Discuss how you might diagnose, manage, and support the following two patients presenting with breast conditions: Discussion: Breast Conditions

Discuss how you might diagnose, manage, and support the following two patients presenting with breast conditions:
Discussion: Breast Conditions

Throughout a woman’s life, her breasts go through many normal, healthy changes. However, patients do not always understand these changes and often visit health care providers for treatment. When examining these patients, you must be able to identify when a breast condition is the result of a safe and normal physiological change and when it is the result of an abnormal change requiring treatment and management. A diagnosis of a breast condition resulting from an abnormal change can be devastating for women, making emotional support as vital to women’s well-being as proper assessment, diagnosis, and management. For this Discussion, consider how you might diagnose, manage, and support the following two patients presenting with breast conditions:

Case Study 1:

You are seeing a 60-year-old Latina female, Gravida 4 Para 3104, who is concerned about a thick greenish discharge from her left breast for the past month. The discharge is spontaneous and associated with dull pain and burning. Upon questioning, she also tells you that she breastfed all her children and is currently not on any medications except for occasional Tylenol for arthritis. Her last mammogram, 14 months ago, was within normal limits. On exam, her left breast around the areola is slightly reddened and edematous. Upon palpation of the right quadrant, a greenish-black discharge exudes from the nipple. You note an ovoid, smooth, very mobile, non-tender 1 cm nodule in the RUIQ at 11:00 5 cm from the nipple. No adenopathy, dimpling, nipple discharge, or other associated findings. Her right breast is unremarkable. The patient expresses her desire to proactively decrease her risk for developing breast cancer.

Case Study 2:

You are seeing a 53-year-old African American female for a lump she found in her right breast two weeks ago in the shower. Her last mammogram was three years ago and she was told it was “benign.” She had two breast biopsies at ages 32 and 34 in her right and left breasts, respectively. At both times she had surgery for removal of fibroadenomas. She does not routinely do breast self-exams. Her mother had a mastectomy for breast cancer at age 63, and she heard that a paternal aunt had a breast removed for cancer when she was in her forties. Both mother and aunt are alive and well today. It was discovered on postmortem exam that her grandfather had prostate cancer. Menarche was at age 15 and she is still having monthly menses. She is Gravida 4 Para 3104 with her first childbirth at age 31. She was on oral contraception for 10 years, has no history of fertility treatments, and had a bilateral tubal ligation after the birth of her last child at age 35. Past medical history is noncontributory. She wants to know how likely it is that she will get breast cancer. Physical exam reveals breasts are symmetrical with no dimpling, retractions, or rash. Her right breast has a 2 cm non-tender, hard, fixed mass at 3:00 6 cm from her nipple. Left breast is non-tender without masses. No nipple discharge bilaterally. No anterior cervical, infra- or supraclavicular, or axillary adenopathy.

To prepare:

Review Chapter 15 of the Schuiling and Likis text.

Review and select one of the two provided case studies. Analyze the patient information.

Consider a differential diagnosis for the patient in the case study you selected. Think about the most likely diagnosis for the patient.

Reflect on the appropriate clinical guidelines. Think about a treatment and management plan for the patient. Be sure to consider appropriate dosages for any recommended pharmacologic and/or nonpharmacologic treatments.

Consider strategies for educating patients on the treatment and management of the disorder you identified as your primary diagnosis.

 

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the potential adverse effects of caffeine intake in children

Caffeine intake in children in the United States and 10-y trends: 2001–20101–4

Namanjeet Ahluwalia, Kirsten Herrick, Alanna Moshfegh, and Michael Rybak

ABSTRACT Background: Because of the increasing concern of the potential adverse effects of caffeine intake in children, recent estimates of caffeine consumption in a representative sample of children are needed. Objectives: We provide estimates of caffeine intake in children in absolute amounts (mg) and in relation to body weight (mg/kg) to examine the association of caffeine consumption with sociodemo- graphic factors and describe trends in caffeine intake in children in the United States. Design: We analyzed caffeine intake in 3280 children aged 2–19 y who participated in a 24-h dietary recall as part of the NHANES, which is a nationally representative survey of the US population with a cross-sectional design, in 2009–2010. Trends over time be- tween 2001 and 2010 were examined in 2–19-y-old children (n = 18,530). Analyses were conducted for all children and repeated for caffeine consumers. Results: In 2009–2010, 71% of US children consumed caffeine on a given day. Median caffeine intakes for 2–5-, 6–11-, and 12–19-y olds were 1.3, 4.5, and 13.6 mg, respectively, and 4.7, 9.1, and 40.6 mg, respectively, in caffeine consumers. Non-Hispanic black chil- dren had lower caffeine intake than that of non-Hispanic white counterparts. Caffeine intake correlated positively with age; this association was independent of body weight. On a given day, 10% of 12–19-y-olds exceeded the suggested maximum caffeine intake of 2.5 mg/kg by Health Canada. A significant linear trend of decline in caffeine intake (in mg or mg/kg) was noted overall for children aged 2–19 y during 2001–2010. Specifically, caffeine in- take declined by 3.0 and 4.6 mg in 2–5- and 6–11-y-old caffeine consumers, respectively; no change was noted in 12–19-y-olds. Conclusion: A majority of US children including preschoolers con- sumed caffeine. Caffeine intake was highest in 12–19-y-olds and remained stable over the 10-y study period in this age group. Am J Clin Nutr 2014;100:1124–32.

