Data cleaning of observations and study-level information.
There’s a shorthand tag for study (first author and year) that we’ll use for the labelling in the forest plots and joining the different datasets, however, this tag is not unique.
So, the study
tag appends with a number if there is more than one study by that author in a year.
tar_read(w_study_key) %>%
filter(str_detect(study, "Arnold")) %>%
mutate(title = str_trunc(title, width = 30)) %>%
gt() %>%
hpp_tab(vertical_divider = "study")
study_identifier | comments | study | title |
---|---|---|---|
Arnold 2002 | Title: A randomized, placebo-controlled, double-blind, flexible-dose study of fluoxetine in the treatment of women with fibromyalgia | Arnold 2002 | A randomized, placebo-contr... |
Arnold 2004 | Title: A double-blind, multicenter trial comparing duloxetine with placebo in the treatment of fibromyalgia patients with or without major depressive disorder | Arnold 2004 | A double-blind, multicenter... |
Arnold 2005 | Title: A randomized, double-blind, placebo-controlled trial of duloxetine in the treatment of women with fibromyalgia with or without major depressive disorder | Arnold 2005 | A randomized, double-blind,... |
Arnold 2010 | Title: Safety and efficacy of esreboxetine in patients with fibromyalgia: An 8-week, multicenter, randomized, double-blind, placebo-controlled study | Arnold 2010 : 1 | Safety and efficacy of esre... |
Arnold 2010 | Title: Efficacy and safety of milnacipran 100 mg/day in patients with fibromyalgia: results of a randomized, double-blind, placebo-controlled trial | Arnold 2010 : 2 | Efficacy and safety of miln... |
Arnold 2010 | Title: Flexible dosed duloxetine in the treatment of fibromyalgia: a randomized, double-blind, placebo-controlled trial | Arnold 2010 : 3 | Flexible dosed duloxetine i... |
Arnold 2012 | Title: Efficacy and safety of duloxetine 30 mg/d in patients with fibromyalgia: a randomized, double-blind, placebo-controlled study | Arnold 2012 : 1 | Efficacy and safety of dulo... |
Arnold 2012 | Title: Safety and efficacy of esreboxetine in patients with fibromyalgia: A fourteen-week, randomized, double-blind, placebo-controlled, multicenter clinical trial | Arnold 2012 : 2 | Safety and efficacy of esre... |
This function is used to construct a study key, and variables are relabelled in the study-level data extracted from Covidence, and the outcome observations extracted by Hollie.
tar_visnetwork(allow = c(
starts_with("r_h_"),
contains("covidence"),
starts_with("w_study_"),
contains("outcome")
))
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Loading required package: dontpanic
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We now have two datasets each with study
and arm
, so we can join them together later.
# table of study/arm level information
tar_read(w_study_label_study_arm_par)
# A tibble: 451 x 25
study arm intervention type class condition main_aim design
<glue> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 Kayir… Neuro… <NA> Neurof… <NA> Fibromya… Neurofe… Paral…
2 Kayir… Escit… Escitalopram Antide… SSRI Fibromya… Neurofe… Paral…
3 Arnol… Place… <NA> Placebo <NA> Fibromya… Fibromy… Paral…
4 Arnol… Fluox… Fluoxetine Antide… SSRI Fibromya… Fibromy… Paral…
