Correlation of Hemoglobin Level With New Inflammatory Markers in the Emergency Department: A Retrospective Study Exploring Neutrophil-to-Lymphocyte, Monocyte-to-Lymphocyte, Platelet-to-Lymphocyte, and Mean Platelet Volume-to-Platelet Count Ratios

Background Anemia of chronic disease is known to be associated with inflammation. However, the relationship between hemoglobin (Hb) levels and potential inflammatory markers such as neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume-to-platelet count ratio (MPV/PC) has not been extensively studied. The primary objective of this retrospective analytical study conducted at Al Zahraa Hospital University Medical Center (ZHUMC), Beirut, was to investigate the correlation between Hb levels and potential inflammatory markers (NLR, MLR, PLR, MPV/PC) in patients visiting the emergency department (ED), across different genders and age groups. The secondary objectives were to compare Hb levels and inflammatory markers values between the referred medical ward group (the hospitalized patients who were admitted to the medical ward), and the non-referred to medical ward group (the patients who were discharged home from the ED), and to evaluate the predictability of inflammatory markers and Hb levels for referral to the medical ward, including the determination of optimal cutoff values for hospital admission to the medical ward. Methods We analyzed the blood parameters of 379 adult patients who presented to the ED with various medical complaints between September 1, 2022, and November 30, 2022 (three months). These patients were included in the study after we checked their eligibility regarding the verification of all our inclusion and exclusion criteria. Results Our findings revealed a significant negative correlation between Hb levels and PLR (r = -0.24) in both genders and across different age groups. The group referred to the medical ward exhibited lower Hb levels and higher NLR, MLR, and PLR values (P < 0.001). NLR/Hb ratio emerged as a predictive factor for admission in genitourinary (R² = 0.158; OR = 5.62) and respiratory groups (R² = 0.206; OR = 5.89), with specific cutoff values of 0.533 (Sensitivity = 57.1% & Specificity = 84.2%) and 0.276 (Sensitivity = 85% & Specificity = 51.1%), respectively. Conclusions Our study demonstrates that hemoglobin level negatively correlates with PLR. NLR, MLR, and PLR stand as important inflammatory markers. Moreover, we present the first study in the literature to show that NLR/Hb ratio can serve as a predictor for referral to the medical ward, particularly in the genitourinary and respiratory patient groups, underscoring its value in risk assessment as a prognostic marker reflecting the need for admission when the case is more serious.

The Role of Neutrophil-to-Lymphocyte Ratio in the Diagnosis of Acute Appendicitis

BACKGROUND

Acute appendicitis (AA), a common reason for episodes of acute abdomen, is a surgical emergency. Its immediate diagnosis and management are of immense significance, as its diagnosis can become challenging at times, especially in resource-limited setups. The goal of this study was to ascertain the threshold value for the neutrophil-to-lymphocyte ratio (NLR) in diagnosing AA and to calculate the validity parameters for the NLR.

METHODOLOGY

 A cross-sectional study was carried out involving 108 patients who were admitted to the surgical wards of Ayub Teaching Hospital, Abbottabad with suspicion of AA and subsequently underwent open appendectomy. Data was collected regarding the demography of the patients, physical examination findings, clinical presentations, and investigations including the histopathology and complete blood count, from which the NLR value was computed, and the Statistical Package for Social Sciences (SPSS), version 25.0 (IBM Corp., Armonk, NY) was utilized for the computation. Receiver operating characteristic (ROC) analysis was done to calculate the cut-off value of the NLR for diagnosing AA, and validity parameters were computed, taking into account statistical significance with a p-value < 0.05.

RESULTS

Based on the ROC analysis, a threshold value for NLR indicating a positive appendectomy was determined to be 2.49 (sensitivity = 71.4% and 1-specificity = 12.5%) with an area under the curve of 90.6% (95% confidence interval {CI} 0.818-0.994, p<0.001). The sensitivity, specificity, and diagnostic accuracy of NLR for diagnosing AA were 71.43%, 87.5%, and 72.73%, respectively.

