Using machine learning models to investigate the relationship between corporeal workload and clinical and epidemiological features of patients infected with Covid-19 in Egypt
Objective: To explore if clinical and epidemiological features of patients positive for coronavirus disease-2019 are affected by somatic work stress. Method: The retrospective study was conducted at Kafrelsheik University Hospital, Egypt, and comprised data of patients admitted between April 1, to...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Pakistan Medical Association
2023-05-01
|
| Series: | Journal of the Pakistan Medical Association |
| Subjects: | |
| Online Access: | https://ojs.jpma.org.pk/index.php/public_html/article/view/9868 |
| _version_ | 1797812132185636864 |
|---|---|
| author | Ahmed Ali. Torad Fayiz El-Shamy Ahmed Mahmoud Tayee Zeinab Sami Ahmed |
| author_facet | Ahmed Ali. Torad Fayiz El-Shamy Ahmed Mahmoud Tayee Zeinab Sami Ahmed |
| author_sort | Ahmed Ali. Torad |
| collection | DOAJ |
| description |
Objective: To explore if clinical and epidemiological features of patients positive for coronavirus disease-2019 are affected by somatic work stress.
Method: The retrospective study was conducted at Kafrelsheik University Hospital, Egypt, and comprised data of patients admitted between April 1, to June 6, 2020, with confirmed coronavirus disease-2019 infection. Health records of healthy subjects who had come to the hospital as part of their routine check-up were also included for comparison, and the researchers were blinded during the gathering and analysis phase. Demographic features, vital signs, infection severity, somatic workload of the patients’ jobs at admission, and detailed discharge profile was noted. The relationship
between clinical features and somatic work stress was evaluated. Data was analysed using SPSS 26.
Results: Of the 1072 cases, 602(56.2%) were men and 470(43.8%) were women. The overall median age was 43 years (interquartile range: 29 years). The healthy group had 500 random subjects. There were significant differences in all vital signs between the patients and healthy controls (p<0.05). Among the patients, infection severity was higher in men, but it was not significant (p>0.05). The overall mortality was 69(6.4%); 46(4.3%) men and 23(2.2%) women. There was no significant association between gender and outcome (p>0.05). There were 816(76.11%) patients with lowintensity physical workload pre-infection, 136(12.68%) moderate and 120(11.19%) high. Infection severity was significantly high in the low-intensity group (p<0.05). However, the fate of the patients was not significantly associated
with their pre-infection work profile (p>0.05).
Conclusion: Coronavirus disease-2019 significantly affected patients’ vital signs, and infection severity was significantly associated with physical work stress. However, mortality and pre-infection somatic workload were not associated.
Keywords: Sulphur dioxide, COVID-19, Epidemiologists, Healthy volunteers, Polymerase, Demography.
|
| first_indexed | 2024-03-13T07:33:39Z |
| format | Article |
| id | doaj.art-da7534536a6b4b14b0eeb930d0c7a32e |
| institution | Directory Open Access Journal |
| issn | 0030-9982 |
| language | English |
| last_indexed | 2024-03-13T07:33:39Z |
| publishDate | 2023-05-01 |
| publisher | Pakistan Medical Association |
| record_format | Article |
| series | Journal of the Pakistan Medical Association |
| spelling | doaj.art-da7534536a6b4b14b0eeb930d0c7a32e2023-06-04T04:23:15ZengPakistan Medical AssociationJournal of the Pakistan Medical Association0030-99822023-05-0173410.47391/JPMA.EGY-S4-48Using machine learning models to investigate the relationship between corporeal workload and clinical and epidemiological features of patients infected with Covid-19 in EgyptAhmed Ali. Torad0Fayiz El-Shamy1Ahmed Mahmoud Tayee2Zeinab Sami Ahmed3Department of Basic Science, Kafrelsheikh University, Egypt.Department of Physical Therapy for Obstetrics and Gynaecology, Kafrelsheikh University, Egypt.Department of Physical Therapy for Surgery, Kafrelsheikh University, Egypt.Department of Physical Therapy for Cardiovascular and Respiratory Disorder and Geriatrics, Cairo University, Egypt. Objective: To explore if clinical and epidemiological features of patients positive for coronavirus disease-2019 are affected by somatic work stress. Method: The retrospective