Week 11 Response to students

5 days ago

Stephanie Minbiole-Snider

RE: Discussion 1 – Week 11

COLLAPSE

Dissertation research question: Is there a difference in infant mortality in mothers with treated verses untreated mental health conditions

Independent variables: Women with history of pregnancy as well as a diagnosis mental illness

Dependent variable: Treatment of mental health condition and infant mortality

To best examine this research question, a researcher would consider a regression model to understand the multiple variables or factors that might influence the outcome. Specifically, the Cox Proportional Hazard will be leveraged to identify the difference between mothers with a mental health condition who lost a child either prenatal or postnatal and if the mother’s mental health condition was treated or untreated. The Cox Proportional Hazard is often used for survival analysis, frequently in disease states such as cancer, but has also been applied to birth analyses (Wuryandari, Kartiko, & Danardono 2018; Rice, Neuman, Saccone … et. al., 2003). Specifically, the test allows us to understand how different factors can affect survival (STHDA, n.d.).

References

Rice, J. P., Neuman, R. J., Saccone, N. L., Corbett, J., Rochberg, N., Hesselbrock, V., Bucholz, K. K., McGuffin, P., & Reich, T. (2003). Age and birth cohort effects on rates of alcohol dependence. Alcoholism: Clinical and Experimental Research, 27(1), 93–99. https://doi.org/10.1111/j.1530-0277.2003.tb02727.x

STHDA. (n.d.). Cox proportional-hazards model. Statistical Tools for High-Throughput Data Analysis. Retrieved November 9, 2021, from http://www.sthda.com/english/wiki/cox-proportional-hazards-model.

Wuryandari, T., Kartiko, S. H., & Danardono. (2018). The Cox proportional hazard model on duration of birth process. Journal of Physics: Conference Series, 1025, 012121. https://doi.org/10.1088/1742-6596/1025/1/012121

4 days ago

Emily Barnard

Kaplan-Meier Analysis – WK 11

COLLAPSE

Research Topic:

Epidemiological analysis of risk factors for healthcare-associated carbapenem-resistant Acinetobacter baumannii (CRAB) outbreaks in an acute care hospital during the COVID-19 pandemic.

Variable Analysis:

Independent variable(s):

  • Prolonged length of stay (hospitalization > 14 days): 0=no; 1= yes
  • Exposure to an intensive care unit (ICU): 0=no; 1= yes
  • Receipt of mechanical ventilation during hospital stay: 0=no; 1= yes
  • Developed sepsis during hospitalization: 0=no; 1= yes
  • Exposure to antimicrobial agents: 0=no; 1= yes
  • Previous history of CRAB infection: 0=no; 1= yeas

Dependent variable: hospital acquired CRAB (onset > 3 days after admission); 0=no; 1=yes

Confounding variables: age, race/ethnicity, gender

Statistical Test Methodology:

Kaplan-Meier statistical analysis methodology

Kaplan-Meier (KM) method was selected to answer the research question to analyze the time-to-event data (Laerd Statistics, n.d.). The community-onset (CO) period is within the first three days of admission and if the patient develops a carbapenem-resistant Acinetobacter baumannii (CRAB) after day three, the infection will be classified as a healthcare-associated infection (HAI). Outbreak investigations will be conducted with surveillance measures and contact tracing to determine the cases are epidemiologically linked. The Centers for Disease Control and Prevention (CDC) defines epi linkage as; “a case in which the patient has/has had contact with one or more persons who have/had the disease, and transmission of the agent by the usual modes of transmission is plausible. A case may be considered epidemiologically linked to a laboratory-confirmed case if at least one case in the chain of transmission is laboratory-confirmed” (Wharton et al., 1990). Risk factors for the development of HAI CRAB were prolonged length of stay (hospitalization > 14 days), exposure to an intensive care unit, receipt of mechanical ventilation during the hospital stay, developed sepsis during hospitalization, previous CRAB infection, and exposure to antimicrobial agents (Murray et al., 2008; Sultan & Seliem, 2018).

References

Laerd Statistics. (n.d.). Kaplan-Meier method in SPSS statistics. https://statistics.laerd.com/spss-tutorials/kaplan-meier-using-spss-statistics.php

Murray, G., Peleg, A., & Doi, Y. (2015). Acinetobacter baumannii: Evolution of antimicrobial resistance—Treatment options. Seminars in Respiratory and Critical Care Medicine, 36(01), 085-098. https://doi.org/10.1055/s-0034-1398388

Sultan, A. M., & Seliem, W. A. (2018). Identifying Risk Factors for Healthcare-Associated Infections Caused by Carbapenem-Resistant Acinetobacter baumannii in a Neonatal Intensive Care Unit. Sultan Qaboos University medical journal, 18(1), e75–e80. https://doi.org/10.18295/squmj.2018.18.01.012

Wharton, E., Chorba, T. L., Vogt, R. L., Morse, D. L., & Buehler, J. W. (1990). Case definitions for public health surveillance. MMWR, 3(RR-13), 1-43. https://www.cdc.gov/mmwr/preview/mmwrhtml/00025629.htm

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