CONCLUSION

 There is a strong correlation between NLR at a cut-off value of 2.49 and the diagnosis of AA. We suggest that NLR should be utilized as a complementary biomarker to clinical examination, aiding in the diagnosis of AA.

Elevated Troponin I as a Marker for Unfavorable Outcomes in Acute Ischemic Stroke

OBJECTIVE

To assess if elevated cardiac troponin I (cTnI) serves as a sign of unfavorable functional outcomes in ischemic stroke.

METHODS

In this single-center prospective cohort study, 100 consecutive patients admitted with acute ischemic stroke (normal troponin I group n = 52, raised troponin I group n = 48) were included. Hospital mortality was documented in both groups; the remaining patients were followed up to 90 days. Then two groups were compared in terms of unfavorable short-term outcomes (Modified Rankin Scale > 3) and mortality. Multivariate logistic regression was conducted to determine the predictive value of elevated cTnI. The Kaplan-Meier curve was drawn and compared to determine the difference in survival between the two groups. To find out the most probable cut-off level for an unfavorable outcome, a receiver operating characteristic (ROC) analysis was conducted.

RESULT

 A higher frequency of coronary artery disease (p=0.030), higher National Institutes of Health Stroke Scale (NIHSS) (p=0.008) score, and lower Glasgow Coma Scale (GCS) (p=0.002) was observed in raised troponin I group. Even after the exclusion of confounding elevated troponin I was found to be an independent predictor of unfavorable outcomes (adjusted odds ratio, OR 8.25 {95% confidence interval, CI: 2.65-25.75}; p<0.001). The patients with raised troponin I had a significantly lower rate of survival after 90 days (p=0.022). The elevated troponin I was observed to have a significantly high accuracy (p<0.001; area under curve, AUC: 0.768 {moderate accuracy}, 95% CI: 0 .676 to 0.861) in predicting unfavorable outcomes.

CONCLUSION

Elevated cTnI is independently associated with unfavorable short-term outcomes. It is also associated with a lower rate of survival.

Predictors of Successful Medical Management With Methotrexate in Unruptured Tubal Ectopic Pregnancy

Introduction Medical treatment with methotrexate (MTX) is a safe and effective alternative to surgery in carefully selected cases of ectopic pregnancies diagnosed early prior to rupture. Aim To determine the optimal pre-treatment levels of beta human chorionic gonadotropin (𝛽-hCG) and its changing trends most likely to have a successful outcome with medical management. Material and methods A prospective observational study was conducted in a tertiary teaching hospital from December 2018 to May 2021. "Single-dose" MTX regime was used for medical management of ectopic pregnancy in patients fulfilling the selection criteria. The 𝛽-hCG levels were recorded at baseline and on day 4 and day 7 of MTX injection. Thereafter, at weekly intervals till complete resolution or surgical intervention due to failure of medical management. In addition, receiver operating characteristic (ROC) curve analysis for a pre-treatment 𝛽-hCG cut-off value and changing trends in post-treatment 𝛽- hCG levels most likely to have a successful outcome with MTX treatment were determined. Results Fifty patients fulfilling the inclusion criteria were included in the study, with successful medical management in 33 (66%). The mean pre-treatment 𝛽-hCG levels in women with successful medical management were 3270.97 (+/- 901) compared to 5249.17 (+/-808.02) for those with treatment failure (p=0.00001). The mean 𝛽-hCG level in the failed treatment group was significantly higher on day 4 than the pre-treatment levels (6742.56 +/- 572 vs. 5249.17+/- 808.02; p<0.05). Inadequate reduction of 𝛽-hCG level on day 7 (<15% of day 4 levels) requiring repeat dosage of MTX was more likely to have an unsuccessful outcome (p=0.00001). The area under curve (AUC) value of 0.905 (95% CI: 0.814-0.996) depicted that pre-treatment 𝛽-hCG level of 4000 mIU/ml taken as the cut-off value was able to predict levels ≤4000 mIU/ml had a greater likelihood of successful outcome with MTX, having a sensitivity of 84.5%, specificity of 83.3%, positive predictive value (PPV) of 90.3%, and negative predictive value (NPV) of 75% (p< 0.05). Demographic variables or previous clinical history, considered risk factors for ectopic pregnancy, did not affect the outcome of medical management in this study. Conclusion Medical management of ectopic pregnancy is a viable first-line treatment option in carefully selected patients. In this study, the most important predictors for the successful outcome of medical management were the pre-treatment β-hCG levels and their fall on day 4 and day 7 after MTX therapy.

