Search results for: mortality prognosis

Authors: Geir Kirkebøen

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Most patients with serious diagnoses want to know their prognosis, in particular their expected survival time. As part of the informed consent process, physicians are legally obligated to communicate such information to patients. However, there is no established (evidence based) ‘best practice’ for how to do this. The two questions explored in this study are: How do physicians communicate expected survival time to patients, and how should it be done? We explored the first, descriptive question in a study with Norwegian oncologists as participants. The study had a scenario and a survey part. In the scenario part, the doctors should imagine that a patient, recently diagnosed with a serious cancer diagnosis, has asked them: ‘How long can I expect to live with such a diagnosis? I want an honest answer from you!’ The doctors should assume that the diagnosis is certain, and that from an extensive recent study they had optimal statistical knowledge, described in detail as a right-skewed survival curve, about how long such patients with this kind of diagnosis could be expected to live. The main finding was that very few of the oncologists would explain to the patient the variation in survival time as described by the survival curve. The majority would not give the patient an answer at all. Of those who gave an answer, the typical answer was that survival time varies a lot, that it is hard to say in a specific case, that we will come back to it later etc. The survey part of the study clearly indicates that the main reason why the oncologists would not deliver the mortality prognosis was discomfort with its uncertainty. The scenario part of the study confirmed this finding. The majority of the oncologists explicitly used the uncertainty, the variation in survival time, as a reason to not give the patient an answer. Many studies show that patients want realistic information about their mortality prognosis, and that they should be given hope. The question then is how to communicate the uncertainty of the prognosis in a realistic and optimistic – hopeful – way. Based on psychological research, our hypothesis is that the best way to do this is by explicitly describing the variation in survival time, the (usually) right skewed survival curve of the prognosis, and emphasize to the patient the (small) possibility of being a ‘lucky outlier’. We tested this hypothesis in two scenario studies with lay people as participants. The data clearly show that people prefer to receive expected survival time as a median value together with explicit information about the survival curve’s right skewedness (e.g., concrete examples of ‘positive outliers’), and that communicating expected survival time this way not only provides people with hope, but also gives them a more realistic understanding compared with the typical way expected survival time is communicated. Our data indicate that it is not the existence of the uncertainty regarding the mortality prognosis that is the problem for patients, but how this uncertainty is, or is not, communicated and explained.

Keywords: cancer patients, decision psychology, doctor-patient communication, mortality prognosis

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Authors: Elizabeth Behrens, Anne Timmermann, Alexander Yerkan, Joshua Thomas, Deborah Katz, Agne Paner, Melissa Larson, Shivi Jain, Seo-Hyun Kim, Celalettin Ustun, Ankur Varma, Parameswaran Venugopal, Jamile Shammo

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Coronavirus Disease-2019 (COVID-19) causes persistent concern for poor outcomes in vulnerable populations. Patients with hematologic malignancies (HM) have been found to have higher COVID-19 case fatality rates compared to those without malignancy. While cytopenias are common in patients with HM, especially in those undergoing chemotherapy treatment, hemoglobin (Hgb) and platelet count have not yet been studied, to our best knowledge, as potential prognostic indicators for patients with HM and COVID-19. The goal of this study is to identify factors that may increase the risk of mortality in patients with HM and COVID-19. In this single-center, retrospective, observational study, 65 patients with HM and laboratory confirmed COVID-19 were identified between March 2020 and January 2021. Information on demographics, laboratory data the day of COVID-19 diagnosis, and prognosis was extracted from the electronic medical record (EMR), chart reviewed, and analyzed using the statistical software SAS version 9.4. Chi-square testing was used for categorical variable analyses. Risk factors associated with mortality were established by logistic regression models. Non-Hodgkin lymphoma (37%), chronic lymphocytic leukemia (20%), and plasma cell dyscrasia (15%) were the most common HM. Higher Hgb level upon COVID-19 diagnosis was related to decreased mortality, odd ratio=0.704 (95% confidence interval [CI]: 0.511-0.969; P = .0263). Platelet count the day of COVID-19 diagnosis was lower in patients who ultimately died (mean 127 ± 72K/uL, n=10) compared to patients who survived (mean 197 ±92K/uL, n=55) (P=.0258). Female sex was related to decreased mortality, odd ratio=0.143 (95% confidence interval [CI]: 0.026-0.785; P = .0353). There was no mortality difference between the patients who were on treatment for HM the day of COVID-19 diagnosis compared to those who were not (P=1.000). Lower Hgb and male sex are independent risk factors associated with increased mortality of HM patients with COVID-19. Clinicians should be especially attentive to patients with HM and COVID-19 who present with cytopenias. Larger multi-center studies are urgently needed to further investigate the impact of anemia, thrombocytopenia, and demographics on outcomes of patients with hematologic malignancies diagnosed with COVID-19.

