 170 cases and 170 controls. In the COVID-19 group, 26.5% of cases had OD (anosmia in 4.7%, hyposmia in 21.8%) versus 3.5% in the control group (6 cases of hyposmia). The TDI score (threshold, discrimination, and identification) in the COVID-19 group was significantly lower than in the control group (32.5 [interquartile range, 29-36.5] vs 36.75 [34-39.5], P < .001). The prevalence of OD was significantly higher in the COVID-19 group, confirming that this result is not due to the underlying prevalence of OD in the general population.

Aortic Valve Calcium Score as Measured by Native Vs. Contrast Enhanced Computer Tomography and the Implications for the Diagnosis of Severe Aortic Stenosis in TAVR Patients With Low Gradient Aortic Stenosis.

Purposewe compared between patients with low gradient (LG) and high gradient (HG) severe aortic stenosis (AS) as regard the burden of aortic valve calcium (AVC) using different methodologies. Moreover, we evaluated the accuracy of published thresholds for the diagnosis of severe AS in both groups. Methodswe measured the calcium volume and score using Agatston methodology in non-contrast (n-c) CT and with modified and fixed 850 Hounsfield unit (HU) thresholds in contrast enhanced (ce) CT. ResultsThe medians (IQR) of Agatston score, score with 850 HU and modified thresholds were 1288 AU (750-1815), 101 (65-256), 701 (239-1632), respectively. The calcium volume in ceCT using fixed 850 HU thresholds is significantly lower than the assessed volume in ncCT or in ceCT using modifiable threshold. LG patients were more obese; BMI 31.2 (29.1-35.1) vs 27.6 (26-31) and presented more with coronary artery disease (71.4% vs 40%). AF was documented in 42% in LG-patients vs 30% in HG patients. LVEF was severely depressed (less than 30%) in 28.6% in LG-patients. LG patients were more symptomatic (NYHA ≥ III in 71.4% patients vs 42%).The LG patients had smaller anatomy: annulus diameter 23.5mm (21.5-27) vs 25mm (23-25.5), LVOT diameter 23mm (20-20) vs 25mm (23-26.7mm). The annulus geometry was more eccentric; eccentric index 0.23 (0.19-0.27) vs 0.11 (0.1-0.2). Agatston score and calcium volume were lower in patients with LG; 1641AU (1292-1990) vs 928AU (572-1284) and 1537mm³ (644-1860) vs 286mm³ (160-700), respectively. Only 20% of patients with LG had Agatston score less than the previously supposed AVC score threshold for the diagnosis of severe AS (>2000AU in men and >1200 in women). The elimination of ncCT from the protocol reduced significantly the radiation dose by 400.3 ± 140 mGy*cm and 2.4 ± 2.8mSv.ConclusionThe diagnosis of severe LGAS should not depend on a single parameter as calcium score. The measurement of calcium score in contrast CT underestimate the calcium load significantly.

Searching sequence databases for functional homologs using profile HMMs: how to set bit score thresholds?

UniProt and BFD databases together have 2.5 billion protein sequences. A large majority of these proteins have been electronically annotated. Automated annotation pipelines, vis-á-vis manual curation, have the advantage of scale and speed but are fraught with relatively higher error rates. This is because sequence homology does not necessarily translate to functional homology, molecular function specification is hierarchic and not all functional families have the same amount of experimental data that one can exploit for annotation. Consequently, customization of annotation workflow is inevitable to minimize annotation errors. In this study, we illustrate possible ways of customizing the search of sequence databases for functional homologs using profile HMMs. Choosing an optimal bit score threshold is a critical step in the application of HMMs. We illustrate ways in which an optimal bit score can be arrived at using four Case Studies. These are the single domain nucleotide sugar 6-dehydrogenase and lysozyme-C families, and SH3 and GT-A domains which are typically found as a part of multi-domain proteins. We also discuss the limitations of using profile HMMs for functional annotation and suggests some possible ways to partially overcome such limitations.