5 Arnol… Place… <NA> Placebo <NA> Fibromya… Pain Paral…
6 Arnol… Esreb… Esreboxetine Antide… SNRI Fibromya… Pain Paral…
7 Gonza… Physi… Ultrasonogra… Ultras… <NA> Fibromya… Pain Paral…
8 Gonza… Sertr… Sertraline Antide… SSRI Fibromya… Pain Paral…
9 Hammo… Prega… Pregabalin Antico… <NA> Fibromya… Pain Paral…
10 Hammo… Amitr… Amitriptyline Antide… TCA Fibromya… Pain Paral…
# … with 441 more rows, and 17 more variables:
# sponsorship_source <chr>, authors_name <chr>,
# duration_weeks <chr>, pain_duration <chr>,
# inclusion_criteria <chr>, exclusion_criteria <chr>,
# total_number_of_participants_randomised <chr>,
# number_in_each_arm_comparators_treatments <chr>,
# number_in_each_arm_intervention_comparators <chr>,
# type_of_participant_e_g_people_with_cancer <chr>,
# type_of_participant_e_g_people_with_cancer_2 <chr>,
# intervention_adverse_events <chr>,
# intervention_adverse_events_n_percent <chr>,
# withdrawal_total_per_arm_n_percent <chr>,
# withdrawal_total_percent <dbl>, withdrawal_total_n <dbl>,
# title <chr>
# list of outcome tables with observations extracted by Hollie
tar_read(w_study_label_obs) %>%
# select first 10 columns bc space
map(select, c(1:10))
[[1]]
# A tibble: 451 x 10
outcome study arm anxiety_1_item_pati… anxiety_1_item_pati…
<chr> <glue> <chr> <lgl> <lgl>
1 mood Lee 20… Placebo NA NA
2 mood Lee 20… Venlafax… NA NA
3 mood dsrhv … Control NA NA
4 mood dsrhv … Amitript… NA NA
5 mood dsrhv … Amitript… NA NA
6 mood dsrhv … Acupunct… NA NA
7 mood Keskin… Gabapent… NA NA
8 mood Keskin… Amitript… NA NA
9 mood Cannon… Placebo NA NA
10 mood Cannon… Clonidine NA NA
# … with 441 more rows, and 5 more variables:
# anxiety_1_item_patient_rated_ni_baseline_se <lgl>,
# anxiety_4_point_nrs_from_0_no_anxiety_to_3_severe_anxiety_baseline_mean <dbl>,
# anxiety_4_point_nrs_from_0_no_anxiety_to_3_severe_anxiety_baseline_n <dbl>,
# anxiety_4_point_nrs_from_0_no_anxiety_to_3_severe_anxiety_baseline_sd <dbl>,
# anxiety_4_point_nrs_from_0_no_anxiety_to_3_severe_anxiety_mid_intervention_week_3_mean <dbl>
[[2]]
# A tibble: 451 x 10
outcome study arm american_college_of_… american_college_of_…
<chr> <glue> <chr> <dbl> <dbl>
1 pain_int Lee 2… Placebo NA NA
2 pain_int Lee 2… Venlaf… NA NA
3 pain_int dsrhv… Control NA NA
4 pain_int dsrhv… Amitri… NA NA
5 pain_int dsrhv… Amitri… NA NA
6 pain_int dsrhv… Acupun… NA NA
7 pain_int Keski… Gabape… NA NA
8 pain_int Keski… Amitri… NA NA
9 pain_int Canno… Placebo NA NA
10 pain_int Canno… Clonid… NA NA
# … with 441 more rows, and 5 more variables:
# american_college_of_rheumatology_acr_fibromyalgia_widespread_pain_index_wpi_baseline_sd <dbl>,
# american_college_of_rheumatology_acr_fibromyalgia_widespread_pain_index_wpi_post_intervention_ls_mean_se_change_from_baseline_mean <dbl>,
# american_college_of_rheumatology_acr_fibromyalgia_widespread_pain_index_wpi_post_intervention_ls_mean_se_change_from_baseline_n <dbl>,
# american_college_of_rheumatology_acr_fibromyalgia_widespread_pain_index_wpi_post_intervention_ls_mean_se_change_from_baseline_sd <dbl>,
# average_of_pain_rating_index_mc_gill_pain_questionnaire_itt_sample_baseline_mean <dbl>
[[3]]
# A tibble: 451 x 10
outcome study arm adverse_drug_reacti… adverse_drug_react…
<chr> <glue> <chr> <dbl> <dbl>
