Four Databases, 1,142 Records and Nine Studies Kept: A Documented Literature Search on Preoperative Carbohydrate Drinks, Reported With a Flow Diagram and Every Decision Written Down
[Student Name]
University of Phoenix
DNP/710: Evidence-Based Practice Measurement and Clinical Inquiry
Week 3 Assignment
[Instructor Name]
[Date]
The search counts are a composite written for a model paper.
My PICOT question asks whether a carbohydrate drink taken shortly before elective surgery, compared with fasting from midnight, reduces thirst and hunger and improves recovery in adults without diabetes. This paper documents the search I conducted to answer it, so another clinician could repeat it and reach the same records.
Choosing Databases
Bramer et al. (2017) analyzed searches for 58 published systematic reviews and reported that searching four particular sources together, two large biomedical indexes, a citation index and a web search engine, found 98.3% of the references the reviews eventually included, that 16% of relevant references appeared in only one database and that specialized databases such as CINAHL added unique references when the topic matched their focus. They estimated that 60% of published reviews missed relevant references because they did not search enough databases. Based on this, I searched MEDLINE through PubMed, Embase, CINAHL and the Cochrane Library. Web of Science was not available through my university, which I note as a limitation, and I used Google Scholar to check the first 200 results for missing trials.
Search Concepts and Terms
From my PICOT question, I built three concept groups: population and setting (elective surgery, surgical procedures, operative, perioperative), intervention (carbohydrate drink, carbohydrate loading, preoperative carbohydrate, oral nutritional supplement, clear fluids) and fasting (preoperative fasting, fasting, nil by mouth, NPO). I did not add outcome terms, because outcomes are often not described in titles and abstracts, and adding them would lower recall.
Subject Headings
In PubMed, I combined Medical Subject Headings, including Preoperative Care, Dietary Carbohydrates and Fasting, with text words. In CINAHL, I used equivalent CINAHL Headings. In Embase, I used Emtree terms. Each database's string is saved in an appendix with the date run.
Limits
I limited results to English-language human studies in adults, with no date limit, so earlier trials would not be missed. I did not limit by study design at the search stage but prioritized systematic reviews and randomized trials when screening.
A search nobody can repeat is an opinion with citations; writing down every string and every exclusion turns it into evidence.
Results and Screening
The searches returned 1,142 records: 398 from PubMed, 421 from Embase, 176 from CINAHL and 147 from the Cochrane Library. After removing 364 duplicates with a reference manager, 778 records remained. I screened titles and abstracts against inclusion criteria: adults, elective surgery, a preoperative carbohydrate drink compared with fasting or placebo and at least one outcome related to comfort, recovery, safety or length of stay. This left 41 records for full-text review. After full-text review, I included 9: 3 systematic reviews and 6 randomized controlled trials. Reasons for exclusion were pediatric populations (7), emergency surgery (4), no relevant comparison (9), conference abstracts without full data (8) and outcomes limited to laboratory markers such as insulin resistance (4).
Managing Duplicates
The reference manager's automatic duplicate detection caught most overlaps, but I also sorted by title and first author to find duplicates with minor differences in formatting. Seven additional duplicates were removed this way. Careful deduplication keeps screening counts accurate.
Reporting the Flow
Page et al. (2021), in the PRISMA 2020 statement, updated reporting guidance for systematic reviews, including a flow diagram showing records identified from each source, duplicates removed, records screened and excluded, reports sought and assessed for eligibility, reports excluded with reasons and studies included. Although my search is not a full systematic review, I used the PRISMA 2020 flow structure to report it transparently.
The Anchor Review
The most important record is Smith et al. (2014), a Cochrane review of 27 trials with 1,976 participants undergoing elective abdominal, orthopedic, cardiac and thyroid surgery. It found that preoperative carbohydrate treatment was associated with a small reduction in length of stay compared with placebo or fasting, about 0.3 days, supported by very low-quality evidence, and that most trials had at least one domain at high risk of bias, particularly from inadequate blinding. This review will anchor my appraisal next week, alongside a second meta-analysis and individual trials measuring comfort outcomes.