COVID-19 Diagnosis on Chest Radiograph Using Artificial Intelligence

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has disrupted the world since 2019, causing significant morbidity and mortality in developed and developing countries alike. Although substantial resources have been diverted to developing diagnostic, preventative, and treatment measures, disparities in the availability and efficacy of these tools vary across countries. We seek to assess the ability of commercial artificial intelligence (AI) technology to diagnose COVID-19 by analyzing chest radiographs.

MATERIALS AND METHODS

Chest radiographs taken from symptomatic patients within two days of polymerase chain reaction (PCR) tests were assessed for COVID-19 infection by board-certified radiologists and commercially available AI software. Sixty patients with negative and 60 with positive COVID reverse transcription-polymerase chain reaction (RT-PCR) tests were chosen. Results were compared against results of the PCR test for accuracy and statistically analyzed by receiver operating characteristic (ROC) curves along with area under the curve (AUC) values.

RESULTS

A total of 120 chest radiographs (60 positive and 60 negative RT-PCR tests) radiographs were analyzed. The AI software performed significantly better than chance (p = 0.001) and did not differ significantly from the radiologist ROC curve (p = 0.78).

CONCLUSION

Commercially available AI software was not inferior compared with trained radiologists in accurately identifying COVID-19 cases by analyzing radiographs. While RT-PCR testing remains the standard, current advances in AI help correctly analyze chest radiographs to diagnose COVID-19 infection.

Impact of Acute Confusional State in Patients With COVID-19 and a Predictive Score

BACKGROUND

Acute confusional state (ACS) in COVID-19 is shown to be associated with poor clinical outcomes.

METHODS

We assessed the impact of ACS - defined as a documented deterioration of mental status from baseline on the alertness and orientation to time, place, and person - on inpatient mortality and the need for intensive care unit (ICU) transfer in inpatient admissions with active COVID-19 infection in a single-center retrospective cohort of inpatient admissions from a designated COVID-19 tertiary care center using an electronic health record system. Furthermore, we developed and validated a neurological history and symptom-based predictive score of developing ACS.

RESULTS

Thirty seven out of 245 (15%) patients demonstrated ACS. Nineteen (51%) patients had multifactorial ACS, followed by 11 (30%) patients because of hypoxemia. ACS patients were significantly older (80 [70-85] years vs 50.5 [38-69] years, p < 0.001) and demonstrated more frequent history of dementia (43% vs 9%, p < 0.001) and epilepsy (16% vs 2%, p = 0.001). ACS patients observed significantly higher in-hospital mortality (45.9% vs 1.9%, aOR [adjusted odds ratio]: 15.7, 95% CI = 3.6-68.0, p < 0.001) and need for ICU transfer (64.9% vs 35.1%, aOR: 2.7, 95% CI = 1.2-6.1, p = 0.015). In patients who survived hospitalization, ACS was associated with longer hospital stay (6 [3.5-10.5] days vs 3 [2-7] day, p = 0.012) and numerically longer ICU stay (6 [4-10] days vs 3 [2-6] days, p = 0.078). A score to predict ACS demonstrated 75.68% sensitivity and 81.73% specificity at a cutoff of ≥3.

CONCLUSION

A high prevalence of ACS was found in patients with COVID-19 in our study cohort. Patients with ACS demonstrated increased mortality and need for ICU care. An internally validated score to predict ACS demonstrated high sensitivity and specificity in our cohort.

