Loading citation data
Load citations from an existing search file using
the load_search() function. In this example, we use a csv
format.
existing_search <- load_search("old_sr_search.csv")Load citations from a new systematic search.
new_search <- load_search("new_sr_search.csv")Combine old and new citation data
Before deduplication, we must bind the citations into one dataframe. First, give each search a different source so that we can specify which citations to retain.
existing_search$source <- "old"
new_search$source <- "new"
all_citations <- plyr::rbind.fill(existing_search, new_search)Automated deduplication
Remove duplicate citations automatically using the
dedup_citations function. Here we have specified the
argument merge=TRUE to indicate that we want to merge
duplicate records and have a record of which citations have been merged
into one. We have specified in the keep_source argument
that we wish to preferentially retain old citations. In practice, this
means that the duplicate_id chosen for a set of records will
preferentially be the record_id of a citation in the OLD systematic
search. This is to facilitate easy record linkage - see later.
results <- dedup_citations(all_citations, merge_citations = TRUE, keep_source = "old")
#> formatting data...
#> identifying potential duplicates...
#> identified duplicates!
#> flagging potential pairs for manual dedup...
#> Joining with `by = join_by(duplicate_id.x, duplicate_id.y)`
#> 8972 citations loaded...
#> 472 duplicate citations removed...
#> 8500 unique citations remaining!The dedup_citations function returns a list of two
dataframes by default. The first contains unique citations after
duplicates were removed automatically by ASySD. In most cases, this will
remove the vast majority of duplicates. There will likely be some
duplicates remaining which need manual review by a human (see next
step).
unique_citations <- results$uniqueManual deduplication
To check for additional duplicates, get the dataframe of citations for manual review. You can review within R or export as a csv / excel file to go through each row of pairs.
potential_duplicates <- results$manual_dedupAfter reviewing the pairs, create a dataframe contianing only
the true duplicate pairs. Here, all the suggested duplicates
look like REAL duplicates. Alternatively, you could go through them
one-by-one using the manual_dedup_shiny() function.
true_duplicates <- potential_duplicatesNow, to get the final deduplication results, use the
dedup_citations_add_manual()function. To account for
additional duplicates you have reviewed, add them into the
additional_pairs argument.
final_results <- dedup_citations_add_manual(unique_citations, additional_pairs = true_duplicates, merge_citations = TRUE, keep_source = "old")
#> Joining with `by = join_by(record_id)`Find new citations identified in update
Now we have a final set of unique citations, how can we find the new citations we added with our latest systematic search?
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
new_citations <- final_results %>%
filter(source == "new")
new_citations %>%
tail(3) %>%
gt::gt() %>%
gt::cols_hide(c(abstract))| duplicate_id | author | year | journal | doi | title | pages | volume | number | isbn | label | source | url | ...1 | uid | keywords | secondarytitle | issn | pmid | ptype | author_country | author_affiliation | record_ids |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| wos:000931052000002 | Lipton, Stuart A. | 2022 | FREE RADICAL BIOLOGY AND MEDICINE | 10.1016/j.freeradbiomed.2022.10.272 | Hidden networks of aberrant protein transnitrosylation contribute to synapse loss in Alzheimer's disease | 171-176 | 193 | NA | NA | 270223 | new | NA | 5561 | wos:000931052000002 | NA | NA | 0891-5849 | NA | NA | NA | NA | wos:000931052000002 |
| wos:000931426100001 | Marini, Sandro; Chung, Jaeyoon; Han, Xudong; Sun, Xinyu; Parodi, Livia; Farrer, Lindsay A.; Rosand, Jonathan; Romero, Jose Rafael; Anderson, Christopher D. | 2023 | INTERNATIONAL JOURNAL OF STROKE | 10.1177/17474930231155816 | Pleiotropy analysis between lobar intracerebral hemorrhage and CSF beta-amyloid highlights new and established associations | NA | NA | NA | NA | 270223 | new | NA | 9861 | wos:000931426100001 | ICH | beta-amyloid | pleiotropy | genetic epidemiology | cadherin | cerebral amyloid angiopathy | NA | 1747-4930 | NA | NA | NA | NA | wos:000931426100001 |
| wos:000932018500001 | Walker, Keenan A.; Duggan, Michael R.; Gong, Zhaoyuan; Dark, Heather E.; Laporte, John P.; Faulkner, Mary E.; An, Yang; Lewis, Alexandria; Moghekar, Abhay R.; Resnick, Susan M.; Bouhrara, Mustapha | 2023 | ANNALS OF CLINICAL AND TRANSLATIONAL NEUROLOGY | 10.1002/acn3.51730 | Kidney and lung crosstalk during critical illness: large-scale cohort study (FEB, 10.1007/s40620-023-01594-z, 2023) | NA | NA | NA | NA | 270223 | new | NA | 6501 | wos:000932018500001 | NA | NA | 2328-9503 | NA | NA | NA | NA | wos:000932018500001 |
Lets also have a look at the citations identified in both searches by removing citations with a single source.
