MétaCan
Menu
Back to cohort

USNS Comfort: Caring for the Sick at Sea

2008· letter· en· W2081098287 on OpenAlexaboutno aff
Philip D. Bailey

Bibliographic record

VenueAnesthesia & Analgesia · 2008
Typeletter
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEmergency managementHumanitarian aidGeneral partnershipMedical emergencyPolitical science

Abstract

fetched live from OpenAlex

To the Editor: In addition to military task, US Naval forces frequently conduct non-combat related missions, including emergency medical response and humanitarian assistance operations. Non-combat-related medical missions have involved the hospital ship USNS Mercy (T-AH 19) during tsunami relief efforts in Southeast Asia in 2004 and a follow-on 2006 humanitarian mission to the same tsunami ravaged region of Southeast Asia. The hospital ship USNS Comfort (T-AH 20) (Fig. 1) responded to the Hurricane Katrina disaster in 2005.Fig 1.: USNS Comfort (T-AH 20).Recently, the USNS Comfort (T-AH 20) embarked on a 4-month humanitarian mission to 12 Central and South American countries from June through October 2007. The USNS Comfort (T-AH 20) is the second ship of the Mercy Class. These ships were former San Clemente Class supertankers that were extensively modified to their present configuration. The Comfort has the capability to provide care for patients of all ages, with a total patient capacity of 1000 beds, 12 operating rooms, and all the ancillary services found in shore-based facilities. Additionally, there is a flight deck that supports helicopter operations and patient transports. The goal of the 2007 mission, appropriately named “Partnership for the Americas,” was to coordinate with host nations and nongovernmental relief organizations (Project Hope and Operation Smile) to provide humanitarian assistance during mission sites in Belize, Guatemala, Panama, Nicaragua, El Salvador, Peru, Ecuador, Colombia, Haiti, Trinidad, Guyana, and Suriname. The main focus of the mission was on preventive and primary care; surgical services were aboard to support this focus. Surgical services offered during the mission were general, general pediatric, gynecology, oral/ maxillofacial, orthopedic, otolaryngology, plastic, and urology surgery. The anesthesiology department consisted of two anesthesiologists and four certified registered nurse anesthetists. At each mission site, advance teams consisting of surgeons and anesthesia providers screened patients ashore before their transport by either boat or helicopter to the ship for surgery. Although the time spent operating in each country varied from 3 to 6 days, the surgical services offered were unchanged. The ship’s operating rooms contained the same contemporary equipment used in shore-based hospitals, which allowed personnel to integrate seamlessly into the surgical theater while underway. The available staffing model gave surgical services the ability to run three operating rooms 12 hours a day while at each mission site. More than 1000 surgical procedures were performed aboard the Comfort during the 4-mo period. This mission exemplified cooperation and teamwork, joining uniformed services medical assets from the US Navy, Army, Air Force, and Public Health Service with those of military health care professionals from Canada and other host nations as well as nongovernmental relief organizations. Indeed, the key to the success of the surgical mission was the interoperability among personnel, regardless of uniform, specialty or nationality. Flexibility, communication, and central focus on the mission led to team-building that facilitated a high-volume case load in an environment of patient safety, setting a standard for which future humanitarian missions should be compared. Philip D. Bailey, Jr., DO Department of Anesthesiology and Pain Management Naval Medical Center Portsmouth Portsmouth, VA [email protected]

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.005
Open science0.0030.001
Research integrity0.0120.017
Insufficient payload (model declined to judge)0.0100.005

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 head0.030
GPT teacher head0.275
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueAnesthesia & AnalgesiaSame topicGlobal Health and SurgeryFrench-language works237,207