Keywords: anemia, COVID-19, hematologic malignancy, prognosis

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Authors: Funda Kul, İsmail Gür

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Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

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Authors: Ayu Nabila Kusuma Pradana, Aprinaldi Jasa Mantau, Tomohiko Akahoshi

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The incidence of Disseminated intravascular coagulation (DIC) following gastrointestinal surgery has a poor prognosis. Therefore, it is important to determine the factors that can predict the prognosis of DIC. This study will investigate the factors that may influence the outcome of DIC in patients after gastrointestinal surgery. Eighty-one patients were admitted to the intensive care unit after gastrointestinal surgery in Kyushu University Hospital from 2003 to 2021. Acute DIC scores were estimated using the new Japanese Association for Acute Medicine (JAAM) score from before and after surgery from day 1, day 3, and day 7. Acute DIC scores will be compared with The Sequential Organ Failure Assessment (SOFA) score, platelet count, lactate level, and a variety of biochemical parameters. This study applied machine learning algorithms to predict the prognosis of DIC after gastrointestinal surgery. The results of this study are expected to be used as an indicator for evaluating patient prognosis so that it can increase life expectancy and reduce mortality from cases of DIC patients after gastrointestinal surgery.

Keywords: the survival rate, gastrointestinal surgery, JAAM score, neural network, machine learning, disseminated intravascular coagulation (DIC)

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Authors: Emna Ketata, Wafa Farhat

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Introduction: Hyponatremia is defined by a blood sodium level of ≤ 136 mmol/L; it is associated with a high risk of morbidity and mortality in the emergency room. This was explained by transit disorders, including diarrhea and inappropriate antidiuretic hormone secretion (Syndrome of inappropriate antidiuretic hormone secretion). Pneumonia can cause dyspnea, stress-causing SIADH and digestive symptoms (diarrhea and vomiting). Aim: The purpose of this study was to determine the link between pneumonia and hyponatremia as a predictor of patient’s prognosis and intra-hospital mortality. Methodology: This is a prospective observational study over a period of 3 years in the emergency department. Inclusion :patients (age > 14 years), with clinical signs in favor of pneumonia. Natremia was measured. Natremia was classified as mild to moderate with a blood sodium level between 121 and 135 mmol/L and as severe with a blood sodium level ≤ 120 mmol/L. Results: This study showed an average serum sodium value of 135 mmol/L (range 114–159 mmol/L) in these patients. Hyponatremia was observed in 123 patients (43.6%), 115 patients (97,8%) had mild to moderate hyponatremia and 2,8% had severe hyponatremia. The mean age was 65±17 years with a sex ratio of 1.05. The main reason for consultation in patients with hyponatremia was cough in 58 patients (47.2%), and digestive symptoms were present in 25 patients (20.3. An altered state of consciousness was observed in 11 patients (3%). Patients with hyponatremia had greater heart rate (p=0.02),white blood cell count (p=0.009) , plasmatic lactate (p=0.002) and higher rate of pneumonia recurrence (p=0.001) .In addition, 80% of them have a positive CURB65 score (>=2). hyponatremia had higher rates of use of oxygen therapy compared to patients with normo-natremia (54% vs. 45%). The analytical study showed that hyponatremia is significantly associated with intra-hospital mortality with( p=0.01), severe hyponatremia p=0.04. Conclusion: Hyponatremia is a predictor of mortality and worse prognosis. Recognition of the pathophysiological mechanisms of hyponatremia in pneumonia will probably allow better management of it.

Keywords: oxygenotherapy, mortality, recurrence, positif curb65

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Authors: Hanan Alsaeid Alshenawy

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Background: Cervical dysplasia, which is potentially precancerous, has increased in young women. Detection of cervical is important for reducing morbidity and mortality in cervical cancer. This study analyzes the immunohistochemical expression of p16, HPV L1 capsid protein and Ki67 in cervical intraepithelial lesions and correlates them with lesion grade to develop a set of markers for diagnosis and detect the prognosis of cervical cancer precursors. Methods: 75 specimens were analyzed including 15 cases CIN 1, 28 CIN 2, 20 CIN 3, and 12 cervical squamous carcinoma, besides 10 normal cervical tissues. They were stained for p16, HPV L1 and Ki-67. Sensitivity, specificity, predictive values and accuracy were evaluated for each marker. Results: p16 expression increased during the progression from CIN 1 to carcinoma. HPV L1 positivity was detected in CIN 2 and decreased gradually as the CIN grade increased but disappear in carcinoma. Strong Ki-67 expression was observed with high grades CIN and carcinoma. p16, HPV L1 and Ki67 were sensitive but with variable specificity in detecting CIN lesions. Conclusions: p16, HPV L1 and Ki67 are useful set of markers in establishing the risk of high-grade CIN. They complete each other to reach accurate diagnosis and prognosis.