INTRODUCTION

Caffeine is a commonly consumed stimulant present naturally in or added to foods and beverages. Caffeine consumption in children has received considerable interest because of the con- cern of adverse health effects. Caffeine intake of 100–400 mg has been associated with nervousness, jitteriness, and fidgetiness (1, 2). Because of the continued brain development involving myelination and pruning processes, children may be particularly sensitive to caffeine (3, 4). There has been some evidence that has linked caffeine intake in children to sleep dysfunction, el-

evated blood pressure, impairments in mineral absorption and bone health, and increased alcohol use or dependence (1, 5–7). In addition, the routine use of caffeinated sugar-sweetened beverages may contribute to weight gain and dental cavities (8). Caffeine toxicity in children has also been described involving tachycardia, central nervous system agitation, gastrointestinal disturbance, and diuresis (6, 9, 10). Health Canada has put forth maximal daily caffeine intake guidelines for children and ado- lescents (6, 11). Although no such recommendations have been set in the United States, the American Academy of Pediatrics has underscored that “caffeine and other stimulant substances contained in energy drinks have no place in the diet of children” (12).

Caffeine consumption has also been associated with certain health benefits such as increased endurance, attention, and vig- ilance and a reduced reaction time in some studies (9, 13, 14). Perceived positive effects on mood and cognition as well as physical performance may encourage preteens and adolescents to consume caffeinated products (2, 15, 16).

The literature on caffeine consumption in a representative sample of US children has been primarily based on older data, namely the US Department of Agriculture Continuing Survey of Food Intakes by Individuals (CSFII)5 1994–1996 and 1998 (16, 17). In addition, caffeine intake from beverages from the 1999 US Share of Intake Panel (SIP) survey in caffeine consumers has also been published (18). A 2010 US Food and Drug Admin- istration report also presented findings from the analysis of older data from NHANES 2005–2006 (19). Because of the current

1 From the Division of Health and Nutrition Examination Surveys, Na-

tional Center for Health Statistics, CDC, Hyattsville, MD (NA and KH);

the National Center for Environmental Health, CDC, Atlanta, GA (MR);

and the Food Surveys Research Group, Beltsville Human Nutrition Research

Center–Agricultural Research Service, USDA, Beltsville, MD (AM). 2 Findings and conclusions in this report are those of the authors and do

not necessarily represent the official position of the National Center for

Health Statistics, CDC. 3 Thiswork was not supported by any external grant. 4 Address correspondence to N Ahluwalia, Division of Health and Nutri-

tion Examination Surveys, National Center for Health Statistics, CDC, 3311

Toledo Road, Room 4110, Hyattsville, MD 20782. E-mail: naman.ahluwalia@

cdc.gov. 5 Abbreviations used: CSFII, Continuing Survey of Food Intakes by In-

dividuals; MEC, mobile examination center; PIR, poverty income ratio; SIP,

Share of Intake Panel.

ReceivedDecember 19, 2013. Accepted for publication July 3, 2014.

First published online August 27, 2014; doi: 10.3945/ajcn.113.082172.

1124 Am J Clin Nutr 2014;100:1124–32. Printed in USA. � 2014 American Society for Nutrition

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debate on the safety of caffeine intake by children (1, 12, 18) and deliberations to evaluate maximal intake recommendations, it is important to describe caffeine intake from more recent data available on a nationally representative sample such as the NHANES.

Trends in beverage consumption have changed over time (16, 20), and several caffeinated beverages and energy drinks have been introduced in the past decade, some marketed especially to youth (12, 15, 16). Few reports have described trends in caffeine intake both in milligrams and milligrams per kilogram of body weight by age in the United States (16, 21). Thus, our objective was to provide estimates of the distribution of caffeine intake in absolute amounts and in milligrams per kilogram in a representative sample of American children (2–19 y old) by using the most recent di- etary data available from the NHANES (ie, 2009–2010) in re- lation to demographic characteristics and examine the trends in caffeine consumption between 2001 and 2010 in children.