1 adverse Lee 20… Placebo NA NA
2 adverse Lee 20… Venlafaxi… NA NA
3 adverse dsrhv … Control NA NA
4 adverse dsrhv … Amitripty… NA NA
5 adverse dsrhv … Amitripty… NA NA
6 adverse dsrhv … Acupunctu… NA NA
7 adverse Keskin… Gabapenti… NA NA
8 adverse Keskin… Amitripty… NA NA
9 adverse Cannon… Placebo NA NA
10 adverse Cannon… Clonidine NA NA
# … with 441 more rows, and 5 more variables:
# adverse_effects_physician_rated_with_the_dotes_endpoint_percent <dbl>,
# adverse_effects_physician_rated_with_the_dotes_endpoint_n <dbl>,
# adverse_events_endpoint_percent <dbl>,
# adverse_events_endpoint_n <dbl>,
# adverse_events_3_months_acute_phase_post_intervention_percent <dbl>
[[4]]
# A tibble: 451 x 10
outcome study arm activity_change_in_a… activity_change_in_a…
<chr> <glue> <chr> <dbl> <dbl>
1 physical Arnol… Placebo NA NA
2 physical Arnol… Esrebo… NA NA
3 physical Gonza… Physic… NA NA
4 physical Gonza… Sertra… NA NA
5 physical Hammo… Pregab… NA NA
6 physical Hammo… Amitri… NA NA
7 physical Carde… Benzot… NA NA
8 physical Carde… Amitri… NA NA
9 physical Gould… Benzot… NA NA
10 physical Gould… Desipr… NA NA
# … with 441 more rows, and 5 more variables:
# activity_change_in_activity_in_daily_lives_post_intervention_unchanged_percent <dbl>,
# activity_change_in_activity_in_daily_lives_post_intervention_unchanged_n <dbl>,
# activity_change_in_activity_in_daily_lives_post_intervention_worse_percent <dbl>,
# activity_change_in_activity_in_daily_lives_post_intervention_worse_n <dbl>,
# activity_vas_0_100_baseline_mean <lgl>
[[5]]
# A tibble: 451 x 10
outcome study arm fibromyalgia_impact_… fibromyalgia_impact…
<chr> <glue> <chr> <dbl> <lgl>
1 qol Arnold… Placebo NA NA
2 qol Arnold… Esrebox… NA NA
3 qol Gonzal… Physica… NA NA
4 qol Gonzal… Sertral… NA NA
5 qol Hammod… Pregaba… NA NA
6 qol Hammod… Amitrip… NA NA
7 qol Carden… Benzotr… NA NA
8 qol Carden… Amitrip… NA NA
9 qol Gould … Benzotr… NA NA
10 qol Gould … Desipra… NA NA
# … with 441 more rows, and 5 more variables:
# fibromyalgia_impact_50_percent_reduction_in_fiq_baseline_percent <dbl>,
# fibromyalgia_impact_50_percent_reduction_in_fiq_baseline_n <dbl>,
# fibromyalgia_impact_fibromyalgia_impact_questionnaire_fiq_baseline_mean <dbl>,
# fibromyalgia_impact_fibromyalgia_impact_questionnaire_fiq_baseline_n <dbl>,
# fibromyalgia_impact_fibromyalgia_impact_questionnaire_fiq_baseline_sd <dbl>
[[6]]
# A tibble: 451 x 10
outcome study arm change_from_baseline… change_from_baseline…
<chr> <glue> <chr> <lgl> <lgl>
1 sleep Lee 2… Placebo NA NA
2 sleep Lee 2… Venlafa… NA NA
3 sleep dsrhv… Control NA NA
4 sleep dsrhv… Amitrip… NA NA
5 sleep dsrhv… Amitrip… NA NA
6 sleep dsrhv… Acupunc… NA NA
7 sleep <NA> Gabapen… NA NA
8 sleep <NA> Amitrip… NA NA
9 sleep Canno… Placebo NA NA
10 sleep Canno… Clonidi… NA NA
# … with 441 more rows, and 5 more variables:
# change_from_baseline_in_the_endpoint_mean_sleep_interference_score_nr_protocol_only_endpoint_se <lgl>,
# change_in_sleep_pattern_baseline_percent <lgl>,
# change_in_sleep_pattern_baseline_n <lgl>,
# change_in_sleep_pattern_decreased_percent <lgl>,
# change_in_sleep_pattern_decreased_n <lgl>
[[7]]
outcome study arm
1 pain_mod <NA> Placebo
2 pain_mod <NA> Venlafaxine - 75mg
3 pain_mod <NA> Control