Keywords: p16, HPV L1, Ki67, CIN, cervical carcinoma

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Authors: Shohreh Ghasemi

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Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

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Authors: Jeffrey Tzu-Hao Tsai, Yi-Shan Wong

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This article proposes a cohort-age-period (CAP) model to characterize multi-population mortality processes using cohort, age, and period variables. Distinct from the factor-based Lee-Carter-type decomposition mortality model, this approach is empirically based and includes the age, period, and cohort variables into the equation system. The model not only provides a fruitful intuition for explaining multivariate mortality change rates but also has a better performance in forecasting future patterns. Using the US and the UK mortality data and performing ten-year out-of-sample tests, our approach shows smaller mean square errors in both countries compared to the models in the literature.

Keywords: longevity risk, stochastic mortality model, multivariate mortality rate, risk management

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Authors: Ayyaz Hussain, Tariq Sadad

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Breast cancer (BC) is one of the widespread ailments among females globally. The early prognosis of BC can decrease the mortality rate. Exact findings of benign tumors can avoid unnecessary biopsies and further treatments of patients under investigation. However, due to variations in images, it is a tough job to isolate cancerous cases from normal and benign ones. The machine learning technique is widely employed in the classification of BC pattern and prognosis. In this research, a deep convolution neural network (DCNN) called AlexNet architecture is employed to get more discriminative features from breast tissues. To achieve higher accuracy, K-nearest neighbor (KNN) classifiers are employed as a substitute for the softmax layer in deep learning. The proposed model is tested on a widely used breast image database called MIAS dataset for experimental purposes and achieved 99% accuracy.

Keywords: breast cancer, DCNN, KNN, mammography

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Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

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Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

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Authors: Mahadev Bhise, Nabanita Majumder

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Recent studies have found association between air pollutants and mortality, particularly how concentration of air pollutant explains under-five mortality across the countries. Thus, the present study evaluates the relationship between Carbon dioxide (CO2) emission and under-five mortality, while controlling other well-being determinant of Under-five mortality in 100 countries using panel unbalanced cross sectional data. We have used PCSE and GMM model for the period 1990-2011 to meet our objectives. Our findings suggest that, the positive relationship between lagged periods of carbon dioxide and under-five mortality; the percentage of rural population with access of improved water is negatively associated with under-five mortality, while in case of urban population with access of improved water, is positively related to under-five mortality. Access of sanitation facility, food production index, GDP per capita, and concentration of urban population have significant negative impact on under-five mortality. Further, total fertility rate is significantly associated (positive) with under-five mortality which indicates relative change in fertility is related to relative change in under-five mortality.

Keywords: arbon dioxide (CO2), under-five mortality (0q5), gross domestic product (GDP), urban population, food production, panel corrected standard errors (PCSE), generalized method of moments (GMM)

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Authors: Hongmeng Su, Luyu Zhao, Yanyan Qian, Hong Fan

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Aim: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that endanger human health seriously. RNA methylation, especially N6-methyladenosine (m⁶A) and 5-methylcytosine (m⁵C), a crucial epigenetic transcriptional regulatory mechanism, plays an important role in tumorigenesis, progression and prognosis. This research aims to systematically evaluate the prognostic value of m⁶A and m⁵C modulators in HCC patients. Methods: Twenty-four modulators of m⁶A and m⁵C were candidates to analyze their expression level and their contribution to predict the prognosis of HCC. Consensus clustering analysis was applied to classify HCC patients. Cox and LASSO regression were used to construct the risk model. According to the risk score, HCC patients were divided into high-risk and low/medium-risk groups. The clinical pathology factors of HCC patients were analyzed by univariate and multivariate Cox regression analysis. Results: The HCC patients were classified into 2 clusters with significant differences in overall survival and clinical characteristics. Nine-gene risk model was constructed including METTL3, VIRMA, YTHDF1, YTHDF2, NOP2, NSUN4, NSUN5, DNMT3A and ALYREF. It was indicated that the risk score could serve as an independent prognostic factor for patients with HCC. Conclusion: This study constructed a Nine-gene risk model by modulators of m⁶A and m⁵C and investigated its effect on the clinical prognosis of HCC. This model may provide important consideration for the therapeutic strategy and prognosis evaluation analysis of patients with HCC.

Keywords: hepatocellular carcinoma, m⁶A, m⁵C, prognosis, RNA methylation

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Authors: Tzu-Jung Tseng, Pei-Hsuen Han, Tsung-Hsueh Lu

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Background: Choropleth mortality map is commonly used to identify areas with higher mortality risk. However, the use of choropleth map alone might result in the misinterpretation of differences in mortality rates between areas. Two areas with different color shades might not actually have a significant difference in mortality rates. The mortality rates estimated for an area with a small population would be less stable. We suggest of bringing the 95% confidence intervals (CI) into the choropleth mortality map to help users interpret the areal mortality rate difference more properly. Method: In the first choropleth mortality map, we used only three color to indicate standardized mortality ratio (SMR) for each district in Tainan, Taiwan. The red color denotes that the SMR of that district was significantly higher than the Tainan average; on the contrary, the green color suggests that the SMR of that district was significantly lower than the Tainan average. The yellow color indicates that the SMR of that district was not statistically significantly different from the Tainan average. In the second choropleth mortality map, we used traditional sequential color scheme (color ramp) for different SMR in 37 districts in Tainan City with bar chart of each SMR with 95% CI in which the users could examine if the line of 95% CI of SMR of two districts overlapped (nonsignificant difference). Results: The all-causes SMR of each district in Tainan for 2008 to 2013 ranged from 0.77 (95% CI 0.75 to 0.80) in East District to 1.39 Beimen (95% CI 1.25 to 1.52). In the first choropleth mortality map, only 16 of 37 districts had red color and 8 districts had green color. For different causes of death, the number of districts with red color differed. In the first choropleth mortality map we added a bar chart with line of 95% CI of SMR in each district, in which the users could visualize the SMR differences between districts. Conclusion: Through the use of 95% CI the users could interpret the aral mortality differences more properly.

