Affective Symptoms

We did a systematic review and network meta-analysis. We searched the Cochrane Central Register of Controlled Trials, CINAHL, Embase, LILACS database, MEDLINE, MEDLINE In-Process, PsycINFO, AMED, the UK National Research Register, and PSYNDEX from the date of their inception to Jan 8, 2016, with no language restrictions. We used the search terms “depress*” OR “dysthymi*” OR “adjustment disorder*” OR “mood disorder*” OR “affective disorder” OR “affective symptoms” combined with a list of all included antidepressants.
We included double-blind, randomised controlled trials (RCTs) comparing antidepressants with placebo or another active antidepressant as oral monotherapy for the acute treatment of adults (≥18 years old and of both sexes) with a primary diagnosis of major depressive disorder according to standard operationalised diagnostic criteria (Feighner criteria, Research Diagnostic Criteria, DSM-III, DSM-III-R, DSM-IV, DSM-5, and ICD-10). We considered only double-blind trials because we included placebo in the network meta-analysis, and because this study design increases methodological rigour by minimising performance and ascertainment biases.⁷ (link) Additionally, we included all second-generation antidepressants approved by the regulatory agencies in the USA, Europe, or Japan: agomelatine, bupropion, citalopram, desvenlafaxine, duloxetine, escitalopram, fluoxetine, fluvoxamine, levomilnacipran, milnacipran, mirtazapine, paroxetine, reboxetine, sertraline, venlafaxine, vilazodone, and vortioxetine. To inform clinical practice globally, we selected the two tricyclics (amitriptyline and clomipramine) included in the WHO Model List of Essential Medicines). We also included trazodone and nefazodone, because of their distinct effect and tolerability profiles. Additionally, we included trials that allowed rescue medications so long as they were equally provided among the randomised groups. We included data only for drugs within the therapeutic range (appendix pp 133, 134). Finally, we excluded quasi-randomised trials and trials that were incomplete or included 20% or more of participants with bipolar disorder, psychotic depression, or treatment-resistant depression; or patients with a serious concomitant medical illness.
The electronic database searches were supplemented with manual searches for published, unpublished, and ongoing RCTs in international trial registers, websites of drug approval agencies, and key scientific journals in the field.⁸ For example, we searched ClinicalTrials.gov using the search term “major depressive disorder” combined with a list of all included antidepressants. We contacted all the pharmaceutical companies marketing antidepressants and asked for supplemental unpublished information about both premarketing and post-marketing studies, with a specific focus on second-generation antidepressants. We also contacted study authors and drug manufacturers to supplement incomplete reports of the original papers or provide data for unpublished studies.
Six pairs of investigators (ACi, TAF, LZA, SL, HGR, YO, NT, YH, EHT, HI, KS, and AT) independently selected the studies, reviewed the main reports and supplementary materials, extracted the relevant information from the included trials, and assessed the risk of bias. Any discrepancies were resolved by consensus and arbitration by a panel of investigators within the review team (ACi, TAF, LZA, EHT, and JRG).
The full protocol of this network meta-analysis has been published.⁸

Given the prominence of Google as a search engine (eg, Google accounts for roughly 88% of the search engine market in the United States [23 ]), these analyses leveraged Google Trends, which allows for public access to search term volume for a given time and location. Several studies have leveraged Google Trends data to examine how mental health information is sought out [22 (link),24 (link),25 (link)]. As can be found in the documentation for Google Trends, the raw counts for a given search term are normalized by location and time of search and then scaled to a number from 0 to 100 representing the proportion of searches on all topics that the given term constitutes. Such normalization allows for easier comparison across geographic regions, where population may play a significant role in relative search term popularity. This analysis downloaded data from Google Trends using the gtrendsR package in R (version 1.4.8; R Foundation for Statistical Computing) [26 ]. To obtain data with the most granularity, hourly trend data were queried. The areas of interest were the 50 states constituting the United States; thus, search terms were normalized across states. As Google Trends only stores hourly data for up to 7 days, hourly data were programmatically pulled each Monday from March 23, 2020, to March 29, 2021. This period of 372 days spans the early days of the pandemic to the widespread availability of the COVID-19 vaccine in the United States. During this time frame, 39 states implemented statewide mask mandates, most of which went into effect before or during the summer of 2020. Thus, the given time frame allowed for careful introspection into the short- and long-term effects of mask mandate implementation on mental health search term activity.
The following 19 mental health search terms were queried from Google Trends, as described previously: “anxiety,” “depression,” “ocd” (obsessive-compulsive disorder), “hopeless,” “angry,” “afraid,” “apathy,” “worthless,” “worried,” “restless,” “irritable,” “tense,” “scattered,” “tired,” “avoiding,” “procrastinate,” “insomnia,” “suicidal,” and “suicide.” Aligning with previous work by the authors [10 (link),22 (link)], these terms were validated from previous research on using Google Trends to assess mental health [27 (link)], as well as from previous research assessing rapid affective symptom changes as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [28 ,29 (link)]. In addition to these terms, physical health search terms, both without known associations to COVID-19 (“abrasion,” “allergic,” “angina,” “apnea,” “bleeding,” “blister,” “bruising,” “conjunctivitis,” “constipation,” “discharge,” “earache,” “flatulence,” “fracture,” “hemorrhage,” “incontinence,” “inflammation,” “itching,” “lesions,” “rash,” “spasms,” “swelling,” and “syncope”; 22 terms) and with known associations to COVID-19 (“bloating,” “blurry,” “congestion,” “cough,” “coughing,” “croup,” “diarrhea,” “dizzy,” “fainting,” “fever,” “pain,” “sneezing,” “strep,” “stuffy,” and “vomiting”; 15 terms) were queried to ascertain whether any significantly detected patterns in mental health search term activity were unique to and distinct from those pertaining to physical health. Note that each mental and physical health search term was considered independently in this study; in other words, composite scores aggregating the individual search term counts to create a composite score capturing total mental and physical health activity were not created. This decision was made because combining individual search terms with differential trends throughout the pandemic may attenuate these individual trends in the composite score such that the composite score may not be reflective of changes in specific mental or physical health symptoms, therefore making it uninformative.

The Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5) specifies the possible symptoms of PMDD as: (1) affective lability (mood swings), (2) irritability or anger, (3) depressed mood, (4) anxiety or tension, (5) decreased interest in usual activities, (6) difficulty concentrating, (7) a sense of being overwhelmed or out of control, (8) change in appetite, overeating, or specific food cravings, (9) hypersomnia or insomnia, (10) fatigue, and (11) one physical symptom (for example, breast tenderness). PMDD diagnosis requires the presence of at least one affective symptom (symptoms 1–4) to reach the total of 5 required symptoms, which must be confirmed in a prospective manner for at least 2 menstrual cycles. In addition, the symptoms must be associated with clinically significant distress or interference with work, school, usual social activities, or relationship with others.
In accordance with DSM-5 criteria, PMDD diagnosis in the proposed study was be assessed prospectively by evaluating the participants’ daily symptom ratings using the DRSP scale [22 (link)] during two–three menstrual cycles. PMDD diagnosis was defined as a 30% or greater increase in 5 or more symptoms, one of which had to be affective, as well as functional impairment, between the luteal (day −7 to −1) and follicular (day 6 to 12) days relative to the range of the scale of each individual participant across the entire menstrual cycle [27 (link)]. PMDD participants defined using these criteria were found to have differential cellular [27 (link),28 (link)] and sex hormone processing [29 (link)], as well as unique transcriptional responses [30 (link)].
Of note, and in references to the discussion section, the diagnosis of premenstrual syndrome (PMS) requires a prospective assessment of symptomatology, with the presence of 1 to 4 symptoms and without the need that one of them must be affective.

During the screening patients were rated by the clinician using Montgomery–Åsberg Depression Rating Scale (MADRS) [38 (link)], Young Mania Rating Scale (YMRS) [39 (link)], Columbia–Suicide Severity Rating Scale (C-SSRS) [40 (link)], The Clinician-Administered Dissociative States Scale (CADSS) [5 (link)], Brief Psychiatric Rating Scale (BPRS) [41 (link)] scales. The MADRS is a clinician-assessed measure of depression severity in clinical trials and was developed to provide a measure of depression severity for use in antidepressant response studies. For this purpose, 10 items were selected based on their ability to detect depression change. The YMRS assesses hypomanic/manic symptom severity. It is an 11-item clinician-administered scale, with a total score range of 0 to 60 (≤12 indicates remission, 13–19—minimal symptoms, 20–25—mildly manic, 26–37—moderately manic, and 38–60—severely manic), while the C-SSRS is partially structured clinical history assessing the severity of suicidal thoughts, their intensity, and suicidal behavior. The CADSS was chosen for analysis as it is the most widely used instrument employed in previous mood disorder studies to assess the acute psychoactive effects of ketamine [7 (link)]. The CADSS includes a 19-item scale used to evaluate the patient’s answers (subjective items) and an 8-item scale used by a trained physician to assess the patient’s responses during ketamine intake (objective items). The subjective items include three components: depersonalization, derealization, and amnesia. The BPRS is an 18-item rating scale used to assess a range of psychotic and affective symptoms based on both observation of the subject and the subject’s own self-report. A variant of the BPRS is the four-item BPRS+, which considers the positive symptoms of suspiciousness, hallucinations, unusual thought content, and conceptual disorganization. The BPRS and the BPRS+ are used to assess treatment-emergent psychotic symptoms. In both tests, each symptom is rated on a scale from 0 to 6, where 1 is “not present” and 6 is “extremely severe” (the score of 0 represents a not assessed item). To demonstrate the CADSS and BPRS fluctuations across treatments, CADSS and BPRS scores taken 30 min post drug administration were analyzed.
A subject was defined as a responder at a given time point if the percent improvement from the baseline total MADRS score was at least 50% and the subject did not remit. The patient was defined as a remitter at a given time point if the total MADRS score was ≤10 points [42 (link)]. The final three groups (responders, remitters, and nonremitters) were determined by MADRS score at the follow-up visit, one week after the last ketamine infusion. The study outcome measure is defined per a MADRS score.