crossover <- final_results %>%
filter(!source == "new") %>%
filter(!source == "old")
crossover %>%
tail(3) %>%
gt::gt() %>%
gt::cols_hide(c(abstract))| duplicate_id | author | year | journal | doi | title | pages | volume | number | isbn | label | source | url | ...1 | uid | keywords | secondarytitle | issn | pmid | ptype | author_country | author_affiliation | record_ids |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| wos:000919545100001 | Larkin, Howard D. D. | 2023 | JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION | 10.1001/jama.2022.24490 | Lecanemab Gains FDA Approval for Early Alzheimer Disease | 363 | 329 | NA | NA | 270223, 270223 | new, new | NA | 3271 | wos:000919545100001 | NA | NA | 0098-7484 | 36652625 | Article | NA | NA | wos:000919545100001, scopus-2-s2.0-85147720543 |
| wos:000924510300006 | Chen, Shanquan; Price, Annabel C.; Cardinal, Rudolf N.; Moylett, Sinead; Kershenbaum, Anne D.; Fitzgerald, James; Mueller, Christoph; Stewart, Robert; O'Brien, John T. | 2022 | PLOS MEDICINE | 10.1371/journal.pmed.1004124 | Association between antidementia medication use and mortality in people diagnosed with dementia with Lewy bodies in the UK: A retrospective cohort study | NA | 19 | NA | NA | 270223, 270223 | new, new | NA | 9981 | wos:000924510300006 | NA | NA | 1549-1277 | NA | NA | NA | NA | wos:000924510300006, wos:000925010400002 |
| wos:000928044600001 | Wang, Lin-Yu; Liu, Jiao; Peng, Yi-Zhu; Zhang, Cai-Ping; Zou, Wei; Liu, Feng; Zhan, Ke-Bin; Zhang, Ping | 2022 | NATURAL PRODUCT COMMUNICATIONS | 10.1177/1934578X221141162 | Curcumin-Nicotinate Attenuates Hippocampal Synaptogenesis Dysfunction in Hyperlipidemia Rats by the BDNF/TrkB/CREB Pathway: Involving Idol/LDLR Signaling to Eliminate A beta Deposition | NA | 17 | NA | NA | 270223, 270223 | new, new | NA | 9791 | wos:000928044600001 | hyperlipidemia | high-fat diet | Curcumin-Nicotinate | amyloid-beta | BDNF | TrkB | CREB signaling | synaptogenesis | Idol/LDLR pathway | NA | 1934-578X | NA | NA | NA | NA | wos:000928044600001, wos:000922862000001 |
To keep good records, we don’t want to lose track of identifiers for studies we have already included in a review. This is why specifying the citation to keep was important! To illustrate this, look specifically at the citations present in the old search.
We can check that the duplicate ids here refer to the original record id in the existing_citations dataframe we imported. As you can see, they are all present. In the record_ids column you can see the different record_ids that have merged into a single citation. In case you make a mistake or don’t specify the record_id to keep as the duplicate_id, you can use these to trace back your citations to the original dataframes.
old_citations_check <- old_citations %>%
filter(duplicate_id %in% existing_search$record_id) #check that all citations use the OLD record_id as the duplicate_id
crossover %>%
tail(3) %>%
gt::gt() %>%
gt::cols_hide(c(abstract))| duplicate_id | author | year | journal | doi | title | pages | volume | number | isbn | label | source | url | ...1 | uid | keywords | secondarytitle | issn | pmid | ptype | author_country | author_affiliation | record_ids |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| wos:000919545100001 | Larkin, Howard D. D. | 2023 | JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION | 10.1001/jama.2022.24490 | Lecanemab Gains FDA Approval for Early Alzheimer Disease | 363 | 329 | NA | NA | 270223, 270223 | new, new | NA | 3271 | wos:000919545100001 | NA | NA | 0098-7484 | 36652625 | Article | NA | NA | wos:000919545100001, scopus-2-s2.0-85147720543 |
| wos:000924510300006 | Chen, Shanquan; Price, Annabel C.; Cardinal, Rudolf N.; Moylett, Sinead; Kershenbaum, Anne D.; Fitzgerald, James; Mueller, Christoph; Stewart, Robert; O'Brien, John T. | 2022 | PLOS MEDICINE | 10.1371/journal.pmed.1004124 | Association between antidementia medication use and mortality in people diagnosed with dementia with Lewy bodies in the UK: A retrospective cohort study | NA | 19 | NA | NA | 270223, 270223 | new, new | NA | 9981 | wos:000924510300006 | NA | NA | 1549-1277 | NA | NA | NA | NA | wos:000924510300006, wos:000925010400002 |
| wos:000928044600001 | Wang, Lin-Yu; Liu, Jiao; Peng, Yi-Zhu; Zhang, Cai-Ping; Zou, Wei; Liu, Feng; Zhan, Ke-Bin; Zhang, Ping | 2022 | NATURAL PRODUCT COMMUNICATIONS | 10.1177/1934578X221141162 | Curcumin-Nicotinate Attenuates Hippocampal Synaptogenesis Dysfunction in Hyperlipidemia Rats by the BDNF/TrkB/CREB Pathway: Involving Idol/LDLR Signaling to Eliminate A beta Deposition | NA | 17 | NA | NA | 270223, 270223 | new, new | NA | 9791 | wos:000928044600001 | hyperlipidemia | high-fat diet | Curcumin-Nicotinate | amyloid-beta | BDNF | TrkB | CREB signaling | synaptogenesis | Idol/LDLR pathway | NA | 1934-578X | NA | NA | NA | NA | wos:000928044600001, wos:000922862000001 |
Exporting results
Once deduplication is complete, you can export the new unique records to a file for import into reference managers or systematic review software.
write_citations(new_citations, type="txt", filename="unique.txt")