Gray Literature and Guidelines
I searched the websites of the national anesthesia society and an enhanced recovery society for guidelines, finding a 2023 update on carbohydrate-containing clear liquids and a guideline for colorectal surgery recovery. Guidelines are not primary evidence but show how evidence has been interpreted.
Why Not Limit by Date
Many important trials of carbohydrate drinks were published around 2000. A limit to the last ten years would have excluded the trial most directly relevant to my comfort outcomes. For questions where early trials remain the main evidence, date limits can remove the most important studies.
Search Log
For each database, my log records the date, the exact string, the number of results and any filters applied. When I reran the PubMed search two weeks later to check for new publications, the log let me see that 3 new records had appeared, none relevant.
Hand Searching
I reviewed the reference lists of the three included reviews and found one additional trial not retrieved by database searches, which I added.
Types of Evidence Found
Of the nine included studies, the three systematic reviews sit highest in the evidence hierarchy for an intervention question. The six trials vary in size and quality, with most enrolling fewer than 150 patients. None was conducted in a United States same-day surgery center, which will matter when I judge applicability.
Limitations
Limitations include English-language only, a single screener without a second reviewer and no access to Web of Science. A second reviewer would reduce selection bias; my faculty mentor agreed to check a random 10% sample of excluded abstracts.
Working With a Librarian
The nursing librarian reviewed my PubMed string before I ran it and suggested adding the subject heading for Carbohydrate Loading and the text word "preoperative nutrition," which retrieved two additional trials. Librarian review is one of the most efficient ways to improve a search.
Screening Criteria in Practice
Some abstracts were ambiguous, for example trials that mixed elective and urgent cases. I retrieved the full text when unsure rather than excluding at the abstract stage, which accounts for part of the 41 full-text reviews. Erring toward inclusion at screening reduces the chance of missing relevant evidence.
Documentation
I saved all search strings with dates, exported results to a reference manager, recorded screening decisions in a spreadsheet and kept the flow counts. This record allows the search to be updated before my project begins.
Conclusion
A search of four databases, supported by evidence on search yield, returned 1,142 records, which after screening and full-text review yielded 9 studies, anchored by a Cochrane review of preoperative carbohydrate treatment. Reporting with the PRISMA 2020 flow structure makes each step reproducible, and documented limitations show where the search could miss evidence.
References
Bramer, W. M., Rethlefsen, M. L., Kleijnen, J., & Franco, O. H. (2017). Optimal database combinations for literature searches in systematic reviews: A prospective exploratory study. Systematic Reviews, 6, Article 245. https://doi.org/10.1186/s13643-017-0644-y
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., . . . Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, Article n71. https://doi.org/10.1136/bmj.n71
Smith, M. D., McCall, J., Plank, L., Herbison, G. P., Soop, M., & Nygren, J. (2014). Preoperative carbohydrate treatment for enhancing recovery after elective surgery. Cochrane Database of Systematic Reviews, 2014(8), Article CD009161. https://doi.org/10.1002/14651858.CD009161.pub2
How this DNP 710 Week 3 example is structured
The DNP/710 Week 3 work usually documents a systematic literature search. This paper makes the search reproducible: databases chosen and why, terms and subject headings, limits, screening steps and counts, and the reasons records were excluded. Students search this week as DNP 710 Week 3, DNP710 Wk 3 or DNP/710 Wk 3; all three are the same assignment.
DNP/710 Week 3 questions, answered
What does DNP/710 Week 3 usually ask for?
Many sections ask students to conduct and document a systematic search for evidence on their PICOT question, including databases, search terms, limits and results.
Which databases should a search include?
A study of systematic reviews found that combining Embase, MEDLINE, Web of Science and Google Scholar retrieved nearly all relevant references, with specialized databases like CINAHL adding unique references for nursing topics.
What is PRISMA 2020?
An updated reporting guideline for systematic reviews that includes a checklist and a flow diagram showing records identified, screened, excluded with reasons and included.
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