Keywords: choropleth map, small area variation, standardized mortality ratio (SMR), Taiwan

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Authors: Chang Liang, Weizhi Gong, Yan Zhang

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Purpose: Hepatocellular carcinoma (HCC) is a malignant tumor with a high mortality rate and poor prognosis worldwide. Murine double minute 2 (MDM2) regulates the tumor suppressor p53, increasing cancer risk and accelerating tumor progression. Speckle-type POX virus and zinc finger protein (SPOP), a key of subunit of Cullin-Ring E3 ligase, inhibits tumor genesis and progression by the ubiquitination of its downstream substrates. This study aimed to clarify whether SPOP and MDM2 are mutually regulated in HCC and the correlation between SPOP and MDM2 and the prognosis of HCC patients. Methods: First, the expression of SPOP and MDM2 in HCC tissues were detected by TCGA database. Then, 53 paired samples of HCC tumor and adjacent tissues were collected to evaluate the expression of SPOP and MDM2 using immunohistochemistry. Chi-square test or Fisher’s exact test were used to analyze the relationship between clinicopathological features and the expression levels of SPOP and MDM2. In addition, Kaplan‒Meier curve analysis and log-rank test were used to investigate the effects of SPOP and MDM2 on the survival of HCC patients. Last, the Multivariate Cox proportional risk regression model analyzed whether the different expression levels of SPOP and MDM2 were independent risk factors for the prognosis of HCC patients. Results: Bioinformatics analysis revealed the low expression of SPOP and high expression of MDM2 were related to worse prognosis of HCC patients. The relationship between the expression of SPOP and MDM2 and tumor stem-like features showed an opposite trend. The immunohistochemistry showed the expression of SPOP protein was significantly downregulated while MDM2 protein significantly upregulated in HCC tissue compared to that in para-cancerous tissue. Tumors with low SPOP expression were related to worse T stage and Barcelona Clinic Liver Cancer (BCLC) stage, but tumors with high MDM2 expression were related to worse T stage, M stage, and BCLC stage. Kaplan–Meier curves showed HCC patients with high SPOP expression and low MDM2 expression had better survival than those with low SPOP expression and high MDM2 expression (P < 0.05). A multivariate Cox proportional risk regression model confirmed that a high MDM2 expression level was an independent risk factor for poor prognosis in HCC patients (P <0.05). Conclusion: The expression of SPOP protein was significantly downregulated, while the expression of MDM2 significantly upregulated in HCC. The low expression of SPOP and high expression. of MDM2 were associated with malignant progression and poor prognosis of HCC patients, indicating a potential therapeutic target for HCC patients.

Keywords: hepatocellular carcinoma, murine double minute 2, speckle-type POX virus and zinc finger protein, ubiquitination

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Authors: Raj Kumari Bahl, Sotirios Sabanis

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In this paper, we are concerned with the valuation of the first Catastrophic Mortality Bond that was launched in the market namely the Swiss Re Mortality Bond 2003. This bond encapsulates the behavior of a well-defined mortality index to generate payoffs for the bondholders. Pricing this bond is a challenging task. We adapt the payoff of the terminal principal of the bond in terms of the payoff of an Asian put option and present an approach to derive model-independent bounds exploiting comonotonic theory. We invoke Jensen’s inequality for the computation of lower bounds and employ Lagrange optimization technique to achieve the upper bound. The success of these bounds is based on the availability of compatible European mortality options in the market. We carry out Monte Carlo simulations to estimate the bond price and illustrate the strength of these bounds across a variety of models. The fact that our bounds are model-independent is a crucial breakthrough in the pricing of catastrophic mortality bonds.

Keywords: mortality bond, Swiss Re Bond, mortality index, comonotonicity

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Authors: Naomi Seidu, Edward Poluyi, Chibuikem Ikwuegbuenyi, Eghosa Morgan

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The current poor prognosis of glioblastoma has called for the need for an improvement in treatment methods in order to improve its survival rate. Despite the different interventions currently available for this tumor, the average survival is still only a few months. (12-15). The aim is to create a more favorable prognosis and have a reduction in the resistance to treatment currently being experienced, even with surgical interventions and chemotherapy. From the available literature, there is a relationship between the presence of HOX genes (Homeobox genes) and glioblastoma, which could be attributable to the increasing treatment resistance. Hence silencing these genes can be a key to improving survival rates of glioblastoma. A series of studies have highlighted the role that HOX genes play in glioblastoma prognosis. Promotion of human glioblastoma initiation, aggressiveness, and resistance to Temozolomide has been associated with HOXA9. The role of HOX gene expression in cancer stem cells should be studied as it could provide a means of designing CSC-targeted therapies, as CSCs play a part in the initiation and progression of solid tumors.