Confidence Score: The Forgotten Dimension of Object Detection Performance Evaluation

When deploying a model for object detection, a confidence score threshold is chosen to filter out false positives and ensure that a predicted bounding box has a certain minimum score. To achieve state-of-the-art performance on benchmark datasets, most neural networks use a rather low threshold as a high number of false positives is not penalized by standard evaluation metrics. However, in scenarios of Artificial Intelligence (AI) applications that require high confidence scores (e.g., due to legal requirements or consequences of incorrect detections are severe) or a certain level of model robustness is required, it is unclear which base model to use since they were mainly optimized for benchmark scores. In this paper, we propose a method to find the optimum performance point of a model as a basis for fairer comparison and deeper insights into the trade-offs caused by selecting a confidence score threshold.

Balancing Biases and Preserving Privacy on Balanced Faces in the Wild

There are demographic biases in current models used for facial recognition (FR). Our Balanced Faces In the Wild (BFW) dataset serves as a proxy to measure bias across ethnicity and gender subgroups, allowing one to characterize FR performances per subgroup. We show performances are non-optimal when a single score threshold is used to determine whether sample pairs are genuine or imposter. Across subgroups, performance ratings vary from the reported across the entire dataset. Thus, claims of specific error rates only hold true for populations matching that of the validation data. We mitigate the imbalanced performances using a novel domain adaptation learning scheme on the facial features extracted using state-of-the-art. Not only does this technique balance performance, but it also boosts the overall performance. A benefit of the proposed is to preserve identity information in facial features while removing demographic knowledge in the lower dimensional features. The removal of demographic knowledge prevents future potential biases from being injected into decision-making. This removal satisfies privacy concerns. We explore why this works qualitatively; we also show quantitatively that subgroup classifiers can no longer learn from the features mapped by the proposed.

Balancing Biases and Preserving Privacy on Balanced Faces in the Wild

There are demographic biases in current models used for facial recognition (FR). Our Balanced Faces In the Wild (BFW) dataset serves as a proxy to measure bias across ethnicity and gender subgroups, allowing one to characterize FR performances per subgroup. We show performances are non-optimal when a single score threshold is used to determine whether sample pairs are genuine or imposter. Across subgroups, performance ratings vary from the reported across the entire dataset. Thus, claims of specific error rates only hold true for populations matching that of the validation data. We mitigate the imbalanced performances using a novel domain adaptation learning scheme on the facial features extracted using state-of-the-art. Not only does this technique balance performance, but it also boosts the overall performance. A benefit of the proposed is to preserve identity information in facial features while removing demographic knowledge in the lower dimensional features. The removal of demographic knowledge prevents future potential biases from being injected into decision-making. This removal satisfies privacy concerns. We explore why this works qualitatively; we also show quantitatively that subgroup classifiers can no longer learn from the features mapped by the proposed.

Evaluation of a Nep-Score Threshold and the Derived Nep-D Score in Predicting Survival of Patients With Typical and Atypical Bronchial Carcinoids

Background: Typical and atypical bronchial carcinoids (TBC and ABC) display a wide range of clinical presentations and may behave very differently. Survival prognostic markers are necessary to better define therapeutic strategies. AIM: verify that the NEP-Score, recently proposed as prognostic score, can be applied in a homogeneous TBC and ABC cohort and identify a derivate prognostic marker taking into account clinical and pathological characteristics at diagnosis. Methods: Age, site of primary tumor, primary tumor surgery, symptoms, Ki67, timing of metastases of 64 patients including TBC and ABC were evaluated to calculate the NEP-Score at the end of follow-up (NEP-T). We then assessed a derivative score considering the NEP-Score at diagnosis (NEP-D): this score does not consider the appearance of new metastases during follow-up. We then considered the patients that were alive or dead at the end of follow-up (EOF). A NEP-Score threshold to predict survival was investigated. Results: live patients at EOF displayed a mean NEP-T and mean NEP-D significantly lower as compared to those that were dead. A NEP-T threshold &gt;138 significantly predicts survival. ABC relapsed more frequently as compared to TBC. Male gender as well as previous malignancy were negative prognostic factors for survival. Conclusions: We found that NEP-Score is applicable to a series of bronchial neuroendocrine neoplasms. In addition, we propose NEP-D as a simple, quick and cheap prognostic score that can help clinicians in decision making. Moreover, the use of a NEP-D threshold can predict NEN aggressiveness and may be used to define the best personalized therapeutic strategy. Furthermore we found additional prognostic factors that together with the NEP-Score could improve prognosis evaluation at diagnosis by using easily accessible information.

