Evidence map›Paper›PMID 35103154›Full record

ArticleCureus2021

Impact of COVID-19 on Key Performance Indicators of the National Hip Fracture Database and the Management of Hip Fracture Patients.

Jennifer L Waterman, Ullas Jayaraju, Joshua K Nadimi, David Morgan

Abstract read
In one paragraph

Article in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jennifer L WatermanSurgery, Royal Glamorgan Hospital, Llantrisant, GBR.
Ullas JayarajuTrauma and Orthopaedics, Royal Glamorgan Hospital, Llantrisant, GBR.
Joshua K NadimiTrauma and Orthopaedics, Royal Glamorgan Hospital, Llantrisant, GBR.
David MorganTrauma and Orthopaedics, Royal Glamorgan Hospital, Llantrisant, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA hospital's performance regarding the management of hip fractures is based on six key performance indicators (KPIs) which are recorded onto the National Hip Fracture Database (NHFD). The aim of this study was to assess the overall impact of coronavirus disease 2019 (COVID-19) on the management and outcomes of hip fracture patients against a similar period in 2019 by utilizing the KPIs.

methodRetrospective data collection of hip fracture patients during a six-week (pre-COVID) period in 2019 and a six-week (COVID-19) period in a single orthopedic unit. The following parameters were compared; patient age, time to theater, surgeon operating time, total time in the operating room, time from ward to recovery, time from hospital presentation to theater, and total time from presentation to hospital discharge.

resultsSome 38 patients in the pre-COVID-19 period vs. 27 patients with hip fractures in the COVID-19 period were included in the study. Time from diagnosis to theater and surgeon operating time were similar in both groups. The mean length of stay was 9.3 days vs. a mean of 31.34 days (p = 0.0004) in the COVID-19 and pre-COVID-19 groups respectively. A 30-day mortality was 22.2% (n = 6) in the COVID-19 group vs. 5.3% (n = 2) in the pre-COVID-19 group.

conclusionOur study demonstrates that the combination of surgical stress and COVID-19 leads to higher mortality rates. Our hospital's structural reorganization during the pandemic has shown progress in achieving important KPIs and improved short-term outcomes for hip fracture and trauma patients.

Indexed as

30 day mortalitycovid-19neck of femur fracturestheatre efficiencytrauma

Identifiers

PMID35103154
PMCPMC8776320

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.