Keywords: GBM- glioblastoma, HOXA gene- homeobox genes cluster, signaling pathways, temozolomide

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Authors: Omonov Jahongir Mahmatkulovic

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Purpose: To study the significance of D-dimer (DD), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen coagulation parameters (Fg) in predicting the course, severity and prognosis of COVID-19. Source and method of research: From September 15, 2021, to November 5, 2021, 93 patients aged 25 to 60 with suspected COVID-19, who are under inpatient treatment at the multidisciplinary clinic of the Tashkent Medical Academy, were retrospectively examined. DD, PT, APTT, and Fg were studied in dynamics and studied changes. Results: Coagulation disorders occurred in the early stages of COVID-19 infection with an increase in DD in 54 (58%) patients and an increase in Fg in 93 (100%) patients. DD and Fg levels are associated with the clinical classification. Of the 33 patients who died, 21 had an increase in DD in the first laboratory study, 27 had an increase in DD in the second and third laboratory studies, and 15 had an increase in PT in the third test. The results of the ROC analysis of mortality showed that the AUC DD was three times 0.721, 0.801, and 0.844, respectively; PT was 0.703, 0.845, and 0.972. (P<0:01). Conclusion”: Coagulation dysfunction is more common in patients with severe and critical conditions. DD and PT can be used as important predictors of mortality from COVID-19.

Keywords: Covid19, DD, PT, Coagulogram analysis, APTT

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Authors: Fae Princess Bermudez

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Background: One of the least significant leads on a 12-lead electrocardiogram is the augmented right lead (aVR), as it is not as specific compared to the other leads. In this case series, the value of lead aVR, which is more often than not ignored, is highlighted. Three cases of aVR ST segment elevation on 12-lead electrocardiogram are described, with the end outcome of demise of all three patients. The importance of immediate revascularization is described to improve prognosis in this group of patients. Objectives: This case series aims to primarily present under-reported cases of isolated aVR ST-segrment elevation myocardial infarction (STEMI), their course and outcome. More specific aims are to identify the criteria in determination of isolated aVR STEMI, know its clinical significance, and determine appropriate management for patients with this ECG finding. Method: A short review of previous studies, case reports, articles and guidelines from 2011-2016 was done. The author reviewed available literature, sorted out those that proved to be significant for the presented cases, and described them in conjunction with the aforementioned cases. Findings: Based on the limited information on these rare or under-reported cases, it was found that isolated aVR STEMI had a poorer prognosis that led to significant mortality and morbidity of patients. The significance of aVR ST-elevation was that of an occlusion of the left coronary artery or a severe three-vessel disease in the presence of an Acute Coronary Syndrome. Guidelines from American Heart Association/American College of Cardiology Foundation in 2013 already recognized ST-elevation of lead aVR in isolation as a STEMI; hence, recommended that patients with this particular ECG finding should undergo reperfusion strategies to improve prognosis. Conclusion: The indispensability of isolated aVR ST-segment elevation on ECG should alert physicians, especially Emergency physicians, to the high probability of Acute Coronary Syndrome with a very poor prognosis. If this group of patients is not promptly managed, demise may ensue, with cardiogenic shock as the most probable cause. With this electrocardiogram finding, physicians must be quick to make clinical decisions to increase chances of survival of this group of patients.

Keywords: AVR ST-elevation, diffuse ST-segment depression, left coronary artery infarction, myocardial infarction

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Authors: Pedro Gomes, Lia Ferreira, Sofia Garcia, Jaime Babulal, Luís Costa, Luís Castelo, José Muras, Isabel Gonçalves, Rui Carvalho

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Introduction: Foot ulcers and their complications are an important cause of morbidity and mortality in diabetes. Objectives: The present study aims to evaluate the outcomes in terms of need for hospitalization, amputation, healing time and mortality in patients with new-onset diabetic foot ulcers in subgroups stratified by etiology. Methods: A retrospective study based on clinical assessment of patients presenting with new ulcers to a multidisciplinary diabetic foot consult during 2012. Outcomes were determined until September 2014, from hospital registers. Baseline clinical examination was done to classify ulcers as neuropathic, ischemic or neuroischemic. Results: 487 patients with new diabetic foot ulcers were observed; 36%, 15% and 49% of patients had neuropathic, ischemic and neuroischemic ulcers, respectively. For analysis, patients were classified as having predominantly neuropathic (36%) or ischemic foot (64%). The mean age was significantly higher in the group with ischemic foot (70±12 vs 63±12 years; p <0.001), as well as the duration of diabetes (18±10 vs 16 ± 10years, p <0.05). A history of previous amputation was also significantly higher in this group (24.7% vs 15.6%, p <0.05). The evolution of ischemic ulcers was significantly worse, with a greater need for hospitalization (27.2% vs 18%, p <0.05), amputation (11.5% vs 3.6% p <0.05) mainly major amputation (3% vs. 0%; p <0.001) and higher mean healing time (151 days vs 89 days, p <0.05). The mortality rate at 18 months, was also significantly higher in the ischemic foot group (7.3% vs 1.8%, p <0.05). Conclusions: All types of diabetic foot ulcers are associated with high morbidity and mortality, however, the presence of arterial disease confers a poor prognosis. Diabetic foot can be successfully treated only by the multidisciplinary team which can provide more comprehensive and integrated care.