4 pain_mod <NA> Amitriptyline 10mg
5 pain_mod <NA> Amitriptyline 10mg + splint
6 pain_mod <NA> Acupuncture
7 pain_mod <NA> Gabapentin 900 – 3600mg
8 pain_mod <NA> Amitriptyline 25 – 150mg
9 pain_mod <NA> Placebo
10 pain_mod <NA> Clonidine
11 pain_mod <NA> Imipramine 50mg
12 pain_mod <NA> Placebo
13 pain_mod <NA> Amitriptyline 75mg
14 pain_mod <NA> Placebo
15 pain_mod <NA> Amitriptyline 100mg
16 pain_mod <NA> Gabapentin ≤3600mg
17 pain_mod <NA> Amitriptyline ≤150mg
18 pain_mod <NA> Diphenhydramine ≤75mg
19 pain_mod <NA> Placebo
20 pain_mod <NA> Venlafaxine 37.5 - 225mg
21 pain_mod <NA> Placebo
22 pain_mod <NA> Paroxetine 20mg
23 pain_mod <NA> Benztropine mesylate 0.5 [active placebo]
24 pain_mod <NA> Desipramine - low
25 pain_mod <NA> Desipramine - medium
26 pain_mod <NA> Desipramine - high
27 pain_mod <NA> Fluoxetine - low
28 pain_mod <NA> Fluoxetine - medium
29 pain_mod <NA> Fluoxetine - high
30 pain_mod <NA> Placebo
31 pain_mod <NA> Fluvoxamine - 50-150mg
32 pain_mod <NA> Physical Therapy
33 pain_mod <NA> Sertraline - 50mg
34 pain_mod <NA> Amitriptyline - ≥10mg
35 pain_mod <NA> Nortriptyline - ≥10mg
36 pain_mod <NA> Placebo
37 pain_mod <NA> Amitriptyline
38 pain_mod <NA> Amitriptyline (Group 1)
39 pain_mod <NA> Amitriptyline + Fluphenazine (Group 2)
40 pain_mod <NA> Fluphenazine (Group 3)
41 pain_mod <NA> Glycopyrrolate (Active Placebo; Group 4)
42 pain_mod <NA> Riboflavin - 15mg
43 pain_mod <NA> Amitriptyline - 75mg + Riboflavin - 15mg
44 pain_mod <NA> Amitriptyline - 25mg + Placebo
45 pain_mod <NA> Fluoxetine - 20mg + Placebo
46 pain_mod <NA> Placebo
47 pain_mod <NA> Milnacipran - 100mg
48 pain_mod <NA> Placebo
49 pain_mod <NA> Amitriptyline - 25mg + Placebo
50 pain_mod <NA> Fluoxetine - 20mg + Placebo
51 pain_mod <NA> Amitriptyline - 25mg + Fluoxetine - 20mg
52 pain_mod <NA> Placebo
53 pain_mod <NA> Imipramine - 150mg
54 pain_mod <NA> Placebo
55 pain_mod <NA> Dothiepin - 75mg
56 pain_mod <NA> Desipramine 12.5 - 150mg
57 pain_mod <NA> Amitriptyline 12.5 - 150mg
58 pain_mod <NA> Placebo
59 pain_mod <NA> Trazodone 200mg
60 pain_mod <NA> Amitriptyline + naproxen (A+N)
61 pain_mod <NA> Placebo + naproxen (N)
62 pain_mod <NA> Amitriptyline + placebo (A)
63 pain_mod <NA> Placebo + placebo (PL)
64 pain_mod <NA> Milnacipran 50 - 200mg
65 pain_mod <NA> Placebo
66 pain_mod <NA> Amitriptyline + pyschotherapy
67 pain_mod <NA> Amitriptyline + support
68 pain_mod <NA> Placebo + psychotherapy
69 pain_mod <NA> Placebo + support
70 pain_mod <NA> Gabapentin 900 - 1800mg
71 pain_mod <NA> Amitriptyline 25 - 75mg
72 pain_mod <NA> Doxepin
73 pain_mod <NA> Desipramine
74 pain_mod <NA> Placebo
75 pain_mod <NA> Milnacipran 25-200mg/day [q.d]
76 pain_mod <NA> Milnacipran 25-200mg/day [b.i.d]
77 pain_mod <NA> Aerobic exercise (Group I)
78 pain_mod <NA> Paroxetine 20mg (Group II)
79 pain_mod <NA> Placebo TENS (Group III)
80 pain_mod <NA> Amitriptyline
81 pain_mod <NA> Maprotiline
82 pain_mod <NA> Placebo
83 pain_mod <NA> Imipramine - 50mg
84 pain_mod <NA> Citalopram - 40mg
85 pain_mod <NA> Placebo
86 pain_mod <NA> Duloxetine - 20mg
87 pain_mod <NA> Duloxetine - 60mg
88 pain_mod <NA> Duloxetine - 120mg
89 pain_mod <NA> Nabilone 0.5-1.0mg
90 pain_mod <NA> Amitriptyline 10-20mg
91 pain_mod <NA> Placebo
92 pain_mod <NA> Escitalopram 10-20mg