The validity of three-class Hotelling trace (3-HT) in describing three-class task performance: comparison of three-class volume under ROC surface (VUS) and 3-HT

In order to describe multiclass classification performance, several figures of merit (FOM) have been proposed. Among the earliest and most widely known of these is the three-class Hotelling trace (3-HT). The goal of this paper is to present theoretical and empirical data demonstrating the failure of 3-HT as a measure of three-class task performance. To help do this, we contrast it to a newly proposed three-class FOM, the volume under the three-class receiver operating characteristic (ROC) surface (VUS). The VUS is obtained from a decision theory based three-class ROC analysis method which has been proved to extend the decision theoretic, linear discriminant analysis (LDA), and psychophysical foundations of binary ROC analysis to a three-class paradigm. We demonstrate empirically that the VUS and 3-HT do not have a monotonic relationship in general when describing three-class task performance. Numerical experiments demonstrated that the VUS provided reasonable results, while the 3-HT failed to distinguish between the case where all objects could be perfectly classified from the case where only one pair of the classes could be perfectly classified. We have provided theoretical explanations of this failure of 3-HT. The significance of this work goes beyond merely demonstrating the problems of the 3-HT, it demonstrates that a FOM that is mathematically correct and has a strong theoretical basis can provide results that violate a common sense understanding of three-class task performance. This fact raises the question of "how to evaluate a classification performance evaluation method?" We believe the answer to this question lies in the theoretical foundations of binary ROC analysis. We have thus contrasted the two FOMs in terms of three fundamental theories underlying binary ROC analysis: decision theory, binary linear discriminant analysis, and the equivalence of two psychophysical classification procedures. These theoretical investigations demonstrated the importance of extending and unifying all the fundamental theories of binary classification in the development of a three-class FOM; violating one of theses fundamental binary classification theories may, as it did for the L-HT, provide predictions of three-class task performance that do not agree with a common sense understanding of three-class task performance.

The meaning and use of the volume under a three-class ROC surface (VUS)

Previously, we have proposed a method for three-class receiver operating characteristic (ROC) analysis based on decision theory. In this method, the volume under a three-class ROC surface (VUS) serves as a figure-of-merit (FOM) and measures three-class task performance. The proposed three-class ROC analysis method was demonstrated to be optimal under decision theory according to several decision criteria. Further, an optimal three-class linear observer was proposed to simultaneously maximize the signal-to-noise ratio (SNR) between the test statistics of each pair of the classes provided certain data linearity condition. Applicability of this three-class ROC analysis method would be further enhanced by the development of an intuitive meaning of the VUS and a more general method to calculate the VUS that provides an estimate of its standard error. In this paper, we investigated the general meaning and usage of VUS as a FOM for three-class classification task performance. We showed that the VUS value, which is obtained from a rating procedure, equals the percent correct in a corresponding categorization procedure for continuous rating data. The significance of this relationship goes beyond providing another theoretical basis for three-class ROC analysis-it enables statistical analysis of the VUS value. Based on this relationship, we developed and tested algorithms for calculating the VUS and its variance. Finally, we reviewed the current status of the proposed three-class ROC analysis methodology, and concluded that it extends and unifies decision theoretic, linear discriminant analysis, and psychophysical foundations of binary ROC analysis in a three-class paradigm.

Receiver operating characteristic study of image preprocessing for teleradiology and digital workstations

The purpose of this study was to evaluate whether digitized analog images displayed on a digital workstation can be improved by using a preprocessing algorithm, and if so, whether the quality of the resulting images can reach that of the original films. The material contained 120 difficult cases (about 50% with selected pathology). Four radiologists each evaluated half of the randomly ordered cases with the digital workstation and half of the cases with the original radiographs. The data were compared with a previous similar study, where the workstation had no option for preprocessed images. Preprocessed digital images were clearly superior to digital images without preprocessing, although for those of the highest diagnostic difficulty they were inferior to the original films. The preprocessing algorithm has improved the diagnostic quality of the digital workstation. There is room yet for improvement compared to plain films, although the current setup may be sufficient in some settings.