study was conducted at Kafrelsheik University Hospital, Egypt, and comprised data of patients admitted between April 1, to June 6, 2020, with confirmed coronavirus disease-2019 infection. Health records of healthy subjects who had come to the hospital as part of their routine check-up were also included for comparison, and the researchers were blinded during the gathering and analysis phase. Demographic features, vital signs, infection severity, somatic workload of the patients’ jobs at admission, and detailed discharge profile was noted. The relationship between clinical features and somatic work stress was evaluated. Data was analysed using SPSS 26. Results: Of the 1072 cases, 602(56.2%) were men and 470(43.8%) were women. The overall median age was 43 years (interquartile range: 29 years). The healthy group had 500 random subjects. There were significant differences in all vital signs between the patients and healthy controls (p<0.05). Among the patients, infection severity was higher in men, but it was not significant (p>0.05). The overall mortality was 69(6.4%); 46(4.3%) men and 23(2.2%) women. There was no significant association between gender and outcome (p>0.05). There were 816(76.11%) patients with lowintensity physical workload pre-infection, 136(12.68%) moderate and 120(11.19%) high. Infection severity was significantly high in the low-intensity group (p<0.05). However, the fate of the patients was not significantly associated with their pre-infection work profile (p>0.05). Conclusion: Coronavirus disease-2019 significantly affected patients’ vital signs, and infection severity was significantly associated with physical work stress. However, mortality and pre-infection somatic workload were not associated. Keywords: Sulphur dioxide, COVID-19, Epidemiologists, Healthy volunteers, Polymerase, Demography. https://ojs.jpma.org.pk/index.php/public_html/article/view/9868Sulphur dioxideCOVID-19EpidemiologistsHealthy volunteersPolymeraseDemography |
| spellingShingle | Ahmed Ali. Torad Fayiz El-Shamy Ahmed Mahmoud Tayee Zeinab Sami Ahmed Using machine learning models to investigate the relationship between corporeal workload and clinical and epidemiological features of patients infected with Covid-19 in Egypt Journal of the Pakistan Medical Association Sulphur dioxide COVID-19 Epidemiologists Healthy volunteers Polymerase Demography |
| title | Using machine learning models to investigate the relationship between corporeal workload and clinical and epidemiological features of patients infected with Covid-19 in Egypt |
| title_full | Using machine learning models to investigate the relationship between corporeal workload and clinical and epidemiological features of patients infected with Covid-19 in Egypt |
| title_fullStr | Using machine learning models to investigate the relationship between corporeal workload and clinical and epidemiological features of patients infected with Covid-19 in Egypt |
| title_full_unstemmed | Using machine learning models to investigate the relationship between corporeal workload and clinical and epidemiological features of patients infected with Covid-19 in Egypt |
| title_short | Using machine learning models to investigate the relationship between corporeal workload and clinical and epidemiological features of patients infected with Covid-19 in Egypt |
| title_sort | using machine learning models to investigate the relationship between corporeal workload and clinical and epidemiological features of patients infected with covid 19 in egypt |
| topic | Sulphur dioxide COVID-19 Epidemiologists Healthy volunteers Polymerase Demography |
| url | https://ojs.jpma.org.pk/index.php/public_html/article/view/9868 |
| work_keys_str_mv | AT ahmedalitorad usingmachinelearningmodelstoinvestigatetherelationshipbetweencorporealworkloadandclinicalandepidemiologicalfeaturesofpatientsinfectedwithcovid19inegypt AT fayizelshamy usingmachinelearningmodelstoinvestigatetherelationshipbetweencorporealworkloadandclinicalandepidemiologicalfeaturesofpatientsinfectedwithcovid19inegypt AT ahmedmahmoudtayee usingmachinelearningmodelstoinvestigatetherelationshipbetweencorporealworkloadandclinicalandepidemiologicalfeaturesofpatientsinfectedwithcovid19inegypt AT zeinabsamiahmed usingmachinelearningmodelstoinvestigatetherelationshipbetweencorporealworkloadandclinicalandepidemiologicalfeaturesofpatientsinfectedwithcovid19inegypt |