Keywords: diabetes, foot ulcers, etiology, outcome

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Authors: Muhammad Dildar Gogi, Muhammad Arshad, Muhammad Ahsan Khan, M. Sufian, Ahmad Nawaz, Mubashir Iqbal, Muhammad Junaid Nisar, Waleed Afzal Naveed

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Larvae of silkworm (Bombyx mori) exhibit very high mortality when reared on mulberry leaves collected from mulberry orchards which get contaminated with metallic/nonmetallic compounds through either drift-deposition or chemigation. There is need to screen out such metallic compound for their toxicity at their various concentrations. The present study was carried out to assess toxicity of metals in different instars of silkworm. Aqueous solutions of nine heavy-metal based salts were prepared by dissolving 50, 100, 150, 200, 250, 300, 350 and 400 mg of each salt in one liter of water and were applied on the mulberry leaves by leaf-dip methods. The results reveal that mortality in 1st, 2nd, 3rd, 4th and 5th instar larvae caused by each heavy metal salts increased with an increase in their concentrations. The 1st instar larvae were found more susceptible to metal salts followed by 2nd, 3rd, 4th and 5th instar larvae of silkworm. Overall, Nickel chloride proved more toxic for all larval instar as it demonstrated approximately 40-99% mortality. On the basis of LC2 and larval mortality, the order of toxicity of heavy metals against all five larval instar was Nickel chloride (LC₂ = 1.9-13.9 mg/L; & 15.0±1.2-69.2±1.7% mortality) followed by Chromium nitrate (LC₂ = 3.3-14.8 mg/L; & 13.3±1.4-62.4±2.8% mortality), Cobalt nitrate (LC₂ = 4.3-30.9; &11.4±0.07-54.9±2.0% mortality), Lead acetate (LC₂ =8.8-53.3 mg/L; & 9.5±1.3-46.4±2.9% mortality), Aluminum sulfate (LC₂ = 15.5-76.6 mg/L; & 8.4±0.08-42.1±2.8% mortality), Barium sulfide (LC₂ = 20.9-105.9; & 7.7±1.1-39.2±2.5% mortality), Copper sulfate (LC2 = 28.5-12.4 mg/L; & 7.3±0.06-37.1±2.4% mortality), Manganese chloride (LC₂ = 29.9-136.9 mg/L; & 6.8±0.09-35.3±1.6% mortality) and Zinc nitrate (LC₂ = 36.3-15 mg/L; & 6.2±1.2-32.1±1.9% mortality). Zinc nitrate @ 50 and 100 mg/L, Barium sulfide @ 50 mg/L, Manganese chloride @ 50 and 100 mg/L and Copper sulfate @ 50 mg/L proved safe for 5th instar larvae as these interaction attributed no mortality. All the heavy metal salts at a concentration of 50 mg/L demonstrated less than 10% mortality.

Keywords: heavy-metals, larval-instars, lethal-concentration, mortality, silkworm

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Authors: G. I. Onwuka, A. Danbaba, S. U. Gulumbe

Abstract:

This study investigated of Infant Mortality Rate as observed at a general hospital in Kaduna-South, Kaduna State, North West Nigeria. The causes of infant Mortality were examined. The data used for this analysis were collected at the statistics unit of the Hospital. The analysis was carried out on the data using Multiple Linear regression Technique and this showed that there is linear relationship between the dependent variable (death) and the independent variables (malaria, measles, anaemia, and coronary heart disease). The resultant model also revealed that a unit increment in each of these diseases would result to a unit increment in death recorded, 98.7% of the total variation in mortality is explained by the given model. The highest number of mortality was recorded in July, 2005 and the lowest mortality recorded in October, 2009.Recommendations were however made based on the results of the study.

Keywords: infant mortality rate, multiple linear regression, diseases, serial correlation

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Authors: Alcino Panguana

Abstract:

All Portuguese-speaking African countries are in Sub-Saharan Africa, a region that has high infant mortality rates, being responsible for 49.6% of deaths in Portuguese-speaking African countries, Angola has levels of infant mortality among children, where 2017, 156 children who died before reaching 1 year of life in 1000 live births. Although there is an increase in studies that document trends and specific causes of infant mortality in each country, historical-comparative studies of infant mortality among these countries remain rare. Understanding the trend of this indicator is important for policymakers and planners in order to improve access to successful child survival operations. Lusophone Africa continues with high infant mortality rates in the order of 64 deaths per thousand births. Assuming heterogeneities that can characterize these countries, raise an analysis investigated indicator at the country level to understand the pattern and historical trend of infant mortality within Lusophone Africa from the year 2021. The result is to understand the levels and evolution of infant mortality in Portuguese-speaking African countries.