93 pain_mod <NA> Benzotropine ≤1mg
94 pain_mod <NA> Morphine ≥15 and ≤90mg
95 pain_mod <NA> Nortriptyline ≥25 and ≤100mg
96 pain_mod <NA> Morphine + Nortriptyline
97 pain_mod <NA> Placebo
98 pain_mod <NA> Duloxetine 60mg
99 pain_mod <NA> Placebo
100 pain_mod <NA> Duloxetine 60mg
moderate_pain_relief_30_percent_relief_baseline_percent
1 NA
2 NA
3 NA
4 NA
5 NA
6 NA
7 NA
8 NA
9 NA
10 NA
11 NA
12 NA
13 NA
14 NA
15 NA
16 NA
17 NA
18 NA
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92 NA
93 NA
94 NA
95 NA
96 NA
97 NA
98 NA
99 NA
100 NA
moderate_pain_relief_30_percent_relief_baseline_n
1 NA
2 NA
3 NA
4 NA
5 NA
6 NA
7 NA
8 NA
9 NA
10 NA
11 NA
12 NA
13 NA
14 NA
15 NA
16 NA
17 NA
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85 NA
86 NA
87 NA
88 NA
89 NA
90 NA
91 NA
92 NA
93 NA
94 NA
95 NA
96 NA
97 NA
98 NA
99 NA
100 NA
moderate_pain_relief_30_percent_relief_of_ped_24_hr_morning_recall_scores_completers_only_15_weeks_within_trial_percent
1 NA
2 NA
3 NA
4 NA
5 NA
6 NA
7 NA
8 NA
9 NA
10 NA
11 NA
12 NA
13 NA
14 NA
15 NA
16 NA
17 NA
18 NA
19 NA
20 NA
21 NA
22 NA
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85 NA
86 NA
87 NA
88 NA
89 NA
90 NA
91 NA
92 NA
93 NA
94 NA
95 NA
96 NA
97 NA
98 NA
99 NA
100 NA
moderate_pain_relief_30_percent_relief_of_ped_24_hr_morning_recall_scores_completers_only_15_weeks_within_trial_n
1 NA
2 NA
3 NA
4 NA
5 NA
6 NA
7 NA
8 NA
9 NA
10 NA
11 NA
12 NA
13 NA
14 NA
15 NA
16 NA
17 NA
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80 NA
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85 NA
86 NA
87 NA
88 NA
89 NA
90 NA
91 NA
92 NA
93 NA
94 NA
95 NA
96 NA
97 NA
98 NA
99 NA
100 NA
number_of_responders_30_percent_improvement_in_brief_pain_inventory_average_pain_bocf_endpoint_percent
1 NA
2 NA
3 NA
4 NA
5 NA
6 NA
7 NA
8 NA
9 NA
10 NA
11 NA
12 NA
13 NA
14 NA
15 NA
16 NA
17 NA
18 NA
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20 NA
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85 NA
86 NA
87 NA
88 NA
89 NA
90 NA
91 NA
92 NA
93 NA
94 NA
95 NA
96 NA
97 NA
98 NA
99 NA
100 NA
number_of_responders_30_percent_improvement_in_brief_pain_inventory_average_pain_bocf_endpoint_n
1 NA
2 NA
3 NA
4 NA
5 NA
6 NA
7 NA
8 NA
9 NA
10 NA
11 NA
12 NA
13 NA
14 NA
15 NA
16 NA
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90 NA
91 NA
92 NA
93 NA
94 NA
95 NA
96 NA
97 NA
98 NA
99 NA
100 NA
number_of_subjects_with_30_percent_reduction_in_weekly_average_pain_intensity_score_endpoint_percent
1 NA
2 NA
3 NA
4 NA
5 NA
6 NA
7 NA
8 NA
9 NA
10 NA
11 NA
12 NA
13 NA
14 NA
15 NA
16 NA
17 NA
18 NA
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95 NA
96 NA
97 NA
98 NA
99 NA
100 NA
[ reached 'max' / getOption("max.print") -- omitted 351 rows ]
[[8]]
# A tibble: 451 x 10
outcome study arm withdrawal_1_year_… withdrawal_1_year…
<chr> <glue> <chr> <dbl> <dbl>
1 withdra… Arnold … Placebo NA NA
2 withdra… Arnold … Esreboxet… NA NA
3 withdra… Gonzale… Physical … NA NA
4 withdra… Gonzale… Sertralin… NA NA
5 withdra… Hammody… Pregabali… NA NA
6 withdra… Hammody… Amitripty… NA NA
7 withdra… Cardena… Benzotrop… NA NA
8 withdra… Cardena… Amitripty… NA NA
9 withdra… Gould 2… Benzotrop… NA NA
10 withdra… Gould 2… Desiprami… NA NA
