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Record W3030743920 · doi:10.1093/sleep/zsaa056.1074

1078 Sleep Problems In Posttraumatic Stress Disorder (PTSD) In A Nationally Representative Us Sample Before And After Controlling For Comorbid Depression: Results From A Nationally Representative US Sample

2020· article· en· W3030743920 on OpenAlexaff
Madhulika A. Gupta, Branka Vujčić

Bibliographic record

VenueSLEEP · 2020
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsWestern University
Fundersnot available
KeywordsDepression (economics)InsomniaPsychiatryAmbulatoryComorbidityDiagnosis codeNational Comorbidity SurveyMedicinePsychologyPopulationInternal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction The impact of psychiatric comorbidities on sleep disturbances in PTSD have been studied in the National Comorbidity Survey (NCS)(Leskin GA, 2002) and the NCS-replication (Lauterbach D, 2011) studies. We examined sleep problems in PTSD before and after controlling for comorbid depressive disease, in the National Ambulatory Medical Care Survey(NAMCS) and National Hospital Ambulatory Medical Care Survey (NHAMCS) which use a multi-stage probability design to collect nationally representative data on health care visits. Methods We examined patient visits(1995-2015) from NAMCS/NHAMCS with a PTSD diagnosis (ICD-9-CM 309.81). Both NAMCS/NHAMCS allow ≥3 reasons for visit(RFV) and ≥3 physician-assigned diagnoses (using ICD9-CM codes). The following variables were created: ‘Insomnia’: ICD9-CM codes 307.41,307.42,780.51,RFV 11351; ‘Sleep Disturbance’(SD): ICD-9CM codes 780.5, 780.50, 780.59; ‘Nightmares’: ICD9-CM code 307.4, RFV 11353; Obstructive sleep apnea (OSA): ICD-CM codes 327.23,780.57, RFV 11355, checklist; and ‘Depression’: ICD9-CM codes 296.2, 296.3, 296.82, 311, 296.20-296.36, 300.4. Results There were an estimated 37,262,245±3,203,047 (unweighted count or UWC=3,995; 66.4%±1.8% female;.mean±age: 40.39 ± 0.56 years; ‘Depression’ was comorbid with 37.7%±1.5% cases) PTSD patients visits. All sleep variables accounted for 11.2%±1.2% (UWC=303) of PTSD visits with their individual frequencies as follows: ‘Insomnia’6.5%±1.1%(UWC=153); ‘Nightmares’: 1.9%±0.4%(UWC=74); ‘SD’: 2.0%±0.3%(UWC=67); OSA: 1.3%±0.3%(UWC=27). Logistic regression analysis using PTSD versus all other patient visits as dependent variable revealed the following sleep predictors of PTSD after controlling for age and sex and: (i) before controlling for ‘Depression’: ‘Insomnia’: OR=7.16, (95%CI 4.78-10.73); ‘SD’: OR=4.43(95%CI 2.55-7.71); ‘Nightmares’:OR=104.29 (95%CI56.65-192.02); ‘OSA’: OR=1.71(95%CI 0.94-3.12); and (ii) after controlling for ‘Depression’: ‘Insomnia’: OR=2.88 (95%CI 1.87-4.42); ‘SD’: OR=2.84 (95%CI 1.73-4.67); and ‘Nightmares’: OR=58.33(95%CI 26.39-128.94); and ‘OSA’: OR=2.02(95%CI 1.14-3.57). Conclusion In a nationally representative sample, the association of PTSD with insomnia, sleep disturbance and nightmares remained significant, albeit decreased, after controlling for the confounding effect of comorbid depression; however the association of PTSD with OSA emerged only after the effect of depression was controlled for. Support None

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.077
GPT teacher head0.421
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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