Keywords: child mortality, levels, trends, lusophone African countries

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Authors: Ziyu Diao, Yanyan Zhang, Zhentao Liu, Ruidong Yan

Abstract:

The update frequency of wear profile in main bearing wear prognosis of internal combustion engine plays an important role in the calculation efficiency and accuracy. In order to investigate the appropriate cycle index of the simplified working condition of wear simulation, the main bearing-crankshaft journal friction pair of a diesel engine in service was studied in this paper. The method of multi-body dynamics simulation was used, and the wear prognosis model of the main bearing was established. Several groups of cycle indexes were set up for the wear calculation, and the maximum wear depth and wear profile were compared and analyzed. The results showed that when the cycle index reaches 3, the maximum deviation rate of the maximum wear depth is about 2.8%, and the maximum deviation rate comes to 1.6% when the cycle index reaches 5. This study provides guidance and suggestions for the optimization of wear prognosis by selecting appropriate value of cycle index according to the requirement of calculation cost and accuracy of the simulation work.

Keywords: cycle index, deviation rate, wear calculation, wear profile

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Authors: Noha E. Hassan

Abstract:

Little is known regarding the influence of lymphatic microvessel density (LMVD) on prognosis in endometrial cancer. Prospective study was done in tertiary education and research hospital (Shatby Alexandria university hospital) on sixty patients presented with endometrial carcinoma underwent complete surgical staging. Our aim was to assess the intratumoral and peritumoral Lymphatic microvessel density (LMVD) of endometrial carcinomas identified by immunohistochemical staining using an antibody against podoplanin and to investigate their association with classical clinicopathological factors and prognosis. The result shows that high LMVD was associated with endometroid type of tumors, lesser myometrial, adnexal, cervical and peritoneal infiltration, lower tumor grade and stage and lesser recurrent cases. There is lower lymph node involvement among cases with high intratumoral LMVD and cases of high peritumoral LMVD; that reach statistical significance only among cases of high intratumoral LMVD. No association was seen between LMVD and lymphovascular space invasion. On the other hand, low LMVD was associated with poor outcome. Finally, we can conclude that increased LMVD is associated with favorable prognosis in endometrial cancer patients.

Keywords: endometrial carcinoma, lymphatic microvessel, microvessel density, prognosis

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Authors: W. Sriwattanapongse, S. Prasitwattanaseree, S. Wongtrangan

Abstract:

The transportation accidents mortality is a major problem that leads to loss of human lives, and economic. The objective was to identify patterns of statistical modeling for estimating mortality rates due to transportation accidents in Thailand by using data from 2000 to 2009. The data was taken from the death certificate, vital registration database. The number of deaths and mortality rates were computed classifying by gender, age, year and region. There were 114,790 cases of transportation accidents deaths. The highest average age-specific transport accident mortality rate is 3.11 per 100,000 per year in males, Southern region and the lowest average age-specific transport accident mortality rate is 1.79 per 100,000 per year in females, North-East region. Linear, poisson and negative binomial models were chosen for fitting statistical model. Among the models fitted, the best was chosen based on the analysis of deviance and AIC. The negative binomial model was clearly appropriate fitted.

Keywords: transportation accidents, mortality, modeling, analysis of deviance

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Authors: Erdem Kirkbesoglu, A. Bugra Soylu, E. Deniz Kahraman

Abstract:

The aim of this study is to examine the effects of some variables on organizational mortality of the Turkish insurance industry and calculate the carrying capacities of Turkish insurance industry according to cities and regions. In the study, organizational mortality was tested with the level of reaching the population's carrying capacity. The findings of this study show that the insurance sales potentials can be calculated according to the provinces and regions of Turkey. It has also been proven that the organizations that feed on the same source will have a carrying capacity in the evolutionary process.

Keywords: insurance, carrying capacity, organizational mortality, organization

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Authors: Florge Francis A. Sy

Abstract:

Acute pancreatitis (AP) is an inflammatory condition of the pancreas with local and systemic complications. Severe acute pancreatitis (SAP) has a higher mortality rate. Laboratory parameters like the neutrophil-to-lymphocyte ratio (NLR), red cell distribution width (RDW), and mean platelet volume (MPV) have been associated with SAP but with conflicting results. This study aims to determine the predictive value of these parameters on the severity and in-hospital mortality of AP. This retrospective, cross-sectional study was done in a private hospital in Cebu City, Philippines. One-hundred five patients were classified according to severity based on the modified Marshall scoring. The admitting hemogram, including the NLR, RDW, and MPV, was obtained from the complete blood count (CBC). Cut-off values for severity and in-hospital mortality were derived from the ROC. Association between NLR, RDW, and MPV with SAP and mortality were determined with a p-value of < 0.05 considered significant. The mean age for AP was 47.6 years, with 50.5% being male. Most had an unknown cause (49.5%), followed by a biliary cause (37.1%). Of the 105 patients, 23 patients had SAP, and 4 died. Older age, longer in-hospital duration, congestive heart failure, elevated creatinine, urea nitrogen, and white blood cell count were seen in SAP. The NLR was associated with in-hospital mortality using a cut-off of > 10.6 (OR 1.133, 95% CI, p-value 0.003) with 100% sensitivity, 70.3% specificity, 11.76% PPV and 100% NPV (AUC 0.855). The NLR was not associated with SAP. The RDW and MPV were not associated with SAP and mortality. The admitting NLR is, therefore, an easily accessible parameter that can predict in-hospital mortality in acute pancreatitis. Although the present study did not show an association of NLR with SAP nor RDW and MPV with both SAP and mortality, further studies are suggested to establish their clinical value.

Keywords: acute pancreatitis, mean platelet volume, neutrophil-lymphocyte ratio, red cell distribution width

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Authors: Narendra Kumar

Abstract:

This study uses data from the ‘National Family Health Survey (NFHS-3) 2005-06’ to investigate the predictors of infant and child mortality among low economic households in East and Northeast region. The cross tabulation, life table survival estimates and Cox proportional hazard model techniques have been used to estimate the predictors of infant and child mortality. The life table survival estimates for infant and child mortality shows that infant mortality in female child is lower in comparison to male child but with child mortality, the rates are higher for female in comparison to male child and the Cox proportional hazard model also give highly significant in female in comparison to male child. The infant and child mortality rates among poor households highest in the Central region followed by North and Northeast region and the lowest in South region in comparison to all regions of India. Education of respondent has been found a significant characteristics in both analyzes, further birth interval, respondent occupation, caste/tribe and place of delivery has substantial impact on infant and child mortality among low economic households in East and Northeast region. Finally these findings specified that an increase in parents’ education, improve health care services and improve socioeconomic conditions of low economic households which should in turn raise infant and child survival and should decrease child mortality among low economic households in India.

Keywords: infant, child, mortality, socio-economic, India

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Authors: Syazreen N. Shair, Saiful A. Ishak, Aida Y. Yusof, Azizah Murad

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In this paper, we forecast age-specific Malaysian mortality rates and life expectancy at births by gender and ethnic groups including Malay, Chinese and Indian. Two mortality forecasting models are adopted the original Lee-Carter model and its recent modified version, the product ratio coherent model. While the first forecasts the mortality rates for each subpopulation independently, the latter accounts for the relationship between sub-populations. The evaluation of both models is performed using the out-of-sample forecast errors which are mean absolute percentage errors (MAPE) for mortality rates and mean forecast errors (MFE) for life expectancy at births. The best model is then used to perform the long-term forecasts up to the year 2030, the year when Malaysia is expected to become an aged nation. Results suggest that in terms of overall accuracy, the product ratio model performs better than the original Lee-Carter model. The association of lower mortality group (Chinese) in the subpopulation model can improve the forecasts of high mortality groups (Malay and Indian).

Keywords: coherent forecasts, life expectancy at births, Lee-Carter model, product-ratio model, mortality rates

Procedia PDF Downloads 187

Authors: Junhong Li, Danni Cheng, Yaxin Luo, Xiaowei Yi, Ke Qiu, Wendu Pang, Minzi Mao, Yufang Rao, Yao Song, Jianjun Ren, Yu Zhao

Abstract:

Background: The number of multiple cancer patients was increasing, and the impact of prior cancer history on salivary gland cancer patients remains unclear. Methods: Clinical, demographic and pathological information on salivary gland cancer patients were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2017, and the characteristics and prognosis between patients with a prior cancer and those without prior caner were compared. Univariate and multivariate cox proportional regression models were used for the analysis of prognosis. A risk score model was established to exam the impact of treatment on patients with a prior cancer in different risk groups. Results: A total of 9098 salivary gland cancer patients were identified, and 1635 of them had a prior cancer history. Salivary gland cancer patients with prior cancer had worse survival compared with those without a prior cancer (p<0.001). Patients with a different type of first cancer had a distinct prognosis (p<0.001), and longer latent time was associated with better survival (p=0.006) in the univariate model, although both became nonsignificant in the multivariate model. Salivary gland cancer patients with a prior cancer were divided into low-risk (n= 321), intermediate-risk (n=223), and high-risk (n=62) groups and the results showed that patients at high risk could benefit from surgery, radiation therapy, and chemotherapy, and those at intermediate risk could benefit from surgery. Conclusion: Prior cancer history had an adverse impact on the survival of salivary gland cancer patients, and individualized treatment should be seriously considered for them.

Keywords: prior cancer history, prognosis, salivary gland cancer, SEER

Procedia PDF Downloads 115