scholarly journals 100 Neonatal Disease Severity Scores and their Predictive Value 3For Early Mortality: A Population-Based Study on Subgroups of VLBW Infants

2012 ◽  
Vol 97 (Suppl 2) ◽  
pp. A28-A28
Author(s):  
R. Hentschel ◽  
K. Gunther ◽  
W. Vach ◽  
M. Teufel ◽  
T. Bohler ◽  
...  
Author(s):  
C. Roberto Simons-Linares ◽  
Suha Abushamma ◽  
Carlos Romero-Marrero ◽  
Amit Bhatt ◽  
Rocio Lopez ◽  
...  

Critical Care ◽  
2015 ◽  
Vol 19 (1) ◽  
pp. 47 ◽  
Author(s):  
Andrea L Conroy ◽  
Michael Hawkes ◽  
Kyla Hayford ◽  
Sophie Namasopo ◽  
Robert O Opoka ◽  
...  

2012 ◽  
Vol 110 (9) ◽  
pp. 1283-1288 ◽  
Author(s):  
Stanley A. Yap ◽  
David Horovitz ◽  
Shabbir M.H. Alibhai ◽  
Robert Abouassaly ◽  
Narhari Timilshina ◽  
...  

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 875-875
Author(s):  
Jude C Jonassaint ◽  
Charles R. Jonassaint ◽  
Charlene M. Flahiff ◽  
Andrea Ball ◽  
Soheir S. Adam ◽  
...  

Abstract Many of the tertiary care hospitals in North Carolina (NC) are often frequented by patients who have to travel a long distance, given the rural nature of the state. Nearly one half of the adult sickle cell disease (SCD) patients seen at the Duke Comprehensive Sickle Cell Center (DCSCC) come from areas further than a 1-hr drive. The current study aims to determine whether geographical proximity to a comprehensive medical center is associated with SCD outcomes, as indicated by severity score, hospitalization frequency, and quality of life. Methods: Two hundred and two patients who primarily receive their SCD disease-related care from DCSCC were enrolled in the study. The sample included 101 males and 101 females, aged 20–69 years (mean=35.6), with SCD disease (SS: n=135; SC: n=47; other: n=20), and level of education ranging from 4–18 years (mean=13.1). Patients lived an average of 50.4 miles (median: 38.6, range:0.4 to 383) from DCSCC. Linear regressions, controlling for age and SCD diagnosis, were used to test associations between continuous variables. Severity scores measuring end organ damage were determined as previously described (Afenyi-Annan et al. 2008), and frequency of hospitalizations over the past 2 years was determined by self-report and medical record review. To measure mental and physical quality of life (QoL) domains, patients were administered the SF36 QoL scale. Hydroxyurea (HU) and opiate pain therapies were also recorded. Patients were considered to be on opiates if they had used opiates daily for a period of thirty days in the previous 12 months. Results and Discussion: Living closer to Duke had a statistically significant association with higher disease severity scores (β = −0.17, p=0.01). Moreover, proximity to Duke was associated with higher frequency of hospitalizations (β = −0.23, p=0.002). These associations were not modified by gender, employment status or education. Medication use did not account for the association between proximity and disease severity, or proximity and frequency of hospitalizations. The mental domain scores of self-reported QoL correlated negatively with hospitalizations (r= −0.18, p=0.02), whereas the physical domain score negatively correlated with both disease severity (r= −0.19, p <0.01) and hospitalizations (r = −0.26, p <0.01). However, proximity to DCSCC was not associated with the mental or the physical QoL domain. Therefore, it is unlikely that patients move closer to Duke due to higher perceived severity of illness and related medical needs. Conclusion: Patients who live closer to our tertiary care comprehensive center had higher disease severity scores and more hospitalizations over a two year period than patients who live farther away. Neither age, disease diagnosis, gender, employment status, education, nor HU and/or opiate medication use accounted for the negative association between proximity to DCSCC and disease outcomes. On the other hand, distance from DCSCC did not affect patients’ quality of life. The cross-sectional nature of the current study makes it difficult to determine causality. However, it is possible that patients who live close to a major medical center rely more on health system availability as a means to managing their disease, while those living further away rely on self-care at home or adhere to long-term medical regimens. Health care providers may need to focus on developing practice guidelines that encourage and empower patients to take a more active role in their medical care and be less dependent on their healthcare providers to decrease frequency of hospitalization and, perhaps decrease the progression of their disease.


2017 ◽  
Vol 22 (4) ◽  
pp. 386-393 ◽  
Author(s):  
Ines Vaz‐Luis ◽  
Nancy U. Lin ◽  
Nancy L. Keating ◽  
William T. Barry ◽  
Eric P. Winer ◽  
...  

PLoS ONE ◽  
2013 ◽  
Vol 8 (9) ◽  
pp. e75168 ◽  
Author(s):  
Ting-An Yen ◽  
Hwai-I Yang ◽  
Wu-Shiun Hsieh ◽  
Hung-Chieh Chou ◽  
Chien-Yi Chen ◽  
...  

2021 ◽  
Vol 9 (1) ◽  
pp. 53
Author(s):  
N. Shivaramakrishna Babji ◽  
Cheruku Rajesh ◽  
Aparajitha Mekala ◽  
Bharathi Rani Siddani

Background: India contributes to 25% of the neonatal deaths worldwide each year. Neonatal disease severity scoring systems are needed to make standardized comparison between performances of different units and also give prognostic information. Existing scoring systems are unsuitable for resource-limited settings which lack investigations like pH, pO2/FiO2 ratio and base excess. Modified sick neonatal score (MSNS) is based on eight routinely measured clinical variables in NICUs namely respiratory effort, heart rate, axillary temperature, capillary refill time, random blood sugar, pulse oximeter saturation, gestational age and birth weight found to be useful in resource poor settings. The aim of the study was to validate MSNS score for its clinical utility in predicting mortality.Methods: This was a cross sectional study done at NICU of Mamata Medical College Hospital. The parameters required for the score were recorded immediately at admission in NICU from 1 January 2020 to 1 January 2021 and scored using Modified sick neonatal score (MSNS). The total score was calculated and outcome was noted. The data collected were coded and analzed using SPSS Statistics for Windows, v21.0 Chi square test, Mann-Whitney U test and ROC analysis.Results: Total of 355 neonates got discharged, while 45 neonates expired. For a cutoff score of ≤10, sensitivity and specificity were 85.9% and 51.1%, respectively. Positive predictive value and negative predictive value were 93.3% and 31.5%, respectively. The Area under the curve (AUC) was 0.811 (95%CI: 0.788-0.835), which indicates the accuracy of 81.1%.Conclusions: MSNS is a better suited neonatal disease severity score for resource poor settings.


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