# … with 441 more rows, and 5 more variables:
# withdrawal_2_weeks_low_dose_endpoint_percent <dbl>,
# withdrawal_2_weeks_low_dose_endpoint_n <dbl>,
# withdrawal_3_months_acute_phase_post_intervention_percent <dbl>,
# withdrawal_3_months_acute_phase_post_intervention_n <dbl>,
# withdrawal_4_weeks_high_dose_endpoint_percent <dbl>
[[9]]
# A tibble: 451 x 10
outcome study arm good_pain_relief_50… good_pain_relief_50…
<chr> <glue> <chr> <dbl> <dbl>
1 pain_sub Arnold… Placebo NA NA
2 pain_sub Arnold… Esrebox… NA NA
3 pain_sub Gonzal… Physica… NA NA
4 pain_sub Gonzal… Sertral… NA NA
5 pain_sub Hammod… Pregaba… NA NA
6 pain_sub Hammod… Amitrip… NA NA
7 pain_sub Carden… Benzotr… NA NA
8 pain_sub Carden… Amitrip… NA NA
9 pain_sub Gould … Benzotr… NA NA
10 pain_sub Gould … Desipra… NA NA
# … with 441 more rows, and 5 more variables:
# number_of_responders_50_percent_improvement_in_brief_pain_inventory_average_pain_bocf_endpoint_percent <dbl>,
# number_of_responders_50_percent_improvement_in_brief_pain_inventory_average_pain_bocf_endpoint_n <lgl>,
# pain_100_percent_decrease_in_weekly_mean_24_hour_pain_severity_patient_diaries_endpoint_percent <dbl>,
# pain_100_percent_decrease_in_weekly_mean_24_hour_pain_severity_patient_diaries_endpoint_n <lgl>,
# pain_50_percent_decrease_from_baseline_in_average_24hr_pain_score_endpoint_percent <dbl>
# desired output structure
tar_read(p_obs)
# A tibble: 1 x 5
outcome study arm obs obs_info
<chr> <chr> <chr> <chr> <chr>
1 mood, pai… unique st… unique … columns with m… "information extract…
# pipeline overview
tar_visnetwork(allow = c(w_study_label_obs, starts_with("w_obs_")))
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Loading required package: dontpanic
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Before we identify timepoints and other observation-level variables, we check that the data are in the correct format. The measure_desc
column is the orgiinal column header from Covidence prefix for the measure. We’ll extract the observation-level variables (timepoint and scale) from this column.
tar_read(w_obs_wide)
# A tibble: 1,444 x 15
outcome study arm covidence_desc scale model_type mean n
<chr> <glue> <chr> <chr> <chr> <chr> <dbl> <int>
1 mood rinta… gabap… depression_cen… cente… smd 7.2 22
2 mood rinta… amitr… depression_cen… cente… smd 7.2 22
3 mood rinta… diphe… depression_cen… cente… smd 7.2 22
4 mood graff… amitr… anxiety_state_… state… smd 80.3 11
5 mood graff… amitr… anxiety_state_… state… smd 65.8 11
6 mood graff… amitr… anxiety_state_… state… smd 76.6 11
7 mood graff… amitr… anxiety_state_… state… smd 84.7 11
8 mood graff… amitr… depression_bec… beck_… smd 12.1 11
9 mood graff… amitr… depression_bec… beck_… smd 11.1 11
10 mood graff… amitr… anxiety_state_… state… smd 64.8 12
# … with 1,434 more rows, and 7 more variables: sd <dbl>,
# range <chr>, se <dbl>, median <dbl>, ci <chr>, iqr <chr>,
# percent <dbl>
We are interested in classifying timepoints as post-intervention, short-term follow up, and long-term follow up.
# get counts for timepoints, particularly interested in checking there are no unmatched timepoints
tar_read(w_obs_time) %>%
count(timepoint)
# A tibble: 5 x 2
timepoint n
<chr> <int>
1 baseline 501
2 follow_up 6
3 mid_int 128
4 post_int 803
5 unmatched 6