SUBJECTS AND METHODS

Study design

TheNHANES is a series of large, complex, stratified, multistage probability surveys of the US civilian, noninstitutionalized pop- ulation conducted by the National Center for Health Statistics, CDC (22). Briefly, NHANES is conducted yearly in w5000 individuals, and data are publicly released every 2 y onw10,000 individuals. Participants in the NHANES are administered a se- ries of questionnaires in a detailed in-home interview followed by a scheduled visit at the mobile examination center (MEC). At the MEC visit, participants receive a physical examination as well as a dietary interview, which is commonly referred to as the What We Eat in America component of the NHANES. The NHANES protocol was approved by the National Center for Health Statistics’s Research Ethics Review board. Informed consent was obtained from persons aged $18 y. For participants ,18 y of age, written parental consent was obtained, and child assent was obtained for individuals from 7 to 17 y of age. The most recent available data on caffeine intake from the NHANES (from the 2009–2010 survey) were used for the current analysis to describe caffeine consumption by demographic characteris- tics; data from this single survey cycle were sufficient to provide stable national estimates. We used NHANES data from 2001 to 2010 (2001–2002, 2003–2004, 2005–2006, 2007–2008, and 2009–2010 survey cycles) to conduct the trends analysis; be- cause of changes in the dietary data collection methodology on merging of the CSFII with NHANES in 1999–2000, data from 1999 to 2000 were not included in the trends analysis. The un- weighted total examination response rate for the 5 survey cycles examined for participants 2–19 y of age ranged from 81% to 88% (23).

Dietary interview

The type and quantity of all foods and beverages consumed in a single 24-h period, specifically the 24-h period before the dietary interview (from midnight to midnight) at the MEC, were collected by trained interviewers with the use of a computer- assisted dietary interview system with standardized probes (ie, the USDA’s Automated Multiple-Pass Method). Specifically for

beverages for which caffeine may be removed such as soda, coffee, tea, and energy drinks, probes were used to ascertain if the bev- erage reported was caffeine free. The Automated Multiple-Pass Method is designed to enhance a complete and accurate data collection while reducing the respondent burden (24, 25). For children aged #5 y, interviews were obtained through proxies, generally a parent. Proxies also assisted with dietary interviews of children aged 6–11 y. Dietary intakes were self-reported for participants aged $12 y. Since 2003–2004, a second, telephone- administered 24-h recall has been collected (3–10 d after the first 24-h recall at the MEC), but only one 24-h dietary recall was included in this analysis to maximize the comparability between surveys. Furthermore, one 24-h recall is sufficient to estimate population means because the effects of random errors associ- ated with dietary recall, including the day-to-day variability, are generally assumed to cancel out if days of the week are evenly represented (26).

Caffeine intake for all…

What competencies you able to develop in researching

SSIGNMENT: What competencies were you able to develop in researching and writing the Comprehensive Project due in Unit 5? How […]

week 7 lab

Week 7 Assignment: Lab

Submit Assignment

  • Due Aug 23 by 11:59pm
  • Points 50
  • Submitting a file upload

Required Resources

Read/review the following resources for this activity:

 

  • Chamberlain University Library

Scenario/Summary

The highlight of this week’s lab is confidence intervals and the use of these intervals in the health sciences. There is a short reading that specifically relates confidence intervals to health sciences and then you are asked to demonstrate your knowledge of confidence intervals by applying them in a practical manner.

Deliverables

The deliverable is a Word document with your answers to the questions posed below based on the article you find.

Required Software

  • Microsoft Word
  • Internet access to read articles

Steps to Complete the Week 7 Lab

Step 1: Find these articles in the Chamberlain Library. Once you click each link, you will be logged into the Library and then click on “PDF Full Text”.

  • First Article: Confidence Intervals, Part 1 (Links to an external site.) (Links to an external site.)Links to an external site. (Links to an external site.)
  • Second Article: Confidence Intervals, Part 2 (Links to an external site.) (Links to an external site.)Links to an external site. (Links to an external site.)

Step 2: Consider the use of confidence intervals in health sciences with these articles as inspiration and insights.

Step 3: Using the data you collected for the Week 5 Lab (heights of 10 different people that you work with), discuss your method of collection for the values that you are using in your study. What are some faults with this type of data collection? What other type of data collection could you have used, and how might this have affected your study?

Step 4: Now use the Week 6 Spreadsheet (Links to an external site.) to help you with calculations for the following questions/statements.

  1. Give a point estimate for the average height of all people at the place where you work. Start by putting the ten heights you are working with into the blue Data column of the spreadsheet. What is your point estimate, and what does this mean?
  2. Find a 95% confidence interval for the true mean height of all the people at your place of work. What is the interval?
  3. Give a practical interpretation of the interval you found in part b, and explain carefully what the output means. (For example, you might say, “I am 95% confident that the true mean height of all of the people in my company is between 64 inches and 68 inches”).
  4. Post a screenshot of your work from the t value Confidence Interval for µ from the Confidence Interval tab on the Week 6 Excel spreadsheet

Step 5: Now, find a 99% confidence interval for the same data. Would the margin of error be larger or smaller for the 99% CI? Explain your reasoning.

Step 6: Save the Week 7 Lab document with your answers and include your name in the title.

 

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