Epidemiological analysis of emergency ophthalmic cases in a specialist hospital in Tianjin

[Objective:] To analyze the disease spectrum of emergency cases at an ophthalmology hospital in Tianjin, offering evidence-based support for standardizing diagnostic procedures and rationing emergency medical resources. [Methods:] Reviewed clinical data of patients at the hospital's emergency department from January 2019 to December 2023, covering demographics, visit timings, seasonal distribution, and preliminary diagnoses. [Results:] A total of 26,077 ophthalmology emergency patients were included, with a male-to-female ratio of 1.12:1 and an average age of 36.82±15.44 years. Most patients were aged <14 years (26.74%) and 31~40 years (21.03%). Daily visits peaked at 10:00—12:00 (11.06%), 14:00—16:00 (10.41%), and 20:00—22:00 (10.43%), and were lowest at 05:00—07:00 (4.83%). April had the fewest visits (3.87%), August the most (11.61%), and summer accounted for the highest quarterly proportion (31.74%). The top 10 preliminary diagnoses were led by conjunctivitis (39.58%) and xerophthalmia (14.32%). Compared to 2019, the top 10 preliminary diagnoses dropped significantly in 2020 and 2021 (both P<0.001), 2020 95%CI(-0.98—-0.68),2021 95%CI(-0.54, -0.11). Similarly, these diagnoses were significantly lower in summer, autumn, and winter than in spring (all P<0.001), summer 95%CI(-0.32, -0.08), autumn 95%CI (-0.39, -0.14), winter 95%CI(-0.54, -0.30). In conjunctivitis cases, winter incidence was significantly lower than in spring and summer (both P<0.001). Gender distribution in the top 10 diagnoses was statistically significant (P<0.001), 95%CI(-0.08, -0.03)and (-0.08, -0.04). Compared to those aged <14, other age groups showed a downward trend in the top 10 preliminary diagnoses (all P<0.001), 14~20 95%CI(-0.88, -0.43), 21~30 95%CI(-1.01, -0.65), 31~40 95%CI(-1.10, -0.82), 41~50 95%CI(-0.97, -0.66), 51~60 95%CI(1.71,-1.38), 61~70 95%CI(-1.45, -1.08), 71~80 95%CI(-1.36, -0.80), >80 95%CI(-1.44,-0.22). [Conclusions:] Ophthalmology emergency patients are mainly children and middle-aged men, with those <14 years old at higher risk. Visit times follow a"three-peak-one-valley" pattern. Most diagnoses are non-urgent conditions like conjunctivitis and xerophthalmia.Conjunctivitis shows marked seasonality, peaking in spring and summer. Total ophthalmology emergency visits declined in 2020 and 2021 versus 2019, particularly for conjunctivitis and xerophthalmia, partially recovering in 2022.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-05-01
DOI
https://doi.org/10.12419/24121401
Primary Topic
Trace Elements in Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Epidemiological analysis of emergency ophthalmic cases in a specialist hospital in Tianjin

SHILAP Revista de lepidopterología
Trace Elements in Health
article

Epidemiological analysis of emergency ophthalmic cases in a specialist hospital in Tianjin

article en

Abstract

[Objective:] To analyze the disease spectrum of emergency cases at an ophthalmology hospital in Tianjin, offering evidence-based support for standardizing diagnostic procedures and rationing emergency medical resources. [Methods:] Reviewed clinical data of patients at the hospital's emergency department from January 2019 to December 2023, covering demographics, visit timings, seasonal distribution, and preliminary diagnoses. [Results:] A total of 26,077 ophthalmology emergency patients were included, with a male-to-female ratio of 1.12:1 and an average age of 36.82±15.44 years. Most patients were aged <14 years (26.74%) and 31~40 years (21.03%). Daily visits peaked at 10:00—12:00 (11.06%), 14:00—16:00 (10.41%), and 20:00—22:00 (10.43%), and were lowest at 05:00—07:00 (4.83%). April had the fewest visits (3.87%), August the most (11.61%), and summer accounted for the highest quarterly proportion (31.74%). The top 10 preliminary diagnoses were led by conjunctivitis (39.58%) and xerophthalmia (14.32%). Compared to 2019, the top 10 preliminary diagnoses dropped significantly in 2020 and 2021 (both P<0.001), 2020 95%CI(-0.98—-0.68),2021 95%CI(-0.54, -0.11). Similarly, these diagnoses were significantly lower in summer, autumn, and winter than in spring (all P<0.001), summer 95%CI(-0.32, -0.08), autumn 95%CI (-0.39, -0.14), winter 95%CI(-0.54, -0.30). In conjunctivitis cases, winter incidence was significantly lower than in spring and summer (both P<0.001). Gender distribution in the top 10 diagnoses was statistically significant (P<0.001), 95%CI(-0.08, -0.03)and (-0.08, -0.04). Compared to those aged <14, other age groups showed a downward trend in the top 10 preliminary diagnoses (all P<0.001), 14~20 95%CI(-0.88, -0.43), 21~30 95%CI(-1.01, -0.65), 31~40 95%CI(-1.10, -0.82), 41~50 95%CI(-0.97, -0.66), 51~60 95%CI(1.71,-1.38), 61~70 95%CI(-1.45, -1.08), 71~80 95%CI(-1.36, -0.80), >80 95%CI(-1.44,-0.22). [Conclusions:] Ophthalmology emergency patients are mainly children and middle-aged men, with those <14 years old at higher risk. Visit times follow a"three-peak-one-valley" pattern. Most diagnoses are non-urgent conditions like conjunctivitis and xerophthalmia.Conjunctivitis shows marked seasonality, peaking in spring and summer. Total ophthalmology emergency visits declined in 2020 and 2021 versus 2019, particularly for conjunctivitis and xerophthalmia, partially recovering in 2022.

SHILAP Revista de lepidopterología
Shandong University (CN), Tianjin Medical University Eye Hospital (CN), Tianjin Medical University (CN)
Good health and well-being
Openalex Percentile: Top 44%
Trace Elements in Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.