Finance and Firm Volatility: Evidence from Small Business Lending in China

The online trading platform Alibaba provides financial technology (FinTech) credit for millions of micro, small, and medium-sized enterprises (MSMEs). Using a novel data set of daily sales and an internal credit score threshold that governs the allocation of credit, we apply a fuzzy regression discontinuity design (RDD) to explore the causal effect of credit access on firm volatility. We find that credit access significantly reduces firm sales volatility and that the effect is stronger for firms with fewer alternative sources of financing. We further look at firm exit probability and find that firms with access to FinTech credit are less likely to go bankrupt or exit the business in the future. Additional channel tests reveal that firms with FinTech credit invest more in advertising and product/sector diversification, particularly during business downturns, which serves as effective mechanisms through which credit access reduces firm volatility. Overall, our findings contribute to a better understanding of the role of FinTech credit in MSMEs. This paper was accepted by Haoxiang Zhu, finance.

The association between depressive symptoms and neurocognitive impairment in people with well-treated HIV in Switzerland

Background: Depression may contribute to neurocognitive impairment (NCI) in people with HIV (PWH). Attributing NCI to depression rather than to HIV is complicated as depression may be both a causal factor and an effect of NCI. This study aimed to determine the association between depressive symptoms and NCI among PWH with well-controlled infection. Methods: The Neurocognitive Assessment in the Metabolic and Ageing Cohort study is an ongoing, prospective, longitudinal study of PWH aged ≥45 years old nested within the Swiss HIV Cohort Study. Neurocognitive Assessment in the Metabolic and Ageing Cohort study participants underwent neurocognitive assessment and grading of depressive symptoms using the Centre for Epidemiological Studies Depression Scale. Neurocognitive impairment categories were defined using Frascati criteria. Participants with NCI related to neurological or psychiatric confounders other than depression were excluded. The cross-sectional association between the Centre for Epidemiological Studies Depression score and neurocognitive impairment was examined taking Centre for Epidemiological Studies Depression score as a continuous variable and then as a binary variable using two score thresholds, 16 and 27. Results: Excluding 79 participants with confounding factors, 902 participants were studied: 81% were men; 96% had plasma viral loads <50 copies/ml; 35% had neurocognitive impairment; 28% had Centre for Epidemiological Studies Depression scores ≥16. Higher Centre for Epidemiological Studies Depression scores were associated with female sex ( p = 0.0003), non-Caucasian origin ( p = 0.011) and current/past intravenous drug use ( p = 0.002). Whilst neurocognitive impairment was associated with higher Centre for Epidemiological Studies Depression scores, the Centre for Epidemiological Studies Depression score was a poor predictor of having neurocognitive impairment (area under the ROC curve 0.604). Applying a Centre for Epidemiological Studies Depression score threshold of 16 predicted the presence of neurocognitive impairment with a sensitivity of 38.3% (specificity 77.2%), increasing the threshold to 27 lowered sensitivity to 15.4% (specificity 93.6%). Conclusion: In this large cohort of PWH in Switzerland, we did not observe a Centre for Epidemiological Studies Depression score threshold that was sensitive in predicting neurocognitive impairment. As neurocognitive impairment was however associated with higher Centre for Epidemiological Studies Depression scores, the data support the screening for and treatment of depression among PWH diagnosed with neurocognitive impairment.